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|
- // Experimental Python Execution
- var python = python || {};
- python.Parser = class {
- constructor(text, file, debug) {
- this._tokenizer = new python.Tokenizer(text, file);
- this._debug = debug;
- python.Parser._precedence = python.Parser._precedence || {
- 'or': 2, 'and': 3, 'not' : 4,
- 'in': 5, 'instanceof': 5, 'is': 5, '<': 5, '>': 5, '<=': 5, '>=': 5, '<>': 5, '==': 5, '!=': 5,
- '|': 6, '^' : 7, '&' : 8,
- '<<': 9, '>>': 9, '+': 10, '-': 10, '*': 11, '@': 11, '/': 11, '//': 11, '%': 11,
- // '+': 12, '-': 12,
- '~': 13, '**': 14
- };
- }
- parse() {
- const node = this._node('program');
- node.body = [];
- while (!this._tokenizer.match('eof')) {
- const statement = this._statement();
- if (statement) {
- node.body.push(statement);
- continue;
- }
- if (this._tokenizer.eat('\n') || this._tokenizer.eat(';') || this._tokenizer.peek().type == 'eof') {
- continue;
- }
- if (this._tokenizer.eat('indent') && this._tokenizer.peek().type == 'eof') {
- continue;
- }
- throw new python.Error('Unsupported statement' + this._tokenizer.location());
- }
- return node;
- }
- _suite() {
- const node = this._node('block');
- node.statements = [];
- let statement = null;
- if (this._tokenizer.eat('\n')) {
- if (this._tokenizer.eat('indent')) {
- while (!this._tokenizer.eat('eof') && !this._tokenizer.eat('dedent')) {
- if (this._tokenizer.eat(';')) {
- continue;
- }
- statement = this._statement();
- if (statement) {
- node.statements.push(statement);
- continue;
- }
- if (this._tokenizer.eat('\n')) {
- continue;
- }
- if (this._tokenizer.match('dedent') || this._tokenizer.match('eof')) {
- continue;
- }
- throw new python.Error('Empty statement' + this._tokenizer.location());
- }
- }
- }
- else if (!this._tokenizer.eat('eof')) {
- while (!this._tokenizer.match('\n') && !this._tokenizer.match('eof') && !this._tokenizer.match('dedent')) {
- if (this._tokenizer.eat(';')) {
- continue;
- }
- statement = this._statement();
- if (statement) {
- node.statements.push(statement);
- continue;
- }
- throw new python.Error('Empty statement' + this._tokenizer.location());
- }
- this._tokenizer.eat('\n');
- }
- return node;
- }
- _statement() {
- let node = this._eat('id', 'break');
- if (node) {
- return node;
- }
- node = this._eat('id', 'continue');
- if (node) {
- return node;
- }
- node = this._eat('id', 'return');
- if (node) {
- node.expression = this._expression(-1, [], true);
- return node;
- }
- node = this._eat('id', 'raise');
- if (node) {
- node.exception = this._expression(-1, [ 'from' ]);
- if (this._tokenizer.eat('id', 'from')) {
- node.from = this._expression();
- }
- else if (this._tokenizer.eat(',')) {
- node.exception = [ node.exception ];
- node.exception.push(this._expression());
- if (this._tokenizer.eat(',')) {
- node.exception.push(this._expression());
- }
- }
- return node;
- }
- node = this._eat('id', 'assert');
- if (node) {
- node.condition = this._expression(-1, [ ',' ]);
- if (this._tokenizer.eat(',')) {
- node.message = this._expression();
- }
- return node;
- }
- node = this._eat('id', 'exec');
- if (node) {
- node.variable = this._expression(-1, [ 'in' ]);
- if (this._tokenizer.eat('in')) {
- do {
- node.target = node.target || [];
- node.target.push(this._expression(-1, [ 'in' ], false));
- }
- while (this._tokenizer.eat(','));
- }
- return node;
- }
- node = this._eat('id', 'global');
- if (node) {
- node.names = [];
- do {
- node.names.push(this._name(true).value);
- }
- while (this._tokenizer.eat(','));
- return node;
- }
- node = this._eat('id', 'nonlocal');
- if (node) {
- node.names = [];
- do {
- node.names.push(this._name(true).value);
- }
- while (this._tokenizer.eat(','));
- return node;
- }
- node = this._eat('id', 'import');
- if (node) {
- node.names = [];
- do {
- const alias = this._node('alias');
- alias.name = this._dottedName();
- if (this._tokenizer.eat('id', 'as')) {
- alias.asname = this._name(true).value;
- }
- node.names.push(alias);
- }
- while (this._tokenizer.eat(','));
- return node;
- }
- node = this._eat('id', 'from');
- if (node) {
- node.type = 'import_from';
- node.level = 0;
- const dots = this._tokenizer.peek();
- if (dots && Array.from(dots.type).every((c) => c == '.')) {
- this._eat(dots.type);
- node.level = Array.from(dots.type).length;
- }
- node.module = this._dottedName();
- this._tokenizer.expect('id', 'import');
- node.names = [];
- const close = this._tokenizer.eat('(');
- do {
- const alias = this._node('alias');
- alias.name = this._name(true).value;
- if (this._tokenizer.eat('id', 'as')) {
- alias.asname = this._name(true).value;
- }
- node.names.push(alias);
- }
- while (this._tokenizer.eat(','));
- if (close) {
- this._tokenizer.expect(')');
- }
- return node;
- }
- let decorator_list = this._decorator();
- node = this._eat('id', 'class');
- if (node) {
- node.name = this._name(true).value;
- if (decorator_list) {
- node.decorator_list = Array.from(decorator_list);
- decorator_list = null;
- }
- node.bases = this._tokenizer.peek().type === '(' ? this._arguments() : [];
- this._tokenizer.expect(':');
- node.body = this._suite();
- return node;
- }
- const async = this._eat('id', 'async');
- if (async &&
- !this._tokenizer.match('id', 'def') &&
- !this._tokenizer.match('id', 'with') &&
- !this._tokenizer.match('id', 'for')) {
- throw new python.Error("Expected 'def', 'with' or 'for'" + this._tokenizer.location());
- }
- node = this._eat('id', 'def');
- if (node) {
- if (async) {
- node.async = async;
- }
- node.name = this._name(true).value;
- if (decorator_list) {
- node.decorator_list = Array.from(decorator_list);
- decorator_list = null;
- }
- this._tokenizer.expect('(');
- node.parameters = this._parameters(')');
- if (this._tokenizer.eat('->')) {
- node.returnType = this._type();
- }
- this._tokenizer.expect(':');
- node.body = this._suite();
- return node;
- }
- if (decorator_list && decorator_list.length > 0) {
- throw new python.Error('Unexpected decorator.');
- }
- node = this._eat('id', 'del');
- if (node) {
- node.expression = this._expression(-1, [], true);
- return node;
- }
- node = this._eat('id', 'print');
- if (node) {
- node.expression = this._expression(-1, [], true);
- return node;
- }
- node = this._eat('id', 'if');
- if (node) {
- node.condition = this._expression();
- this._tokenizer.expect(':');
- node.then = this._suite();
- let current = node;
- this._tokenizer.eat('\n');
- while (this._tokenizer.eat('id', 'elif')) {
- current.else = this._node('if');
- current = current.else;
- current.condition = this._expression();
- this._tokenizer.expect(':');
- current.then = this._suite();
- this._tokenizer.eat('\n');
- }
- if (this._tokenizer.eat('id', 'else')) {
- this._tokenizer.expect(':');
- current.else = this._suite();
- }
- return node;
- }
- node = this._eat('id', 'while');
- if (node) {
- node.condition = this._expression();
- this._tokenizer.expect(':');
- node.body = this._suite();
- if (this._tokenizer.eat('id', 'else')) {
- this._tokenizer.expect(':');
- node.else = this._suite();
- }
- return node;
- }
- node = this._eat('id', 'pass');
- if (node) {
- return node;
- }
- node = this._eat('id', 'for');
- if (node) {
- node.variable = [];
- node.variable.push(this._expression(-1, [ 'in' ]));
- while (this._tokenizer.eat(',')) {
- if (this._tokenizer.match('id', 'in')) {
- node.variable.push({});
- break;
- }
- node.variable.push(this._expression(-1, [ 'in' ]));
- }
- this._tokenizer.expect('id', 'in');
- node.target = [];
- node.target.push(this._expression());
- while (this._tokenizer.eat(',')) {
- if (this._tokenizer.match(':')) {
- node.target.push({});
- break;
- }
- node.target.push(this._expression(-1, [ 'in' ]));
- }
- this._tokenizer.expect(':');
- node.body = this._suite();
- if (this._tokenizer.eat('id', 'else')) {
- this._tokenizer.expect(':');
- node.else = this._suite();
- }
- return node;
- }
- node = this._eat('id', 'with');
- if (node) {
- if (async) {
- node.async = async;
- }
- node.item = [];
- do {
- const item = this._node();
- item.type = 'with_item';
- item.expression = this._expression();
- if (this._tokenizer.eat('id', 'as')) {
- item.variable = this._expression();
- }
- node.item.push(item);
- }
- while (this._tokenizer.eat(','));
- this._tokenizer.expect(':');
- node.body = this._suite();
- return node;
- }
- node = this._eat('id', 'try');
- if (node) {
- this._tokenizer.expect(':');
- node.body = this._suite();
- node.except = [];
- while (this._tokenizer.match('id', 'except')) {
- const except = this._node('except');
- this._tokenizer.expect('id', 'except');
- except.clause = [];
- except.clause.push(this._expression());
- while (this._tokenizer.eat(',')) {
- if (this._tokenizer.match(':') || this._tokenizer.match('as')) {
- except.clause.push({});
- break;
- }
- except.clause.push(this._expression());
- }
- if (this._tokenizer.eat('id', 'as')) {
- except.variable = this._expression();
- }
- this._tokenizer.expect(':');
- except.body = this._suite();
- node.except.push(except);
- }
- if (this._tokenizer.match('id', 'else')) {
- node.else = this._node('else');
- this._tokenizer.expect('id', 'else');
- this._tokenizer.expect(':');
- node.else.body = this._suite();
- }
- if (this._tokenizer.match('id', 'finally')) {
- node.finally = this._node('finally');
- this._tokenizer.expect('id', 'finally');
- this._tokenizer.expect(':');
- node.finally.body = this._suite();
- }
- return node;
- }
- const expression = this._expression(-1, [], true);
- if (expression) {
- if (expression.type == 'id' && this._tokenizer.eat(':')) {
- node = this._node('var');
- node.name = expression.value;
- node.location = expression.location;
- node.variableType = this._expression(-1, [ '=' ]);
- if (this._tokenizer.eat('=')) {
- node.initializer = this._expression();
- }
- return node;
- }
- switch (expression.type) {
- case '=':
- case ':=':
- case '==':
- case '!=':
- case '+=':
- case '-=':
- case '*=':
- case '@=':
- case '/=':
- case '//=':
- case '**=':
- case '&=':
- case '|=':
- case '%=':
- case '>>=':
- case '<<=':
- case '>>':
- case '<<':
- case '>=':
- case '<=':
- case '<':
- case '>':
- case '%':
- case '^=':
- case '...':
- case 'call':
- case 'assert':
- case 'raise':
- case 'string':
- case 'list':
- case 'var':
- case '.':
- case '[]':
- case 'yield':
- case '+':
- case '-':
- case '*':
- case '**':
- case '@':
- case '/':
- case '//':
- case '~':
- case '&':
- case '^':
- case '|':
- case 'not':
- case 'id':
- case 'number':
- case 'in':
- case 'and':
- case 'or':
- case 'if':
- case 'for':
- case 'tuple':
- case 'lambda':
- case 'await':
- return expression;
- default:
- throw new python.Error("Unhandled expression" + this._tokenizer.location());
- }
- }
- return null;
- }
- _expression(minPrecedence, terminal, tuple) {
- minPrecedence = minPrecedence || -1;
- const terminalSet = new Set(terminal);
- const stack = [];
- for (;;) {
- let node = this._node();
- const token = this._tokenizer.peek();
- if (stack.length == 1 && terminalSet.has(token.value)) {
- break;
- }
- const precedence = python.Parser._precedence[token.value];
- if (precedence) {
- if (precedence >= minPrecedence) {
- this._tokenizer.read();
- node.type = token.value;
- if (token.type == 'id' && (token.value === 'in' || token.value === 'not')) {
- if (token.value === 'in') {
- node.type = 'in';
- }
- else if (this._tokenizer.eat('id', 'in')) {
- node.type = 'not in';
- }
- else {
- node.type = 'not';
- node.expression = this._expression(precedence, terminal, tuple === false ? false : true);
- stack.push(node);
- continue;
- }
- }
- else if (token.value == '~') {
- node.type = '~';
- node.expression = this._expression(precedence, terminal, tuple === false ? false : true);
- stack.push(node);
- continue;
- }
- else if (token.type == 'id' && token.value == 'is') {
- if (this._tokenizer.eat('id', 'not')) {
- node.type = 'is not';
- }
- }
- if (stack.length > 0) {
- node.op = node.type;
- node.type = 'binary';
- node.left = stack.pop();
- node.right = this._expression(precedence, terminal, tuple === true ? true : false);
- }
- else {
- node.op = node.type;
- node.type = 'unary';
- node.operand = this._expression(precedence, terminal, tuple === true ? true : false);
- }
- stack.push(node);
- continue;
- }
- }
- if (this._tokenizer.eat(':=')) {
- node.type = ':=';
- node.target = stack.pop();
- node.expression = this._expression(-1, terminal, tuple === false ? false : true);
- stack.push(node);
- continue;
- }
- if (this._tokenizer.eat('=')) {
- node.type = '=';
- node.target = stack.pop();
- node.expression = this._expression(-1, terminal, tuple === false ? false : true);
- stack.push(node);
- continue;
- }
- switch (token.type) {
- case '-=':
- case '**=':
- case '*=':
- case '//=':
- case '/=':
- case '&=':
- case '%=':
- case '^=':
- case '+=':
- case '<<=':
- case '>>=':
- case '|=':
- case '@=':
- node = this._node(token.type);
- this._tokenizer.expect(token.type);
- node.target = stack.pop();
- node.expression = this._expression(-1, terminal, true);
- stack.push(node);
- continue;
- default:
- break;
- }
- node = this._eat('id', 'if');
- if (node) {
- node.then = stack.pop();
- node.condition = this._expression();
- this._tokenizer.expect('id', 'else');
- node.else = this._expression();
- stack.push(node);
- continue;
- }
- while (this._tokenizer.match('id', 'for') || this._tokenizer.match('id', 'async')) {
- const async = this._eat('id', 'async');
- if (async && !this._tokenizer.match('id', 'for')) {
- throw new python.Error("Expected 'for'" + this._tokenizer.location());
- }
- node = this._eat('id', 'for');
- if (node) {
- if (async) {
- node.async = async;
- }
- node.expression = stack.pop();
- node.variable = this._expression(-1, [ 'in' ], true);
- this._tokenizer.expect('id', 'in');
- node.target = this._expression(-1, [ 'for', 'if' ], true);
- while (this._tokenizer.eat('id', 'if')) {
- node.condition = node.condition || [];
- node.condition.push(this._expression(-1, [ 'for', 'if' ]));
- }
- stack.push(node);
- }
- }
- node = this._eat('id', 'lambda');
- if (node) {
- node.parameters = this._parameters(':');
- node.body = this._expression(-1, terminal, false);
- stack.push(node);
- continue;
- }
- node = this._eat('id', 'yield');
- if (node) {
- if (this._tokenizer.eat('id', 'from')) {
- node.from = this._expression(-1, [], true);
- }
- else {
- node.expression = [];
- do {
- node.expression.push(this._expression(-1, [], false));
- }
- while (this._tokenizer.eat(','));
- }
- stack.push(node);
- continue;
- }
- node = this._eat('id', 'await');
- if (node) {
- node.expression = this._expression(minPrecedence, terminal, tuple);
- stack.push(node);
- continue;
- }
- node = this._eat('.');
- if (node) {
- this._tokenizer.eat('\n');
- node.target = stack.pop();
- node.member = this._name();
- stack.push(node);
- continue;
- }
- if (this._tokenizer.peek().type === '(') {
- if (stack.length == 0) {
- node = this._node('tuple');
- const args = this._arguments();
- if (args.length == 1) {
- stack.push(args[0]);
- }
- else {
- node.value = args;
- stack.push(node);
- }
- }
- else {
- node = this._node('call');
- node.target = stack.pop();
- node.arguments = this._arguments();
- stack.push(node);
- }
- continue;
- }
- if (this._tokenizer.peek().type === '[') {
- if (stack.length == 0) {
- stack.push(this._expressions());
- }
- else {
- node = this._node('[]');
- node.target = stack.pop();
- node.arguments = this._slice();
- stack.push(node);
- }
- continue;
- }
- if (this._tokenizer.peek().type == '{') {
- stack.push(this._dictOrSetMaker());
- continue;
- }
- node = this._node();
- const literal = this._literal();
- if (literal) {
- if (stack.length > 0 && literal.type == 'number' &&
- (literal.value.startsWith('-') || literal.value.startsWith('+'))) {
- node.type = literal.value.substring(0, 1);
- literal.value = literal.value.substring(1);
- node.left = stack.pop();
- node.right = literal;
- stack.push(node);
- }
- else if (stack.length == 1 && literal.type == 'string' && stack[0].type == 'string') {
- stack[0].value += literal.value;
- }
- else {
- if (literal.type === 'number') {
- switch (literal.value) {
- case 'inf': literal.value = Infinity; break;
- case '-inf': literal.value = -Infinity; break;
- default: break;
- }
- }
- stack.push(literal);
- }
- continue;
- }
- if (this._tokenizer.peek().keyword) {
- break;
- }
- node = this._eat('...');
- if (node) {
- stack.push(node);
- continue;
- }
- const identifier = this._name();
- if (identifier) {
- stack.push(identifier);
- continue;
- }
- if (tuple === true && stack.length == 1 && this._tokenizer.eat(',')) {
- if (stack[0].type === 'tuple') {
- node = stack[0];
- }
- else {
- node = this._node('tuple');
- node.value = [ stack.pop() ];
- stack.push(node);
- }
- // for, bar, = <expr>
- if (this._tokenizer.peek().type === '=') {
- continue;
- }
- if (!this._tokenizer.match('=') && !terminalSet.has(this._tokenizer.peek().value)) {
- const nextTerminal = terminal.slice(0).concat([ ',', '=' ]);
- const expression = this._expression(minPrecedence, nextTerminal, tuple);
- if (expression) {
- node.value.push(expression);
- continue;
- }
- }
- break;
- }
- break;
- }
- if (stack.length == 1) {
- return stack.pop();
- }
- if (stack.length != 0) {
- throw new python.Error('Unexpected expression' + this._tokenizer.location());
- }
- return null;
- }
- _decorator() {
- let list = null;
- while (this._tokenizer.eat('@')) {
- const node = this._node('decorator');
- node.value = this._expression();
- if (!node.value || (node.value.type !== 'call' && node.value.type !== 'id' && node.value.type !== '.')) {
- throw new python.Error('Invalid decorator' + this._tokenizer.location());
- }
- this._tokenizer.eat('\n');
- list = list !== null ? list : [];
- list.push(node);
- }
- return list;
- }
- _dictOrSetMaker() {
- const list = [];
- this._tokenizer.expect('{');
- let dict = true;
- while (!this._tokenizer.eat('}')) {
- const item = this._expression(-1, [], false);
- if (item == null) {
- throw new python.Error('Expected expression' + this._tokenizer.location());
- }
- if (!this._tokenizer.eat(':')) {
- dict = false;
- }
- if (dict) {
- const value = this._expression(-1, [], false);
- if (value == null) {
- throw new python.Error('Expected expression' + this._tokenizer.location());
- }
- list.push({ type: 'pair', key: item, value: value });
- }
- else {
- list.push(item);
- }
- this._tokenizer.eat(',');
- this._tokenizer.eat('\n');
- if (this._tokenizer.eat('}')) {
- break;
- }
- }
- if (dict) {
- return { type: 'dict', value: list };
- }
- return { type: 'set', value: list };
- }
- _expressions() {
- const list = [];
- this._tokenizer.expect('[');
- while (!this._tokenizer.eat(']')) {
- const expression = this._expression();
- if (expression == null) {
- throw new python.Error('Expected expression' + this._tokenizer.location());
- }
- list.push(expression);
- this._tokenizer.eat(',');
- while (this._tokenizer.eat('\n')) {
- // continue
- }
- if (this._tokenizer.eat(']')) {
- break;
- }
- }
- return { type: 'list', value: list };
- }
- _slice() {
- let node = { type: '::' };
- let list = [];
- const group = [ 'start', 'stop', 'step' ];
- this._tokenizer.expect('[');
- while (!this._tokenizer.eat(']')) {
- if (this._tokenizer.eat(':')) {
- node[group.shift()] = { type: 'list', value: list };
- list = [];
- continue;
- }
- if (this._tokenizer.eat(',')) {
- // list.push({});
- continue;
- }
- if (this._tokenizer.peek().type != ']') {
- const expression = this._expression();
- if (expression == null) {
- throw new python.Error('Expected expression' + this._tokenizer.location());
- }
- list.push(expression);
- }
- }
- if (list.length > 0) {
- node[group.shift()] = { type: 'list', value: list };
- }
- if (node.start && !node.stop && !node.step) {
- node = node.start;
- }
- return node;
- }
- _name(required) {
- const token = this._tokenizer.peek();
- if (token.type == 'id' && !token.keyword) {
- this._tokenizer.read();
- return token;
- }
- if (required) {
- throw new python.Error("Invalid syntax" + this._tokenizer.location());
- }
- return null;
- }
- _dottedName() {
- const list = [];
- do {
- list.push(this._name(true).value);
- }
- while (this._tokenizer.eat('.'));
- return list.join('.');
- }
- _literal() {
- const token = this._tokenizer.peek();
- if (token.type == 'string' || token.type == 'number' || token.type == 'boolean') {
- this._tokenizer.read();
- return token;
- }
- return null;
- }
- _typeArguments() {
- const list = [];
- this._tokenizer.expect('[');
- while (!this._tokenizer.eat(']')) {
- const type = this._type();
- if (type == null) {
- throw new python.Error('Expected type ' + this._tokenizer.location());
- }
- list.push(type);
- if (!this._tokenizer.eat(',')) {
- this._tokenizer.expect(']');
- break;
- }
- }
- return list;
- }
- _type() {
- const type = this._node();
- type.type = 'type';
- type.name = this._expression(-1, [ '[', '=' ]);
- if (type.name) {
- if (this._tokenizer.peek().value === '[') {
- type.arguments = this._typeArguments();
- }
- return type;
- }
- return null;
- }
- _parameter(terminal) {
- const node = this._node('parameter');
- if (this._tokenizer.eat('/')) {
- node.name = '/';
- return node;
- }
- if (this._tokenizer.eat('**')) {
- node.parameterType = '**';
- }
- if (this._tokenizer.eat('*')) {
- node.parameterType = '*';
- }
- const identifier = this._name();
- if (identifier !== null) {
- node.name = identifier.value;
- if (terminal !== ':' && this._tokenizer.eat(':')) {
- node.parameterType = this._type();
- }
- if (this._tokenizer.eat('=')) {
- node.initializer = this._expression();
- }
- return node;
- }
- return null;
- }
- _parameters(terminal) {
- const list = [];
- while (!this._tokenizer.eat(terminal)) {
- this._tokenizer.eat('\n');
- if (this._tokenizer.eat('(')) {
- list.push(this._parameters(')'));
- }
- else {
- list.push(this._parameter(terminal));
- }
- this._tokenizer.eat('\n');
- if (!this._tokenizer.eat(',')) {
- this._tokenizer.expect(terminal);
- break;
- }
- }
- return list;
- }
- _arguments() {
- const list = [];
- this._tokenizer.expect('(');
- while (!this._tokenizer.eat(')')) {
- if (this._tokenizer.eat('\n')) {
- continue;
- }
- const expression = this._expression(-1, [], false);
- if (expression == null) {
- throw new python.Error('Expected expression ' + this._tokenizer.location());
- }
- list.push(expression);
- if (!this._tokenizer.eat(',')) {
- this._tokenizer.eat('\n');
- this._tokenizer.expect(')');
- break;
- }
- }
- return list;
- }
- _node(type) {
- const node = {};
- node.location = this._tokenizer.location();
- if (type) {
- node.type = type;
- }
- return node;
- }
- _eat(type, value) {
- if (this._tokenizer.match(type, value)) {
- const node = this._node(type === 'id' ? value : type);
- this._tokenizer.expect(type, value);
- return node;
- }
- return null;
- }
- };
- python.Tokenizer = class {
- constructor(text, file) {
- this._text = text;
- this._file = file;
- this._position = 0;
- this._lineStart = 0;
- this._line = 0;
- this._token = { type: '', value: '' };
- this._brackets = 0;
- this._indentation = [];
- this._outdent = 0;
- if (!python.Tokenizer._whitespace) {
- python.Tokenizer._whitespace = new RegExp('[\u1680\u180e\u2000-\u200a\u202f\u205f\u3000\ufeff]');
- const identifierStartChars = '\xaa\xb5\xba\xc0-\xd6\xd8-\xf6\xf8-\u02c1\u02c6-\u02d1\u02e0-\u02e4\u02ec\u02ee\u0370-\u0374\u0376\u0377\u037a-\u037d\u0386\u0388-\u038a\u038c\u038e-\u03a1\u03a3-\u03f5\u03f7-\u0481\u048a-\u0527\u0531-\u0556\u0559\u0561-\u0587\u05d0-\u05ea\u05f0-\u05f2\u0620-\u064a\u066e\u066f\u0671-\u06d3\u06d5\u06e5\u06e6\u06ee\u06ef\u06fa-\u06fc\u06ff\u0710\u0712-\u072f\u074d-\u07a5\u07b1\u07ca-\u07ea\u07f4\u07f5\u07fa\u0800-\u0815\u081a\u0824\u0828\u0840-\u0858\u08a0\u08a2-\u08ac\u0904-\u0939\u093d\u0950\u0958-\u0961\u0971-\u0977\u0979-\u097f\u0985-\u098c\u098f\u0990\u0993-\u09a8\u09aa-\u09b0\u09b2\u09b6-\u09b9\u09bd\u09ce\u09dc\u09dd\u09df-\u09e1\u09f0\u09f1\u0a05-\u0a0a\u0a0f\u0a10\u0a13-\u0a28\u0a2a-\u0a30\u0a32\u0a33\u0a35\u0a36\u0a38\u0a39\u0a59-\u0a5c\u0a5e\u0a72-\u0a74\u0a85-\u0a8d\u0a8f-\u0a91\u0a93-\u0aa8\u0aaa-\u0ab0\u0ab2\u0ab3\u0ab5-\u0ab9\u0abd\u0ad0\u0ae0\u0ae1\u0b05-\u0b0c\u0b0f\u0b10\u0b13-\u0b28\u0b2a-\u0b30\u0b32\u0b33\u0b35-\u0b39\u0b3d\u0b5c\u0b5d\u0b5f-\u0b61\u0b71\u0b83\u0b85-\u0b8a\u0b8e-\u0b90\u0b92-\u0b95\u0b99\u0b9a\u0b9c\u0b9e\u0b9f\u0ba3\u0ba4\u0ba8-\u0baa\u0bae-\u0bb9\u0bd0\u0c05-\u0c0c\u0c0e-\u0c10\u0c12-\u0c28\u0c2a-\u0c33\u0c35-\u0c39\u0c3d\u0c58\u0c59\u0c60\u0c61\u0c85-\u0c8c\u0c8e-\u0c90\u0c92-\u0ca8\u0caa-\u0cb3\u0cb5-\u0cb9\u0cbd\u0cde\u0ce0\u0ce1\u0cf1\u0cf2\u0d05-\u0d0c\u0d0e-\u0d10\u0d12-\u0d3a\u0d3d\u0d4e\u0d60\u0d61\u0d7a-\u0d7f\u0d85-\u0d96\u0d9a-\u0db1\u0db3-\u0dbb\u0dbd\u0dc0-\u0dc6\u0e01-\u0e30\u0e32\u0e33\u0e40-\u0e46\u0e81\u0e82\u0e84\u0e87\u0e88\u0e8a\u0e8d\u0e94-\u0e97\u0e99-\u0e9f\u0ea1-\u0ea3\u0ea5\u0ea7\u0eaa\u0eab\u0ead-\u0eb0\u0eb2\u0eb3\u0ebd\u0ec0-\u0ec4\u0ec6\u0edc-\u0edf\u0f00\u0f40-\u0f47\u0f49-\u0f6c\u0f88-\u0f8c\u1000-\u102a\u103f\u1050-\u1055\u105a-\u105d\u1061\u1065\u1066\u106e-\u1070\u1075-\u1081\u108e\u10a0-\u10c5\u10c7\u10cd\u10d0-\u10fa\u10fc-\u1248\u124a-\u124d\u1250-\u1256\u1258\u125a-\u125d\u1260-\u1288\u128a-\u128d\u1290-\u12b0\u12b2-\u12b5\u12b8-\u12be\u12c0\u12c2-\u12c5\u12c8-\u12d6\u12d8-\u1310\u1312-\u1315\u1318-\u135a\u1380-\u138f\u13a0-\u13f4\u1401-\u166c\u166f-\u167f\u1681-\u169a\u16a0-\u16ea\u16ee-\u16f0\u1700-\u170c\u170e-\u1711\u1720-\u1731\u1740-\u1751\u1760-\u176c\u176e-\u1770\u1780-\u17b3\u17d7\u17dc\u1820-\u1877\u1880-\u18a8\u18aa\u18b0-\u18f5\u1900-\u191c\u1950-\u196d\u1970-\u1974\u1980-\u19ab\u19c1-\u19c7\u1a00-\u1a16\u1a20-\u1a54\u1aa7\u1b05-\u1b33\u1b45-\u1b4b\u1b83-\u1ba0\u1bae\u1baf\u1bba-\u1be5\u1c00-\u1c23\u1c4d-\u1c4f\u1c5a-\u1c7d\u1ce9-\u1cec\u1cee-\u1cf1\u1cf5\u1cf6\u1d00-\u1dbf\u1e00-\u1f15\u1f18-\u1f1d\u1f20-\u1f45\u1f48-\u1f4d\u1f50-\u1f57\u1f59\u1f5b\u1f5d\u1f5f-\u1f7d\u1f80-\u1fb4\u1fb6-\u1fbc\u1fbe\u1fc2-\u1fc4\u1fc6-\u1fcc\u1fd0-\u1fd3\u1fd6-\u1fdb\u1fe0-\u1fec\u1ff2-\u1ff4\u1ff6-\u1ffc\u2071\u207f\u2090-\u209c\u2102\u2107\u210a-\u2113\u2115\u2119-\u211d\u2124\u2126\u2128\u212a-\u212d\u212f-\u2139\u213c-\u213f\u2145-\u2149\u214e\u2160-\u2188\u2c00-\u2c2e\u2c30-\u2c5e\u2c60-\u2ce4\u2ceb-\u2cee\u2cf2\u2cf3\u2d00-\u2d25\u2d27\u2d2d\u2d30-\u2d67\u2d6f\u2d80-\u2d96\u2da0-\u2da6\u2da8-\u2dae\u2db0-\u2db6\u2db8-\u2dbe\u2dc0-\u2dc6\u2dc8-\u2dce\u2dd0-\u2dd6\u2dd8-\u2dde\u2e2f\u3005-\u3007\u3021-\u3029\u3031-\u3035\u3038-\u303c\u3041-\u3096\u309d-\u309f\u30a1-\u30fa\u30fc-\u30ff\u3105-\u312d\u3131-\u318e\u31a0-\u31ba\u31f0-\u31ff\u3400-\u4db5\u4e00-\u9fcc\ua000-\ua48c\ua4d0-\ua4fd\ua500-\ua60c\ua610-\ua61f\ua62a\ua62b\ua640-\ua66e\ua67f-\ua697\ua6a0-\ua6ef\ua717-\ua71f\ua722-\ua788\ua78b-\ua78e\ua790-\ua793\ua7a0-\ua7aa\ua7f8-\ua801\ua803-\ua805\ua807-\ua80a\ua80c-\ua822\ua840-\ua873\ua882-\ua8b3\ua8f2-\ua8f7\ua8fb\ua90a-\ua925\ua930-\ua946\ua960-\ua97c\ua984-\ua9b2\ua9cf\uaa00-\uaa28\uaa40-\uaa42\uaa44-\uaa4b\uaa60-\uaa76\uaa7a\uaa80-\uaaaf\uaab1\uaab5\uaab6\uaab9-\uaabd\uaac0\uaac2\uaadb-\uaadd\uaae0-\uaaea\uaaf2-\uaaf4\uab01-\uab06\uab09-\uab0e\uab11-\uab16\uab20-\uab26\uab28-\uab2e\uabc0-\uabe2\uac00-\ud7a3\ud7b0-\ud7c6\ud7cb-\ud7fb\uf900-\ufa6d\ufa70-\ufad9\ufb00-\ufb06\ufb13-\ufb17\ufb1d\ufb1f-\ufb28\ufb2a-\ufb36\ufb38-\ufb3c\ufb3e\ufb40\ufb41\ufb43\ufb44\ufb46-\ufbb1\ufbd3-\ufd3d\ufd50-\ufd8f\ufd92-\ufdc7\ufdf0-\ufdfb\ufe70-\ufe74\ufe76-\ufefc\uff21-\uff3a\uff41-\uff5a\uff66-\uffbe\uffc2-\uffc7\uffca-\uffcf\uffd2-\uffd7\uffda-\uffdc';
- const identifierChars = '\u0300-\u036f\u0483-\u0487\u0591-\u05bd\u05bf\u05c1\u05c2\u05c4\u05c5\u05c7\u0610-\u061a\u0620-\u0649\u0672-\u06d3\u06e7-\u06e8\u06fb-\u06fc\u0730-\u074a\u0800-\u0814\u081b-\u0823\u0825-\u0827\u0829-\u082d\u0840-\u0857\u08e4-\u08fe\u0900-\u0903\u093a-\u093c\u093e-\u094f\u0951-\u0957\u0962-\u0963\u0966-\u096f\u0981-\u0983\u09bc\u09be-\u09c4\u09c7\u09c8\u09d7\u09df-\u09e0\u0a01-\u0a03\u0a3c\u0a3e-\u0a42\u0a47\u0a48\u0a4b-\u0a4d\u0a51\u0a66-\u0a71\u0a75\u0a81-\u0a83\u0abc\u0abe-\u0ac5\u0ac7-\u0ac9\u0acb-\u0acd\u0ae2-\u0ae3\u0ae6-\u0aef\u0b01-\u0b03\u0b3c\u0b3e-\u0b44\u0b47\u0b48\u0b4b-\u0b4d\u0b56\u0b57\u0b5f-\u0b60\u0b66-\u0b6f\u0b82\u0bbe-\u0bc2\u0bc6-\u0bc8\u0bca-\u0bcd\u0bd7\u0be6-\u0bef\u0c01-\u0c03\u0c46-\u0c48\u0c4a-\u0c4d\u0c55\u0c56\u0c62-\u0c63\u0c66-\u0c6f\u0c82\u0c83\u0cbc\u0cbe-\u0cc4\u0cc6-\u0cc8\u0cca-\u0ccd\u0cd5\u0cd6\u0ce2-\u0ce3\u0ce6-\u0cef\u0d02\u0d03\u0d46-\u0d48\u0d57\u0d62-\u0d63\u0d66-\u0d6f\u0d82\u0d83\u0dca\u0dcf-\u0dd4\u0dd6\u0dd8-\u0ddf\u0df2\u0df3\u0e34-\u0e3a\u0e40-\u0e45\u0e50-\u0e59\u0eb4-\u0eb9\u0ec8-\u0ecd\u0ed0-\u0ed9\u0f18\u0f19\u0f20-\u0f29\u0f35\u0f37\u0f39\u0f41-\u0f47\u0f71-\u0f84\u0f86-\u0f87\u0f8d-\u0f97\u0f99-\u0fbc\u0fc6\u1000-\u1029\u1040-\u1049\u1067-\u106d\u1071-\u1074\u1082-\u108d\u108f-\u109d\u135d-\u135f\u170e-\u1710\u1720-\u1730\u1740-\u1750\u1772\u1773\u1780-\u17b2\u17dd\u17e0-\u17e9\u180b-\u180d\u1810-\u1819\u1920-\u192b\u1930-\u193b\u1951-\u196d\u19b0-\u19c0\u19c8-\u19c9\u19d0-\u19d9\u1a00-\u1a15\u1a20-\u1a53\u1a60-\u1a7c\u1a7f-\u1a89\u1a90-\u1a99\u1b46-\u1b4b\u1b50-\u1b59\u1b6b-\u1b73\u1bb0-\u1bb9\u1be6-\u1bf3\u1c00-\u1c22\u1c40-\u1c49\u1c5b-\u1c7d\u1cd0-\u1cd2\u1d00-\u1dbe\u1e01-\u1f15\u200c\u200d\u203f\u2040\u2054\u20d0-\u20dc\u20e1\u20e5-\u20f0\u2d81-\u2d96\u2de0-\u2dff\u3021-\u3028\u3099\u309a\ua640-\ua66d\ua674-\ua67d\ua69f\ua6f0-\ua6f1\ua7f8-\ua800\ua806\ua80b\ua823-\ua827\ua880-\ua881\ua8b4-\ua8c4\ua8d0-\ua8d9\ua8f3-\ua8f7\ua900-\ua909\ua926-\ua92d\ua930-\ua945\ua980-\ua983\ua9b3-\ua9c0\uaa00-\uaa27\uaa40-\uaa41\uaa4c-\uaa4d\uaa50-\uaa59\uaa7b\uaae0-\uaae9\uaaf2-\uaaf3\uabc0-\uabe1\uabec\uabed\uabf0-\uabf9\ufb20-\ufb28\ufe00-\ufe0f\ufe20-\ufe26\ufe33\ufe34\ufe4d-\ufe4f\uff10-\uff19\uff3f';
- python.Tokenizer._identifierStart = new RegExp('[' + identifierStartChars + ']');
- /* eslint-disable */
- python.Tokenizer._identifierChar = new RegExp('[' + identifierStartChars + identifierChars + ']');
- /* eslint-enable */
- }
- }
- peek() {
- if (!this._cache) {
- this._tokenize();
- this._cache = true;
- }
- return this._token;
- }
- read() {
- if (!this._cache) {
- this._tokenize();
- }
- const next = this._position + this._token.value.length;
- while (this._position < next) {
- if (python.Tokenizer._isNewline(this._get(this._position))) {
- this._position = this._newLine(this._position);
- this._lineStart = this._position;
- this._line++;
- }
- else {
- this._position++;
- }
- }
- this._cache = false;
- return this._token;
- }
- match(type, value) {
- const token = this.peek();
- if (token.type === type && (!value || token.value === value)) {
- return true;
- }
- return false;
- }
- eat(type, value) {
- const token = this.peek();
- if (token.type === type && (!value || token.value === value)) {
- this.read();
- return true;
- }
- return false;
- }
- expect(type, value) {
- const token = this.peek();
- if (token.type !== type) {
- throw new python.Error("Unexpected '" + token.value + "' instead of '" + type + "'" + this.location());
- }
- if (value && token.value !== value) {
- throw new python.Error("Unexpected '" + token.value + "' instead of '" + value + "'" + this.location());
- }
- this.read();
- }
- location() {
- return ' at ' + this._file + ':' + (this._line + 1).toString() + ':' + (this._position - this._lineStart + 1).toString();
- }
- static _isSpace(c) {
- switch (c) {
- case ' ':
- case '\t':
- case '\v': // 11
- case '\f': // 12
- case '\xA0': // 160
- return true;
- default:
- if (c.charCodeAt(0) >= 0x1680) {
- return python.Tokenizer._whitespace.test(c);
- }
- return false;
- }
- }
- static _isNewline(c) {
- switch (c) {
- case '\n':
- case '\r':
- case '\u2028': // 8232
- case '\u2029': // 8233
- return true;
- default:
- return false;
- }
- }
- static _isIdentifierStartChar(c) {
- if (c < 'A') {
- return c === '$';
- }
- if (c <= 'Z') {
- return true;
- }
- if (c < 'a') {
- return c === '_';
- }
- if (c <= 'z') {
- return true;
- }
- const code = c.charCodeAt(0);
- if (code >= 0xAA) {
- return python.Tokenizer._identifierStart.test(c);
- }
- return false;
- }
- static _isIdentifierChar(c) {
- if (c < '0') {
- return c === '$';
- }
- if (c <= '9') {
- return true;
- }
- if (c < 'A') {
- return false;
- }
- if (c <= 'Z') {
- return true;
- }
- if (c < 'a') {
- return c === '_';
- }
- if (c <= 'z') {
- return true;
- }
- const code = c.charCodeAt(0);
- if (code >= 0xAA) {
- return python.Tokenizer._identifierChar.test(c);
- }
- return false;
- }
- _get(position) {
- return position >= this._text.length ? '\0' : this._text[position];
- }
- _skipLine() {
- while (this._position < this._text.length) {
- if (python.Tokenizer._isNewline(this._get(this._position))) {
- break;
- }
- this._position++;
- }
- }
- _skipWhitespace() {
- while (this._position < this._text.length) {
- const c = this._text[this._position];
- if (c == '#') {
- this._skipLine();
- }
- else if (python.Tokenizer._isSpace(c)) {
- this._position++;
- }
- else if (c == '\\') {
- // Explicit Line Continuation
- this._position++;
- if (python.Tokenizer._isNewline(this._get(this._position))) {
- this._position = this._newLine(this._position);
- this._lineStart = this._position;
- this._line++;
- }
- else {
- throw new python.Error("Unexpected '" + this._text[this._position] + "' after line continuation" + this.location());
- }
- }
- else if (this._brackets > 0 && python.Tokenizer._isNewline(c)) {
- // Implicit Line Continuation
- this._position = this._newLine(this._position);
- this._lineStart = this._position;
- this._line++;
- }
- else {
- break;
- }
- }
- }
- _newLine(position) {
- if ((this._get(position) === '\n' && this._get(position + 1) === '\r') ||
- (this._get(position) === '\r' && this._get(position + 1) === '\n')) {
- return position + 2;
- }
- return position + 1;
- }
- _tokenize() {
- if (this._token.type !== '\n') {
- this._skipWhitespace();
- }
- if (this._token.type === 'dedent') {
- this._indentation.pop();
- this._outdent--;
- if (this._outdent > 0) {
- this._token = { type: 'dedent', value: '' };
- return;
- }
- }
- if (this._token.type == '\n') {
- let indent = '';
- let i = this._position;
- while (i < this._text.length) {
- const c = this._text[i];
- if (python.Tokenizer._isSpace(c)) {
- indent += c;
- i++;
- }
- else if (python.Tokenizer._isNewline(c)) {
- indent = '';
- i = this._newLine(i);
- this._position = i;
- this._lineStart = i;
- this._line++;
- }
- else if (c == '#') {
- indent = '';
- while (i < this._text.length && !python.Tokenizer._isNewline(this._text[i])) {
- i++;
- }
- continue;
- }
- else {
- break;
- }
- }
- let type = null;
- if (indent.length > 0) {
- const current = this._indentation.length > 0 ? this._indentation[this._indentation.length - 1] : '';
- if (indent.length > current.length) {
- type = 'indent';
- this._indentation.push(indent);
- }
- else if (indent.length > 0 && indent.length < current.length) {
- type = 'dedent';
- this._outdent = 0;
- for (let j = this._indentation.length - 1; j >= 0 && indent.length < this._indentation[j].length; j--) {
- this._outdent++;
- }
- }
- else {
- this._position += indent.length;
- }
- }
- else if (i >= this._text.length) {
- this._token = { type: 'eof', value: '' };
- return;
- }
- else if (this._indentation.length > 0) {
- type = 'dedent';
- this._outdent = this._indentation.length;
- }
- if (type === 'indent' || type === 'dedent') {
- this._token = { type: type, value: indent };
- return;
- }
- }
- if (this._position >= this._text.length) {
- this._token = { type: 'eof', value: '' };
- return;
- }
- const c = this._get(this._position);
- const string = this._string();
- if (string) {
- this._token = string;
- return;
- }
- switch (c) {
- case '(':
- case '[':
- case '{':
- this._brackets++;
- this._token = { type: c, value: c };
- return;
- case ')':
- case ']':
- case '}':
- if (this._brackets === 0) {
- throw new python.Error("Unexpected '" + c + "'" + this.location);
- }
- this._brackets--;
- this._token = { type: c, value: c };
- return;
- case ',':
- case ';':
- case '?':
- this._token = { type: c, value: c };
- return;
- default: {
- const number = this._number();
- if (number) {
- this._token = number;
- return;
- }
- if (c === '.') {
- let end = this._position + 1;
- while (this._get(end) === '.') {
- end++;
- }
- const text = this._text.substring(this._position, end);
- this._token = { type: text, value: text };
- return;
- }
- const identifier = this._identifier();
- if (identifier) {
- this._token = identifier;
- return;
- }
- const operator = this._operator();
- if (operator) {
- this._token = operator;
- return;
- }
- break;
- }
- }
- if (c === '.') {
- this._token = { type: c, value: c };
- return;
- }
- if (c === '\\') {
- this._token = { type: '\\', value: c };
- return;
- }
- if (python.Tokenizer._isNewline(c)) {
- this._token = { type: '\n', value: this._text.substring(this._position, this._newLine(this._position)) };
- return;
- }
- throw new python.Error("Unexpected token '" + c + "'" + this.location());
- }
- _number() {
- const octal = (c) => c >= '0' && c <= '7' || c === '_';
- const binary = (c) => c === '0' || c === '1' || c === '_';
- const decimal = (c) => c >= '0' && c <= '9' || c === '_';
- const hex = (c) => decimal(c) || (c >= 'a' && c <= 'f') || (c >= 'A' && c <= 'F') || c === '_';
- let c = this._get(this._position);
- const sign = (c === '-' || c === '+') ? 1 : 0;
- let i = this._position + sign;
- c = this._get(i);
- if (c === '0') {
- let radix = 0;
- const n = this._get(i + 1);
- if ((n === 'x' || n === 'X') && hex(this._get(i + 2))) {
- i += 2;
- while (hex(this._get(i))) {
- i += 1;
- }
- if (this._get(i) === 'l' || this._get(i) === 'L') {
- i += 1;
- }
- radix = 16;
- }
- else if ((n === 'b' || n === 'B') && binary(this._get(i + 2))) {
- i += 2;
- while (binary(this._get(i))) {
- i++;
- }
- radix = 2;
- }
- else if ((n === 'o' || n === 'O') && octal(this._get(i + 2))) {
- i += 2;
- while (octal(this._get(i))) {
- i++;
- }
- radix = 8;
- }
- else if (n >= '0' && n <= '7') {
- i++;
- while (octal(this._get(i))) {
- i += 1;
- }
- if (this._get(i) === 'l' || this._get(i) === 'L') {
- i += 1;
- }
- radix = 8;
- }
- if (radix > 0 && this._get(i) !== '.') {
- const radixText = this._text.substring(this._position, i);
- const radixParseText = radixText.indexOf('_') !== -1 ? radixText.split('_').join('') : radixText;
- if (!isNaN(parseInt(radixParseText, radix))) {
- return { type: 'number', value: radixText };
- }
- }
- }
- i = this._position + sign;
- let isDecimal = false;
- if (this._get(i) >= '1' && this._get(i) <= '9') {
- while (decimal(this._get(i))) {
- i++;
- }
- c = this._get(i).toLowerCase();
- isDecimal = c !== '.' && c !== 'e';
- }
- if (this._get(i) === '0') {
- i++;
- c = this._get(i).toLowerCase();
- isDecimal = !decimal(c) && c !== '.' && c !== 'e' && c !== 'j';
- }
- if (isDecimal) {
- if (this._get(i) === 'j' || this._get(i) === 'J' || this._get(i) === 'l' || this._get(i) === 'L') {
- return { 'type': 'number', value: this._text.substring(this._position, i + 1) };
- }
- const intText = this._text.substring(this._position, i);
- if (!isNaN(parseInt(intText, 10))) {
- return { type: 'number', value: intText };
- }
- }
- i = this._position + sign;
- if ((this._get(i) >= '0' && this._get(i) <= '9') ||
- (this._get(i) === '.' && this._get(i + 1) >= '0' && this._get(i + 1) <= '9')) {
- while (decimal(this._get(i))) {
- i++;
- }
- if (this._get(i) === '.') {
- i++;
- }
- while (decimal(this._get(i))) {
- i++;
- }
- if (i > (this._position + sign)) {
- if (this._get(i) === 'e' || this._get(i) === 'E') {
- i++;
- if (this._get(i) == '-' || this._get(i) == '+') {
- i++;
- }
- if (!decimal(this._get(i))) {
- i = this._position;
- }
- else {
- while (decimal(this._get(i))) {
- i++;
- }
- }
- }
- else {
- while (decimal(this._get(i))) {
- i++;
- }
- }
- }
- if (i > (this._position + sign)) {
- if (this._get(i) === 'j' || this._get(i) === 'J') {
- return { type: 'number', value: this._text.substring(this._position, i + 1) };
- }
- const floatText = this._text.substring(this._position, i);
- const floatParseText = floatText.indexOf('_') != -1 ? floatText.split('_').join('') : floatText;
- if (!isNaN(parseFloat(floatParseText))) {
- return { type: 'number', value: floatText };
- }
- }
- }
- return null;
- }
- _identifier() {
- let i = this._position;
- if (python.Tokenizer._isIdentifierStartChar(this._get(i))) {
- i++;
- while (python.Tokenizer._isIdentifierChar(this._get(i))) {
- i++;
- }
- }
- if (i > this._position) {
- const text = this._text.substring(this._position, i);
- let keyword = false;
- switch (text) {
- case 'and':
- case 'as':
- case 'else':
- case 'for':
- case 'if':
- case 'import':
- case 'in':
- case 'is':
- case 'not':
- case 'or':
- keyword = true;
- break;
- default:
- keyword = false;
- break;
- }
- return { type: 'id', value: text, keyword: keyword };
- }
- return null;
- }
- _operator() {
- let length = 0;
- const c0 = this._get(this._position);
- const c1 = this._get(this._position + 1);
- const c2 = this._get(this._position + 2);
- switch (c0) {
- case '+':
- case '&':
- case '|':
- case '^':
- case '=':
- case '!':
- case '%':
- case '~':
- length = c1 === '=' ? 2 : 1;
- break;
- case '-':
- length = c1 === '=' || c1 === '>' ? 2 : 1;
- break;
- case '*':
- length = c1 === '*' ? (c2 === '=' ? 3 : 2) : (c1 === '=' ? 2 : 1);
- break;
- case '/':
- length = c1 === '/' ? (c2 === '=' ? 3 : 2) : (c1 === '=' ? 2 : 1);
- break;
- case '<':
- length = c1 === '>' ? 2 : (c1 === '<' ? (c2 === '=' ? 3 : 2) : (c1 === '=' ? 2 : 1));
- break;
- case '>':
- length = c1 === '>' ? (c2 === '=' ? 3 : 2) : (c1 === '=' ? 2 : 1);
- break;
- case '@':
- length = c1 === '=' ? 2 : 1;
- break;
- case ':':
- length = c1 === '=' ? 2 : 1;
- break;
- default:
- return null;
- }
- const text = this._text.substring(this._position, this._position + length);
- return { type: text, value: text };
- }
- _string() {
- let i = this._position;
- let prefix = -1;
- if (this._get(i) === "'" || this._get(i) === '"') {
- prefix = '';
- }
- else if (this._get(i + 1) === "'" || this._get(i + 1) === '"') {
- const c = this._get(i);
- switch (c.toLowerCase()) {
- case 'b':
- case 'f':
- case 'r':
- case 'u':
- prefix = c;
- break;
- default:
- break;
- }
- }
- else if (this._get(i + 2) === "'" || this._get(i + 2) === '"') {
- const cc = this._text.substr(this._position, 2);
- switch (cc.toLowerCase()) {
- case 'br':
- case 'fr':
- case 'rb':
- case 'rf':
- case 'ur':
- prefix = cc;
- break;
- default:
- break;
- }
- }
- if (prefix.length >= 0) {
- i += prefix.length;
- let quote = '';
- let count = 0;
- const q0 = this._get(i);
- const q1 = this._get(i + 1);
- const q2 = this._get(i + 2);
- switch (q0) {
- case "'":
- quote = q0;
- count = (q1 === "'" && q2 === "'") ? 3 : 1;
- break;
- case '"':
- quote = q0;
- count = (q1 === '"' && q2 === '"') ? 3 : 1;
- break;
- default:
- throw new python.Error("Unsupported string quote '" + q0 + "'.");
- }
- i += count;
- if (count == 1) {
- while (i < this._text.length) {
- if (this._text[i] === quote) {
- return { type: 'string', value: this._text.substring(this._position, i + 1) };
- }
- else if (this._text[i] === '\\' &&
- (this._get(i + 1) == quote || this._get(i + 1) == '\n' || this._get(i + 1) == '\\')) {
- i += 2;
- }
- else if (this._text[i] === '\r' || this._text[i] === '\n') {
- break;
- }
- else {
- i++;
- }
- }
- }
- else if (count == 3) {
- while (i < this._text.length) {
- if (this._get(i) === quote && this._get(i + 1) === quote && this._get(i + 2) === quote) {
- return { type: 'string', value: this._text.substring(this._position, i + 3) };
- }
- else if (this._get(i) === '\\' && this._get(i + 1) === quote) {
- i += 2;
- continue;
- }
- i++;
- }
- }
- }
- i = this._position;
- if (this._get(i) === '`') {
- i++;
- while (i < this._text.length) {
- if (this._text[i] === '`') {
- return { type: 'string', value: this._text.substring(this._position, i + 1) };
- }
- i++;
- }
- }
- return null;
- }
- };
- python.Execution = class {
- constructor(sources) {
- const self = this;
- const execution = self;
- this._sources = sources || new Map();
- this._events = new Map();
- this._utf8Decoder = new TextDecoder('utf-8');
- this._unresolved = new Map();
- const dict = class extends Map {
- constructor(items) {
- super();
- if (items) {
- for (const pair of items) {
- this.__setitem__(pair[0], pair[1]);
- }
- }
- }
- __contains__(key) {
- return this.has(key);
- }
- __setitem__(key, value) {
- this.set(key, value);
- }
- __getitem__(key) {
- return this.get(key);
- }
- };
- this._modules = new dict();
- this._registry = new Map();
- const module = class {
- constructor(name) {
- this.__name__ = name;
- }
- };
- this._builtins = this.register('builtins', new module('builtins'));
- this._registry.set('__builtin__', this._builtins);
- this.registerType('builtins.type', class {}).__class__ = this._builtins.type;
- this.registerType('builtins.module', module);
- this.registerType('builtins.method', class {});
- this.registerType('builtins.function', class {});
- this.import('builtins');
- this.registerType('builtins.builtin_function_or_method', class {});
- this._typing = this.register('typing');
- this.register('_codecs');
- this.register('argparse');
- this.register('collections');
- this.register('copy_reg');
- this.register('cuml');
- this.register('gensim');
- this.register('io');
- this.register('joblib');
- this.register('keras');
- this.register('lightgbm');
- this.register('nolearn');
- const math = this.register('math');
- math.inf = Infinity;
- const numpy = this.register('numpy');
- const pickle = this.register('pickle');
- this.register('sklearn');
- const torch = this.register('torch');
- this.register('torch.storage');
- this.register('torch.nn.parameter');
- this.register('torch.ops');
- this.register('torch.ops.torchvision');
- this.register('torch.ops.torchaudio');
- this.register('torch.ops._caffe2');
- this.register('torchvision');
- this.register('__torch__');
- this.register('sys').modules = this._modules;
- this.register('xgboost');
- this.registerType('builtins.dict', dict);
- this.registerType('builtins.list', class {});
- this.registerType('builtins.number', class {});
- this.registerFunction('builtins.__import__', function(name, globals, locals, fromlist, level) {
- return execution.__import__(name, globals, locals, fromlist, level);
- });
- this.registerFunction('builtins.bool', function(value) {
- if (value) {
- if (value.__bool__) {
- return value.__bool__();
- }
- if (value.__len__) {
- return value.__len__() > 0;
- }
- }
- return false;
- });
- this.registerFunction('builtins.int', function(value) {
- if (value) {
- if (value.__int__) {
- return value.__int__();
- }
- if (Number.isInteger(value)) {
- return value;
- }
- }
- return NaN;
- });
- this.registerFunction('builtins.float', function(value) {
- if (value) {
- if (value.__float__) {
- return value.__float__();
- }
- if (Number(value) === value) {
- return value;
- }
- }
- return NaN;
- });
- this.registerFunction('builtins.str', function(value) {
- if (value) {
- if (value.__str__) {
- return value.__str__();
- }
- }
- return JSON.stringify(value);
- });
- this.registerType('builtins.object', class {});
- this.registerType('builtins.tuple', class extends Array {
- constructor(items) {
- super(items ? items.length : 0);
- if (items) {
- for (let i = 0; i < items.length; i++) {
- this[i] = items[i];
- }
- }
- }
- });
- this.registerFunction('builtins.long', this.builtins.int);
- this.registerFunction('builtins.print', function() {});
- this.registerFunction('builtins.unicode', function(/* value */) {
- throw new python.Error('Not implemented.');
- });
- this.registerType('builtins.Warning', class {});
- this.registerType('builtins.FutureWarning', class extends this._builtins.Warning {});
- this.registerType('typing._Final', class {});
- this.registerType('typing._SpecialForm', class extends this._typing._Final {});
- this.registerType('typing._BaseGenericAlias', class extends this._typing._Final {});
- this.registerType('typing._GenericAlias', class extends this._typing._BaseGenericAlias {});
- this.registerType('typing._SpecialGenericAlias', class extends this._typing._BaseGenericAlias {});
- this.registerType('typing._TupleType', class extends this._typing._SpecialGenericAlias {});
- this._typing.Optional = Reflect.construct(this._typing._SpecialForm, []);
- this._typing.List = Reflect.construct(this._typing._SpecialGenericAlias, []);
- this._typing.Dict = Reflect.construct(this._typing._SpecialGenericAlias, []);
- this._typing.Tuple = Reflect.construct(this._typing._TupleType, []);
- this._typing.Any = Reflect.construct(this._typing._SpecialForm, []);
- this.registerType('argparse.Namespace', class {
- constructor(args) {
- this.args = args;
- }
- });
- this.registerType('collections.deque', class extends Array {
- constructor(iterable) {
- super();
- if (Array.isArray(iterable)) {
- for (const value of iterable) {
- this.push(value);
- }
- }
- }
- });
- this.registerType('collections.OrderedDict', class extends dict {});
- this.registerType('cuml.common.array_descriptor.CumlArrayDescriptorMeta', class {});
- this.registerType('cuml.ensemble.randomforestclassifier.RandomForestClassifier', class {});
- this.registerType('cuml.raft.common.handle.Handle', class {
- __setstate__(state) {
- this._handle = state;
- }
- });
- this.registerType('dnnlib.tflib.network.Network', class {});
- this.registerType('dnnlib.util.EasyDict', class extends dict {});
- this.registerType('haiku._src.data_structures.FlatMapping', class {
- constructor(dict) {
- Object.assign(this, dict);
- }
- });
- this.registerType('haiku._src.data_structures.frozendict', class {
- constructor(obj) {
- Object.assign(this, obj);
- }
- });
- this.registerType('hmmlearn.hmm.MultinomialHMM', class {
- __setstate__(state) {
- Object.assign(this, state);
- }
- });
- this.registerType('hmmlearn.base.ConvergenceMonitor', class {
- __setstate__(state) {
- Object.assign(this, state);
- }
- });
- this.registerType('io.BytesIO', class {
- constructor(buf, mode) {
- this.mode = mode || 'r';
- this._buf = this.mode === 'w' ? null : buf;
- this._point = 0;
- }
- seek(offset) {
- this._point = offset;
- }
- read(size) {
- const start = this._point;
- this._point = size !== undefined ? start + size : this._buf.length;
- return this._buf.subarray(start, this._point);
- }
- write(data) {
- const src = this._buf || new Uint8Array();
- this._point = src.length + data.length;
- this._buf = new Uint8Array(this._point);
- this._buf.set(src, 0);
- this._buf.set(data, src.length);
- }
- });
- this.registerType('numpy.dtype', class {
- constructor(obj, align, copy) {
- if (typeof obj === 'string' && (obj.startsWith('<') || obj.startsWith('>'))) {
- this.byteorder = obj[0];
- obj = obj.substring(1);
- }
- else {
- this.byteorder = '=';
- }
- switch (obj) {
- case 'b1': case 'bool': this.itemsize = 1; this.kind = 'b'; break;
- case 'i1': case 'int8': this.itemsize = 1; this.kind = 'i'; break;
- case 'i2': case 'int16': this.itemsize = 2; this.kind = 'i'; break;
- case 'i4': case 'int32': this.itemsize = 4; this.kind = 'i'; break;
- case 'i8': case 'int64': case 'int': this.itemsize = 8; this.kind = 'i'; break;
- case 'u1': case 'uint8': this.itemsize = 1; this.kind = 'u'; break;
- case 'u2': case 'uint16': this.itemsize = 2; this.kind = 'u'; break;
- case 'u4': case 'uint32': this.itemsize = 4; this.kind = 'u'; break;
- case 'u8': case 'uint64': case 'uint': this.itemsize = 8; this.kind = 'u'; break;
- case 'f2': case 'float16': this.itemsize = 2; this.kind = 'f'; break;
- case 'f4': case 'float32': this.itemsize = 4; this.kind = 'f'; break;
- case 'f8': case 'float64': case 'float': this.itemsize = 8; this.kind = 'f'; break;
- case 'c8': case 'complex64': this.itemsize = 8; this.kind = 'c'; break;
- case 'c16': case 'complex128': case 'complex': this.itemsize = 16; this.kind = 'c'; break;
- case 'M8': case 'M': this.itemsize = 8; this.kind = 'M'; break;
- default:
- if (obj.startsWith('V')) {
- this.itemsize = parseInt(obj.substring(1), 10);
- this.kind = 'V';
- }
- else if (obj.startsWith('O')) {
- this.itemsize = obj === 'O' ? 8 : parseInt(obj.substring(1), 10);
- this.kind = 'O';
- }
- else if (obj.startsWith('S')) {
- this.itemsize = parseInt(obj.substring(1), 10);
- this.kind = 'S';
- }
- else if (obj.startsWith('U')) { // Unicode string
- this.kind = 'U';
- this.itemsize = 4 * parseInt(obj.substring(1), 10);
- }
- else {
- throw new python.Error("Unsupported dtype '" + obj.toString() + "'.");
- }
- break;
- }
- if (align) {
- this.align = align;
- }
- if (copy) {
- this.copy = copy;
- }
- }
- get str() {
- return (this.byteorder === '=' ? '<' : this.byteorder) + this.kind + this.itemsize.toString();
- }
- get name() {
- switch (this.kind) {
- case 'V': return 'void' + (this.itemsize === 0 ? '' : (this.itemsize * 8).toString());
- case 'S': return 'bytes' + (this.itemsize === 0 ? '' : (this.itemsize * 8).toString());
- case 'U': return 'str' + (this.itemsize === 0 ? '' : (this.itemsize * 8).toString());
- case 'M': return 'datetime64';
- case 'b': return 'bool';
- default: return this.__name__;
- }
- }
- __setstate__(state) {
- switch (state.length) {
- case 8:
- this.version = state[0];
- this.byteorder = state[1];
- this.subarray = state[2];
- this.names = state[3];
- this.fields = state[4];
- this.elsize = state[5];
- this.alignment = state[6];
- this.int_dtypeflags = state[7];
- break;
- case 9:
- this.version = state[0];
- this.byteorder = state[1];
- this.subarray = state[2];
- this.names = state[3];
- this.fields = state[4];
- this.elsize = state[5];
- this.alignment = state[6];
- this.int_dtypeflags = state[7];
- this.metadata = state[8];
- break;
- default:
- throw new python.Error("Unsupported numpy.dtype setstate length '" + state.length.toString() + "'.");
- }
- }
- get __name__() {
- switch (this.kind) {
- case 'b':
- switch (this.itemsize) {
- case 1: return 'boolean';
- default: throw new python.Error("Unsupported boolean itemsize '" + this.itemsize + "'.");
- }
- case 'i':
- switch (this.itemsize) {
- case 1: return 'int8';
- case 2: return 'int16';
- case 4: return 'int32';
- case 8: return 'int64';
- default: throw new python.Error("Unsupported int itemsize '" + this.itemsize + "'.");
- }
- case 'u':
- switch (this.itemsize) {
- case 1: return 'uint8';
- case 2: return 'uint16';
- case 4: return 'uint32';
- case 8: return 'uint64';
- default: throw new python.Error("Unsupported uint itemsize '" + this.itemsize + "'.");
- }
- case 'f':
- switch (this.itemsize) {
- case 2: return 'float16';
- case 4: return 'float32';
- case 8: return 'float64';
- default: throw new python.Error("Unsupported float itemsize '" + this.itemsize + "'.");
- }
- case 'c':
- switch (this.itemsize) {
- case 8: return 'complex64';
- case 16: return 'complex128';
- default: throw new python.Error("Unsupported complex itemsize '" + this.itemsize + "'.");
- }
- case 'S':
- case 'U':
- return 'string';
- case 'M':
- return 'datetime';
- case 'O':
- return 'object';
- case 'V':
- return 'void';
- default:
- throw new python.Error("Unsupported dtype kind '" + this.kind + "'.");
- }
- }
- });
- this.registerType('numpy.generic', class {});
- this.registerType('numpy.inexact', class {});
- this.registerType('numpy.number', class extends numpy.generic {});
- this.registerType('numpy.integer', class extends numpy.number {});
- this.registerType('numpy.floating', class extends numpy.inexact {});
- this.registerType('numpy.float32', class extends numpy.floating {});
- this.registerType('numpy.float64', class extends numpy.floating {});
- this.registerType('numpy.signedinteger', class extends numpy.integer {});
- this.registerType('numpy.int8', class extends numpy.signedinteger {});
- this.registerType('numpy.int16', class extends numpy.signedinteger {});
- this.registerType('numpy.int32', class extends numpy.signedinteger {});
- this.registerType('numpy.int64', class extends numpy.signedinteger {});
- this.registerType('numpy.unsignedinteger', class extends numpy.integer {});
- this.registerType('numpy.uint8', class extends numpy.unsignedinteger {});
- this.registerType('numpy.uint16', class extends numpy.unsignedinteger {});
- this.registerType('numpy.uint32', class extends numpy.unsignedinteger {});
- this.registerType('numpy.uint64', class extends numpy.unsignedinteger {});
- this.registerType('fastai.callback.core.TrainEvalCallback', class {});
- this.registerType('fastai.callback.hook._hook_inner', class {});
- this.registerType('fastai.callback.hook.Hook', class {});
- this.registerType('fastai.callback.hook.Hooks', class {});
- this.registerType('fastai.callback.progress.ProgressCallback', class {});
- this.registerType('fastai.data.core.DataLoaders', class {});
- this.registerType('fastai.data.core.Datasets', class {});
- this.registerType('fastai.data.core.TfmdDL', class {});
- this.registerType('fastai.data.core.TfmdLists', class {});
- this.registerType('fastai.data.load._FakeLoader', class {});
- this.registerType('fastai.data.load._wif', class {});
- this.registerType('fastai.data.transforms.Categorize', class {});
- this.registerType('fastai.data.transforms.CategoryMap', class {});
- this.registerType('fastai.data.transforms.IntToFloatTensor', class {});
- this.registerType('fastai.data.transforms.Normalize', class {});
- this.registerType('fastai.data.transforms.parent_label', class {});
- this.registerType('fastai.data.transforms.ToTensor', class {});
- this.registerType('fastai.imports.noop', class {});
- this.registerType('fastai.layers.AdaptiveConcatPool2d', class {});
- this.registerType('fastai.layers.ConvLayer', class {});
- this.registerType('fastai.layers.Flatten', class {});
- this.registerType('fastai.layers.MergeLayer', class {});
- this.registerType('fastai.layers.PixelShuffle_ICNR', class {});
- this.registerType('fastai.layers.ResBlock', class {});
- this.registerType('fastai.layers.SelfAttention', class {});
- this.registerType('fastai.learner.AvgLoss', class {});
- this.registerType('fastai.learner.AvgMetric', class {});
- this.registerType('fastai.learner.AvgSmoothLoss', class {});
- this.registerType('fastai.learner.Learner', class {});
- this.registerType('fastai.learner.Recorder', class {});
- this.registerType('fastai.losses.CrossEntropyLossFlat', class {});
- this.registerType('fastai.metrics.error_rate', class {});
- this.registerType('fastai.optimizer.Adam', class {});
- this.registerType('fastai.torch_core._fa_rebuild_tensor', class {});
- this.registerType('fastai.torch_core.TensorBase', class {});
- this.registerType('fastai.torch_core.TensorCategory', class {});
- this.registerType('fastai.torch_core.TensorImage', class {});
- this.registerType('fastai.vision.augment._BrightnessLogit', class {});
- this.registerType('fastai.vision.augment._ContrastLogit', class {});
- this.registerType('fastai.vision.augment._WarpCoord', class {});
- this.registerType('fastai.vision.augment.Brightness', class {});
- this.registerType('fastai.vision.augment.flip_mat', class {});
- this.registerType('fastai.vision.augment.Flip', class {});
- this.registerType('fastai.vision.augment.RandomResizedCropGPU', class {});
- this.registerType('fastai.vision.augment.Resize', class {});
- this.registerType('fastai.vision.augment.rotate_mat', class {});
- this.registerType('fastai.vision.augment.zoom_mat', class {});
- this.registerType('fastai.vision.core.PILImage', class {});
- this.registerType('fastai.vision.learner._resnet_split', class {});
- this.registerType('fastai.vision.models.unet.DynamicUnet', class {});
- this.registerType('fastai.vision.models.unet.ResizeToOrig', class {});
- this.registerType('fastai.vision.models.unet.UnetBlock', class {});
- this.registerType('fastcore.basics.fastuple', class {});
- this.registerType('fastcore.basics.GetAttr', class {});
- this.registerType('fastcore.dispatch._TypeDict', class {});
- this.registerType('fastcore.dispatch.TypeDispatch', class {});
- this.registerType('fastcore.foundation.L', class {});
- this.registerType('fastcore.transform.Pipeline', class {});
- this.registerType('fastcore.transform.Transform', class {});
- this.registerType('functools.partial', class {});
- this.registerType('gensim.models.doc2vec.Doctag', class {});
- this.registerType('gensim.models.doc2vec.Doc2Vec', class {});
- this.registerType('gensim.models.doc2vec.Doc2VecTrainables', class {});
- this.registerType('gensim.models.doc2vec.Doc2VecVocab', class {});
- this.registerType('gensim.models.fasttext.FastText', class {});
- this.registerType('gensim.models.fasttext.FastTextTrainables', class {});
- this.registerType('gensim.models.fasttext.FastTextVocab', class {});
- this.registerType('gensim.models.fasttext.FastTextKeyedVectors', class {});
- this.registerType('gensim.models.keyedvectors.Doc2VecKeyedVectors', class {});
- this.registerType('gensim.models.keyedvectors.FastTextKeyedVectors', class {});
- this.registerType('gensim.models.keyedvectors.KeyedVectors', class {});
- this.registerType('gensim.models.keyedvectors.Vocab', class {});
- this.registerType('gensim.models.keyedvectors.Word2VecKeyedVectors', class {});
- this.registerType('gensim.models.phrases.Phrases', class {});
- this.registerType('gensim.models.tfidfmodel.TfidfModel', class {});
- this.registerType('gensim.models.word2vec.Vocab', class {});
- this.registerType('gensim.models.word2vec.Word2Vec', class {});
- this.registerType('gensim.models.word2vec.Word2VecTrainables', class {});
- this.registerType('gensim.models.word2vec.Word2VecVocab', class {});
- this.registerType('google3.learning.deepmind.research.nbr.pbl_jax.clean_jaxline.utils.optimizers.ScaleByLarsState', class {
- constructor(obj) {
- Object.assign(this, obj);
- }
- });
- this.registerType('joblib.numpy_pickle.NumpyArrayWrapper', class {
- constructor(/* subtype, shape, dtype */) {
- }
- __setstate__(state) {
- this.subclass = state.subclass;
- this.dtype = state.dtype;
- this.shape = state.shape;
- this.order = state.order;
- this.allow_mmap = state.allow_mmap;
- }
- __read__(unpickler) {
- if (this.dtype.__name__ == 'object') {
- return unpickler.load();
- }
- const size = this.dtype.itemsize * this.shape.reduce((a, b) => a * b, 1);
- this.data = unpickler.read(size);
- return execution.invoke(this.subclass, [ this.shape, this.dtype, this.data ]);
- }
- });
- this.registerType('keras.engine.sequential.Sequential', class {});
- this.registerType('lasagne.layers.conv.Conv2DLayer', class {});
- this.registerType('lasagne.layers.dense.DenseLayer', class {});
- this.registerType('lasagne.layers.input.InputLayer', class {});
- this.registerType('lasagne.layers.pool.MaxPool2DLayer', class {});
- this.registerType('lightgbm.sklearn.LGBMRegressor', class {});
- this.registerType('lightgbm.sklearn.LGBMClassifier', class {});
- this.registerType('lightgbm.basic.Booster', class {
- constructor() {
- this.average_output = false;
- this.models = [];
- this.loaded_parameter = '';
- }
- __setstate__(state) {
- if (typeof state.handle === 'string') {
- this.LoadModelFromString(state.handle);
- return;
- }
- Object.assign(this, state);
- }
- LoadModelFromString(model_str) {
- const lines = model_str.split('\n');
- const signature = lines.shift() || '?';
- if (signature.trim() !== 'tree') {
- throw new python.Error("Invalid signature '" + signature.trim() + "'.");
- }
- // GBDT::LoadModelFromString() in https://github.com/microsoft/LightGBM/blob/master/src/boosting/gbdt_model_text.cpp
- const key_vals = new Map();
- while (lines.length > 0 && !lines[0].startsWith('Tree=')) {
- const cur_line = lines.shift().trim();
- if (cur_line.length > 0) {
- const strs = cur_line.split('=');
- if (strs.length === 1) {
- key_vals.set(strs[0], '');
- }
- else if (strs.length === 2) {
- key_vals.set(strs[0], strs[1]);
- }
- else if (strs.length > 2) {
- if (strs[0] === "feature_names") {
- key_vals.set(strs[0], cur_line.substring("feature_names=".length));
- }
- else if (strs[0] == 'monotone_constraints') {
- key_vals.set(strs[0], cur_line.substring('monotone_constraints='.length));
- }
- else {
- throw new python.Error('Wrong line: ' + cur_line.substring(0, Math.min(128, cur_line.length)));
- }
- }
- }
- }
- const atoi = (key, value) => {
- if (key_vals.has(key)) {
- return parseInt(key_vals.get(key), 10);
- }
- if (value !== undefined) {
- return value;
- }
- throw new python.Error('Model file does not specify ' + key + '.');
- };
- const list = (key, size) => {
- if (key_vals.has(key)) {
- const value = key_vals.get(key).split(' ');
- if (value.length !== size) {
- throw new python.Error('Wrong size of ' + key + '.');
- }
- return value;
- }
- throw new python.Error('Model file does not contain ' + key + '.');
- };
- this.version = key_vals.get('version') || '';
- this.num_class = atoi('num_class');
- this.num_tree_per_iteration = atoi('num_tree_per_iteration', this.num_class);
- this.label_index = atoi('label_index');
- this.max_feature_idx = atoi('max_feature_idx');
- if (key_vals.has('average_output')) {
- this.average_output = true;
- }
- this.feature_names = list('feature_names', this.max_feature_idx + 1);
- this.feature_infos = list('feature_infos', this.max_feature_idx + 1);
- if (key_vals.has('monotone_constraints')) {
- this.monotone_constraints = list('monotone_constraints', this.max_feature_idx + 1);
- }
- if (key_vals.has('objective')) {
- this.objective = key_vals.get('objective');
- }
- let tree = null;
- while (lines.length > 0) {
- const text = lines.shift();
- const line = text.trim();
- if (line.length === 0) {
- continue;
- }
- if (line.startsWith('Tree=')) {
- tree = { index: parseInt(line.split('=').pop(), 10) };
- this.models.push(tree);
- continue;
- }
- if (line === 'end of trees') {
- break;
- }
- const param = line.split('=');
- if (param.length !== 2) {
- throw new python.Error("Invalid property '" + line + "'.");
- }
- const name = param[0].trim();
- const value = param[1].trim();
- tree[name] = value;
- }
- const ss = [];
- let is_inparameter = false;
- while (lines.length > 0) {
- const text = lines.shift();
- const line = text.trim();
- if (line === 'parameters:') {
- is_inparameter = true;
- continue;
- }
- else if (line === 'end of parameters') {
- break;
- }
- else if (is_inparameter) {
- ss.push(line);
- }
- }
- if (ss.length > 0) {
- this.loaded_parameter = ss.join('\n');
- }
- }
- });
- this.registerFunction('megengine.functional.nn.conv2d', function() {});
- this.registerFunction('megengine.functional.nn.relu', function() {});
- this.registerFunction('megengine.module.qat.module.QATModule._apply_fakequant_with_observer', function() {});
- this.registerFunction('megengine.functional.tensor.concat', function() {});
- this.registerFunction('megengine.functional.tensor.flatten', function() {});
- this.registerType('megengine.core._imperative_rt.common.CompNode', class {});
- this.registerType('megengine.core._imperative_rt.ops.FakeQuant', class {});
- this.registerType('megengine.core._imperative_rt.ops.GetVarShape', class {});
- this.registerType('megengine.core.ops._internal.param_defs.ConvolutionV0.Mode', class {});
- this.registerType('megengine.core.ops._internal.param_defs.Convolution.ComputeMode', class {});
- this.registerType('megengine.module.activation.ReLU', class {});
- this.registerType('megengine.module.batchnorm.BatchNorm1d', class {});
- this.registerType('megengine.module.batchnorm.BatchNorm2d', class {});
- this.registerType('megengine.module.conv.Conv2d', class {});
- this.registerType('megengine.module.conv.ConvTranspose2d', class {});
- this.registerType('megengine.module.identity.Identity', class {});
- this.registerType('megengine.module.linear.Linear', class {});
- this.registerType('megengine.module.module.Module', class {});
- this.registerType('megengine.module.pooling.AvgPool2d', class {});
- this.registerType('megengine.module.pooling.MaxPool2d', class {});
- this.registerType('megengine.module.qat.concat.Concat', class {});
- this.registerType('megengine.module.qat.elemwise.Elemwise', class {});
- this.registerType('megengine.module.sequential.Sequential', class {});
- this.registerType('megengine.quantization.fake_quant.FakeQuantize', class {});
- this.registerType('megengine.quantization.utils.QParams', class {});
- this.registerType('megengine.quantization.utils.QuantMode', class {});
- this.registerType('megengine.quantization.observer.PassiveObserver', class {});
- this.registerType('megengine.quantization.observer.MinMaxObserver', class {});
- this.registerType('megengine.quantization.observer.ExponentialMovingAverageObserver', class {});
- this.registerType('megengine.traced_module.expr.Apply', class {});
- this.registerType('megengine.traced_module.expr.CallFunction', class {});
- this.registerType('megengine.traced_module.expr.CallMethod', class {});
- this.registerType('megengine.traced_module.expr.Constant', class {});
- this.registerType('megengine.traced_module.expr.GetAttr', class {});
- this.registerType('megengine.traced_module.expr.Input', class {});
- this.registerType('megengine.traced_module.fake_quant.FakeQuantize', class {});
- this.registerType('megengine.traced_module.node.ModuleNode', class {});
- this.registerType('megengine.traced_module.node.NodeMixin', class {});
- this.registerType('megengine.traced_module.node.TensorNode', class {});
- this.registerType('megengine.traced_module.pytree.ArgsIndex', class {});
- this.registerType('megengine.traced_module.serialization._ModuleState', class {});
- this.registerType('megengine.traced_module.traced_module.InternalGraph', class {});
- this.registerType('megengine.traced_module.traced_module.NameSpace', class {});
- this.registerType('megengine.traced_module.traced_module.TracedModule', class {});
- this.registerType('megengine.tensor.Parameter', class {
- constructor(data, dtype, device) {
- this.data = data;
- this.dtype = dtype;
- this.device = device;
- }
- });
- this.registerType('megengine.traced_module.pytree.TreeDef', class {
- toString() {
- let content = '';
- for (const child of this.children_defs) {
- content += child.toString() + ",";
- }
- if (typeof this.type === "string") {
- return this.type.split(".").slice(-1) + '(' + content + ')';
- }
- return this.type.__name__ + '(' + content + ')';
- }
- });
- this.registerType('megengine.traced_module.pytree.LeafDef', class {
- toString() {
- let content = '';
- if (this.const_val !== null) {
- content += this.const_val;
- }
- else {
- content += '[';
- }
- for (var t of Object.values(this.type)) {
- content += t.__name__;
- }
- content += ']';
- return content;
- }
- });
- this.registerType('megengine.tensor.Tensor', class {
- constructor(data, dtype, device) {
- this.data = data;
- this.dtype = dtype;
- this.device = device;
- }
- });
- this.registerType('megengine.core.tensor.dtype.QuantDtypeMeta', class {
- constructor(name, cname, np_dtype, qmin, qmax, is_signed) {
- this.name = name;
- this.cname = cname;
- this.np_dtype = np_dtype;
- this.qmin = qmin;
- this.qmax = qmax;
- this.is_signed = is_signed;
- }
- });
- this.registerType('nolearn.lasagne.base.BatchIterator', class {});
- this.registerType('nolearn.lasagne.base.Layers', class {});
- this.registerType('nolearn.lasagne.base.NeuralNet', class {});
- this.registerType('nolearn.lasagne.base.TrainSplit', class {});
- this.registerType('nolearn.lasagne.handlers.PrintLayerInfo', class {});
- this.registerType('nolearn.lasagne.handlers.PrintLog', class {});
- this.registerType('numpy.ndarray', class {
- constructor(shape, dtype, buffer, offset, strides, order) {
- this.shape = shape;
- this.dtype = dtype;
- this.data = buffer !== undefined ? buffer : null;
- this.offset = offset !== undefined ? offset : 0;
- this.strides = strides !== undefined ? strides : null;
- this.order = offset !== undefined ? order : null;
- this.flags = {};
- this._read();
- }
- __setstate__(state) {
- this.version = state[0];
- this.shape = state[1];
- this.dtype = state[2];
- this.flags.fnc = state[3];
- this.data = state[4];
- this._read();
- }
- tobytes() {
- return this.data;
- }
- tolist() {
- if (this.shape.length < 0 || this.shape.length > 1) {
- throw new Error(JSON.stringify(this.shape));
- }
- const size = this.shape.reduce((a, b) => a * b, 1);
- const list = new Array(size);
- switch (this.dtype.kind) {
- case 'U': {
- const data = new Uint32Array(new Uint8Array(this.data).buffer);
- const itemsize = this.dtype.itemsize >> 2;
- let offset = 0;
- for (let i = 0; i < size; i++) {
- const buffer = data.subarray(offset, offset + itemsize);
- const index = buffer.indexOf(0);
- list[i] = Array.from(index >= 0 ? buffer.subarray(0, index) : buffer).map((c) => String.fromCodePoint(c)).join('');
- offset += itemsize;
- }
- return list;
- }
- case 'S': {
- const data = this.data;
- const itemsize = this.dtype.itemsize;
- const decoder = new TextDecoder('utf-8');
- let offset = 0;
- for (let i = 0; i < size; i++) {
- const buffer = data.subarray(offset, offset + itemsize);
- const index = buffer.indexOf(0);
- list[i] = decoder.decode(index >= 0 ? buffer.subarray(0, index) : buffer);
- offset += itemsize;
- }
- return list;
- }
- case 'O': {
- return this.data;
- }
- default: {
- throw new python.Error("Type kind '" + this.dtype.kind + "' not implemented.");
- }
- }
- }
- get size() {
- return (this.shape || []).reduce((a, b) => a * b, 1);
- }
- _read() {
- if (this.data) {
- const length = this.dtype.itemsize * this.size;
- if (typeof this.data == 'string') {
- this.data = this._unescape(this.data, length);
- if (this.data.length != length) {
- throw new python.Error('Invalid string array data size.');
- }
- }
- else if (this.data.length != length) {
- // throw new python.Error('Invalid array data size.');
- }
- }
- }
- _unescape(token, size) {
- const length = token.length;
- const a = new Uint8Array(length);
- if (size && size == length) {
- for (let p = 0; p < size; p++) {
- a[p] = token.charCodeAt(p);
- }
- return a;
- }
- let i = 0;
- let o = 0;
- while (i < length) {
- let c = token.charCodeAt(i++);
- if (c !== 0x5C || i >= length) {
- a[o++] = c;
- }
- else {
- c = token.charCodeAt(i++);
- switch (c) {
- case 0x27: a[o++] = 0x27; break; // '
- case 0x5C: a[o++] = 0x5C; break; // \\
- case 0x22: a[o++] = 0x22; break; // "
- case 0x72: a[o++] = 0x0D; break; // \r
- case 0x6E: a[o++] = 0x0A; break; // \n
- case 0x74: a[o++] = 0x09; break; // \t
- case 0x62: a[o++] = 0x08; break; // \b
- case 0x58: // x
- case 0x78: { // X
- const xsi = i - 1;
- const xso = o;
- for (let xi = 0; xi < 2; xi++) {
- if (i >= length) {
- i = xsi;
- o = xso;
- a[o] = 0x5c;
- break;
- }
- let xd = token.charCodeAt(i++);
- xd = xd >= 65 && xd <= 70 ? xd - 55 : xd >= 97 && xd <= 102 ? xd - 87 : xd >= 48 && xd <= 57 ? xd - 48 : -1;
- if (xd === -1) {
- i = xsi;
- o = xso;
- a[o] = 0x5c;
- break;
- }
- a[o] = a[o] << 4 | xd;
- }
- o++;
- break;
- }
- default:
- if (c < 48 || c > 57) { // 0-9
- a[o++] = 0x5c;
- a[o++] = c;
- }
- else {
- i--;
- const osi = i;
- const oso = o;
- for (let oi = 0; oi < 3; oi++) {
- if (i >= length) {
- i = osi;
- o = oso;
- a[o] = 0x5c;
- break;
- }
- const od = token.charCodeAt(i++);
- if (od < 48 || od > 57) {
- i = osi;
- o = oso;
- a[o] = 0x5c;
- break;
- }
- a[o] = a[o] << 3 | od - 48;
- }
- o++;
- }
- break;
- }
- }
- }
- return a.slice(0, o);
- }
- });
- this.registerType('numpy.ma.core.MaskedArray', class extends numpy.ndarray {
- constructor(data /*, mask, dtype, copy, subok, ndmin, fill_value, keep_mask, hard_mask, shrink, order */) {
- super(data.shape, data.dtype, data.data);
- }
- });
- this.registerType('numpy.core.memmap.memmap', class extends numpy.ndarray {
- constructor(shape, dtype) {
- super(shape, dtype);
- }
- });
- this.registerType('pathlib.Path', class {});
- this.registerType('pathlib.PosixPath', class {});
- this.registerType('pathlib.WindowsPath', class {});
- this.registerType('sklearn.calibration._CalibratedClassifier', class {});
- this.registerType('sklearn.calibration._SigmoidCalibration', class {});
- this.registerType('sklearn.calibration.CalibratedClassifierCV', class {});
- this.registerType('sklearn.compose._column_transformer.ColumnTransformer', class {});
- this.registerType('sklearn.compose._target.TransformedTargetRegressor', class {});
- this.registerType('sklearn.cluster._agglomerative.FeatureAgglomeration', class {});
- this.registerType('sklearn.cluster._dbscan.DBSCAN', class {});
- this.registerType('sklearn.cluster._kmeans.KMeans', class {});
- this.registerType('sklearn.decomposition._fastica.FastICA', class {});
- this.registerType('sklearn.decomposition._pca.PCA', class {});
- this.registerType('sklearn.decomposition._truncated_svd.TruncatedSVD', class {});
- this.registerType('sklearn.decomposition.PCA', class {});
- this.registerType('sklearn.decomposition.pca.PCA', class {});
- this.registerType('sklearn.decomposition.truncated_svd.TruncatedSVD', class {});
- this.registerType('sklearn.discriminant_analysis.LinearDiscriminantAnalysis', class {});
- this.registerType('sklearn.discriminant_analysis.QuadraticDiscriminantAnalysis', class {});
- this.registerType('sklearn.dummy.DummyClassifier', class {});
- this.registerType('sklearn.dummy.DummyRegressor', class {});
- this.registerType('sklearn.externals.joblib.numpy_pickle.NumpyArrayWrapper', class {
- constructor(/* subtype, shape, dtype */) {
- }
- __setstate__(state) {
- this.subclass = state.subclass;
- this.dtype = state.dtype;
- this.shape = state.shape;
- this.order = state.order;
- this.allow_mmap = state.allow_mmap;
- }
- __read__(unpickler) {
- if (this.dtype.__name__ == 'object') {
- return unpickler.load();
- }
- const size = this.dtype.itemsize * this.shape.reduce((a, b) => a * b, 1);
- this.data = unpickler.read(size);
- return execution.invoke(this.subclass, [ this.shape, this.dtype, this.data ]);
- }
- });
- this.registerType('sklearn.externals.joblib.numpy_pickle.NDArrayWrapper', class {
- constructor(/* subtype, shape, dtype */) {
- }
- __setstate__(state) {
- this.subclass = state.subclass;
- this.filename = state.state;
- this.allow_mmap = state.allow_mmap;
- }
- __read__(/* unpickler */) {
- return this; // return execution.invoke(this.subclass, [ this.shape, this.dtype, this.data ]);
- }
- });
- this.registerType('sklearn.ensemble._bagging.BaggingClassifier', class {});
- this.registerType('sklearn.ensemble._forest.RandomForestRegressor', class {});
- this.registerType('sklearn.ensemble._forest.RandomForestClassifier', class {});
- this.registerType('sklearn.ensemble._forest.ExtraTreesClassifier', class {});
- this.registerType('sklearn.ensemble._gb_losses.BinomialDeviance', class {});
- this.registerType('sklearn.ensemble._gb_losses.LeastSquaresError', class {});
- this.registerType('sklearn.ensemble._gb_losses.MultinomialDeviance', class {});
- this.registerType('sklearn.ensemble._gb.GradientBoostingClassifier', class {});
- this.registerType('sklearn.ensemble._gb.GradientBoostingRegressor', class {});
- this.registerType('sklearn.ensemble._hist_gradient_boosting.binning._BinMapper', class {});
- this.registerType('sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingRegressor', class {});
- this.registerType('sklearn.ensemble._hist_gradient_boosting.loss.LeastSquares', class {});
- this.registerType('sklearn.ensemble._hist_gradient_boosting.predictor.TreePredictor', class {});
- this.registerType('sklearn.ensemble._iforest.IsolationForest', class {});
- this.registerType('sklearn.ensemble._stacking.StackingClassifier', class {});
- this.registerType('sklearn.ensemble._voting.VotingClassifier', class {});
- this.registerType('sklearn.ensemble._weight_boosting.AdaBoostClassifier', class {});
- this.registerType('sklearn.ensemble.forest.RandomForestClassifier', class {});
- this.registerType('sklearn.ensemble.forest.RandomForestRegressor', class {});
- this.registerType('sklearn.ensemble.forest.ExtraTreesClassifier', class {});
- this.registerType('sklearn.ensemble.gradient_boosting.BinomialDeviance', class {});
- this.registerType('sklearn.ensemble.gradient_boosting.GradientBoostingClassifier', class {});
- this.registerType('sklearn.ensemble.gradient_boosting.LogOddsEstimator', class {});
- this.registerType('sklearn.ensemble.gradient_boosting.MultinomialDeviance', class {});
- this.registerType('sklearn.ensemble.gradient_boosting.PriorProbabilityEstimator', class {});
- this.registerType('sklearn.ensemble.weight_boosting.AdaBoostClassifier', class {});
- this.registerType('sklearn.feature_extraction._hashing.FeatureHasher', class {});
- this.registerType('sklearn.feature_extraction.text.CountVectorizer', class {});
- this.registerType('sklearn.feature_extraction.text.HashingVectorizer', class {});
- this.registerType('sklearn.feature_extraction.text.TfidfTransformer', class {});
- this.registerType('sklearn.feature_extraction.text.TfidfVectorizer', class {});
- this.registerType('sklearn.feature_selection._from_model.SelectFromModel', class {});
- this.registerType('sklearn.feature_selection._univariate_selection.GenericUnivariateSelect', class {});
- this.registerType('sklearn.feature_selection._univariate_selection.SelectKBest', class {});
- this.registerType('sklearn.feature_selection._univariate_selection.SelectPercentile', class {});
- this.registerType('sklearn.feature_selection._variance_threshold.VarianceThreshold', class {});
- this.registerType('sklearn.feature_selection.univariate_selection.SelectKBest', class {});
- this.registerType('sklearn.feature_selection.variance_threshold.VarianceThreshold', class {});
- this.registerType('sklearn.gaussian_process._gpr.GaussianProcessRegressor', class {});
- this.registerType('sklearn.gaussian_process.gpc.GaussianProcessClassifier', class {});
- this.registerType('sklearn.gaussian_process.kernels.ConstantKernel', class {});
- this.registerType('sklearn.gaussian_process.kernels.DotProduct', class {});
- this.registerType('sklearn.gaussian_process.kernels.Product', class {});
- this.registerType('sklearn.gaussian_process.kernels.RBF', class {});
- this.registerType('sklearn.gaussian_process.kernels.Sum', class {});
- this.registerType('sklearn.gaussian_process.kernels.WhiteKernel', class {});
- this.registerType('sklearn.grid_search._CVScoreTuple', class {});
- this.registerType('sklearn.grid_search.GridSearchCV', class {});
- this.registerType('sklearn.impute._base.SimpleImputer', class {});
- this.registerType('sklearn.impute.SimpleImputer', class {});
- this.registerType('sklearn.isotonic.IsotonicRegression', class {});
- this.registerType('sklearn.linear_model._base.LinearRegression', class {});
- this.registerType('sklearn.linear_model._bayes.BayesianRidge', class {});
- this.registerType('sklearn.linear_model._coordinate_descent.ElasticNetCV', class {});
- this.registerType('sklearn.linear_model._coordinate_descent.ElasticNet', class {});
- this.registerType('sklearn.linear_model._logistic.LogisticRegression', class {});
- this.registerType('sklearn.linear_model._ridge.Ridge', class {});
- this.registerType('sklearn.linear_model._ridge.RidgeClassifier', class {});
- this.registerType('sklearn.linear_model._sgd_fast.Hinge', class {});
- this.registerType('sklearn.linear_model._sgd_fast.Log', class {});
- this.registerType('sklearn.linear_model._sgd_fast.ModifiedHuber', class {});
- this.registerType('sklearn.linear_model._sgd_fast.SquaredHinge', class {});
- this.registerType('sklearn.linear_model._stochastic_gradient.SGDClassifier', class {});
- this.registerType('sklearn.linear_model.base.LinearRegression', class {});
- this.registerType('sklearn.linear_model.sgd_fast.Hinge', class {});
- this.registerType('sklearn.linear_model.LogisticRegression', class {});
- this.registerType('sklearn.linear_model.logistic.LogisticRegression', class {});
- this.registerType('sklearn.linear_model.logistic.LogisticRegressionCV', class {});
- this.registerType('sklearn.linear_model.LassoLars', class {});
- this.registerType('sklearn.linear_model.ridge.Ridge', class {});
- this.registerType('sklearn.linear_model.sgd_fast.Log', class {});
- this.registerType('sklearn.linear_model.stochastic_gradient.SGDClassifier', class {});
- this.registerType('sklearn.metrics._classification.accuracy_score', class {});
- this.registerType('sklearn.metrics._regression.mean_squared_error', class {});
- this.registerType('sklearn.metrics._scorer._PredictScorer', class {});
- this.registerType('sklearn.metrics.scorer._PredictScorer', class {});
- this.registerType('sklearn.metrics._scorer._ThresholdScorer', class {});
- this.registerType('sklearn.mixture._bayesian_mixture.BayesianGaussianMixture', class {});
- this.registerType('sklearn.model_selection._search.GridSearchCV', class {});
- this.registerType('sklearn.model_selection._search.RandomizedSearchCV', class {});
- this.registerType('sklearn.model_selection._split.KFold', class {});
- this.registerType('sklearn.model_selection._split.StratifiedKFold', class {});
- this.registerType('sklearn.multiclass.OneVsRestClassifier', class {});
- this.registerType('sklearn.multioutput.MultiOutputClassifier', class {});
- this.registerType('sklearn.multioutput.MultiOutputRegressor', class {});
- this.registerType('sklearn.naive_bayes.BernoulliNB', class {});
- this.registerType('sklearn.naive_bayes.ComplementNB', class {});
- this.registerType('sklearn.naive_bayes.GaussianNB', class {});
- this.registerType('sklearn.naive_bayes.MultinomialNB', class {});
- this.registerType('sklearn.neighbors._classification.KNeighborsClassifier', class {});
- this.registerType('sklearn.neighbors._dist_metrics.newObj', class {});
- this.registerType('sklearn.neighbors._dist_metrics.EuclideanDistance', class {});
- this.registerType('sklearn.neighbors._kd_tree.KDTree', class {});
- this.registerType('sklearn.neighbors._kd_tree.newObj', class {});
- this.registerType('sklearn.neighbors._regression.KNeighborsRegressor', class {});
- this.registerType('sklearn.neighbors.classification.KNeighborsClassifier', class {});
- this.registerType('sklearn.neighbors.dist_metrics.newObj', class {});
- this.registerType('sklearn.neighbors.dist_metrics.EuclideanDistance', class {});
- this.registerType('sklearn.neighbors.kd_tree.newObj', class {});
- this.registerType('sklearn.neighbors.kd_tree.KDTree', class {});
- this.registerType('sklearn.neighbors.KNeighborsClassifier', class {});
- this.registerType('sklearn.neighbors.KNeighborsRegressor', class {});
- this.registerType('sklearn.neighbors.regression.KNeighborsRegressor', class {});
- this.registerType('sklearn.neighbors.unsupervised.NearestNeighbors', class {});
- this.registerType('sklearn.neural_network._multilayer_perceptron.MLPClassifier', class {});
- this.registerType('sklearn.neural_network._multilayer_perceptron.MLPRegressor', class {});
- this.registerType('sklearn.neural_network._stochastic_optimizers.AdamOptimizer', class {});
- this.registerType('sklearn.neural_network._stochastic_optimizers.SGDOptimizer', class {});
- this.registerType('sklearn.neural_network.rbm.BernoulliRBM', class {});
- this.registerType('sklearn.neural_network.multilayer_perceptron.MLPClassifier', class {});
- this.registerType('sklearn.neural_network.multilayer_perceptron.MLPRegressor', class {});
- this.registerType('sklearn.neural_network.stochastic_gradient.SGDClassifier', class {});
- this.registerType('sklearn.pipeline.Pipeline', class {});
- this.registerType('sklearn.pipeline.FeatureUnion', class {});
- this.registerType('sklearn.preprocessing._data.MinMaxScaler', class {});
- this.registerType('sklearn.preprocessing._data.MaxAbsScaler', class {});
- this.registerType('sklearn.preprocessing._data.Normalizer', class {});
- this.registerType('sklearn.preprocessing._data.PolynomialFeatures', class {});
- this.registerType('sklearn.preprocessing._data.PowerTransformer', class {});
- this.registerType('sklearn.preprocessing._data.QuantileTransformer', class {});
- this.registerType('sklearn.preprocessing._data.RobustScaler', class {});
- this.registerType('sklearn.preprocessing._data.StandardScaler', class {});
- this.registerType('sklearn.preprocessing._discretization.KBinsDiscretizer', class {});
- this.registerType('sklearn.preprocessing._encoders.OneHotEncoder', class {});
- this.registerType('sklearn.preprocessing._function_transformer.FunctionTransformer', class {});
- this.registerType('sklearn.preprocessing._label.LabelBinarizer', class {});
- this.registerType('sklearn.preprocessing._label.LabelEncoder', class {});
- this.registerType('sklearn.preprocessing._label.MultiLabelBinarizer', class {});
- this.registerType('sklearn.preprocessing._polynomial.PolynomialFeatures', class {});
- this.registerType('sklearn.preprocessing.data.Binarizer', class {});
- this.registerType('sklearn.preprocessing.data.MaxAbsScaler', class {});
- this.registerType('sklearn.preprocessing.data.MinMaxScaler', class {});
- this.registerType('sklearn.preprocessing.data.Normalizer', class {});
- this.registerType('sklearn.preprocessing.data.OneHotEncoder', class {});
- this.registerType('sklearn.preprocessing.data.PolynomialFeatures', class {});
- this.registerType('sklearn.preprocessing.data.PowerTransformer', class {});
- this.registerType('sklearn.preprocessing.data.RobustScaler', class {});
- this.registerType('sklearn.preprocessing.data.QuantileTransformer', class {});
- this.registerType('sklearn.preprocessing.data.StandardScaler', class {});
- this.registerType('sklearn.preprocessing.imputation.Imputer', class {});
- this.registerType('sklearn.preprocessing.label.LabelBinarizer', class {});
- this.registerType('sklearn.preprocessing.label.LabelEncoder', class {});
- this.registerType('sklearn.preprocessing.label.MultiLabelBinarizer', class {});
- this.registerType('sklearn.svm._classes.LinearSVC', class {});
- this.registerType('sklearn.svm._classes.NuSVC', class {});
- this.registerType('sklearn.svm._classes.OneClassSVM', class {});
- this.registerType('sklearn.svm._classes.SVC', class {});
- this.registerType('sklearn.svm._classes.SVR', class {});
- this.registerType('sklearn.svm.classes.LinearSVC', class {});
- this.registerType('sklearn.svm.classes.OneClassSVM', class {});
- this.registerType('sklearn.svm.classes.SVC', class {});
- this.registerType('sklearn.svm.classes.SVR', class {});
- this.registerType('sklearn.tree._classes.DecisionTreeClassifier', class {});
- this.registerType('sklearn.tree._classes.DecisionTreeRegressor', class {});
- this.registerType('sklearn.tree._classes.ExtraTreeClassifier', class {});
- this.registerType('sklearn.tree._classes.ExtraTreeRegressor', class {});
- this.registerType('sklearn.tree._tree.Tree', class {
- constructor(n_features, n_classes, n_outputs) {
- this.n_features = n_features;
- this.n_classes = n_classes;
- this.n_outputs = n_outputs;
- }
- __setstate__(state) {
- this.max_depth = state.max_depth;
- this.node_count = state.node_count;
- this.nodes = state.nodes;
- this.values = state.values;
- }
- });
- this.registerType('sklearn.tree.tree.DecisionTreeClassifier', class {});
- this.registerType('sklearn.tree.tree.DecisionTreeRegressor', class {});
- this.registerType('sklearn.tree.tree.ExtraTreeClassifier', class {});
- this.registerType('sklearn.utils._bunch.Bunch', class {});
- this.registerType('sklearn.utils.deprecation.DeprecationDict', class {});
- this.registerType('pickle.Unpickler', class {
- constructor(data) {
- this._reader = data instanceof Uint8Array ? new python.BinaryReader(data) : new python.StreamReader(data);
- this.persistent_load = () => {
- throw new python.Error('Unsupported persistent id.');
- };
- }
- load() {
- const reader = this._reader;
- const marker = [];
- let stack = [];
- const memo = new Map();
- while (reader.position < reader.length) {
- const opcode = reader.byte();
- // console.log((reader.position - 1).toString() + ' ' + Object.entries(OpCode).find((entry) => entry[1] === opcode)[0]);
- // https://svn.python.org/projects/python/trunk/Lib/pickletools.py
- // https://github.com/python/cpython/blob/master/Lib/pickle.py
- switch (opcode) {
- case 128: { // PROTO
- const version = reader.byte();
- if (version > 5) {
- throw new python.Error("Unsupported protocol version '" + version + "'.");
- }
- break;
- }
- case 99: { // GLOBAL 'c'
- const module = reader.line();
- const name = reader.line();
- stack.push(this.find_class(module, name));
- break;
- }
- case 147: { // STACK_GLOBAL '\x93' (Protocol 4)
- const name = stack.pop();
- const module = stack.pop();
- stack.push(this.find_class(module, name));
- break;
- }
- case 111: { // OBJ 'o'
- const args = stack;
- const cls = args.pop();
- stack = marker.pop();
- const obj = this._instantiate(cls, args);
- stack.push(obj);
- break;
- }
- case 112 : { // PUT 'p'
- const index = parseInt(reader.line(), 10);
- memo.set(index, stack[stack.length - 1]);
- break;
- }
- case 103: { // GET 'g'
- const index = parseInt(reader.line(), 10);
- stack.push(memo.get(index));
- break;
- }
- case 48: // POP '0'
- stack.pop();
- break;
- case 49: // POP_MARK '1'
- stack = marker.pop();
- break;
- case 50: // DUP '2'
- stack.push(stack[stack.length-1]);
- break;
- case 80: // PERSID 'P'
- stack.push(this.persistent_load(reader.line()));
- break;
- case 81: // BINPERSID 'Q'
- stack.push(this.persistent_load(stack.pop()));
- break;
- case 82: { // REDUCE 'R'
- const args = stack.pop();
- const func = stack.pop();
- stack.push(this._reduce(func, args));
- break;
- }
- case 129: { // NEWOBJ
- const args = stack.pop();
- const cls = stack.pop();
- const obj = this._newobj(cls, args);
- stack.push(obj);
- break;
- }
- case 146: { // NEWOBJ_EX '\x92' (Protocol 4)
- const kwargs = stack.pop();
- const args = stack.pop();
- const cls = stack.pop();
- if (Object.entries(kwargs).length > 0) {
- throw new python.Error("Unpickle 'NEWOBJ_EX' not implemented.");
- }
- const obj = this._newobj(cls, args);
- stack.push(obj);
- break;
- }
- case 104: // BINGET 'h'
- stack.push(memo.get(reader.byte()));
- break;
- case 105: { // INST 'i'
- const module = reader.line();
- const name = reader.line();
- const args = stack;
- const cls = module + '.' + name;
- stack = marker.pop();
- // TODO
- // cls = this.find_class(module, name)
- const obj = this._instantiate(cls, args);
- stack.push(obj);
- break;
- }
- case 106: // LONG_BINGET 'j'
- stack.push(memo.get(reader.uint32()));
- break;
- case 113: // BINPUT 'q'
- memo.set(reader.byte(), stack[stack.length - 1]);
- break;
- case 114: // LONG_BINPUT 'r'
- memo.set(reader.uint32(), stack[stack.length - 1]);
- break;
- case 74: // BININT 'J'
- stack.push(reader.int32());
- break;
- case 75: // BININT1 'K'
- stack.push(reader.byte());
- break;
- case 76: // LONG 'L'
- stack.push(parseInt(reader.line(), 10));
- break;
- case 77: // BININT2 'M'
- stack.push(reader.uint16());
- break;
- case 66: // BINBYTES 'B' (Protocol 3)
- stack.push(reader.read(reader.int32()));
- break;
- case 67: // SHORT_BINBYTES 'C' (Protocol 3)
- stack.push(reader.read(reader.byte()));
- break;
- case 142: // BINBYTES8 '\x8e' (Protocol 4)
- stack.push(reader.read(reader.int64()));
- break;
- case 70: // FLOAT 'F'
- stack.push(parseFloat(reader.line()));
- break;
- case 71: // BINFLOAT 'G'
- stack.push(reader.float64());
- break;
- case 73: { // INT 'I'
- const value = reader.line();
- if (value == '01') {
- stack.push(true);
- }
- else if (value == '00') {
- stack.push(false);
- }
- else {
- stack.push(parseInt(value, 10));
- }
- break;
- }
- case 93: // EMPTY_LIST ']'
- stack.push([]);
- break;
- case 41: // EMPTY_TUPLE ')'
- stack.push([]);
- break;
- case 143: // EMPTY_SET '\x8f' (Protocol 4)
- stack.push([]);
- break;
- case 144: { // ADDITEMS '\x90' (Protocol 4)
- const items = stack;
- stack = marker.pop();
- const obj = stack[stack.length - 1];
- for (let i = 0; i < items.length; i++) {
- obj.push(items[i]);
- }
- break;
- }
- case 145: { // FROZENSET '\x91' (Protocol 4)
- const items = stack;
- stack = marker.pop();
- stack.push(items);
- break;
- }
- case 100: { // DICT 'd'
- const items = stack;
- stack = marker.pop();
- const dict = {};
- for (let i = 0; i < items.length; i += 2) {
- dict[items[i]] = items[i + 1];
- }
- stack.push(dict);
- break;
- }
- case 108: { // LIST 'l'
- const items = stack;
- stack = marker.pop();
- stack.push(items);
- break;
- }
- case 116: { // TUPLE 't'
- const items = stack;
- stack = marker.pop();
- stack.push(items);
- break;
- }
- case 133: { // TUPLE1 // '\x85'
- stack.push([ stack.pop() ]);
- break;
- }
- case 134: { // TUPLE2 '\x86'
- const b = stack.pop();
- const a = stack.pop();
- stack.push([ a, b ]);
- break;
- }
- case 135: { // TUPLE3 '\x87'
- const c = stack.pop();
- const b = stack.pop();
- const a = stack.pop();
- stack.push([ a, b, c ]);
- break;
- }
- case 115: { // SETITEM 's'
- const value = stack.pop();
- const key = stack.pop();
- const obj = stack[stack.length - 1];
- if (obj.__setitem__) {
- obj.__setitem__(key, value);
- }
- else {
- obj[key] = value;
- }
- break;
- }
- case 117: { // SETITEMS 'u'
- const items = stack;
- stack = marker.pop();
- const obj = stack[stack.length - 1];
- for (let i = 0; i < items.length; i += 2) {
- if (obj.__setitem__) {
- obj.__setitem__(items[i], items[i + 1]);
- }
- else {
- obj[items[i]] = items[i + 1];
- }
- }
- break;
- }
- case 125: // EMPTY_DICT '}'
- stack.push({});
- break;
- case 97: { // APPEND 'a'
- const append = stack.pop();
- stack[stack.length-1].push(append);
- break;
- }
- case 101: { // APPENDS 'e'
- const appends = stack;
- stack = marker.pop();
- const list = stack[stack.length - 1];
- list.push.apply(list, appends);
- break;
- }
- case 83: { // STRING 'S'
- const str = reader.line();
- stack.push(str.substr(1, str.length - 2));
- break;
- }
- case 84: // BINSTRING 'T'
- stack.push(reader.string(reader.uint32()));
- break;
- case 85 : // SHORT_BINSTRING 'U'
- stack.push(reader.string(reader.byte()));
- break;
- case 86: // UNICODE 'V'
- stack.push(reader.line());
- break;
- case 88: // BINUNICODE 'X
- stack.push(reader.string(reader.uint32(), 'utf-8'));
- break;
- case 140: // SHORT_BINUNICODE '\x8c' (Protocol 4)
- stack.push(reader.string(reader.byte(), 'utf-8'));
- break;
- case 98: { // BUILD 'b'
- const state = stack.pop();
- let obj = stack.pop();
- if (obj.__setstate__) {
- if (obj.__setstate__.__call__) {
- obj.__setstate__.__call__([ obj, state ]);
- }
- else {
- obj.__setstate__(state);
- }
- }
- else if (ArrayBuffer.isView(state) || Object(state) !== state) {
- obj.__state__ = state;
- }
- else if (obj instanceof Map) {
- for (const key in state) {
- obj.set(key, state[key]);
- }
- }
- else {
- Object.assign(obj, state);
- }
- if (obj.__read__) {
- obj = obj.__read__(this);
- }
- stack.push(obj);
- break;
- }
- case 40: // MARK '('
- marker.push(stack);
- stack = [];
- break;
- case 136: // NEWTRUE '\x88'
- stack.push(true);
- break;
- case 137: // NEWFALSE '\x89'
- stack.push(false);
- break;
- case 138: { // LONG1 '\x8a'
- const data = reader.read(reader.byte());
- let number = 0;
- switch (data.length) {
- case 0: number = 0; break;
- case 1: number = data[0]; break;
- case 2: number = data[1] << 8 | data[0]; break;
- case 3: number = data[2] << 16 | data[1] << 8 | data[0]; break;
- case 4: number = data[3] << 24 | data[2] << 16 | data[1] << 8 | data[0]; break;
- case 5: number = data[4] * 0x100000000 + ((data[3] << 24 | data[2] << 16 | data[1] << 8 | data[0]) >>> 0); break;
- default: number = Array.prototype.slice.call(data, 0); break;
- }
- stack.push(number);
- break;
- }
- case 139: // LONG4 '\x8b'
- // TODO decode LONG4
- stack.push(reader.read(reader.uint32()));
- break;
- case 148: // MEMOIZE '\x94' (Protocol 4)
- memo.set(memo.size, stack[stack.length - 1]);
- break;
- case 149: // FRAME '\x95' (Protocol 4)
- reader.read(8);
- break;
- case 150: { // BYTEARRAY8 '\x96' (Protocol 5)
- stack.push(reader.read(reader.int64()));
- break;
- }
- case 78: // NONE 'N'
- stack.push(null);
- break;
- case 46: // STOP '.'
- return stack.pop();
- case 141: // BINUNICODE8 '\x8d' (Protocol 4)
- case 151: // NEXT_BUFFER '\x97' (Protocol 5)
- case 152: // READONLY_BUFFER '\x98' (Protocol 5)
- default:
- throw new python.Error('Unknown opcode ' + opcode + ' at position ' + (reader.position - 1).toString() + '.');
- }
- }
- throw new python.Error('Unexpected end of file.');
- }
- find_class(module, name) {
- execution.__import__(module);
- return execution.resolve(module + '.' + name);
- }
- _instantiate(cls, args) {
- return execution.invoke(cls, args);
- }
- _newobj(cls, args) {
- // cls.__new__(cls, args)
- return execution.invoke(cls, args);
- }
- _reduce(func, args) {
- return execution.invoke(func, args);
- }
- read(size) {
- return this._reader.read(size);
- }
- stream(size) {
- return this._reader.stream(size);
- }
- });
- this.registerType('random.Random', class {});
- this.registerType('re.Pattern', class {
- constructor(pattern, flags) {
- this.pattern = pattern;
- this.flags = flags;
- }
- });
- this.registerType('spacy._ml.PrecomputableAffine', class {
- __setstate__(state) {
- Object.assign(this, new pickle.Unpickler(state).load());
- }
- });
- this.registerType('spacy.syntax._parser_model.ParserModel', class {
- __setstate__(state) {
- Object.assign(this, new pickle.Unpickler(state).load());
- }
- });
- this.registerType('theano.compile.function_module._constructor_Function', class {});
- this.registerType('theano.compile.function_module._constructor_FunctionMaker', class {});
- this.registerType('theano.compile.function_module.Function', class {});
- this.registerType('theano.compile.function_module.Supervisor', class {});
- this.registerType('theano.compile.io.In', class {});
- this.registerType('theano.compile.io.SymbolicOutput', class {});
- this.registerType('theano.compile.mode.Mode', class {});
- this.registerType('theano.compile.ops.OutputGuard', class {});
- this.registerType('theano.compile.ops.Shape', class {});
- this.registerType('theano.compile.ops.Shape_i', class {});
- this.registerType('theano.gof.destroyhandler.DestroyHandler', class {});
- this.registerType('theano.gof.fg.FunctionGraph', class {});
- this.registerType('theano.gof.graph.Apply', class {});
- this.registerType('theano.gof.link.Container', class {});
- this.registerType('theano.gof.opt._metadict', class {});
- this.registerType('theano.gof.opt.ChangeTracker', class {});
- this.registerType('theano.gof.opt.MergeFeature', class {});
- this.registerType('theano.gof.optdb.Query', class {});
- this.registerType('theano.gof.toolbox.PreserveVariableAttributes', class {});
- this.registerType('theano.gof.toolbox.ReplaceValidate', class {});
- this.registerType('theano.gof.utils.scratchpad', class {});
- this.registerType('theano.misc.ordered_set.Link', class {});
- this.registerType('theano.misc.ordered_set.OrderedSet', class {});
- this.registerType('theano.sandbox.cuda.basic_ops.HostFromGpu', class {});
- this.registerType('theano.sandbox.cuda.type.CudaNdarray_unpickler', class {});
- this.registerType('theano.sandbox.cuda.type.CudaNdarrayType', class {});
- this.registerType('theano.sandbox.cuda.var.CudaNdarraySharedVariable', class {});
- this.registerType('theano.scalar.basic.Abs', class {});
- this.registerType('theano.scalar.basic.Add', class {});
- this.registerType('theano.scalar.basic.Cast', class {});
- this.registerType('theano.scalar.basic.Composite', class {});
- this.registerType('theano.scalar.basic.EQ', class {});
- this.registerType('theano.scalar.basic.GE', class {});
- this.registerType('theano.scalar.basic.Identity', class {});
- this.registerType('theano.scalar.basic.IntDiv', class {});
- this.registerType('theano.scalar.basic.Inv', class {});
- this.registerType('theano.scalar.basic.LE', class {});
- this.registerType('theano.scalar.basic.LT', class {});
- this.registerType('theano.scalar.basic.Mul', class {});
- this.registerType('theano.scalar.basic.Neg', class {});
- this.registerType('theano.scalar.basic.Scalar', class {});
- this.registerType('theano.scalar.basic.ScalarConstant', class {});
- this.registerType('theano.scalar.basic.ScalarVariable', class {});
- this.registerType('theano.scalar.basic.Second', class {});
- this.registerType('theano.scalar.basic.Sgn', class {});
- this.registerType('theano.scalar.basic.specific_out', class {});
- this.registerType('theano.scalar.basic.Sub', class {});
- this.registerType('theano.scalar.basic.Switch', class {});
- this.registerType('theano.scalar.basic.Tanh', class {});
- this.registerType('theano.scalar.basic.transfer_type', class {});
- this.registerType('theano.scalar.basic.TrueDiv', class {});
- this.registerType('theano.tensor.basic.Alloc', class {});
- this.registerType('theano.tensor.basic.Dot', class {});
- this.registerType('theano.tensor.basic.MaxAndArgmax', class {});
- this.registerType('theano.tensor.basic.Reshape', class {});
- this.registerType('theano.tensor.basic.ScalarFromTensor', class {});
- this.registerType('theano.tensor.blas.Dot22', class {});
- this.registerType('theano.tensor.blas.Dot22Scalar', class {});
- this.registerType('theano.tensor.blas.Gemm', class {});
- this.registerType('theano.tensor.elemwise.DimShuffle', class {});
- this.registerType('theano.tensor.elemwise.Elemwise', class {});
- this.registerType('theano.tensor.elemwise.Sum', class {});
- this.registerType('theano.tensor.nnet.abstract_conv.AbstractConv2d', class {});
- this.registerType('theano.tensor.nnet.abstract_conv.AbstractConv2d_gradInputs', class {});
- this.registerType('theano.tensor.nnet.abstract_conv.AbstractConv2d_gradWeights', class {});
- this.registerType('theano.tensor.nnet.corr.CorrMM', class {});
- this.registerType('theano.tensor.nnet.corr.CorrMM_gradInputs', class {});
- this.registerType('theano.tensor.nnet.corr.CorrMM_gradWeights', class {});
- this.registerType('theano.tensor.nnet.nnet.CrossentropyCategorical1Hot', class {});
- this.registerType('theano.tensor.nnet.nnet.CrossentropyCategorical1HotGrad', class {});
- this.registerType('theano.tensor.nnet.nnet.CrossentropySoftmax1HotWithBiasDx', class {});
- this.registerType('theano.tensor.nnet.nnet.CrossentropySoftmaxArgmax1HotWithBias', class {});
- this.registerType('theano.tensor.nnet.nnet.Softmax', class {});
- this.registerType('theano.tensor.nnet.nnet.SoftmaxGrad', class {});
- this.registerType('theano.tensor.nnet.nnet.SoftmaxWithBias', class {});
- this.registerType('theano.tensor.opt.MakeVector', class {});
- this.registerType('theano.tensor.opt.ShapeFeature', class {});
- this.registerType('theano.tensor.sharedvar.TensorSharedVariable', class {});
- this.registerType('theano.tensor.signal.pool.MaxPoolGrad', class {});
- this.registerType('theano.tensor.signal.pool.Pool', class {});
- this.registerType('theano.tensor.subtensor.Subtensor', class {});
- this.registerType('theano.tensor.type.TensorType', class {});
- this.registerType('theano.tensor.var.TensorConstant', class {});
- this.registerType('theano.tensor.var.TensorConstantSignature', class {});
- this.registerType('theano.tensor.var.TensorVariable', class {});
- this.registerType('thinc.describe.Biases', class {
- __setstate__(state) {
- Object.assign(this, state);
- }
- });
- this.registerType('thinc.describe.Dimension', class {
- __setstate__(state) {
- Object.assign(this, state);
- }
- });
- this.registerType('thinc.describe.Gradient', class {
- __setstate__(state) {
- Object.assign(this, state);
- }
- });
- this.registerType('thinc.describe.Weights', class {
- __setstate__(state) {
- Object.assign(this, state);
- }
- });
- this.registerType('thinc.describe.Synapses', class {
- __setstate__(state) {
- Object.assign(this, state);
- }
- });
- this.registerType('thinc.neural._classes.affine.Affine', class {
- __setstate__(state) {
- Object.assign(this, new pickle.Unpickler(state).load());
- }
- });
- this.registerType('thinc.neural._classes.convolution.ExtractWindow', class {
- __setstate__(state) {
- Object.assign(this, new pickle.Unpickler(state).load());
- }
- });
- this.registerType('thinc.neural._classes.feature_extracter.FeatureExtracter', class {
- __setstate__(state) {
- Object.assign(this, new pickle.Unpickler(state).load());
- }
- });
- this.registerType('thinc.neural._classes.feed_forward.FeedForward', class {
- __setstate__(state) {
- Object.assign(this, new pickle.Unpickler(state).load());
- }
- });
- this.registerType('thinc.neural._classes.function_layer.FunctionLayer', class {
- __setstate__(state) {
- Object.assign(this, new pickle.Unpickler(state).load());
- }
- });
- this.registerType('thinc.neural._classes.hash_embed.HashEmbed', class {
- __setstate__(state) {
- Object.assign(this, new pickle.Unpickler(state).load());
- }
- });
- this.registerType('thinc.neural._classes.layernorm.LayerNorm', class {
- __setstate__(state) {
- Object.assign(this, new pickle.Unpickler(state).load());
- }
- });
- this.registerType('thinc.neural._classes.maxout.Maxout', class {
- __setstate__(state) {
- Object.assign(this, new pickle.Unpickler(state).load());
- }
- });
- this.registerType('thinc.neural._classes.resnet.Residual', class {
- __setstate__(state) {
- Object.assign(this, new pickle.Unpickler(state).load());
- }
- });
- this.registerType('thinc.neural._classes.softmax.Softmax', class {
- __setstate__(state) {
- Object.assign(this, new pickle.Unpickler(state).load());
- }
- });
- this.registerType('thinc.neural.mem.Memory', class {
- });
- this.registerType('thinc.neural.ops.NumpyOps', class {
- });
- this.registerType('__main__.BYOLState', class {
- constructor(dict) {
- Object.assign(this, dict);
- }
- });
- this.registerType('types.CodeType', class {});
- this.register('types').ObjectType = this._builtins.object;
- this.register('types').ModuleType = this._builtins.module;
- this.register('types').MethodType = this._builtins.method;
- this.register('types').FunctionType = this._builtins.function;
- this.registerType('xgboost.compat.XGBoostLabelEncoder', class {});
- this.registerType('xgboost.core.Booster', class {});
- this.registerType('xgboost.sklearn.XGBClassifier', class {});
- this.registerType('xgboost.sklearn.XGBRegressor', class {});
- this.registerFunction('_codecs.encode', function(obj, encoding) {
- return execution.invoke('builtins.bytearray', [ obj, encoding ]);
- });
- this.registerFunction('builtins.bytearray', function(source, encoding /*, errors */) {
- if (source) {
- if (Array.isArray(source) || source instanceof Uint8Array) {
- const target = new Uint8Array(source.length);
- for (let i = 0; i < source.length; i++) {
- target[i] = source[i];
- }
- return target;
- }
- if (encoding === 'latin-1' || encoding === 'latin1') {
- const target = new Uint8Array(source.length);
- const length = source.length;
- for (let i = 0; i < length; i++) {
- target[i] = source.charCodeAt(i);
- }
- return target;
- }
- throw new python.Error("Unsupported bytearray encoding '" + JSON.stringify(encoding) + "'.");
- }
- return [];
- });
- this.registerFunction('builtins.bytes', function(source, encoding /*, errors */) {
- if (source) {
- if (Array.isArray(source) || source instanceof Uint8Array) {
- const target = new Uint8Array(source.length);
- for (let i = 0; i < source.length; i++) {
- target[i] = source[i];
- }
- return target;
- }
- if (encoding === 'latin-1') {
- const array = new Uint8Array(source.length);
- for (let i = 0; i < source.length; i++) {
- array[i] = source.charCodeAt(i);
- }
- return array;
- }
- throw new python.Error("Unsupported bytes encoding '" + JSON.stringify(encoding) + "'.");
- }
- return [];
- });
- this.registerFunction('builtins.frozenset', function(iterable) {
- return iterable ? iterable : [];
- });
- this.registerFunction('builtins.getattr', function(obj, name, defaultValue) {
- if (Object.prototype.hasOwnProperty.call(obj, name)) {
- return obj[name];
- }
- return defaultValue;
- });
- this.registerFunction('builtins.set', function(iterable) {
- return iterable ? iterable : [];
- });
- this.registerFunction('builtins.slice', function(start, stop, step) {
- return [ start, stop, step ];
- });
- this.registerFunction('cloudpickle.cloudpickle._builtin_type', function(name) {
- return name;
- });
- this.registerFunction('collections.Counter', function(/* iterable */) {
- return { __module__: 'collections', __name__: 'Counter' };
- });
- this.registerFunction('collections.defaultdict', function(/* default_factory */) {
- return {};
- });
- this.registerFunction('copy_reg._reconstructor', function(cls, base, state) {
- // copyreg._reconstructor in Python 3
- if (base === '__builtin__.object' || base === self._builtins.object) {
- return self.invoke(cls, []);
- }
- else if (base === '__builtin__.tuple' || base === self._builtins.tuple) {
- const obj = self.invoke(cls, []);
- for (let i = 0; i < state.length; i++) {
- obj[i] = state[i];
- }
- return obj;
- }
- throw new python.Error("Unsupported copy_reg._reconstructor base type '" + base + "'.");
- });
- this.registerFunction('copy.deepcopy', function(/* x */) {
- throw new python.Error('Unsupported copy.deepcopy().');
- });
- this.registerFunction('dill._dill._create_cell', function(/* args */) {
- return function() {
- // TODO
- };
- });
- this.registerFunction('dill._dill._create_code', function(args) {
- return self.invoke('types.CodeType', [ args ]);
- });
- this.registerFunction('dill._dill._create_function', function(/* fcode, fglobals, fname, fdefaults, fclosure, fdict, fkwdefaults */) {
- return function() {
- // TODO
- };
- });
- this.registerFunction('dill._dill._create_namedtuple', function(name, fieldnames, modulename /*, defaults */) {
- const obj = execution.invoke('dill._dill._import_module', [ modulename + '.' + name ]);
- if (obj) {
- return obj;
- }
- return undefined;
- });
- this.registerFunction('dill._dill._get_attr', function(self, name) {
- if (Object.prototype.hasOwnProperty.call(self, name)) {
- return self[name];
- }
- return undefined;
- });
- this.registerFunction('dill._dill._import_module', function(import_name, safe) {
- try {
- if (import_name.startsWith('__runtime__.')) {
- return execution.module(import_name);
- }
- else if (import_name.indexOf('.') === -1) {
- return execution.__import__(import_name);
- }
- return execution.resolve(import_name);
- }
- catch (err) {
- if (safe) {
- return null;
- }
- throw err;
- }
- });
- this.registerFunction('dill._dill._load_type', function(name) {
- return self.resolve('types.' + name);
- });
- this.registerFunction('lasagne.nonlinearities.rectify', function() {
- throw new python.Error('Function not implemented.');
- });
- this.registerFunction('lasagne.nonlinearities.softmax', function() {
- throw new python.Error('Function not implemented.');
- });
- this.registerFunction('lasagne.objectives.categorical_crossentropy', function() {
- throw new python.Error('Function not implemented.');
- });
- this.registerFunction('lasagne.updates.nesterov_momentum', function() {
- throw new python.Error('Function not implemented.');
- });
- this.registerFunction('msgpack.unpackb', function(packed, ext_hook) {
- const BinaryReader = class {
- constructor(buffer, ext_hook) {
- // https://github.com/msgpack/msgpack-javascript/blob/master/src/Decoder.ts
- // https://github.com/msgpack/msgpack-python/blob/main/msgpack/_unpacker.pyx
- this._buffer = buffer;
- this._position = 0;
- this._view = new DataView(buffer.buffer, buffer.byteOffset, buffer.byteLength);
- this._ext_hook = ext_hook;
- }
- value() {
- const c = this._view.getUint8(this.skip(1));
- if (c >= 0xe0) {
- return c - 0x100;
- }
- if (c < 0xC0) {
- if (c < 0x80) {
- return c;
- }
- if (c < 0x90) {
- return this.map(c - 0x80);
- }
- if (c < 0xa0) {
- return this.array(c - 0x90);
- }
- return this.string(c - 0xa0);
- }
- switch (c) {
- case 0xC0: return null;
- case 0xC2: return false;
- case 0xC3: return true;
- case 0xC4: return this.read(this._view.getUint8(this.skip(1)));
- case 0xC5: return this.read(this._view.getUint16(this.skip(2)));
- case 0xC6: return this.read(this._view.getUint32(this.skip(4)));
- case 0xC7: return this.extension(this._view.getUint8(this.skip(1)));
- case 0xC8: return this.extension(this._view.getUint16(this.skip(2)));
- case 0xC9: return this.extension(this._view.getUint32(this.skip(4)));
- case 0xCA: return this._view.getFloat32(this.skip(4));
- case 0xCB: return this._view.getFloat64(this.skip(8));
- case 0xCC: return this._view.getUint8(this.skip(1));
- case 0xCD: return this._view.getUint16(this.skip(2));
- case 0xCE: return this._view.getUint32(this.skip(4));
- case 0xCF: return this._view.getUint64(this.skip(8));
- case 0xD0: return this._view.getInt8(this.skip(1));
- case 0xD1: return this._view.getInt16(this.skip(2));
- case 0xD2: return this._view.getInt32(this.skip(4));
- case 0xD3: return this._view.getInt64(this.skip(8));
- case 0xD4: return this.extension(1);
- case 0xD5: return this.extension(2);
- case 0xD6: return this.extension(4);
- case 0xD7: return this.extension(8);
- case 0xD8: return this.extension(16);
- case 0xD9: return this.string(this._view.getUint8(this.skip(1)));
- case 0xDA: return this.string(this._view.getUint16(this.skip(2)));
- case 0xDB: return this.string(this._view.getUint32(this.skip(4)));
- case 0xDC: return this.array(this._view.getUint16(this.skip(2)));
- case 0xDD: return this.array(this._view.getUint32(this.skip(4)));
- case 0xDE: return this.map(this._view.getUint16(this.skip(2)));
- case 0xDF: return this.map(this._view.getUint32(this.skip(4)));
- default: throw new python.Error("Invalid code '" + c + "'.");
- }
- }
- map(size) {
- const map = {};
- for (let i = 0; i < size; i++) {
- const key = this.value();
- const value = this.value();
- map[key] = value;
- }
- return map;
- }
- array(size) {
- const array = new Array(size);
- for (let i = 0; i < size; i++) {
- array[i] = this.value();
- }
- return array;
- }
- extension(size) {
- const code = this._view.getUint8(this.skip(1));
- const data = this.read(size);
- return this._ext_hook(code, data);
- }
- skip(offset) {
- const position = this._position;
- this._position += offset;
- if (this._position > this._buffer.length) {
- throw new python.Error('Expected ' + (this._position - this._buffer.length) + ' more bytes. The file might be corrupted. Unexpected end of file.');
- }
- return position;
- }
- read(size) {
- const data = this._buffer.subarray(this._position, this._position + size);
- this._position += size;
- return data;
- }
- string(size) {
- const buffer = this.read(size);
- this._decoder = this._decoder || new TextDecoder('utf8');
- return this._decoder.decode(buffer);
- }
- };
- return new BinaryReader(packed, ext_hook).value();
- });
- this.registerFunction('nolearn.lasagne.base.objective', function() {
- throw new python.Error('Function not implemented.');
- });
- this.registerFunction('numpy._reconstruct', function(subtype, shape, dtype) {
- return self.invoke(subtype, [ shape, dtype ]);
- });
- this.registerFunction('numpy.core._multiarray_umath._reconstruct', function(subtype, shape, dtype) {
- return self.invoke(subtype, [ shape, dtype ]);
- });
- this.registerFunction('numpy.core.multiarray._reconstruct', function(subtype, shape, dtype) {
- return self.invoke(subtype, [ shape, dtype ]);
- });
- this.registerFunction('numpy.core.multiarray.scalar', function(dtype, rawData) {
- let data = rawData;
- if (typeof rawData === 'string' || rawData instanceof String) {
- data = new Uint8Array(rawData.length);
- for (let i = 0; i < rawData.length; i++) {
- data[i] = rawData.charCodeAt(i);
- }
- }
- switch (dtype.kind) {
- case 'b': {
- const view = new DataView(data.buffer, data.byteOffset, data.byteLength);
- switch (dtype.itemsize) {
- case 1: return view.getInt8(0) ? true : false;
- default: throw new python.Error("Unsupported scalar dtype boolean itemsize '" + dtype.itemsize + "'.");
- }
- }
- case 'f': {
- const view = new DataView(data.buffer, data.byteOffset, data.byteLength);
- switch (dtype.itemsize) {
- case 4: return view.getFloat32(0, dtype.byteorder === '<');
- case 8: return view.getFloat64(0, dtype.byteorder === '<');
- default: throw new python.Error("Unsupported scalar dtype float itemsize '" + dtype.itemsize + "'.");
- }
- }
- case 'i': {
- const view = new DataView(data.buffer, data.byteOffset, data.byteLength);
- switch (dtype.itemsize) {
- case 1: return view.getInt8(0);
- case 2: return view.getInt16(0, dtype.byteorder === '<');
- case 4: return view.getInt32(0, dtype.byteorder === '<');
- case 8: return view.getInt64(0, dtype.byteorder === '<');
- default: throw new python.Error("Unsupported scalar dtype int itemsize '" + dtype.itemsize + "'.");
- }
- }
- case 'u': {
- const view = new DataView(data.buffer, data.byteOffset, data.byteLength);
- switch (dtype.itemsize) {
- case 1: return view.getUint8(0);
- case 2: return view.getUint16(0, dtype.byteorder === '<');
- case 4: return view.getUint32(0, dtype.byteorder === '<');
- case 8: return view.getUint64(0, dtype.byteorder === '<');
- default: throw new python.Error("Unsupported scalar dtype uint itemsize '" + dtype.itemsize + "'.");
- }
- }
- case 'U': {
- const view = new DataView(data.buffer, data.byteOffset, data.byteLength);
- const list = [];
- for (let i = 0; i < dtype.itemsize; i += 4) {
- list.push(String.fromCodePoint(view.getUint32(i, true)));
- }
- return list.join('');
- }
- default: {
- throw new python.Error("Unsupported scalar dtype kind '" + dtype.kind + "'.");
- }
- }
- });
- this.registerFunction('numpy.core._multiarray_umath.scalar', function(dtype, rawData) {
- let data = rawData;
- if (typeof rawData === 'string') {
- data = new Uint8Array(rawData.length);
- for (let i = 0; i < rawData.length; i++) {
- data[i] = rawData.charCodeAt(i);
- }
- }
- const dataView = new DataView(data.buffer, data.byteOffset, data.byteLength);
- switch (dtype.__name__) {
- case 'uint8':
- return dataView.getUint8(0);
- case 'float32':
- return dataView.getFloat32(0, true);
- case 'float64':
- return dataView.getFloat64(0, true);
- case 'int8':
- return dataView.getInt8(0, true);
- case 'int16':
- return dataView.getInt16(0, true);
- case 'int32':
- return dataView.getInt32(0, true);
- case 'int64':
- return dataView.getInt64(0, true);
- default:
- throw new python.Error("Unsupported scalar type '" + dtype.__name__ + "'.");
- }
- });
- this.registerFunction('numpy.load', function(file) {
- // https://github.com/numpy/numpy/blob/main/numpy/lib/format.py
- const signature = [ 0x93, 0x4E, 0x55, 0x4D, 0x50, 0x59 ];
- if (!file.read(6).every((v, i) => v == signature[i])) {
- throw new python.Error('Invalid signature.');
- }
- const major = file.read(1)[0];
- const minor = file.read(1)[0];
- if (major > 3) {
- throw new python.Error("Invalid version '" + [ major, minor ].join('.') + "'.");
- }
- const buffer = new Uint8Array([ 0, 0, 0, 0 ]);
- buffer.set(file.read(major >= 2 ? 4 : 2), 0);
- const header_length = buffer[3] << 24 | buffer[2] << 16 | buffer[1] << 8 | buffer[0];
- let header = file.read(header_length);
- const decoder = new TextDecoder(major >= 3 ? 'utf-8' : 'ascii');
- header = decoder.decode(header);
- header = JSON.parse(header.replace(/\(/,'[').replace(/\)/,']').replace('[,','[1,]').replace(',]',',1]').replace(/'/g, '"').replace(/:\s*False\s*,/,':false,').replace(/:\s*True\s*,/,':true,').replace(/,\s*\}/, ' }'));
- if (!header.descr || header.descr.length < 2) {
- throw new python.Error("Missing property 'descr'.");
- }
- if (!header.shape) {
- throw new python.Error("Missing property 'shape'.");
- }
- const shape = header.shape;
- const dtype = self.invoke('numpy.dtype', [ header.descr.substring(1) ]);
- dtype.byteorder = header.descr[0];
- let data = null;
- switch (dtype.byteorder) {
- case '|': {
- data = file.read();
- if (dtype.kind === 'O') {
- const unpickler = execution.invoke('pickle.Unpickler', [ data ]);
- return unpickler.load();
- }
- break;
- }
- case '>':
- case '<': {
- if (header.descr.length !== 3) {
- throw new python.Error("Unsupported data type '" + header.descr + "'.");
- }
- const count = shape.length === 0 ? 1 : shape.reduce((a, b) => a * b, 1);
- data = file.read(dtype.itemsize * count);
- break;
- }
- default: {
- throw new python.Error("Unsupported data type '" + header.descr + "'.");
- }
- }
- if (header.fortran_order) {
- data = null;
- }
- return self.invoke('numpy.ndarray', [ shape, dtype, data ]);
- });
- this.registerFunction('numpy.save', function(file, arr) {
- const descr = arr.dtype.str;
- if (descr[0] !== '<' && descr[0] !== '>') {
- throw new python.Error("Unsupported byte order '" + descr + "'.");
- }
- if (descr.length !== 3 || (descr[1] !== 'f' && descr[1] !== 'i' && descr[1] !== 'u' && descr[1] !== 'c' && descr.substring(1) !== 'b1')) {
- throw new python.Error("Unsupported data type '" + descr + "'.");
- }
- let shape = '';
- switch (arr.shape.length) {
- case 0: shape = '()'; break;
- case 1: shape = '(' + arr.shape[0].toString() + ',)'; break;
- default: shape = '(' + arr.shape.map((dimension) => dimension.toString()).join(', ') + ')'; break;
- }
- const properties = [
- "'descr': '" + descr + "'",
- "'fortran_order': False",
- "'shape': " + shape
- ];
- let header = '{ ' + properties.join(', ') + ' }';
- header += ' '.repeat(64 - ((header.length + 2 + 8 + 1) & 0x3f)) + '\n';
- const encoder = new TextEncoder('ascii');
- file.write([ 0x93, 0x4E, 0x55, 0x4D, 0x50, 0x59, 0x01, 0x00 ]); // '\\x93NUMPY' + version
- file.write([ header.length & 0xff, (header.length >> 8) & 0xff ]);
- file.write(encoder.encode(header));
- file.write(arr.tobytes());
- });
- this.registerFunction('numpy.asarray', function(a, dtype) {
- const encode = (context, data, dim) => {
- const size = context.shape[dim];
- const littleendian = context.littleendian;
- if (dim == context.shape.length - 1) {
- for (let i = 0; i < size; i++) {
- switch (context.dtype) {
- case 'f2':
- context.view.setFloat16(context.position, data[i], littleendian);
- break;
- case 'f4':
- context.view.setFloat32(context.position, data[i], littleendian);
- break;
- case 'f8':
- context.view.setFloat64(context.position, data[i], littleendian);
- break;
- case 'i1':
- context.view.setInt8(context.position, data[i], littleendian);
- break;
- case 'i2':
- context.view.setInt16(context.position, data[i], littleendian);
- break;
- case 'i4':
- context.view.setInt32(context.position, data[i], littleendian);
- break;
- case 'i8':
- context.view.setInt64(context.position, data[i], littleendian);
- break;
- case 'u1':
- context.view.setUint8(context.position, data[i], littleendian);
- break;
- case 'u2':
- context.view.setUint16(context.position, data[i], littleendian);
- break;
- case 'u4':
- context.view.setUint32(context.position, data[i], littleendian);
- break;
- case 'u8':
- context.view.setUint64(context.position, data[i], littleendian);
- break;
- case 'c8':
- context.view.setComplex64(context.position, data[i], littleendian);
- break;
- case 'c16':
- context.view.setComplex128(context.position, data[i], littleendian);
- break;
- default:
- throw new python.Error("Unsupported tensor data type '" + context.dtype + "'.");
- }
- context.position += context.itemsize;
- }
- }
- else {
- for (let j = 0; j < size; j++) {
- encode(context, data[j], dim + 1);
- }
- }
- };
- const array_size = (value) => {
- if (value.every((item) => Array.isArray(item))) {
- const dims = value.map((item) => array_size(item));
- const dim = dims[0];
- for (let i = 1; i < dims.length; i++) {
- if (dim.length === dims[i].length) {
- if (!dims[i].every((value, i) => value ===dim[i])) {
- throw new python.Error('Invalid array shape.');
- }
- }
- }
- return [ value.length ].concat(dim);
- }
- return [ value.length ];
- };
- const shape = Array.isArray(a) ? array_size(a) : [];
- const size = dtype.itemsize * shape.reduce((a, b) => a * b, 1);
- const context = {
- position: 0,
- itemsize: dtype.itemsize,
- dtype: dtype.str.substring(1),
- littleendian: dtype.str[0],
- shape: shape,
- data: new Uint8Array(size)
- };
- context.view = new DataView(context.data.buffer, context.data.byteOffset, size);
- encode(context, a, 0);
- return self.invoke('numpy.ndarray', [ shape, dtype, context.data ]);
- });
- this.registerFunction('numpy.ma.core._mareconstruct', function(subtype, baseclass, baseshape, basetype) {
- const data = self.invoke(baseclass, [ baseshape, basetype ]);
- // = ndarray.__new__(ndarray, baseshape, make_mask_descr(basetype))
- const mask = self.invoke('numpy.ndarray', [ baseshape, '' ]);
- return self.invoke(subtype, [ data, mask, basetype ]);
- });
- this.registerFunction('numpy.random.__RandomState_ctor', function() {
- return {};
- });
- this.registerFunction('numpy.random._pickle.__randomstate_ctor', function() {
- return {};
- });
- this.registerFunction('numpy.core.numeric._frombuffer', function(/* buf, dtype, shape, order */) {
- return {};
- });
- this.registerFunction('sklearn.metrics.scorer._passthrough_scorer', function() {
- throw new python.Error("Function not implemented.");
- });
- this.registerFunction('sklearn.feature_selection._univariate_selection.f_classif', function() {
- throw new python.Error("Function not implemented.");
- });
- this.registerFunction('re._compile', function(pattern, flags) {
- return self.invoke('re.Pattern', [ pattern, flags ]);
- });
- this.registerFunction('srsly.cloudpickle.cloudpickle._builtin_type', function(name) {
- return function() {
- return self.invoke('types.' + name, arguments);
- };
- });
- this.registerFunction('theano.scalar.basic.same_out', function() {
- throw new python.Error('Function not implemented.');
- });
- this.registerFunction('theano.scalar.basic.same_out_nocomplex', function() {
- throw new python.Error('Function not implemented.');
- });
- this.registerFunction('theano.scalar.basic.upcast_out', function() {
- throw new python.Error('Function not implemented.');
- });
- this.registerFunction('theano.scalar.basic.upgrade_to_float', function() {
- throw new python.Error('Function not implemented.');
- });
- this.registerFunction('theano.tensor.nnet.conv2d', function() {
- throw new python.Error('Function not implemented.');
- });
- this.registerFunction('theano.tensor.type.values_eq_approx_remove_inf_nan', function() {
- throw new python.Error('Function not implemented.');
- });
- this.registerFunction('theano.tensor.type.values_eq_approx_remove_nan', function() {
- throw new python.Error('Function not implemented.');
- });
- this.registerType('torch.nn.modules.module.Module', class {
- constructor() {
- this._modules = execution.invoke('collections.OrderedDict', []);
- this._parameters = execution.invoke('collections.OrderedDict', []);
- this._buffers = execution.invoke('collections.OrderedDict', []);
- }
- __setattr__(name, value) {
- if (value instanceof torch.nn.modules.module.Module) {
- this._modules.set(name, value);
- }
- else {
- this[name] = value;
- }
- }
- __getattr__(name) {
- if (this._modules.has(name)) {
- return this._modules.get(name);
- }
- return this[name];
- }
- });
- torch.nn.Module = torch.nn.modules.module.Module;
- torch.nn.modules.Module = torch.nn.modules.module.Module;
- this.registerType('torch.ao.quantization.observer._PartialWrapper', class {});
- this.registerType('torch.ao.quantization.observer.HistogramObserver', class {});
- this.registerType('torch.ao.quantization.observer.MovingAverageMinMaxObserver', class {});
- this.registerType('torch.ao.quantization.observer.PerChannelMinMaxObserver', class {});
- this.registerType('torch.ao.quantization.qconfig.QConfig', class {});
- this.registerType('torch.ao.quantization.stubs.DeQuantStub', class {});
- this.registerType('torch.ao.quantization.stubs.QuantStub', class {});
- this.registerType('torch.autograd.variable.Variable', class {});
- this.registerType('torch.backends.cudnn.rnn.Unserializable', class {});
- this.registerType('torch.distributions.bernoulli.Bernoulli', class {});
- this.registerType('torch.distributions.constraints._LowerCholesky', class {});
- this.registerType('torch.distributions.constraints._Real', class {});
- this.registerType('torch.distributions.multivariate_normal.MultivariateNormal', class {});
- this.registerType('torch.distributions.normal.Normal', class {});
- this.registerType('torch.distributions.transforms.LowerCholeskyTransform', class {});
- this.registerType('torch.distributions.uniform.Uniform', class {});
- this.registerType('torch.nn.backends.thnn._get_thnn_function_backend', class {});
- this.registerType('torch.nn.intrinsic.modules.fused.ConvBnReLU2d', class {});
- this.registerType('torch.nn.intrinsic.modules.fused.ConvReLU2d', class {});
- this.registerType('torch.nn.intrinsic.modules.fused.BNReLU2d', class {});
- this.registerType('torch.nn.intrinsic.qat.modules.conv_fused.ConvBn2d', class {});
- this.registerType('torch.nn.intrinsic.qat.modules.conv_fused.ConvBnReLU2d', class {});
- this.registerType('torch.nn.intrinsic.qat.modules.conv_fused.ConvReLU2d', class {});
- this.registerType('torch.nn.intrinsic.quantized.modules.conv_relu.ConvReLU2d', class {});
- this.registerType('torch.nn.intrinsic.quantized.modules.linear_relu.LinearReLU', class {});
- this.registerType('torch.nn.modules.activation.CELU', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.ELU', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.GELU', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.GLU', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.Hardtanh', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.Hardswish', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.Hardsigmoid', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.LeakyReLU', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.LogSigmoid', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.LogSoftmax', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.Mish', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.MultiheadAttention', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.ReLU', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.ReLU6', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.PReLU', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.RReLU', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.SELU', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.Sigmoid', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.SiLU', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.Softmax', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.Softmax2d', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.Softplus', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.Tanh', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.Tanhshrink', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.activation.Threshold', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.batchnorm._NormBase', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.batchnorm._BatchNorm', class extends torch.nn.modules.batchnorm._NormBase {});
- this.registerType('torch.nn.modules.batchnorm.BatchNorm1d', class extends torch.nn.modules.batchnorm._BatchNorm {});
- this.registerType('torch.nn.modules.batchnorm.BatchNorm2d', class extends torch.nn.modules.batchnorm._BatchNorm {});
- this.registerType('torch.nn.modules.batchnorm.BatchNorm3d', class extends torch.nn.modules.batchnorm._BatchNorm {});
- this.registerType('torch.nn.modules.batchnorm.LazyBatchNorm1d', class {});
- this.registerType('torch.nn.modules.batchnorm.SyncBatchNorm', class {});
- this.registerType('torch.nn.modules.container.ModuleDict', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.container.ModuleList', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.container.ParameterDict', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.container.ParameterList', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.container.Sequential', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.conv._ConvNd', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.conv.Conv1d', class extends torch.nn.modules.conv._ConvNd {});
- this.registerType('torch.nn.modules.conv.Conv2d', class extends torch.nn.modules.conv._ConvNd {});
- this.registerType('torch.nn.modules.conv.Conv3d', class extends torch.nn.modules.conv._ConvNd {});
- this.registerType('torch.nn.modules.conv._ConvTransposeNd', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.conv.ConvTranspose1d', class extends torch.nn.modules.conv._ConvTransposeNd {});
- this.registerType('torch.nn.modules.conv.ConvTranspose2d', class extends torch.nn.modules.conv._ConvTransposeNd {});
- this.registerType('torch.nn.modules.conv.ConvTranspose3d', class extends torch.nn.modules.conv._ConvTransposeNd {});
- this.registerType('torch.nn.modules.distance.CosineSimilarity', class {});
- this.registerType('torch.nn.modules.dropout._DropoutNd', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.dropout.AlphaDropout', class extends torch.nn.modules.dropout._DropoutNd {});
- this.registerType('torch.nn.modules.dropout.Dropout', class extends torch.nn.modules.dropout._DropoutNd {});
- this.registerType('torch.nn.modules.dropout.Dropout2d', class extends torch.nn.modules.dropout._DropoutNd {});
- this.registerType('torch.nn.modules.dropout.Dropout3d', class extends torch.nn.modules.dropout._DropoutNd {});
- this.registerType('torch.nn.modules.fold.Fold', class {});
- this.registerType('torch.nn.modules.fold.Unfold', class {});
- this.registerType('torch.nn.modules.flatten.Flatten', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.flatten.Unflatten', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.instancenorm.InstanceNorm1d', class {});
- this.registerType('torch.nn.modules.instancenorm.InstanceNorm2d', class {});
- this.registerType('torch.nn.modules.instancenorm.InstanceNorm3d', class {});
- this.registerType('torch.nn.modules.linear._LinearWithBias', class {});
- this.registerType('torch.nn.modules.linear.Bilinear', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.linear.Identity', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.linear.LazyLinear', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.linear.Linear', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.linear.NonDynamicallyQuantizableLinear', class extends torch.nn.modules.linear.Linear {});
- this.registerType('torch.nn.modules.loss._Loss', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.loss._WeightedLoss', class extends torch.nn.modules.loss._Loss {});
- this.registerType('torch.nn.modules.loss.BCELoss', class extends torch.nn.modules.loss._Loss {});
- this.registerType('torch.nn.modules.loss.BCEWithLogitsLoss', class extends torch.nn.modules.loss._Loss {});
- this.registerType('torch.nn.modules.loss.CrossEntropyLoss', class extends torch.nn.modules.loss._Loss {});
- this.registerType('torch.nn.modules.loss.CTCLoss', class extends torch.nn.modules.loss._Loss {});
- this.registerType('torch.nn.modules.loss.KLDivLoss', class extends torch.nn.modules.loss._Loss {});
- this.registerType('torch.nn.modules.loss.L1Loss', class extends torch.nn.modules.loss._Loss {});
- this.registerType('torch.nn.modules.loss.MarginRankingLoss', class extends torch.nn.modules.loss._Loss {});
- this.registerType('torch.nn.modules.loss.MSELoss', class extends torch.nn.modules.loss._Loss {});
- this.registerType('torch.nn.modules.loss.NLLLoss', class extends torch.nn.modules.loss._WeightedLoss {});
- this.registerType('torch.nn.modules.loss.NLLLoss2d', class extends torch.nn.modules.loss.NLLLoss {});
- this.registerType('torch.nn.modules.loss.SmoothL1Loss', class {});
- this.registerType('torch.nn.modules.module._IncompatibleKeys', class {});
- this.registerType('torch.nn.modules.module.PatchForward', class {});
- this.registerType('torch.nn.modules.normalization.CrossMapLRN2d', class {});
- this.registerType('torch.nn.modules.normalization.GroupNorm', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.normalization.LayerNorm', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.normalization.LocalResponseNorm', class {});
- this.registerType('torch.nn.modules.padding._ReflectionPadNd', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.padding.ReflectionPad1d', class extends torch.nn.modules.padding._ReflectionPadNd {});
- this.registerType('torch.nn.modules.padding.ReflectionPad2d', class extends torch.nn.modules.padding._ReflectionPadNd {});
- this.registerType('torch.nn.modules.padding.ReflectionPad3d', class extends torch.nn.modules.padding._ReflectionPadNd {});
- this.registerType('torch.nn.modules.padding._ReplicationPadNd', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.padding.ReplicationPad1d', class extends torch.nn.modules.padding._ReplicationPadNd {});
- this.registerType('torch.nn.modules.padding.ReplicationPad2d', class extends torch.nn.modules.padding._ReplicationPadNd {});
- this.registerType('torch.nn.modules.padding.ReplicationPad3d', class extends torch.nn.modules.padding._ReplicationPadNd {});
- this.registerType('torch.nn.modules.padding.ZeroPad2d', class {});
- this.registerType('torch.nn.modules.padding.ConstantPad1d', class {});
- this.registerType('torch.nn.modules.padding.ConstantPad2d', class {});
- this.registerType('torch.nn.modules.padding.ConstantPad3d', class {});
- this.registerType('torch.nn.modules.pixelshuffle.PixelShuffle', class {});
- this.registerType('torch.nn.modules.pixelshuffle.PixelUnshuffle', class {});
- this.registerType('torch.nn.modules.pooling._AdaptiveAvgPoolNd', class extends torch.nn.Module {});
- this.registerType('torch.nn.modules.pooling.AdaptiveAvgPool1d', class extends torch.nn.modules.pooling._AdaptiveAvgPoolNd {});
- this.registerType('torch.nn.modules.pooling.AdaptiveAvgPool2d', class extends torch.nn.modules.pooling._AdaptiveAvgPoolNd {});
- this.registerType('torch.nn.modules.pooling.AdaptiveAvgPool3d', class extends torch.nn.modules.pooling._AdaptiveAvgPoolNd {});
- this.registerType('torch.nn.modules.pooling.AdaptiveMaxPool1d', class {});
- this.registerType('torch.nn.modules.pooling.AdaptiveMaxPool2d', class {});
- this.registerType('torch.nn.modules.pooling.AdaptiveMaxPool3d', class {});
- this.registerType('torch.nn.modules.pooling.AvgPool1d', class {});
- this.registerType('torch.nn.modules.pooling.AvgPool2d', class {});
- this.registerType('torch.nn.modules.pooling.AvgPool3d', class {});
- this.registerType('torch.nn.modules.pooling.FractionalMaxPool2d', class {});
- this.registerType('torch.nn.modules.pooling.LPPool2d', class {});
- this.registerType('torch.nn.modules.pooling.MaxPool1d', class {});
- this.registerType('torch.nn.modules.pooling.MaxPool2d', class {});
- this.registerType('torch.nn.modules.pooling.MaxPool3d', class {});
- this.registerType('torch.nn.modules.pooling.MaxUnpool1d', class {});
- this.registerType('torch.nn.modules.pooling.MaxUnpool2d', class {});
- this.registerType('torch.nn.modules.pooling.MaxUnpool3d', class {});
- this.registerType('torch.nn.modules.rnn.GRU', class {});
- this.registerType('torch.nn.modules.rnn.GRUCell', class {});
- this.registerType('torch.nn.modules.rnn.LSTM', class {});
- this.registerType('torch.nn.modules.rnn.LSTMCell', class {});
- this.registerType('torch.nn.modules.rnn.RNN', class {});
- this.registerType('torch.nn.modules.rnn.RNNCell', class {});
- this.registerType('torch.nn.modules.sparse.Embedding', class {});
- this.registerType('torch.nn.modules.sparse.EmbeddingBag', class {});
- this.registerType('torch.nn.modules.transformer.Transformer', class {});
- this.registerType('torch.nn.modules.transformer.TransformerDecoder', class {});
- this.registerType('torch.nn.modules.transformer.TransformerDecoderLayer', class {});
- this.registerType('torch.nn.modules.transformer.TransformerEncoder', class {});
- this.registerType('torch.nn.modules.transformer.TransformerEncoderLayer', class {});
- this.registerType('torch.nn.modules.upsampling.Upsample', class {});
- this.registerType('torch.nn.modules.upsampling.UpsamplingBilinear2d', class {});
- this.registerType('torch.nn.modules.upsampling.UpsamplingNearest2d', class {});
- this.registerType('torch.nn.parallel.data_parallel.DataParallel', class {});
- this.registerType('torch.nn.parallel.distributed._DDPUnevenInputsConfig', class {});
- this.registerType('torch.nn.parallel.distributed.DistributedDataParallel', class {});
- this.registerType('torch.nn.qat.modules.conv.Conv2d', class {});
- this.registerType('torch.nn.qat.modules.linear.Linear', class {});
- this.registerType('torch.nn.quantized.modules.activation.ReLU', class {});
- this.registerType('torch.nn.quantized.modules.activation.LeakyReLU', class {});
- this.registerType('torch.nn.quantized.dynamic.modules.linear.Linear', class {});
- this.registerType('torch.nn.quantized.dynamic.modules.rnn.GRU', class {});
- this.registerType('torch.nn.quantized.dynamic.modules.rnn.LSTM', class {});
- this.registerType('torch.nn.quantized.dynamic.modules.rnn.LSTMCell', class {});
- this.registerType('torch.nn.quantized.dynamic.modules.rnn.PackedParameter', class {});
- this.registerType('torch.nn.quantized.modules.activation.ReLU6', class {});
- this.registerType('torch.nn.quantized.modules.batchnorm.BatchNorm2d', class {});
- this.registerType('torch.nn.quantized.modules.conv.Conv1d', class {});
- this.registerType('torch.nn.quantized.modules.conv.Conv2d', class {});
- this.registerType('torch.nn.quantized.modules.conv.ConvTranspose2d', class {});
- this.registerType('torch.nn.quantized.modules.DeQuantize', class {});
- this.registerType('torch.nn.quantized.modules.dropout.Dropout', class {});
- this.registerType('torch.nn.quantized.modules.embedding_ops.Embedding', class {});
- this.registerType('torch.nn.quantized.modules.embedding_ops.EmbeddingPackedParams', class {});
- this.registerType('torch.nn.quantized.modules.functional_modules.FloatFunctional', class {});
- this.registerType('torch.nn.quantized.modules.functional_modules.QFunctional', class {});
- this.registerType('torch.nn.quantized.modules.linear.Linear', class {});
- this.registerType('torch.nn.quantized.modules.linear.LinearPackedParams', class {});
- this.registerType('torch.nn.quantized.modules.normalization.InstanceNorm2d', class {});
- this.registerType('torch.nn.quantized.modules.normalization.LayerNorm', class {});
- this.registerType('torch.nn.quantized.modules.Quantize', class {});
- this.registerType('torch.nn.utils.prune.L1Unstructured', class {});
- this.registerType('torch.nn.utils.spectral_norm.SpectralNorm', class {});
- this.registerType('torch.nn.utils.spectral_norm.SpectralNormStateDictHook', class {});
- this.registerType('torch.nn.utils.spectral_norm.SpectralNormLoadStateDictPreHook', class {});
- this.registerType('torch.nn.utils.weight_norm.WeightNorm', class {});
- this.registerType('torch.torch_version.TorchVersion', class extends String {});
- this.registerType('torch.optim.adam.Adam', class {});
- this.registerType('torch.optim.adamw.AdamW', class {});
- this.registerType('torch.optim.adagrad.Adagrad', class {});
- this.registerType('torch.optim.adadelta.Adadelta', class {});
- this.registerType('torch.optim.lr_scheduler.CosineAnnealingLR', class {});
- this.registerType('torch.optim.lr_scheduler.CyclicLR', class {});
- this.registerType('torch.optim.lr_scheduler.ExponentialLR', class {});
- this.registerType('torch.optim.lr_scheduler.LambdaLR', class {});
- this.registerType('torch.optim.lr_scheduler.MultiStepLR', class {});
- this.registerType('torch.optim.lr_scheduler.OneCycleLR', class {});
- this.registerType('torch.optim.lr_scheduler.ReduceLROnPlateau', class {});
- this.registerType('torch.optim.lr_scheduler.StepLR', class {});
- this.registerType('torch.optim.optimizer._RequiredParameter', class {});
- this.registerType('torch.optim.rmsprop.RMSprop', class {});
- this.registerType('torch.optim.sgd.SGD', class {});
- this.registerType('torch.optim.sparse_adam.SparseAdam', class {});
- this.registerType('torch.quantization.fake_quantize.FakeQuantize', class {});
- this.registerType('torch.quantization.observer._PartialWrapper', class {});
- this.registerType('torch.quantization.observer.MinMaxObserver', class {});
- this.registerType('torch.quantization.observer.MovingAverageMinMaxObserver', class {});
- this.registerType('torch.quantization.observer.MovingAveragePerChannelMinMaxObserver', class {});
- this.registerType('torch.quantization.qconfig.QConfig', class {});
- this.registerType('torch.quantization.stubs.DeQuantStub', class {});
- this.registerType('torch.quantization.stubs.QuantStub', class {});
- this.registerType('torch.utils.data.dataloader._MultiProcessingDataLoaderIter', class {});
- this.registerType('torch.utils.data.dataloader.DataLoader', class {});
- this.registerType('torch.utils.data.dataset.Subset', class {});
- this.registerType('torch.utils.data.dataset.ConcatDataset', class {});
- this.registerType('torch.utils.data.dataset.TensorDataset', class {});
- this.registerType('torch.utils.data.sampler.BatchSampler', class {});
- this.registerType('torch.utils.data.sampler.RandomSampler', class {});
- this.registerType('torch.utils.data.sampler.SequentialSampler', class {});
- this.registerType('torchvision.datasets.folder.ImageFolder', class {});
- this.registerType('torchvision.datasets.mnist.MNIST', class {});
- this.registerType('torchvision.datasets.vision.StandardTransform', class {});
- this.registerType('torchvision.models.alexnet.AlexNet', class {});
- this.registerType('torchvision.models.densenet.DenseNet', class {});
- this.registerType('torchvision.models.densenet._DenseBlock', class {});
- this.registerType('torchvision.models.densenet._DenseLayer', class {});
- this.registerType('torchvision.models.densenet._Transition', class {});
- this.registerType('torchvision.models.detection._utils.BalancedPositiveNegativeSampler', class {});
- this.registerType('torchvision.models.detection._utils.BoxCoder', class {});
- this.registerType('torchvision.models.detection._utils.Matcher', class {});
- this.registerType('torchvision.models.detection._utils.SSDMatcher', class {});
- this.registerType('torchvision.models.detection.anchor_utils.AnchorGenerator', class {});
- this.registerType('torchvision.models.detection.anchor_utils.DefaultBoxGenerator', class {});
- this.registerType('torchvision.models.detection.backbone_utils.BackboneWithFPN', class {});
- this.registerType('torchvision.models.detection.faster_rcnn.FasterRCNN', class {});
- this.registerType('torchvision.models.detection.faster_rcnn.FastRCNNPredictor', class {});
- this.registerType('torchvision.models.detection.faster_rcnn.TwoMLPHead', class {});
- this.registerType('torchvision.models.detection.keypoint_rcnn.KeypointRCNN', class {});
- this.registerType('torchvision.models.detection.keypoint_rcnn.KeypointRCNNHeads', class {});
- this.registerType('torchvision.models.detection.keypoint_rcnn.KeypointRCNNPredictor', class {});
- this.registerType('torchvision.models.detection.mask_rcnn.MaskRCNN', class {});
- this.registerType('torchvision.models.detection.mask_rcnn.MaskRCNNHeads', class {});
- this.registerType('torchvision.models.detection.mask_rcnn.MaskRCNNPredictor', class {});
- this.registerType('torchvision.models.detection.retinanet.RetinaNet', class {});
- this.registerType('torchvision.models.detection.retinanet.RetinaNetClassificationHead', class {});
- this.registerType('torchvision.models.detection.retinanet.RetinaNetHead', class {});
- this.registerType('torchvision.models.detection.retinanet.RetinaNetRegressionHead', class {});
- this.registerType('torchvision.models.detection.roi_heads.RoIHeads', class {});
- this.registerType('torchvision.models.detection.rpn.AnchorGenerator', class {});
- this.registerType('torchvision.models.detection.rpn.RegionProposalNetwork', class {});
- this.registerType('torchvision.models.detection.rpn.RPNHead', class {});
- this.registerType('torchvision.models.detection.ssd.SSD', class {});
- this.registerType('torchvision.models.detection.ssdlite.SSDLiteClassificationHead', class {});
- this.registerType('torchvision.models.detection.ssdlite.SSDLiteFeatureExtractorMobileNet', class {});
- this.registerType('torchvision.models.detection.ssdlite.SSDLiteHead', class {});
- this.registerType('torchvision.models.detection.ssdlite.SSDLiteRegressionHead', class {});
- this.registerType('torchvision.models.detection.transform.GeneralizedRCNNTransform', class {});
- this.registerType('torchvision.models.efficientnet.EfficientNet', class {});
- this.registerType('torchvision.models.efficientnet.MBConv', class {});
- this.registerType('torchvision.models.googlenet.BasicConv2d', class {});
- this.registerType('torchvision.models.googlenet.GoogLeNet', class {});
- this.registerType('torchvision.models.googlenet.Inception', class {});
- this.registerType('torchvision.models.googlenet.InceptionAux', class {});
- this.registerType('torchvision.models.inception.BasicConv2d', class {});
- this.registerType('torchvision.models.inception.Inception3', class {});
- this.registerType('torchvision.models.inception.InceptionAux', class {});
- this.registerType('torchvision.models.inception.InceptionA', class {});
- this.registerType('torchvision.models.inception.InceptionB', class {});
- this.registerType('torchvision.models.inception.InceptionC', class {});
- this.registerType('torchvision.models.inception.InceptionD', class {});
- this.registerType('torchvision.models.inception.InceptionE', class {});
- this.registerType('torchvision.models.mnasnet._InvertedResidual', class {});
- this.registerType('torchvision.models.mnasnet.MNASNet', class {});
- this.registerType('torchvision.models.mobilenet.ConvBNReLU', class {});
- this.registerType('torchvision.models.mobilenet.MobileNetV2', class {});
- this.registerType('torchvision.models.mobilenet.InvertedResidual', class {});
- this.registerType('torchvision.models.mobilenetv2.ConvBNActivation', class {});
- this.registerType('torchvision.models.mobilenetv2.InvertedResidual', class {});
- this.registerType('torchvision.models.mobilenetv2.MobileNetV2', class {});
- this.registerType('torchvision.models.mobilenetv3.InvertedResidual', class {});
- this.registerType('torchvision.models.mobilenetv3.MobileNetV3', class {});
- this.registerType('torchvision.models.mobilenetv3.SqueezeExcitation', class {});
- this.registerType('torchvision.models.resnet.Bottleneck', class {});
- this.registerType('torchvision.models.resnet.BasicBlock', class {});
- this.registerType('torchvision.models.quantization.mobilenet.QuantizableInvertedResidual', class {});
- this.registerType('torchvision.models.quantization.mobilenet.QuantizableMobileNetV2', class {});
- this.registerType('torchvision.models.quantization.mobilenetv2.QuantizableInvertedResidual', class {});
- this.registerType('torchvision.models.quantization.mobilenetv2.QuantizableMobileNetV2', class {});
- this.registerType('torchvision.models.quantization.resnet.QuantizableBasicBlock', class {});
- this.registerType('torchvision.models.quantization.resnet.QuantizableBottleneck', class {});
- this.registerType('torchvision.models.quantization.resnet.QuantizableResNet', class {});
- this.registerType('torchvision.models.segmentation.deeplabv3.ASPP', class {});
- this.registerType('torchvision.models.segmentation.deeplabv3.ASPPConv', class {});
- this.registerType('torchvision.models.segmentation.deeplabv3.ASPPPooling', class {});
- this.registerType('torchvision.models.segmentation.deeplabv3.DeepLabHead', class {});
- this.registerType('torchvision.models.segmentation.deeplabv3.DeepLabV3', class {});
- this.registerType('torchvision.models.segmentation.fcn.FCN', class {});
- this.registerType('torchvision.models.segmentation.fcn.FCNHead', class {});
- this.registerType('torchvision.models.shufflenetv2.ShuffleNetV2', class {});
- this.registerType('torchvision.models.shufflenetv2.InvertedResidual', class {});
- this.registerType('torchvision.models.squeezenet.Fire', class {});
- this.registerType('torchvision.models.squeezenet.SqueezeNet', class {});
- this.registerType('torchvision.models.resnet.ResNet', class {});
- this.registerType('torchvision.models.vgg.VGG', class {});
- this.registerType('torchvision.models.video.resnet.BasicBlock', class {});
- this.registerType('torchvision.models.video.resnet.BasicStem', class {});
- this.registerType('torchvision.models.video.resnet.Conv2Plus1D', class {});
- this.registerType('torchvision.models.video.resnet.Conv3DNoTemporal', class {});
- this.registerType('torchvision.models.video.resnet.Conv3DSimple', class {});
- this.registerType('torchvision.models.video.resnet.R2Plus1dStem', class {});
- this.registerType('torchvision.models.video.resnet.VideoResNet', class {});
- this.registerType('torchvision.models._utils.IntermediateLayerGetter', class {});
- this.registerType('torchvision.ops.deform_conv.DeformConv2d', class {});
- this.registerType('torchvision.ops.feature_pyramid_network.FeaturePyramidNetwork', class {});
- this.registerType('torchvision.ops.feature_pyramid_network.LastLevelMaxPool', class {});
- this.registerType('torchvision.ops.feature_pyramid_network.LastLevelP6P7', class {});
- this.registerType('torchvision.ops.misc.Conv2dNormActivation', class {});
- this.registerType('torchvision.ops.misc.ConvNormActivation', class {});
- this.registerType('torchvision.ops.misc.ConvTranspose2d', class {});
- this.registerType('torchvision.ops.misc.FrozenBatchNorm2d', class {});
- this.registerType('torchvision.ops.misc.SqueezeExcitation', class {});
- this.registerType('torchvision.ops.poolers.LevelMapper', class {});
- this.registerType('torchvision.ops.poolers.MultiScaleRoIAlign', class {});
- this.registerType('torchvision.ops.stochastic_depth.StochasticDepth', class {});
- this.registerType('torchvision.transforms.functional.InterpolationMode', class {});
- this.registerType('torchvision.transforms.transforms.Compose', class {});
- this.registerType('torchvision.transforms.transforms.CenterCrop', class {});
- this.registerType('torchvision.transforms.transforms.Grayscale', class {});
- this.registerType('torchvision.transforms.transforms.Normalize', class {});
- this.registerType('torchvision.transforms.transforms.RandomAffine', class {});
- this.registerType('torchvision.transforms.transforms.RandomCrop', class {});
- this.registerType('torchvision.transforms.transforms.RandomHorizontalFlip', class {});
- this.registerType('torchvision.transforms.transforms.RandomRotation', class {});
- this.registerType('torchvision.transforms.transforms.Resize', class {});
- this.registerType('torchvision.transforms.transforms.Scale', class {});
- this.registerType('torchvision.transforms.transforms.ToPILImage', class {});
- this.registerType('torchvision.transforms.transforms.ToTensor', class {});
- this.registerFunction('torchvision.models.resnet.resnet34', function() {});
- this.registerFunction('builtins.annotate', function(type, value) {
- if (type === self._builtins.int) {
- return Number.isInteger(value) ? value : NaN;
- }
- if (type === self._builtins.float) {
- return typeof value === 'number' ? value : NaN;
- }
- if (type === self._builtins.number) {
- // if (pytorch.Utility.isTensor(value)) {
- // value.resize_([]);
- // }
- }
- return value;
- });
- this.registerFunction('builtins.unchecked_cast', function(type, value) {
- return value;
- });
- this.registerFunction('builtins.uninitialized', function(/* type */) {
- return undefined;
- });
- this.registerFunction('ops.prim.data', function(tensor) {
- return tensor;
- });
- this.registerFunction('ops.prim.device', function(tensor) {
- return tensor.device;
- });
- this.registerFunction('ops.prim.dtype', function(tensor) {
- return tensor.dtype.scalar_type();
- });
- this.registerFunction('ops.prim.is_quantized', function(tensor) {
- return tensor.is_quantized;
- });
- this.registerFunction('ops.prim.is_cuda', function(/* tensor */) {
- return false;
- });
- this.registerFunction('ops.prim.is_nested', function(tensor) {
- return tensor.is_nested;
- });
- this.registerFunction('ops.prim.is_sparse', function(tensor) {
- return tensor.is_sparse;
- });
- this.registerFunction('ops.prim.unchecked_unwrap_optional', function(value) {
- return value;
- });
- this.registerFunction('ops.prim.NumToTensor', function(value) {
- const tensor = self.invoke('torch.Tensor', []);
- tensor.value = value; // TODO
- return tensor;
- });
- this.registerFunction('ops.prim.min', function(value) {
- if (Array.isArray(value)) {
- return Math.min.apply(null, value);
- }
- return Math.min.apply(null, arguments);
- });
- this.registerFunction('ops.prim.max', function(value) {
- if (Array.isArray(value)) {
- return Math.max.apply(null, value);
- }
- return Math.max.apply(null, arguments);
- });
- this.registerFunction('ops.prim.shape', function(tensor) {
- return tensor && tensor.size ? tensor.size() : undefined;
- });
- this.registerFunction('ops.quantized.conv_prepack', function(weight, bias, stride, padding, dilation, groups) {
- const params = self.invoke('__torch__.torch.classes.quantized.Conv2dPackedParamsBase', []);
- params.weight = weight;
- params.bias = bias;
- params.stride = stride;
- params.padding =padding;
- params.dilation = dilation;
- params.groups = groups;
- return params;
- });
- this.registerFunction('ops.quantized.conv1d_prepack', function(weight, bias, stride, padding, dilation, groups) {
- const params = self.invoke('__torch__.torch.classes.quantized.Conv2dPackedParamsBase', []);
- params.weight = weight;
- params.bias = bias;
- params.stride = stride;
- params.padding =padding;
- params.dilation = dilation;
- params.groups = groups;
- return params;
- });
- this.registerFunction('ops.quantized.conv2d_prepack', function(weight, bias, stride, padding, dilation, groups) {
- const params = self.invoke('__torch__.torch.classes.quantized.Conv2dPackedParamsBase', []);
- params.weight = weight;
- params.bias = bias;
- params.stride = stride;
- params.padding =padding;
- params.dilation = dilation;
- params.groups = groups;
- return params;
- });
- this.registerFunction('ops.quantized.conv3d_prepack', function(weight, bias, stride, padding, dilation, groups) {
- const params = self.invoke('__torch__.torch.classes.quantized.Conv3dPackedParamsBase', []);
- params.weight = weight;
- params.bias = bias;
- params.stride = stride;
- params.padding =padding;
- params.dilation = dilation;
- params.groups = groups;
- return params;
- });
- this.registerFunction('ops.quantized.conv_transpose1d_prepack', function(weight, bias, stride, padding, output_padding, dilation, groups) {
- const params = self.invoke('__torch__.torch.classes.quantized.Conv2dPackedParamsBase', []);
- params.weight = weight;
- params.bias = bias;
- params.stride = stride;
- params.padding =padding;
- params.output_padding = output_padding;
- params.dilation = dilation;
- params.groups = groups;
- return params;
- });
- this.registerFunction('ops.quantized.conv_transpose2d_prepack', function(weight, bias, stride, padding, output_padding, dilation, groups) {
- const params = self.invoke('__torch__.torch.classes.quantized.Conv2dPackedParamsBase', []);
- params.weight = weight;
- params.bias = bias;
- params.stride = stride;
- params.padding =padding;
- params.output_padding = output_padding;
- params.dilation = dilation;
- params.groups = groups;
- return params;
- });
- this.registerFunction('ops.quantized.linear_prepack', function(weight, bias) {
- const params = self.invoke('__torch__.torch.classes.quantized.LinearPackedParamsBase', []);
- params.weight = weight;
- params.bias = bias;
- return params;
- });
- this.registerFunction('ops.prim.RaiseException', function(message) {
- throw new python.Error(message);
- });
- this.registerFunction('builtins.range', function(start, stop, step) {
- if (stop === undefined && step === undefined) {
- if (Number.isInteger(start)) {
- return Array(start).keys();
- }
- if (isNaN(start)) {
- return [];
- }
- }
- throw new python.Error('Unsupported range(' + JSON.stringify(start) + ', ' + JSON.stringify(stop) + ', ' + JSON.stringify(step) + ')');
- });
- this.registerFunction('torch._utils._rebuild_sparse_tensor', function(layout, data) {
- if (layout === torch.sparse_coo) {
- return self.invoke('torch._sparse_coo_tensor_unsafe', data);
- }
- throw new python.Error("Unsupported sparse tensor layout '" + (layout ? layout.__str__() : '') + "'.");
- });
- this.registerFunction('torch.from_numpy', function(obj) {
- const dtypes = new Map([
- [ '<f2', torch.float16 ],
- [ '<f4', torch.float32 ],
- [ '<f8', torch.float64 ],
- [ '<i2', torch.int16 ],
- [ '<i4', torch.int32 ],
- [ '<i8', torch.int64 ],
- ]);
- if (!dtypes.has(obj.dtype.str)) {
- throw new python.Error("Unsupported numpy.ndarray type '" + obj.dtype.str + "'.");
- }
- const dtype = dtypes.get(obj.dtype.str);
- const storage = execution.invoke('torch.storage._TypedStorage', [ obj.size, dtype ]);
- storage._set_cdata(obj.data);
- const tensor = execution.invoke('torch.Tensor', []);
- tensor.__setstate__([ storage, 0, obj.shape, null ]);
- return tensor;
- });
- this.registerFunction('torch._utils._rebuild_device_tensor_from_numpy', function(data, dtype, device, requires_grad) {
- const tensor = execution.invoke('torch.from_numpy', [ data ]);
- // tensor = tensor.to(dtype, device)
- tensor.requires_grad = requires_grad;
- return tensor;
- });
- this.registerFunction('torch._sparse_coo_tensor_unsafe', function(indices, values, size) {
- const tensor = self.invoke('torch.Tensor', []);
- tensor._layout = torch.sparse_coo;
- tensor._indices = indices;
- tensor._values = values;
- tensor._shape = size;
- return tensor;
- });
- this.registerFunction('torch._utils._rebuild_tensor', function (storage, storage_offset, size, stride) {
- if (Array.isArray(storage) && storage.length === 5 && storage[0] === 'storage') {
- const storage_type = storage[1];
- const size = storage[4];
- storage = new storage_type(size);
- }
- const name = storage.__class__.__module__ + '.' + storage.__class__.__name__.replace('Storage', 'Tensor');
- const tensor = self.invoke(name, []);
- tensor.__setstate__([ storage, storage_offset, size, stride ]);
- return tensor;
- });
- this.registerFunction('torch._utils._rebuild_tensor_v2', function (storage, storage_offset, size, stride, requires_grad, backward_hooks) {
- const tensor = execution.invoke('torch._utils._rebuild_tensor', [ storage, storage_offset, size, stride ]);
- tensor.requires_grad = requires_grad;
- tensor.backward_hooks = backward_hooks;
- return tensor;
- });
- this.registerFunction('torch._utils._rebuild_parameter', function(data, requires_grad, backward_hooks) {
- const obj = self.invoke('torch.nn.parameter.Parameter', [ data, requires_grad ]);
- obj.backward_hooks = backward_hooks;
- return obj;
- });
- this.registerFunction('torch._utils._rebuild_qtensor', function(storage, storage_offset, size, stride, quantizer_params, requires_grad, backward_hooks) {
- const tensor = execution.invoke('torch._utils._rebuild_tensor_v2', [ storage, storage_offset, size, stride, requires_grad, backward_hooks ]);
- tensor.quantizer_params = quantizer_params;
- return tensor;
- });
- this.registerFunction('torch._set_item', function(dict, key, value) {
- dict[key] = value;
- });
- this.registerFunction('torch.__and__', function(left, right) {
- return left && right;
- });
- this.registerFunction('torch.__contains__', function(dict, key) {
- return dict[key] !== undefined;
- });
- this.registerFunction('torch.__derive_index', function(index, start, step) {
- return start + index * step;
- });
- this.registerFunction('torch.__is__', function(left, right) {
- if (left === null && right === null) {
- return true;
- }
- if ((left !== null && right === null) || (left === null && right !== null)) {
- return false;
- }
- throw new python.Error("Unsupported 'torch.__is__' expression type.");
- });
- this.registerFunction('torch.__isnot__', function(left, right) {
- if (left === null && right === null) {
- return false;
- }
- if ((left !== null && right === null) || (left === null && right !== null)) {
- return true;
- }
- throw new python.Error("Unsupported 'torch.__isnot__' expression type.");
- });
- this.registerFunction('torch.__not__', function(value) {
- if (typeof value === 'boolean') {
- return !value;
- }
- throw new python.Error("Unsupported 'torch.__not__' expression type.");
- });
- this.registerFunction('torch.__range_length', function(lo, hi, step) {
- if (step === 0) {
- throw new python.Error('range() arg 3 must not be zero');
- }
- if (step > 0 && lo < hi) {
- return 1 + (hi - 1 - lo) / step;
- }
- else if (step < 0 && lo > hi) {
- return 1 + (lo - 1 - hi) / (0 - step);
- }
- return 0;
- });
- this.registerFunction('torch._unwrap_optional', function(value) {
- return value; // TODO
- });
- this.registerFunction('torch.add', function(left, right) {
- if (typeof left === 'number' && typeof right === 'number') {
- return left * right;
- }
- if (Array.isArray(left) && Array.isArray(right)) {
- return left.concat(right);
- }
- if (typeof left === 'string' && typeof right === 'string') {
- return left + right;
- }
- throw new python.Error('Unsupported torch.add expression type.');
- });
- this.registerFunction('torch.append', function(list, value) {
- list.push(value);
- return value;
- });
- this.registerFunction('torch.extend', function(list, value) {
- list.push(...value);
- });
- this.registerFunction('torch.insert', function(list, index, value) {
- list.splice(index, 0, value);
- return value;
- });
- this.registerFunction('torch.clear', function(value) {
- if (Object(value) === value) {
- for (const key of Object.keys(value)) {
- delete value[key];
- }
- }
- });
- this.registerFunction('torch.replace', function(value) {
- return value;
- });
- this.registerFunction('torch.dict', function(args) {
- const obj = {};
- if (args) {
- if (Array.isArray(args)) {
- for (const pair of args) {
- const key = pair[0];
- const value = pair[1];
- obj[key] = value;
- }
- }
- else {
- throw new python.Error("'torch.dict' arguments not supported.");
- }
- }
- return obj;
- });
- this.registerFunction('torch.dim', function(tensor) {
- if (tensor && tensor.size) {
- const size = tensor.size();
- if (size) {
- return size.length;
- }
- }
- return NaN; // TODO
- });
- this.registerFunction('torch.numel', function(tensor) {
- if (tensor && tensor.size) {
- const size = tensor.size();
- if (size) {
- return size.reduce((a, b) => a * b, 1);
- }
- }
- return NaN;
- });
- this.registerFunction('torch.eq', function(left, right) {
- if (typeof left === 'string' && typeof right === 'string') {
- return left === right;
- }
- if (typeof left === 'number' && typeof right === 'number') {
- if (isNaN(left) && isNaN(right)) {
- return true;
- }
- return left === right;
- }
- if (left === undefined || right === undefined) {
- return true;
- }
- if (Array.isArray(left) && Array.isArray(right)) {
- return left.length === right.length && left.every((item, index) => item === right[index]);
- }
- throw new python.Error("Unsupported 'torch.eq' expression type.");
- });
- this.registerFunction('torch.floor', function(value) {
- return Math.floor(value);
- });
- this.registerFunction('torch.ceil', function(value) {
- return Math.ceil(value);
- });
- this.registerFunction('torch.floordiv', function(left, right) {
- return Math.floor(left / right);
- });
- this.registerFunction('torch.format', function() {
- const args = Array.from(arguments);
- const list = args.shift().split(/({}D?)/);
- return list.map((text) => {
- if (text === '{}' || text === '{}D') {
- const arg = args.shift();
- return Array.isArray(arg) ? '[' + arg.map((item) => item.toString()).join(', ') + ']' : arg ? arg.toString() : '?';
- }
- return text;
- }).join('');
- });
- this.registerFunction('torch.gt', function(left, right) {
- if (typeof left === 'number' && typeof right === 'number') {
- if (!isNaN(left) && !isNaN(right)) {
- return left > right;
- }
- }
- if (isNaN(left) && !isNaN(right)) {
- return true;
- }
- throw new python.Error("Unsupported 'torch.gt' expression type.");
- });
- this.registerFunction('torch.ge', function(left, right) {
- if (typeof left === 'number' && typeof right === 'number') {
- if (!isNaN(left) && !isNaN(right)) {
- return left > right;
- }
- }
- if (isNaN(left) && !isNaN(right)) {
- return true;
- }
- throw new python.Error("Unsupported 'torch.ge' expression type.");
- });
- this.registerFunction('torch.is_floating_point', function(tensor) {
- const type = tensor.dtype.scalar_type();
- return (type === 5 || type === 6 || type === 7);
- });
- this.registerFunction('torch.is_grad_enabled', function() {
- return false;
- });
- this.registerFunction('torch.set_grad_enabled', function(/* value */) {
- });
- this.registerFunction('torch.serialization._get_layout', function(name) {
- const value = name.startsWith('torch.') ? torch[name.split('.')[1]] : null;
- return value instanceof torch.layout ? value : null;
- });
- this.registerFunction('torch.storage._load_from_bytes', function(b) {
- return torch.load(b);
- });
- this.registerFunction('torch.jit._pickle.build_boollist', function(data) {
- return data;
- });
- this.registerFunction('torch.jit._pickle.build_doublelist', function(data) {
- return data;
- });
- this.registerFunction('torch.jit._pickle.build_intlist', function(data) {
- return data;
- });
- this.registerFunction('torch.jit._pickle.build_tensorlist', function(data) {
- return data;
- });
- this.registerFunction('torch.jit._pickle.build_tensor_from_id', function(data) {
- return self.builtins.CONSTANTS['c' + data.toString()];
- });
- this.registerFunction('torch.jit._pickle.restore_type_tag', function(value /*, type_str */) {
- return value;
- });
- this.registerFunction('torch.keys', function(dict) {
- return Object.keys(dict);
- });
- this.registerFunction('torch.len', function(value) {
- if (Array.isArray(value)) {
- return value.length;
- }
- if (value && value.shape && value.__len__) {
- return value.__len__();
- }
- return NaN;
- });
- this.registerFunction('torch.le', function(left, right) {
- if (typeof left === 'number' && typeof right === 'number') {
- if (isNaN(left) || isNaN(right)) {
- return false;
- }
- return left <= right;
- }
- if (left === undefined || right === undefined) {
- return true;
- }
- throw new python.Error("Unsupported 'torch.le' expression type.");
- });
- this.registerFunction('torch.list', function(args) {
- return args;
- });
- this.registerFunction('torch.list_with_default', function(size /*, defaults */) {
- return size;
- });
- this.registerFunction('torch.load', function(f) {
- const legacy_load = (entries) => {
- const deserialized_objects = {};
- if (entries.has('storages')) {
- const data = entries.get('storages');
- const unpickler = execution.invoke('pickle.Unpickler', [ data ]);
- const num_storages = unpickler.load();
- for (let i = 0; i < num_storages; i++) {
- const args = unpickler.load();
- const key = args[0];
- const storage_type = args[2];
- const obj = storage_type._new_with_file(unpickler);
- deserialized_objects[key] = obj;
- }
- /*
- let storage_views = unpickler.load();
- for target_cdata, root_cdata, offset, size in storage_views:
- root = deserialized_objects[root_cdata]
- deserialized_objects[target_cdata] = root[offset:offset + size]
- */
- }
- if (entries.has('tensors')) {
- const data = entries.get('tensors');
- const unpickler = execution.invoke('pickle.Unpickler', [ data ]);
- const num_tensors = unpickler.load();
- const int32 = (unpickler) => {
- const buffer = unpickler.read(4);
- return buffer[0] + (buffer[1] << 8) + (buffer[2] << 16) + (buffer[3] << 24);
- };
- const int64 = (unpickler) => {
- const buffer = unpickler.read(8);
- if (buffer[6] !== 0 && buffer[7] !== 0) {
- throw new python.Error('Unsigned 64-bit value exceeds 32-bit range.');
- }
- return buffer[0] + (buffer[1] << 8) + (buffer[2] << 16) + (buffer[3] << 24) + (buffer[4] * 4294967296) + (buffer[5] * 1099511627776);
- };
- for (let i = 0; i < num_tensors; i++) {
- const args = unpickler.load();
- const key = args[0];
- const storage_id = args[1];
- const storage = deserialized_objects[storage_id];
- const ndim = int32(unpickler);
- unpickler.read(4);
- const shape = Array.from(new Array(ndim)).map(() => int64(unpickler));
- const stride = Array.from(new Array(ndim)).map(() => int64(unpickler));
- const storage_offset = int64(unpickler);
- const tensor = execution.invoke('torch._utils._rebuild_tensor', [ storage, storage_offset, shape, stride ]);
- deserialized_objects[key] = tensor;
- }
- }
- const data = entries.get('pickle');
- const unpickler = execution.invoke('pickle.Unpickler', [ data ]);
- unpickler.persistent_load = (saved_id) => deserialized_objects[saved_id];
- return unpickler.load();
- };
- const _legacy_load = () => {
- const unpickler = execution.invoke('pickle.Unpickler', [ f ]);
- unpickler.load(); // magic_number
- const protocol_version = unpickler.load();
- if (protocol_version != 1001) {
- throw new python.Error("Unsupported protocol version '" + protocol_version + "'.");
- }
- const sys_info = unpickler.load();
- if (sys_info.protocol_version != 1001) {
- throw new python.Error("Unsupported protocol version '" + sys_info.protocol_version + "'.");
- }
- if (sys_info.little_endian === false) {
- throw new python.Error("Unsupported big-endian storage data.");
- }
- const module_source_map = new Map();
- const deserialized_objects = new Map();
- unpickler.persistent_load = (saved_id) => {
- const typename = saved_id[0];
- switch (typename) {
- case 'module': {
- const module = saved_id[1];
- const source = saved_id[3];
- module_source_map.set(module, source);
- return saved_id[1];
- }
- case 'storage': {
- const storage_type = saved_id[1];
- const root_key = saved_id[2];
- /// const location = saved_id[3];
- const size = saved_id[4];
- const view_metadata = saved_id[5];
- if (!deserialized_objects.has(root_key)) {
- const obj = new storage_type(size);
- deserialized_objects.set(root_key, obj);
- }
- if (view_metadata) {
- const view_key = view_metadata.shift();
- view_metadata.shift(); // view_offset
- view_metadata.shift(); // view_size
- if (!deserialized_objects.has(view_key)) {
- const view = null; // storage.slice(view_offset, view_offset + view_size);
- deserialized_objects.set(view_key, view);
- }
- return deserialized_objects.get(view_key);
- }
- return deserialized_objects.get(root_key);
- }
- default: {
- throw new python.Error("Unsupported persistent load type '" + typename + "'.");
- }
- }
- };
- const obj = unpickler.load();
- const deserialized_storage_keys = unpickler.load();
- for (const deserialized_storage_key of deserialized_storage_keys) {
- const storage = deserialized_objects.get(deserialized_storage_key);
- storage._set_from_file(unpickler);
- }
- if (!obj) {
- throw new python.Error('File format is not PyTorch.');
- }
- if (obj === 'None') {
- throw new python.Error("File contains 'None' root object.");
- }
- return obj;
- };
- const _load = (entries) => {
- if (f.has('constant.pkl')) {
- throw python.Error("TorchScript 'torch.load' not supported.");
- }
- const loaded_storages = new Map();
- const persistent_load = (saved_id) => {
- const typename = saved_id[0];
- if (typename !== 'storage') {
- throw new python.Error("Unsupported persistent load type '" + typename + "'.");
- }
- const storage_type = saved_id[1];
- const key = saved_id[2];
- const numel = saved_id[4];
- if (!loaded_storages.has(key)) {
- const storage = new storage_type(numel);
- const name = 'data/' + key;
- const stream = entries.get(name);
- storage._set_cdata(stream);
- loaded_storages.set(key, storage);
- }
- return loaded_storages.get(key);
- };
- const data_file = entries.get('data.pkl');
- const unpickler = execution.invoke('pickle.Unpickler', [ data_file ]);
- unpickler.persistent_load = persistent_load;
- const result = unpickler.load();
- return result;
- };
- if (f instanceof Map) {
- if (f.has('pickle')) {
- return legacy_load(f);
- }
- if (f.has('data.pkl')) {
- return _load(f);
- }
- throw new python.Error("Unsupported 'torch.load' input '" + JSON.stringify(Array.from(f.keys())) + "'.");
- }
- return _legacy_load(f);
- });
- this.registerFunction('torch.lt', function(left, right) {
- if (typeof left === 'number' && typeof right === 'number') {
- return left < right;
- }
- throw new python.Error("Unsupported 'torch.lt' expression type.");
- });
- this.registerFunction('torch.mul', function(left, right) {
- if (typeof left === 'number' && typeof right === 'number') {
- return left * right;
- }
- if (isNaN(left) || isNaN(right)) {
- return NaN;
- }
- if (Array.isArray(left) && left.every((value) => typeof value === 'number') && typeof right === 'number') {
- return left.map((value) => value * right);
- }
- throw new python.Error("Unsupported 'torch.mul' expression type.");
- });
- this.registerFunction('torch.div', function(left, right) {
- if (typeof left === 'number' && typeof right === 'number') {
- return left / right;
- }
- if (isNaN(left) || isNaN(right)) {
- return NaN;
- }
- throw new python.Error("Unsupported 'torch.div' expression type.");
- });
- this.registerFunction('torch.round', function(value) {
- if (typeof value === 'number') {
- return Math.round(value);
- }
- if (isNaN(value)) {
- return value;
- }
- throw new python.Error("Unsupported 'torch.round' expression type.");
- });
- this.registerFunction('torch.remainder', function(left, right) {
- if (typeof left === 'number' && typeof right === 'number') {
- return left % right;
- }
- if (isNaN(left) || isNaN(right)) {
- return NaN;
- }
- throw new python.Error("Unsupported 'torch.remainder' expression type.");
- });
- this.registerFunction('torch.ne', function(left, right) {
- if (typeof left === 'boolean' && typeof right === 'boolean') {
- return left !== right;
- }
- if (typeof left === 'number' && typeof right === 'number') {
- if (isNaN(left) || isNaN(right)) {
- return false;
- }
- return left !== right;
- }
- if (Array.isArray(left) && Array.isArray(right) && left.length === right.length) {
- return false;
- }
- if (typeof left === 'string' && typeof right === 'string') {
- return left !== right;
- }
- if (left === undefined || right === undefined) {
- return true;
- }
- throw new python.Error("Unsupported 'torch.ne' expression type.");
- });
- this.registerFunction('torch.neg', function(value) {
- if (typeof value === 'number') {
- return -value;
- }
- throw new python.Error("Unsupported 'torch.neg' expression type.");
- });
- this.registerFunction('torch.q_scale', function(/* tensor */) {
- return -1; // TODO
- });
- this.registerFunction('torch.t', function(tensor) {
- return tensor;
- });
- this.registerFunction('torch.size', function(tensor, dim) {
- if (tensor && tensor.size) {
- const size = tensor.size();
- if (Array.isArray(size)) {
- if (dim === undefined) {
- return size;
- }
- if (Number.isInteger(dim)) {
- if (dim >= 0 && dim < size.length) {
- return size[dim];
- }
- if (dim < 0 && -dim < size.length) {
- return size[size.length + dim];
- }
- }
- throw new python.Error('Dimension out of range (expected to be in range of ' + JSON.stringify(size) + ', but got ' + JSON.stringify(dim) + ').');
- }
- }
- if (Number.isInteger(dim)) {
- return NaN;
- }
- return [];
- });
- this.registerFunction('torch.slice', function(l, start, end, step) {
- if (!Array.isArray(l)) {
- throw new python.Error('Slicing expected array');
- }
- step = step || 1;
- if (step !== 1) {
- throw new python.Error('Slicing only supports step=1');
- }
- start = Math.max(0, start >= 0 ? start : l.length + start);
- end = Math.min(l.length, end || Number.MAX_SAFE_INTEGER);
- return l.slice(start, end);
- });
- this.registerFunction('torch.sub', function(left, right) {
- if (typeof left === 'number' && typeof right === 'number') {
- return left - right;
- }
- throw new python.Error("Unsupported 'torch.sub' expression type.");
- });
- this.registerFunction('torch.nn.functional.gelu', function(/* input */) {
- throw new python.Error("Function not implemented.");
- });
- this.registerFunction('torch.nn.functional.interpolate', function(/* input */) {
- throw new python.Error("Function not implemented.");
- });
- this.registerFunction('torch.nn.functional.leaky_relu', function(/* input */) {
- throw new python.Error("Function not implemented.");
- });
- this.registerFunction('torch.nn.functional.linear', function(/* input */) {
- throw new python.Error("Function not implemented.");
- });
- this.registerFunction('torch.nn.functional.relu', function(/* input */) {
- throw new python.Error("Function not implemented.");
- });
- this.registerFunction('torch.nn.functional.tanh', function(/* input */) {
- throw new python.Error("Function not implemented.");
- });
- this.registerFunction('torch.values', function(dict) {
- return Object.keys(dict).map((key) => dict[key]);
- });
- this.registerFunction('torch.warn', function() {
- });
- this.registerFunction('torch.fx.graph_module.reduce_graph_module', function(body /*, import_block */) {
- // https://github.com/pytorch/pytorch/blob/master/torch/fx/graph_module.py
- return body;
- });
- this.registerFunction('torch_utils.persistence._reconstruct_persistent_obj', function(meta) {
- const name = '_imported_module_' + Math.floor(Math.random() * 10000).toString();
- const module = execution.invoke('types.ModuleType', [ name ]);
- execution.register('sys').modules.set(name, module);
- const context = new python.Execution.Context(module, null);
- execution.exec(meta.module_src, context);
- const obj = execution.invoke(name + '.' + meta.class_name, []);
- if (meta.state) {
- if (obj.__setstate__) {
- obj.__setstate__(meta.state);
- }
- else {
- Object.assign(obj, meta.state);
- }
- }
- return obj;
- });
- this.registerFunction('torch_utils.misc.assert_shape', function(/* tensor, ref_shape */) {});
- this.registerFunction('torch_utils.ops.conv2d_resample.conv2d_resample', function(/* x, w, f, up, down, padding, groups, flip_weight, flip_filter */) {});
- this.registerFunction('torch_utils.ops.upfirdn2d.setup_filter', function(/* x, f, up, down, padding, flip_filter, gain, impl */) {});
- this.registerFunction('torch_utils.ops.bias_act', function(/* x, b, dim, act, alpha, gain, clamp, impl */) {});
- this.registerFunction('torch_utils.ops.fma.fma', function(/* a, b, c */) {});
- this.registerType('torch.device', class {
- constructor(type, index) {
- this.type = type;
- if (index) {
- this.index = index;
- }
- }
- });
- this.registerType('torch.dtype', class {
- constructor(scalar_type, name, itemsize) {
- this._scalar_type = scalar_type;
- this._name = name;
- this._itemsize = itemsize;
- }
- scalar_type() {
- return this._scalar_type;
- }
- itemsize() {
- return this._itemsize;
- }
- __reduce__() {
- return this._name;
- }
- __str__() {
- return 'torch.' + this._name;
- }
- toString() {
- return this.__str__();
- }
- });
- this.registerType('torch.layout', class {
- constructor(name) {
- this._name = name;
- }
- __str__() {
- return this._name;
- }
- toString() {
- return this.__str__();
- }
- });
- this.registerType('torch.qscheme', class {
- constructor(name) {
- this._name = name;
- }
- __str__() {
- return this._name;
- }
- toString() {
- return this.__str__();
- }
- });
- this.registerType('torch.utils.hooks.RemovableHandle', class {
- __setstate__(state) {
- this.hooks_dict_ref = state[0] || new Map();
- this.id = state[1];
- }
- });
- this.registerType('torch.storage._StorageBase', class {
- constructor(size, dtype) {
- this._size = size;
- this._dtype = dtype;
- this._device = null;
- }
- get device() {
- return this._device;
- }
- get dtype() {
- return this._dtype;
- }
- element_size() {
- return this._dtype.element_size;
- }
- size() {
- return this._size;
- }
- get data() {
- return this._cdata;
- }
- _set_cdata(data) {
- const length = this.size() * this.dtype.itemsize();
- if (length !== data.length) {
- throw new python.Error('Storage data size mismatch.');
- }
- this._cdata = data;
- }
- _set_from_file(unpickler) {
- const buffer = unpickler.read(8);
- const size = buffer.reverse().reduce((a, b) => (a*256)+b, 0);
- if (size !== this.size()) {
- throw new python.Error('Storage size mismatch.');
- }
- const itemsize = this.dtype.itemsize();
- const data = unpickler.stream(itemsize * size);
- this._set_cdata(data);
- }
- static _new_with_file(unpickler) {
- const buffer = unpickler.read(8);
- const size = buffer.reverse().reduce((a, b) => (a*256)+b, 0);
- const storage = new this(size);
- const itemsize = storage.dtype.itemsize();
- const data = unpickler.stream(itemsize * size);
- storage._set_cdata(data);
- return storage;
- }
- });
- this.registerType('torch.storage._UntypedStorage', class extends torch.storage._StorageBase {
- constructor() {
- super();
- throw new python.Error('_UntypedStorage not implemented.');
- }
- });
- this.registerType('torch.storage._TypedStorage', class {
- constructor() {
- if (arguments.length >= 2 && Number.isInteger(arguments[0]) && arguments[1] instanceof torch.dtype) {
- this._size = arguments[0];
- this._dtype = arguments[1];
- if (arguments[3] instanceof torch.device) {
- this._device = arguments[3];
- }
- }
- else {
- throw new python.Error("Unsupported _TypedStorage arguments '" + JSON.stringify(arguments) + "'.");
- }
- }
- get device() {
- return this._device;
- }
- get dtype() {
- return this._dtype;
- }
- element_size() {
- return this._dtype.element_size;
- }
- size() {
- return this._size;
- }
- get data() {
- return this._cdata;
- }
- _set_cdata(data) {
- const length = this.size() * this.dtype.itemsize();
- if (length !== data.length) {
- throw new python.Error('Storage data size mismatch.');
- }
- this._cdata = data;
- }
- _set_from_file(unpickler) {
- const buffer = unpickler.read(8);
- const size = buffer.reverse().reduce((a, b) => (a*256)+b, 0);
- if (size !== this.size()) {
- throw new python.Error('Storage size mismatch.');
- }
- const itemsize = this.dtype.itemsize();
- const data = unpickler.stream(itemsize * size);
- this._set_cdata(data);
- }
- static _new_with_file(unpickler) {
- const buffer = unpickler.read(8);
- const size = buffer.reverse().reduce((a, b) => (a*256)+b, 0);
- const storage = new this(size);
- const itemsize = storage.dtype.itemsize();
- const data = unpickler.stream(itemsize * size);
- storage._set_cdata(data);
- return storage;
- }
- });
- this.registerType('torch.storage._LegacyStorage', class extends torch.storage._TypedStorage {
- constructor() {
- super();
- throw new python.Error('_LegacyStorage not implemented.');
- }
- });
- this.registerType('torch.BoolStorage', class extends torch.storage._StorageBase {
- constructor(size) {
- super(size, torch.bool);
- }
- });
- this.registerType('torch.ByteStorage', class extends torch.storage._StorageBase {
- constructor(size) {
- super(size, torch.uint8);
- }
- });
- this.registerType('torch.CharStorage', class extends torch.storage._StorageBase {
- constructor(size) {
- super(size, torch.int8);
- }
- });
- this.registerType('torch.ShortStorage', class extends torch.storage._StorageBase {
- constructor(size) {
- super(size, torch.int16);
- }
- });
- this.registerType('torch.IntStorage', class extends torch.storage._StorageBase {
- constructor(size) {
- super(size, torch.int32);
- }
- });
- this.registerType('torch.LongStorage', class extends torch.storage._StorageBase {
- constructor(size) {
- super(size, torch.int64);
- }
- });
- this.registerType('torch.HalfStorage', class extends torch.storage._StorageBase {
- constructor(size) {
- super(size, torch.float16);
- }
- });
- this.registerType('torch.FloatStorage', class extends torch.storage._StorageBase {
- constructor(size) {
- super(size, torch.float32);
- }
- });
- this.registerType('torch.DoubleStorage', class extends torch.storage._StorageBase {
- constructor(size) {
- super(size, torch.float64);
- }
- });
- this.registerType('torch.ComplexHalfStorage', class extends torch.storage._StorageBase {
- constructor(size) {
- super(size, torch.complex32);
- }
- });
- this.registerType('torch.ComplexFloatStorage', class extends torch.storage._StorageBase {
- constructor(size) {
- super(size, torch.complex64);
- }
- });
- this.registerType('torch.ComplexDoubleStorage', class extends torch.storage._StorageBase {
- constructor(size) {
- super(size, torch.complex128);
- }
- });
- this.registerType('torch.QInt8Storage', class extends torch.storage._StorageBase {
- constructor(size) {
- super(size, torch.qint8);
- }
- });
- this.registerType('torch.QUInt8Storage', class extends torch.storage._StorageBase {
- constructor(size) {
- super(size, torch.quint8);
- }
- });
- this.registerType('torch.QInt32Storage', class extends torch.storage._StorageBase {
- constructor(size) {
- super(size, torch.qint32);
- }
- });
- this.registerType('torch.BFloat16Storage', class extends torch.storage._StorageBase {
- constructor(size) {
- super(size, torch.bfloat16);
- }
- });
- this.registerType('torch.Size', class extends Array {
- constructor(size) {
- super(size.length);
- for (let i = 0; i < size.length; i++) {
- this[i] = size[i];
- }
- }
- __len__() {
- return this.length;
- }
- });
- this.registerType('torch.Tensor', class {
- constructor() {
- this._layout = torch.strided;
- }
- get device() {
- return this.storage().device;
- }
- get dtype() {
- if (this._layout === torch.sparse_coo) {
- return this._values.dtype();
- }
- return this.storage().dtype;
- }
- get shape() {
- return this._shape;
- }
- get layout() {
- return this._layout;
- }
- get values() {
- if (this._layout === torch.sparse_coo) {
- return this._values;
- }
- throw new python.Error("Unsupported values in layout'" + this._layout.__str__() + "'.");
- }
- get indices() {
- if (this._layout === torch.sparse_coo) {
- return this._indices;
- }
- throw new python.Error("Unsupported indices in layout'" + this._indices.__str__() + "'.");
- }
- get is_quantized() {
- return this.__quantized__ === true;
- }
- get is_nested() {
- return this.__nested__ === true;
- }
- get is_sparse() {
- return this.layout !== torch.strided;
- }
- size() {
- return this._shape;
- }
- storage() {
- if (!this._storage) {
- const name = this.__class__.__name__ == 'Tensor' ? 'FloatStorage' : this.__storage__.__name__.replace('Tensor', 'Storage');
- this._storage = self.invoke(this.__class__.__module__ + '.' + name, []);
- }
- return this._storage;
- }
- storage_offset() {
- return this._storage_offset;
- }
- stride() {
- return this._stride;
- }
- resize_(shape) {
- this._shape = shape;
- }
- __len__() {
- return this._shape[0];
- }
- __setstate__(state) {
- this._storage = state[0];
- this._storage_offset = state[1];
- this._shape = state[2];
- this._stride = state[3];
- }
- __bool__() {
- return true;
- }
- __int__() {
- const storage = this.storage();
- if (storage && storage.dtype.__reduce__() === 'int64' && storage.data.length === 8) {
- const buffer = storage.data.peek ? storage.data.peek() : storage.data;
- const view = new DataView(buffer.buffer, buffer.byteOffset, buffer.byteLength);
- return view.getInt64(0, true);
- }
- return NaN;
- }
- __float__() {
- const storage = this.storage();
- if (storage && storage.dtype.__reduce__() === 'float32') {
- if (storage.size() !== undefined && storage.data.length === 4) {
- const buffer = storage.data.peek ? storage.data.peek() : storage.data;
- const view = new DataView(buffer.buffer, buffer.byteOffset, buffer.byteLength);
- return view.getFloat32(0, true);
- }
- }
- return NaN;
- }
- __str__() {
- return 'tensor(...)';
- }
- });
- this.registerType('torch.nn.parameter.Parameter', class extends torch.Tensor {
- constructor(data, requires_grad) {
- super();
- if (!data) {
- data = self.invoke('torch.Tensor', [[]]);
- }
- this.data = data;
- this.requires_grad = requires_grad !== undefined ? requires_grad : true;
- }
- __setstate__(state) {
- switch (state.length) {
- case 3:
- this.data = null;
- break;
- case 4:
- this.data = state[0];
- break;
- case 5:
- this.data = state[0];
- break;
- default:
- throw new python.Error("Unsupported parameter state length '" + state.length + "'.");
- }
- }
- });
- this.registerType('torch.nn.parameter.UninitializedParameter', class extends torch.nn.parameter.Parameter {
- constructor(requires_grad /*, device, dtype */) {
- super(undefined, requires_grad);
- }
- });
- this.registerType('torch.BoolTensor', class extends torch.Tensor {});
- this.registerType('torch.ByteTensor', class extends torch.Tensor {});
- this.registerType('torch.CharTensor', class extends torch.Tensor {});
- this.registerType('torch.ShortTensor', class extends torch.Tensor {});
- this.registerType('torch.IntTensor', class extends torch.Tensor {});
- this.registerType('torch.LongTensor', class extends torch.Tensor {});
- this.registerType('torch.HalfTensor', class extends torch.Tensor {});
- this.registerType('torch.FloatTensor', class extends torch.Tensor {});
- this.registerType('torch.DoubleTensor', class extends torch.Tensor {});
- this.registerType('torch.ComplexFloatTensor', class extends torch.Tensor {});
- this.registerType('torch.ComplexDoubleTensor', class extends torch.Tensor {});
- this.registerType('torch.QInt8Tensor', class extends torch.Tensor {});
- this.registerType('torch.QUInt8Tensor', class extends torch.Tensor {});
- this.registerType('torch.QInt32Tensor', class extends torch.Tensor {});
- this.registerType('torch.BFloat16Tensor', class extends torch.Tensor {});
- this.registerType('torch.cuda.FloatTensor', class extends torch.Tensor {});
- this.registerType('torch.cuda.DoubleTensor', class extends torch.Tensor {});
- this.register('torch.nn').Module = this.register('torch.nn.modules.module').Module;
- this.register('torch.optim').Adam = this.register('torch.optim.adam').Adam;
- this.register('torch.nn').ReLU = this.register('torch.nn.modules.activation').ReLU;
- this.register('sklearn.utils').Bunch = this.register('sklearn.utils._bunch').Bunch;
- torch.uint8 = torch.ByteStorage.dtype = new torch.dtype(0, 'uint8', 1);
- torch.int8 = torch.CharStorage.dtype = new torch.dtype(1, 'int8', 1);
- torch.int16 = torch.ShortStorage.dtype = new torch.dtype(2, 'int16', 2);
- torch.int32 = torch.IntStorage.dtype = new torch.dtype(3, 'int32', 4);
- torch.int64 = torch.LongStorage.dtype = new torch.dtype(4, 'int64', 8);
- torch.float16 = torch.HalfStorage.dtype = new torch.dtype(5, 'float16', 2);
- torch.float32 = torch.FloatStorage.dtype = new torch.dtype(6, 'float32', 4);
- torch.float64 = torch.DoubleStorage.dtype = new torch.dtype(7, 'float64', 8);
- torch.complex32 = torch.ComplexHalfStorage.dtype = new torch.dtype(8, 'complex32', 4);
- torch.complex64 = torch.ComplexFloatStorage.dtype = new torch.dtype(9, 'complex64', 8);
- torch.complex128 = torch.ComplexDoubleStorage.dtype = new torch.dtype(10, 'complex128', 16);
- torch.bool = torch.BoolStorage.dtype = new torch.dtype(11, 'boolean', 1);
- torch.qint8 = torch.QInt8Storage.dtype = new torch.dtype(12, 'qint8', 1);
- torch.quint8 = torch.QUInt8Storage.dtype = new torch.dtype(13, 'quint8', 1);
- torch.qint32 = torch.QInt32Storage.dtype = new torch.dtype(14, 'qint32', 4);
- torch.bfloat16 = torch.BFloat16Storage.dtype = new torch.dtype(15, 'bfloat16', 2);
- torch.quint4x2 = new torch.dtype(16, 'quint4x2');
- torch.strided = new torch.layout('torch.strided');
- torch.sparse_coo = new torch.layout('torch.sparse_coo');
- torch.sparse_csr = new torch.layout('torch.sparse_csr');
- torch.sparse_csc = new torch.layout('torch.sparse_csc');
- torch.sparse_bsr = new torch.layout('torch.sparse_bsr');
- torch.sparse_bsc = new torch.layout('torch.sparse_bsc');
- torch._mkldnn = new torch.layout('torch._mkldnn');
- torch.per_tensor_affine = new torch.qscheme('torch.per_tensor_affine');
- torch.per_channel_affine = new torch.qscheme('torch.per_channel_affine');
- torch.per_tensor_symmetric = new torch.qscheme('torch.per_tensor_symmetric');
- torch.per_channel_symmetric = new torch.qscheme('torch.per_channel_symmetric');
- torch.per_channel_affine_float_qparams = new torch.qscheme('torch.per_channel_affine_float_qparams');
- torch.inf = this.register('math').inf;
- }
- get builtins() {
- return this._builtins;
- }
- source(file) {
- return this._sources.has(file) ? this._sources.get(file) : null;
- }
- debug(/* file */) {
- }
- exec(code , context) {
- const reader = new python.Parser(code, '', null);
- const program = reader.parse();
- if (!program) {
- throw new python.Error("Module '" + '?' + "' parse error.");
- }
- this.block(program.body, context);
- }
- parse(file) {
- const buffer = this.source(file);
- if (buffer) {
- const debug = this.debug(file);
- const code = this._utf8Decoder.decode(buffer);
- const parser = new python.Parser(code, file, debug);
- const program = parser.parse();
- if (!program) {
- throw new python.Error("Module '" + file + "' parse error.");
- }
- return program;
- }
- return null;
- }
- import(name, current, level) {
- if (level) {
- let bits = current.split('.');
- if (bits.length < level) {
- throw new python.Error('Invalid relative import beyond top-level package.');
- }
- bits = bits.slice(0, bits.length - level);
- const base = bits.join('.');
- name = name ? [ base, name ].join('.') : base;
- }
- const index = name.lastIndexOf('.');
- let parent = null;
- let child = null;
- if (index > 0) {
- parent = name.substring(0, index);
- child = name.substring(index + 1);
- this.import(parent);
- }
- if (!this._modules.has(name)) {
- const module = this._registry.get(name) || new this._builtins.module(name);
- module.__package__ = name;
- this._modules.set(name, module);
- const path = name.split('.').join('/');
- module.__path__ = [ path ];
- const file = path + '.py';
- const program = this.parse(file);
- if (program) {
- module.__file__ = file;
- for (const entry of Object.entries(this.builtins)) {
- switch (entry[0]) {
- case '__class__':
- case '__package__':
- case '__module__':
- case '__name__':
- case '__path__':
- case '__file__':
- break;
- default:
- module[entry[0]] = entry[1];
- break;
- }
- }
- const context = new python.Execution.Context(module, null);
- if (name !== 'builtins') {
- context.set('__builtins__', this._modules.get('builtins'));
- }
- this.block(program.body, context);
- }
- if (parent) {
- const parent_module = this._modules.get(parent);
- parent_module[child] = module;
- }
- }
- return this._modules.get(name);
- }
- __import__(name, globals, locals, fromlist, level) {
- let module = null;
- level = level || 0;
- if (level === 0) {
- module = this.import(name);
- }
- else {
- globals = globals || {};
- let current = globals.__package__;
- if (!current) {
- const spec = globals.__spec__;
- if (spec) {
- current = spec.parent;
- }
- else {
- const name = globals.__name__;
- const bits = name.split('.');
- bits.pop();
- current = bits.join('.');
- }
- }
- module = this.import(name, current, level);
- }
- if (!fromlist) {
- if (level === 0) {
- return this.import(name.split('.')[0]);
- }
- else if (name) {
- throw new python.Error("Unsupported relative import '" + name + "'.");
- // cut_off = len(name) - len(name.partition('.')[0])
- // return sys.modules[module.__name__[:len(module.__name__)-cut_off]]
- }
- }
- else if (module.__path__) {
- const handle_fromlist = (module, fromlist, recursive) => {
- for (const name of fromlist) {
- if (name == '*') {
- if (!recursive && module.__all__) {
- handle_fromlist(module, module.__all__, true);
- }
- }
- else if (!module[name]) {
- this.import(module.__name__ + '.' + name);
- }
- }
- return module;
- };
- handle_fromlist(module, fromlist);
- }
- return module;
- }
- module(name) {
- return this._modules.get(name);
- }
- resolve(name) {
- const index = name.lastIndexOf('.');
- const memberName = index === -1 ? name : name.substring(index + 1, name.length);
- const moduleName = index === -1 ? '' : name.substring(0, index);
- const module = this.import(moduleName);
- let type = module ? module[memberName] : null;
- if (!type) {
- if (!this._unresolved.has(name)) {
- const moduleName = name.split('.').shift();
- if (this._registry.has(moduleName) && moduleName !== '__main__') {
- this.emit('resolve', name);
- }
- const type = this._createType(name, class {});
- this._unresolved.set(name, type);
- }
- type = this._unresolved.get(name);
- }
- return type;
- }
- invoke(target, args) {
- if (typeof target === 'string') {
- target = this.resolve(target);
- }
- if (target) {
- if (target.__class__ === this._builtins.type) {
- if (target.prototype && target.prototype.__class__ === target) {
- return Reflect.construct(target, args);
- }
- const obj = Object.create(target);
- if (obj.__init__ && typeof obj.__init__ === 'function') {
- obj.__init__.apply(obj, args);
- }
- return obj;
- }
- else if (target.__class__ === this._builtins.function) {
- if (target.__call__) {
- return target.__call__(args);
- }
- return target.apply(null, args);
- }
- }
- throw new python.Error('Unsupported invoke target.');
- }
- call(target, name, args, context) {
- const callTarget = this.target(target, context);
- const callArguments = args.map((argument) => this.expression(argument, context));
- if (!callTarget || (name !== null && !callTarget[name])) {
- if (name === '__new__' && callArguments.length === 1 && callArguments[0] == callTarget) {
- name = null;
- callArguments.shift();
- }
- else {
- const format = (expression) => {
- if (expression.type == 'id') {
- return expression.value;
- }
- if (expression.type == '.') {
- return format(expression.target) + '.' + format(expression.member);
- }
- return null;
- };
- const targetName = format(target) + '.' + name;
- throw new python.Error("Unknown function '" + targetName + "'.");
- }
- }
- const func = name ? callTarget[name] : callTarget;
- if (func.__class__ === this._builtins.type) {
- if (func.prototype && func.prototype.__class__ === func) {
- return Reflect.construct(func, args);
- }
- const obj = Object.create(func);
- obj.__class__ = func;
- if (obj.__init__ && typeof obj.__init__ === 'function') {
- obj.__init__.apply(obj, args);
- }
- return obj;
- }
- if (func.__class__ === this._builtins.function) {
- if (func.__call__) {
- return func.__call__(callArguments);
- }
- }
- if (func.__class__ === this._builtins.method) {
- if (func.__call__) {
- return func.__call__([ callTarget ].concat(callArguments));
- }
- }
- if (typeof func === 'function') {
- return func.apply(callTarget, callArguments);
- }
- throw new python.Error("Unsupported call expression.");
- }
- apply(method, args, context) {
- const locals = Array.prototype.slice.call(args);
- context = new python.Execution.Context(context.globals, {});
- for (const parameter of method.parameters) {
- let value = locals.shift();
- if (value === undefined && parameter.initializer) {
- value = this.expression(parameter.initializer, context);
- }
- context.set(parameter.name, value);
- }
- return this.block(method.body.statements, context);
- }
- block(statements, context) {
- statements = Array.prototype.slice.call(statements);
- while (statements.length > 0) {
- const statement = statements.shift();
- const value = this.statement(statement, context);
- if (value !== undefined) {
- return value;
- }
- }
- return undefined;
- }
- statement(statement, context) {
- switch (statement.type) {
- case 'pass': {
- break;
- }
- case 'return': {
- return this.expression(statement.expression, context);
- }
- case 'def': {
- const module = context.get('__name__');
- const self = this;
- const parent = context.get('__class__');
- const type = (parent === this._builtins.module) ? this._builtins.function : this._builtins.method;
- const func = {
- __class__: type,
- __globals__: context,
- __module__: module,
- __name__: statement.name,
- __code__: statement,
- __call__: function(args) {
- return self.apply(this.__code__, args, this.__globals__);
- }
- };
- context.set(statement.name, func);
- break;
- }
- case 'class': {
- const bases = statement.bases.map((arg) => this.expression(arg, context));
- if (bases.length > 1) {
- throw new python.Error("Unsupported multiple bases for class '" + statement.name + "'.");
- }
- const base = bases.length === 1 ? bases[0] : null;
- const name = context.get('__name__') + '.' + statement.name;
- const value = this._createType(name, base ? class extends base {} : class {});
- value.__bases__ = bases;
- context.set(statement.name, value);
- this.block(statement.body.statements, new python.Execution.Context(context.globals, value.prototype));
- break;
- }
- case 'var': {
- context.set(statement.name, statement.initializer ? this.expression(statement.initializer, context) : undefined);
- break;
- }
- case '=': {
- this.expression(statement, context);
- break;
- }
- case 'if': {
- const condition = this.expression(statement.condition, context);
- if (condition === true || condition) {
- const value = this.block(statement.then.statements, context);
- if (value !== undefined) {
- return value;
- }
- break;
- }
- else if (condition === false) {
- const value = this.block(statement.else.statements, context);
- if (value !== undefined) {
- return value;
- }
- break;
- }
- throw new python.Error("Unsupported condition.");
- }
- case 'for': {
- if (statement.target.length == 1 &&
- statement.variable.length === 1 && statement.variable[0].type === 'id') {
- const range = this.expression(statement.target[0], context);
- const variable = statement.variable[0];
- for (const current of range) {
- this.statement({ type: '=', target: variable, expression: { type: 'number', value: current } }, context);
- const value = this.block(statement.body.statements, context);
- if (value !== undefined) {
- return value;
- }
- }
- break;
- }
- throw new python.Error("Unsupported 'for' statement.");
- }
- case 'while': {
- const condition = this.expression(statement.condition, context);
- if (condition) {
- const value = this.block(statement.body.statements, context);
- if (value !== undefined) {
- return value;
- }
- }
- break;
- }
- case 'with': {
- const items = [];
- for (const item of statement.item) {
- items.push(this.expression(item.expression, context));
- }
- for (const item of items) {
- if (item.__enter__ && item.__enter__.__call__) {
- item.__enter__.__call__([ item ]);
- }
- }
- const value = this.block(statement.body.statements, context);
- for (const item of items) {
- if (item.__exit__ && item.__exit__.__call__) {
- item.__exit__.__call__([ item ]);
- }
- }
- if (value !== undefined) {
- return value;
- }
- break;
- }
- case 'call': {
- this.expression(statement, context);
- break;
- }
- case 'import': {
- for (const alias of statement.names) {
- let module = this.__import__(alias.name, context);
- if (alias.asname) {
- const bits = alias.name.split('.').reverse();
- bits.pop();
- while (bits.length > 0) {
- module = module[bits.pop()];
- }
- context.set(alias.asname, module);
- }
- else {
- context.set(alias.name.split('.')[0], module);
- }
- }
- break;
- }
- case 'import_from': {
- const fromlist = statement.names.map((name) => name.name);
- const module = this.__import__(statement.module, context.globals, context.locals, fromlist, statement.level);
- for (const entry of statement.names) {
- const name = entry.name;
- const asname = entry.asname ? entry.asname : null;
- if (!module[name]) {
- throw new python.Error("Cannot import '" + name + "' from '" + statement.module + "'.");
- }
- context.set(asname ? asname : name, module[name]);
- }
- break;
- }
- case 'string': {
- break;
- }
- default: {
- throw new python.Error("Unsupported statement '" + statement.type + "'.");
- }
- }
- return undefined;
- }
- expression(expression, context) {
- const self = context.get('self');
- switch (expression.type) {
- case '=': {
- const target = expression.target;
- if (target.type === 'id') {
- context.set(target.value, this.expression(expression.expression, context));
- return undefined;
- }
- else if (target.type === '[]') {
- if (target.target.type === 'id' &&
- target.arguments.type === 'list' &&
- target.arguments.value.length === 1) {
- const index = this.expression(target.arguments.value[0], context);
- if (target.target.value === '__annotations__') {
- context.set(target.target.value, context.get(target.target.value) || {});
- }
- const obj = context.get(target.target.value);
- const value = this.expression(expression.expression, context);
- if (obj instanceof Map) {
- obj.set(index, value);
- }
- else {
- obj[index] = value;
- }
- return undefined;
- }
- }
- else if (target.type === '.' &&
- target.member.type === 'id') {
- this.expression(target.target, context)[target.member.value] = this.expression(expression.expression, context);
- return undefined;
- }
- else if (target.type === 'tuple') {
- context.target.push(target.value);
- const value = this.expression(expression.expression, context);
- context.target.pop();
- if (target.value.every((item) => item.type === 'id')) {
- if (target.value.length < value.length) {
- throw new python.Error('ValueError: too many values to unpack (expected ' + target.value.length + ', actual ' + value.length + ').');
- }
- if (target.value.length > value.length) {
- throw new python.Error('ValueError: not enough values to unpack (expected ' + target.value.length + ', actual ' + value.length + ').');
- }
- for (let i = 0; i < value.length; i++) {
- context.set(target.value[i].value, value[i]);
- }
- return undefined;
- }
- }
- break;
- }
- case 'list': {
- return expression.value.map((item) => this.expression(item, context));
- }
- case 'string': {
- return expression.value.substring(1, expression.value.length - 1);
- }
- case 'number': {
- return Number(expression.value);
- }
- case '[]': {
- if (expression.target.type === 'id' &&
- expression.arguments.type === 'list' &&
- expression.arguments.value.length === 1) {
- if (context.get(expression.target.value)) {
- const index = this.expression(expression.arguments.value[0], context);
- const target = context.get(expression.target.value);
- if (target instanceof Map) {
- return target.get(index);
- }
- return target[index < 0 ? target.length + index : index];
- }
- }
- const target = this.expression(expression.target, context);
- if (target && expression.arguments.type === 'list' &&
- (target.__class__ === this._typing._TupleType ||
- target.__class__ === this._typing._SpecialGenericAlias ||
- target.__class__ === this._typing._SpecialForm)) {
- const type = Object.assign({}, target);
- type.__args__ = expression.arguments.value.map((arg) => this.expression(arg, context));
- return type;
- }
- if (expression.arguments.type === 'list' && expression.arguments.value.length === 1) {
- const index = this.expression(expression.arguments.value[0], context);
- if (target instanceof Map) {
- return target.get(index);
- }
- return target[index < 0 ? target.length + index : index];
- }
- break;
- }
- case '.': {
- if (expression.member.type == 'id') {
- const target = this.target(expression.target, context);
- return target[expression.member.value];
- }
- throw new python.Error("Unsupported field expression.");
- }
- case 'call': {
- if (expression.target.type === 'id' && expression.target.value === 'unchecked_cast' && expression.arguments.length === 2) {
- return this.expression(expression.arguments[1], context);
- }
- if (expression.target.type === '.') {
- return this.call(expression.target.target, expression.target.member.value, expression.arguments, context);
- }
- return this.call(expression.target, null, expression.arguments, context);
- }
- case 'id': {
- switch (expression.value) {
- case 'self': return self;
- case 'None': return null;
- case 'True': return true;
- case 'False': return false;
- default: {
- const type = (value) => {
- return value &&
- (value.__class__ === this._builtins.type ||
- value.__class__ === this._typing._TupleType ||
- value.__class__ === this._typing._SpecialGenericAlias ||
- value.__class__ === this._typing._SpecialForm);
- };
- const builtin = this._builtins[expression.value];
- if (type(builtin)) {
- return builtin;
- }
- const value = context.get(expression.value);
- if (value === undefined) {
- const typing = this._typing[expression.value];
- if (type(typing)) {
- return typing;
- }
- }
- return value;
- }
- }
- }
- case 'tuple': {
- return expression.value.map((expression) => this.expression(expression, context));
- }
- case 'dict': {
- const dict = {};
- for (const pair of expression.value) {
- if (pair.type !== 'pair') {
- throw new python.Error("Unsupported dict item type '" + pair.type + "'.");
- }
- const key = this.expression(pair.key, context);
- const value = this.expression(pair.value, context);
- dict[key] = value;
- }
- return dict;
- }
- case 'unary': {
- switch (expression.op) {
- case '-': {
- return -this.expression(expression.operand, context);
- }
- default: {
- throw new python.Error("Unsupported unary expression '" + expression.op + "'.");
- }
- }
- }
- default: {
- throw new python.Error("Unsupported expression '" + expression.type + "'.");
- }
- }
- return undefined;
- }
- target(expression, context) {
- let current = expression;
- let path = [];
- for (;;) {
- if (current.type === '.' && current.member && current.member.type === 'id') {
- path.push(current.member.value);
- current = current.target;
- }
- else if (current.type === 'id' && current.value !== 'self' && current.value !== 'CONSTANTS') {
- path.push(current.value);
- break;
- }
- else {
- path = null;
- break;
- }
- }
- if (path) {
- let target = null;
- for (let i = path.length - 1; i >= 0; i--) {
- target = target ? target[path[i]] : context.get(path[i]);
- if (!target) {
- break;
- }
- }
- if (!target) {
- path.reverse();
- const name = path.join('.');
- const file = path.join('/') + '.py';
- if (this._sources.has(file)) {
- target = this.import(name);
- }
- else {
- target = this.resolve(name);
- }
- }
- return target;
- }
- return this.expression(expression, context);
- }
- add(name, source) {
- this._sources.set(name, source);
- }
- on(event, listener) {
- const value = this._events.get(event) || [];
- value.push(listener);
- this._events.set(event, value);
- }
- emit(event, ...args) {
- if (this._events.has(event)) {
- for (const callback of this._events.get(event)) {
- callback(this, ...args);
- }
- }
- }
- register(name, value) {
- if (!this._registry.has(name)) {
- value = value || new (this._registry.get('builtins').module)(name);
- this._registry.set(name, value);
- let current = name;
- for (;;) {
- const index = current.lastIndexOf('.');
- if (index === -1) {
- break;
- }
- const child = current.substring(index + 1);
- current = current.substring(0, index);
- const parent = this.register(current);
- parent[child] = value;
- value = parent;
- }
- }
- return this._registry.get(name);
- }
- registerFunction(name, value) {
- const parts = name.split('.');
- value.__class__ = this._builtins.function;
- value.__name__ = parts.pop();
- value.__module__ = parts.join('.');
- const module = this.register(value.__module__);
- if (module[name]) {
- throw new python.Error("Function '" + name + "' is already registered.");
- }
- module[value.__name__] = value;
- return value;
- }
- _createType(name, value) {
- const parts = name.split('.');
- value.__class__ = this._builtins.type;
- value.__name__ = parts.pop();
- value.__module__ = parts.join('.');
- value.prototype.__class__ = value;
- return value;
- }
- registerType(name, value) {
- value = this._createType(name, value);
- const parts = name.split('.');
- const memberName = parts.pop();
- const moduleName = parts.join('.');
- const module = this.register(moduleName);
- if (module[memberName]) {
- throw new python.Error("Class '" + memberName + "' is already registered.");
- }
- module[memberName] = value;
- return value;
- }
- };
- python.Execution.Context = class {
- constructor(globals, locals) {
- this.globals = globals;
- this.locals = locals;
- }
- set(name, value) {
- if (this.locals) {
- this.locals[name] = value;
- }
- else {
- this.globals[name] = value;
- }
- }
- get(name) {
- if (this.locals && name in this.locals) {
- return this.locals[name];
- }
- if (name in this.globals) {
- return this.globals[name];
- }
- return undefined;
- }
- get target() {
- this._target = this._target || [];
- return this._target;
- }
- };
- python.BinaryReader = class {
- constructor(buffer) {
- this._buffer = buffer;
- this._length = buffer.length;
- this._position = 0;
- this._view = new DataView(buffer.buffer, buffer.byteOffset, buffer.byteLength);
- this._utf8Decoder = new TextDecoder('utf-8');
- this._asciiDecoder = new TextDecoder('ascii');
- }
- get position() {
- return this._position;
- }
- get length() {
- return this._length;
- }
- seek(position) {
- this._position = position >= 0 ? position : this._length + position;
- if (this._position > this._buffer.length) {
- throw new Error('Expected ' + (this._position - this._buffer.length) + ' more bytes. The file might be corrupted. Unexpected end of file.');
- }
- }
- skip(offset) {
- this._position += offset;
- if (this._position > this._buffer.length) {
- throw new python.Error('Expected ' + (this._position - this._buffer.length) + ' more bytes. The file might be corrupted. Unexpected end of file.');
- }
- }
- stream(length) {
- const buffer = this.read(length);
- return new python.BinaryReader(buffer);
- }
- peek(length) {
- const position = this._position;
- length = length !== undefined ? length : this._length - this._position;
- this.skip(length);
- const end = this._position;
- this.skip(-length);
- if (position === 0 && length === this._length) {
- return this._buffer;
- }
- return this._buffer.subarray(position, end);
- }
- read(length) {
- const position = this._position;
- length = length !== undefined ? length : this._length - this._position;
- this.skip(length);
- if (position === 0 && length === this._length) {
- return this._buffer;
- }
- return this._buffer.subarray(position, this._position);
- }
- byte() {
- const position = this._position;
- this.skip(1);
- return this._view.getUint8(position);
- }
- uint16() {
- const position = this._position;
- this.skip(2);
- return this._view.getUint16(position, true);
- }
- int32() {
- const position = this._position;
- this.skip(4);
- return this._view.getInt32(position, true);
- }
- uint32() {
- const position = this._position;
- this.skip(4);
- return this._view.getUint32(position, true);
- }
- int64() {
- const position = this._position;
- this.skip(8);
- return this._view.getInt64(position, true).toNumber();
- }
- float64() {
- const position = this._position;
- this.skip(8);
- return this._view.getFloat64(position, false);
- }
- string(size, encoding) {
- const data = this.read(size);
- return (encoding == 'utf-8') ?
- this._utf8Decoder.decode(data) :
- this._asciiDecoder.decode(data);
- }
- line() {
- const index = this._buffer.indexOf(0x0A, this._position);
- if (index == -1) {
- throw new python.Error("Could not find end of line.");
- }
- const size = index - this._position;
- const text = this.string(size, 'ascii');
- this.skip(1);
- return text;
- }
- };
- python.StreamReader = class {
- constructor(stream) {
- this._stream = stream;
- this._length = stream.length;
- this._position = 0;
- this._utf8Decoder = new TextDecoder('utf-8');
- this._asciiDecoder = new TextDecoder('ascii');
- }
- get position() {
- return this._position;
- }
- get length() {
- return this._length;
- }
- seek(position) {
- this._stream.seek(position);
- this._position = this._stream.position;
- }
- skip(offset) {
- this._position += offset;
- if (this._position > this._length) {
- throw new python.Error('Expected ' + (this._position - this._length) + ' more bytes. The file might be corrupted. Unexpected end of file.');
- }
- }
- stream(length) {
- this._stream.seek(this._position);
- this.skip(length);
- return this._stream.stream(length);
- }
- peek(length) {
- this._stream.seek(this._position);
- return this._stream.peek(length);
- }
- read(length) {
- this._stream.seek(this._position);
- this.skip(length);
- return this._stream.read(length);
- }
- byte() {
- const position = this._fill(1);
- return this._view.getUint8(position);
- }
- uint16() {
- const position = this._fill(2);
- return this._view.getUint16(position, true);
- }
- int32() {
- const position = this._fill(4);
- return this._view.getInt32(position, true);
- }
- uint32() {
- const position = this._fill(4);
- return this._view.getUint32(position, true);
- }
- int64() {
- const position = this._fill(8);
- return this._view.getInt64(position, true).toNumber();
- }
- float64() {
- const position = this._fill(8);
- return this._view.getFloat64(position, true);
- }
- string(size, encoding) {
- const data = this.read(size);
- return (encoding == 'utf-8') ?
- this._utf8Decoder.decode(data) :
- this._asciiDecoder.decode(data);
- }
- line() {
- let position = this._fill(0);
- let index = this._buffer.indexOf(0x0A, position);
- if (index == -1) {
- const size = Math.min(0x1000000, this._stream.length - this._position);
- this._fill(size);
- this.skip(-size);
- position = this._fill(0);
- index = this._buffer.indexOf(0x0A, position);
- if (index == -1) {
- throw new python.Error("Could not find end of line.");
- }
- }
- const size = index - position;
- const text = this.string(size, 'ascii');
- this.skip(1);
- return text;
- }
- _fill(length) {
- if (this._position + length > this._length) {
- throw new Error('Expected ' + (this._position + length - this._length) + ' more bytes. The file might be corrupted. Unexpected end of file.');
- }
- if (!this._buffer || this._position < this._offset || this._position + length > this._offset + this._buffer.length) {
- this._offset = this._position;
- this._stream.seek(this._offset);
- this._buffer = this._stream.read(Math.min(0x10000000, this._length - this._offset));
- this._view = new DataView(this._buffer.buffer, this._buffer.byteOffset, this._buffer.byteLength);
- }
- const position = this._position;
- this._position += length;
- return position - this._offset;
- }
- };
- python.Error = class extends Error {
- constructor(message) {
- super(message);
- this.name = 'Python Error';
- }
- };
- if (typeof module !== 'undefined' && typeof module.exports === 'object') {
- module.exports.Execution = python.Execution;
- }
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