netron/source/rknn.js

/* jshint esversion: 6 */

var rknn = rknn || {};
var json = json || require('./json');

rknn.ModelFactory = class {

    match(context) {
        const stream = context.stream;
        const signature = [ 0x52, 0x4B, 0x4E, 0x4E, 0x00, 0x00, 0x00, 0x00 ];
        if (signature.length <= stream.length && stream.peek(signature.length).every((value, index) => value === signature[index])) {
            return true;
        }
        return false;
    }

    open(context) {
        return rknn.Metadata.open(context).then((metadata) => {
            const stream = context.stream;
            const container = rknn.Container.open(stream);
            return new rknn.Model(metadata, container.model, container.weights);
        });
    }
};

rknn.Model = class {

    constructor(metadata, model, weights) {
        this._version = model.version;
        this._producer = model.ori_network_platform || model.network_platform || '';
        this._runtime = model.target_platform ? model.target_platform.join(',') : '';
        this._graphs = [ new rknn.Graph(metadata, model, weights) ];
    }

    get format() {
        return 'RKNN v' + this._version;
    }

    get producer() {
        return this._producer;
    }

    get runtime() {
        return this._runtime;
    }

    get graphs() {
        return this._graphs;
    }
};

rknn.Graph = class {

    constructor(metadata, model, weights) {
        this._name = model.name || '';
        this._inputs = [];
        this._outputs = [];
        this._nodes = [];

        const args = new Map();
        for (const const_tensor of model.const_tensor) {
            const name = 'const_tensor:' + const_tensor.tensor_id.toString();
            const shape = new rknn.TensorShape(const_tensor.size);
            const type = new rknn.TensorType(const_tensor.dtype, shape);
            const tensor = new rknn.Tensor(type, const_tensor.offset, weights);
            const argument = new rknn.Argument(name, type, tensor);
            args.set(name, argument);
        }
        for (const virtual_tensor of model.virtual_tensor) {
            const name = virtual_tensor.node_id.toString() + ':' + virtual_tensor.output_port.toString();
            const argument = new rknn.Argument(name, null, null);
            args.set(name, argument);
        }
        for (const norm_tensor of model.norm_tensor) {
            const name = 'norm_tensor:' + norm_tensor.tensor_id.toString();
            const shape = new rknn.TensorShape(norm_tensor.size);
            const type = new rknn.TensorType(norm_tensor.dtype, shape);
            const argument = new rknn.Argument(name, type, null);
            args.set(name, argument);
        }

        for (const node of model.nodes) {
            node.input = [];
            node.output = [];
        }
        for (const connection of model.connection) {
            switch (connection.left) {
                case 'input':
                    model.nodes[connection.node_id].input.push(connection);
                    if (connection.right_node) {
                        model.nodes[connection.right_node.node_id].output[connection.right_node.tensor_id] = connection;
                    }
                    break;
                case 'output':
                    model.nodes[connection.node_id].output.push(connection);
                    break;
            }
        }

        for (const graph of model.graph) {
            const key = graph.right + ':' + graph.right_tensor_id.toString();
            const argument = args.get(key);
            if (!argument) {
                throw new rknn.Error("Invalid argument '" + key + "'.");
            }
            const name = graph.left + ((graph.left_tensor_id === 0) ? '' : graph.left_tensor_id.toString());
            const parameter = new rknn.Parameter(name, [ argument ]);
            switch (graph.left) {
                case 'input': {
                    this._inputs.push(parameter);
                    break;
                }
                case 'output': {
                    this._outputs.push(parameter);
                    break;
                }
            }
        }

        for (const node of model.nodes) {
            this._nodes.push(new rknn.Node(metadata, node, args));
        }
    }

    get name() {
        return this._name;
    }

    get inputs() {
        return this._inputs;
    }

    get outputs() {
        return this._outputs;
    }

    get nodes() {
        return this._nodes;
    }
};

rknn.Parameter = class {

    constructor(name, args) {
        this._name = name;
        this._arguments = args;
    }

    get name() {
        return this._name;
    }

    get visible() {
        return true;
    }

    get arguments() {
        return this._arguments;
    }
};

rknn.Argument = class {

    constructor(name, type, initializer) {
        if (typeof name !== 'string') {
            throw new rknn.Error("Invalid argument identifier '" + JSON.stringify(name) + "'.");
        }
        this._name = name;
        this._type = type || null;
        this._initializer = initializer || null;
    }

    get name() {
        return this._name;
    }

    get type() {
        return this._type;
    }

    get initializer() {
        return this._initializer;
    }
};

rknn.Node = class {

    constructor(metadata, node, args) {
        this._metadata = metadata;
        this._name = node.name || '';
        this._type = node.op;
        this._inputs = [];
        this._outputs = [];
        this._attributes = [];
        const schema = this._metadata.type(this._type);
        node.input = node.input || [];
        for (let i = 0; i < node.input.length; ) {
            const input = schema && schema.inputs && i < schema.inputs.length ? schema.inputs[i] : { name: i === 0 ? 'input' : i.toString() };
            const count = input.list ? node.input.length - i : 1;
            const list = node.input.slice(i, i + count).map((input) => {
                if (input.right_tensor) {
                    const key = input.right_tensor.type + ':' + input.right_tensor.tensor_id.toString();
                    const argument = args.get(key);
                    if (!argument) {
                        throw new rknn.Error("Invalid input argument '" + key + "'.");
                    }
                    return argument;
                }
                if (input.right_node) {
                    const key = input.right_node.node_id.toString() + ':' + input.right_node.tensor_id.toString();
                    const argument = args.get(key);
                    if (!argument) {
                        throw new rknn.Error("Invalid input argument '" + key + "'.");
                    }
                    return argument;
                }
                throw new rknn.Error('Invalid input argument.');
            });
            this._inputs.push(new rknn.Parameter(input.name, list));
            i += count;
        }
        node.output = node.output || [];
        for (let i = 0; i < node.output.length; ) {
            const output = schema && schema.outputs && i < schema.outputs.length ? schema.outputs[i] : { name: i === 0 ? 'output' : i.toString() };
            const count = output.list ? node.output.length - i : 1;
            const list = node.output.slice(i, i + count).map((output) => {
                if (output.right_tensor) {
                    const key = output.right_tensor.type + ':' + output.right_tensor.tensor_id.toString();
                    const argument = args.get(key);
                    if (!argument) {
                        throw new rknn.Error("Invalid output argument '" + key + "'.");
                    }
                    return argument;
                }
                if (output.right_node) {
                    const key = output.right_node.node_id.toString() + ':' + output.right_node.tensor_id.toString();
                    const argument = args.get(key);
                    if (!argument) {
                        throw new rknn.Error("Invalid output argument '" + key + "'.");
                    }
                    return argument;
                }
                throw new rknn.Error('Invalid output argument.');
            });
            this._outputs.push(new rknn.Parameter(output.name, list));
            i += count;
        }
        if (node.nn) {
            const nn = node.nn;
            for (const key of Object.keys(nn)) {
                const params = nn[key];
                for (const name of Object.keys(params)) {
                    const value = params[name];
                    this._attributes.push(new rknn.Attribute(name, value));
                }
            }
        }
    }

    get name() {
        return this._name;
    }

    get type() {
        const prefix = 'VSI_NN_OP_';
        return this._type.startsWith(prefix) ? this._type.substring(prefix.length) : this.type;
    }

    get metadata() {
        return this._metadata.type(this._type);
    }

    get inputs() {
        return this._inputs;
    }

    get outputs() {
        return this._outputs;
    }

    get attributes() {
        return this._attributes;
    }
};

rknn.Attribute = class {

    constructor(name, value) {
        this._name = name;
        this._value = value;
    }

    get name() {
        return this._name;
    }

    get value() {
        return this._value;
    }
};

rknn.Tensor = class {

    constructor(type, offset, weights) {
        this._type = type;
        let size = 0;
        switch (this._type.dataType) {
            case 'uint8': size = 1; break;
            case 'int8': size = 1; break;
            case 'int32': size = 4; break;
            case 'float16': size = 2; break;
            case 'float32': size = 4; break;
        }
        const shape = type.shape.dimensions;
        size = size * (shape.length === 0 ? 1 : shape.reduce((a, b) => a * b));
        if (size > 0) {
            this._data = weights.slice(offset, offset + size);
        }
    }

    get type() {
        return this._type;
    }

    get state() {
        return this._context().state || null;
    }

    get value() {
        const context = this._context();
        if (context.state) {
            return null;
        }
        context.limit = Number.MAX_SAFE_INTEGER;
        return this._decode(context, 0);
    }

    toString() {
        const context = this._context();
        if (context.state) {
            return '';
        }
        context.limit = 10000;
        const value = this._decode(context, 0);
        return JSON.stringify(value, '', '    ');
    }

    _context() {
        const context = {};
        if (!this._type.dataType) {
            context.state = 'Tensor data type is not implemented.';
            return context;
        }
        if (!this._data) {
            context.state = 'Tensor data is empty.';
            return context;
        }
        context.index = 0;
        context.count = 0;
        context.shape = this._type.shape.dimensions;
        context.dataType = this._type.dataType;
        context.view = new DataView(this._data.buffer, this._data.byteOffset, this._data.byteLength);
        return context;
    }

    _decode(context, dimension) {
        const shape = context.shape.length !== 0 ? context.shape : [ 1 ];
        const results = [];
        const size = shape[dimension];
        if (dimension == shape.length - 1) {
            for (let i = 0; i < size; i++) {
                if (context.count > context.limit) {
                    results.push('...');
                    return results;
                }
                switch (context.dataType) {
                    case 'float16':
                        results.push(context.view.getFloat16(context.index, true));
                        context.index += 2;
                        context.count++;
                        break;
                    case 'float32':
                        results.push(context.view.getFloat32(context.index, true));
                        context.index += 4;
                        context.count++;
                        break;
                    case 'uint8':
                        results.push(context.view.getUint8(context.index, true));
                        context.index++;
                        context.count++;
                        break;
                    case 'int8':
                        results.push(context.view.getInt8(context.index, true));
                        context.index += 1;
                        context.count++;
                        break;
                    case 'int32':
                        results.push(context.view.getInt32(context.index, true));
                        context.index += 4;
                        context.count++;
                        break;
                }
            }
        }
        else {
            for (let j = 0; j < size; j++) {
                if (context.count > context.limit) {
                    results.push('...');
                    return results;
                }
                results.push(this._decode(context, dimension + 1));
            }
        }
        if (context.shape.length == 0) {
            return results[0];
        }
        return results;
    }
};

rknn.TensorType = class {

    constructor(dataType, shape) {
        switch (dataType.vx_type) {
            case 'VSI_NN_TYPE_UINT8': this._dataType = 'uint8'; break;
            case 'VSI_NN_TYPE_INT8': this._dataType = 'int8'; break;
            case 'VSI_NN_TYPE_INT16': this._dataType = 'int16'; break;
            case 'VSI_NN_TYPE_INT32': this._dataType = 'int32'; break;
            case 'VSI_NN_TYPE_INT64': this._dataType = 'int64'; break;
            case 'VSI_NN_TYPE_FLOAT16': this._dataType = 'float16'; break;
            case 'VSI_NN_TYPE_FLOAT32': this._dataType = 'float32'; break;
            default:
                throw new rknn.Error("Invalid data type '" + JSON.stringify(dataType) + "'.");
        }
        this._shape = shape;
    }

    get dataType() {
        return this._dataType;
    }

    get shape() {
        return this._shape;
    }

    toString() {
        return this.dataType + this._shape.toString();
    }
};

rknn.TensorShape = class {

    constructor(shape) {
        this._dimensions = shape;
    }

    get dimensions() {
        return this._dimensions;
    }

    toString() {
        if (!this._dimensions || this._dimensions.length == 0) {
            return '';
        }
        return '[' + this._dimensions.join(',') + ']';
    }
};

rknn.Container = class {

    static open(stream) {
        const signature = [ 0x52, 0x4B, 0x4E, 0x4E, 0x00, 0x00, 0x00, 0x00 ];
        if (signature.length <= stream.length && stream.peek(signature.length).every((value, index) => value === signature[index])) {
            return new rknn.Container(stream);
        }
        return null;
    }

    constructor(stream) {
        this._reader = new rknn.Container.StreamReader(stream);
    }

    get version() {
        this._read();
        return this._version;
    }

    get weights() {
        this._read();
        return this._weights;
    }

    get model() {
        this._read();
        return this._model;
    }

    _read() {
        if (this._reader) {
            this._reader.uint64();
            this._version = this._reader.uint64();
            this._weights = this._reader.read();
            const buffer = this._reader.read();
            const reader = json.TextReader.create(buffer);
            this._model = reader.read();
            delete this._reader;
        }
    }
};

rknn.Container.StreamReader = class {

    constructor(stream) {
        this._stream = stream;
        this._length = stream.length;
        this._position = 0;
    }

    skip(offset) {
        this._position += offset;
        if (this._position > this._length) {
            throw new rknn.Error('Expected ' + (this._position - this._length) + ' more bytes. The file might be corrupted. Unexpected end of file.');
        }
    }

    uint64() {
        this.skip(8);
        const buffer = this._stream.read(8);
        const view = new DataView(buffer.buffer, buffer.byteOffset, buffer.byteLength);
        return view.getUint64(0, true).toNumber();
    }

    read() {
        const size = this.uint64();
        this.skip(size);
        return this._stream.read(size);
    }
};

rknn.Metadata = class {

    static open(context) {
        if (rknn.Metadata._metadata) {
            return Promise.resolve(rknn.Metadata._metadata);
        }
        return context.request('rknn-metadata.json', 'utf-8', null).then((data) => {
            rknn.Metadata._metadata = new rknn.Metadata(data);
            return rknn.Metadata._metadata;
        }).catch(() => {
            rknn.Metadata._metadata = new rknn.Metadata(null);
            return rknn.Metadata._metadata;
        });
    }

    constructor(data) {
        this._map = new Map();
        if (data) {
            const metadata = JSON.parse(data);
            this._map = new Map(metadata.map((item) => [ item.name, item ]));
        }
    }

    type(name) {
        return this._map.has(name) ? this._map.get(name) : null;
    }

    attribute(type, name) {
        const schema = this.type(type);
        if (schema) {
            let attributeMap = schema.attributeMap;
            if (!attributeMap) {
                attributeMap = {};
                if (schema.attributes) {
                    for (const attribute of schema.attributes) {
                        attributeMap[attribute.name] = attribute;
                    }
                }
                schema.attributeMap = attributeMap;
            }
            const attributeSchema = attributeMap[name];
            if (attributeSchema) {
                return attributeSchema;
            }
        }
        return null;
    }
};

rknn.Error = class extends Error {

    constructor(message) {
        super(message);
        this.name = 'Error loading RKNN model.';
    }
};

if (typeof module !== 'undefined' && typeof module.exports === 'object') {
    module.exports.ModelFactory = rknn.ModelFactory;
}