Update paddle-proto.js

source/paddle-proto.js

@@ -810,10 +810,10 @@ paddle.framework.proto.VarType = class VarType {
                     message.selected_rows = paddle.framework.proto.VarType.TensorDesc.decode(reader, reader.uint32());
                     break;
                 case 3:
-                    message.lod_tensor = paddle.framework.proto.VarType.LoDTensorDesc.decode(reader, reader.uint32());
+                    message.dense_tensor = paddle.framework.proto.VarType.DenseTensorDesc.decode(reader, reader.uint32());
                     break;
                 case 4:
-                    message.tensor_array = paddle.framework.proto.VarType.LoDTensorArrayDesc.decode(reader, reader.uint32());
+                    message.tensor_array = paddle.framework.proto.VarType.DenseTensorArrayDesc.decode(reader, reader.uint32());
                     break;
                 case 5:
                     message.reader = paddle.framework.proto.VarType.ReaderDesc.decode(reader, reader.uint32());
@@ -859,11 +859,11 @@ paddle.framework.proto.VarType = class VarType {
                 case "selected_rows":
                     message.selected_rows = paddle.framework.proto.VarType.TensorDesc.decodeText(reader);
                     break;
-                case "lod_tensor":
-                    message.lod_tensor = paddle.framework.proto.VarType.LoDTensorDesc.decodeText(reader);
+                case "dense_tensor":
+                    message.dense_tensor = paddle.framework.proto.VarType.DenseTensorDesc.decodeText(reader);
                     break;
                 case "tensor_array":
-                    message.tensor_array = paddle.framework.proto.VarType.LoDTensorArrayDesc.decodeText(reader);
+                    message.tensor_array = paddle.framework.proto.VarType.DenseTensorArrayDesc.decodeText(reader);
                     break;
                 case "reader":
                     message.reader = paddle.framework.proto.VarType.ReaderDesc.decodeText(reader);
@@ -900,7 +900,7 @@ paddle.framework.proto.VarType = class VarType {
 
 paddle.framework.proto.VarType.prototype.type = 0;
 paddle.framework.proto.VarType.prototype.selected_rows = null;
-paddle.framework.proto.VarType.prototype.lod_tensor = null;
+paddle.framework.proto.VarType.prototype.dense_tensor = null;
 paddle.framework.proto.VarType.prototype.tensor_array = null;
 paddle.framework.proto.VarType.prototype.reader = null;
 paddle.framework.proto.VarType.prototype.tuple = null;
@@ -1001,10 +1001,10 @@ paddle.framework.proto.VarType.TensorDesc = class TensorDesc {
 
 paddle.framework.proto.VarType.TensorDesc.prototype.data_type = 0;
 
-paddle.framework.proto.VarType.LoDTensorDesc = class LoDTensorDesc {
+paddle.framework.proto.VarType.DenseTensorDesc = class DenseTensorDesc {
 
     static decode(reader, length) {
-        const message = new paddle.framework.proto.VarType.LoDTensorDesc();
+        const message = new paddle.framework.proto.VarType.DenseTensorDesc();
         const end = length === undefined ? reader.length : reader.position + length;
         while (reader.position < end) {
             const tag = reader.uint32();
@@ -1027,7 +1027,7 @@ paddle.framework.proto.VarType.LoDTensorDesc = class LoDTensorDesc {
     }
 
     static decodeText(reader) {
-        const message = new paddle.framework.proto.VarType.LoDTensorDesc();
+        const message = new paddle.framework.proto.VarType.DenseTensorDesc();
         reader.start();
         while (!reader.end()) {
             const tag = reader.tag();
@@ -1050,13 +1050,13 @@ paddle.framework.proto.VarType.LoDTensorDesc = class LoDTensorDesc {
     }
 };
 
-paddle.framework.proto.VarType.LoDTensorDesc.prototype.tensor = null;
-paddle.framework.proto.VarType.LoDTensorDesc.prototype.lod_level = 0;
+paddle.framework.proto.VarType.DenseTensorDesc.prototype.tensor = null;
+paddle.framework.proto.VarType.DenseTensorDesc.prototype.lod_level = 0;
 
-paddle.framework.proto.VarType.LoDTensorArrayDesc = class LoDTensorArrayDesc {
+paddle.framework.proto.VarType.DenseTensorArrayDesc = class DenseTensorArrayDesc {
 
     static decode(reader, length) {
-        const message = new paddle.framework.proto.VarType.LoDTensorArrayDesc();
+        const message = new paddle.framework.proto.VarType.DenseTensorArrayDesc();
         const end = length === undefined ? reader.length : reader.position + length;
         while (reader.position < end) {
             const tag = reader.uint32();
@@ -1079,7 +1079,7 @@ paddle.framework.proto.VarType.LoDTensorArrayDesc = class LoDTensorArrayDesc {
     }
 
     static decodeText(reader) {
-        const message = new paddle.framework.proto.VarType.LoDTensorArrayDesc();
+        const message = new paddle.framework.proto.VarType.DenseTensorArrayDesc();
         reader.start();
         while (!reader.end()) {
             const tag = reader.tag();
@@ -1102,13 +1102,13 @@ paddle.framework.proto.VarType.LoDTensorArrayDesc = class LoDTensorArrayDesc {
     }
 };
 
-paddle.framework.proto.VarType.LoDTensorArrayDesc.prototype.tensor = null;
-paddle.framework.proto.VarType.LoDTensorArrayDesc.prototype.lod_level = 0;
+paddle.framework.proto.VarType.DenseTensorArrayDesc.prototype.tensor = null;
+paddle.framework.proto.VarType.DenseTensorArrayDesc.prototype.lod_level = 0;
 
 paddle.framework.proto.VarType.ReaderDesc = class ReaderDesc {
 
     constructor() {
-        this.lod_tensor = [];
+        this.dense_tensor = [];
     }
 
     static decode(reader, length) {
@@ -1118,7 +1118,7 @@ paddle.framework.proto.VarType.ReaderDesc = class ReaderDesc {
             const tag = reader.uint32();
             switch (tag >>> 3) {
                 case 1:
-                    message.lod_tensor.push(paddle.framework.proto.VarType.LoDTensorDesc.decode(reader, reader.uint32()));
+                    message.dense_tensor.push(paddle.framework.proto.VarType.DenseTensorDesc.decode(reader, reader.uint32()));
                     break;
                 default:
                     reader.skipType(tag & 7);
@@ -1134,8 +1134,8 @@ paddle.framework.proto.VarType.ReaderDesc = class ReaderDesc {
         while (!reader.end()) {
             const tag = reader.tag();
             switch (tag) {
-                case "lod_tensor":
-                    message.lod_tensor.push(paddle.framework.proto.VarType.LoDTensorDesc.decodeText(reader));
+                case "dense_tensor":
+                    message.dense_tensor.push(paddle.framework.proto.VarType.DenseTensorDesc.decodeText(reader));
                     break;
                 default:
                     reader.field(tag, message);

source/paddle-schema.js

@@ -70,8 +70,8 @@ paddle.lite.fbs.proto.VarType = class VarType {
         const $ = new paddle.lite.fbs.proto.VarType();
         $.type = reader.int32_(position, 4, 0);
         $.selected_rows = reader.table(position, 6, paddle.lite.fbs.proto.VarType_.TensorDesc);
-        $.lod_tensor = reader.table(position, 8, paddle.lite.fbs.proto.VarType_.LoDTensorDesc);
-        $.tensor_array = reader.table(position, 10, paddle.lite.fbs.proto.VarType_.LoDTensorArrayDesc);
+        $.dense_tensor = reader.table(position, 8, paddle.lite.fbs.proto.VarType_.DenseTensorDesc);
+        $.tensor_array = reader.table(position, 10, paddle.lite.fbs.proto.VarType_.DenseTensorArrayDesc);
         $.reader = reader.table(position, 12, paddle.lite.fbs.proto.VarType_.ReaderDesc);
         $.tuple = reader.table(position, 14, paddle.lite.fbs.proto.VarType_.Tuple);
         return $;
@@ -81,8 +81,8 @@ paddle.lite.fbs.proto.VarType = class VarType {
         const $ = new paddle.lite.fbs.proto.VarType();
         $.type = paddle.lite.fbs.proto.VarType_.Type[json.type];
         $.selected_rows = reader.object(json.selected_rows, paddle.lite.fbs.proto.VarType_.TensorDesc);
-        $.lod_tensor = reader.object(json.lod_tensor, paddle.lite.fbs.proto.VarType_.LoDTensorDesc);
-        $.tensor_array = reader.object(json.tensor_array, paddle.lite.fbs.proto.VarType_.LoDTensorArrayDesc);
+        $.dense_tensor = reader.object(json.dense_tensor, paddle.lite.fbs.proto.VarType_.DenseTensorDesc);
+        $.tensor_array = reader.object(json.tensor_array, paddle.lite.fbs.proto.VarType_.DenseTensorArrayDesc);
         $.reader = reader.object(json.reader, paddle.lite.fbs.proto.VarType_.ReaderDesc);
         $.tuple = reader.object(json.tuple, paddle.lite.fbs.proto.VarType_.Tuple);
         return $;
@@ -248,7 +248,7 @@ paddle.lite.fbs.proto.VarType_.Type = {
     FP16: 4,
     FP32: 5,
     FP64: 6,
-    LOD_TENSOR: 7,
+    DENSE_TENSOR: 7,
     SELECTED_ROWS: 8,
     FEED_MINIBATCH: 9,
     FETCH_LIST: 10,
@@ -281,34 +281,34 @@ paddle.lite.fbs.proto.VarType_.TensorDesc = class TensorDesc {
     }
 };
 
-paddle.lite.fbs.proto.VarType_.LoDTensorDesc = class LoDTensorDesc {
+paddle.lite.fbs.proto.VarType_.DenseTensorDesc = class DenseTensorDesc {
 
     static decode(reader, position) {
-        const $ = new paddle.lite.fbs.proto.VarType_.LoDTensorDesc();
+        const $ = new paddle.lite.fbs.proto.VarType_.DenseTensorDesc();
         $.tensor = reader.table(position, 4, paddle.lite.fbs.proto.VarType_.TensorDesc);
         $.lod_level = reader.int32_(position, 6, 0);
         return $;
     }
 
     static decodeText(reader, json) {
-        const $ = new paddle.lite.fbs.proto.VarType_.LoDTensorDesc();
+        const $ = new paddle.lite.fbs.proto.VarType_.DenseTensorDesc();
         $.tensor = reader.object(json.tensor, paddle.lite.fbs.proto.VarType_.TensorDesc);
         $.lod_level = reader.value(json.lod_level, 0);
         return $;
     }
 };
 
-paddle.lite.fbs.proto.VarType_.LoDTensorArrayDesc = class LoDTensorArrayDesc {
+paddle.lite.fbs.proto.VarType_.DenseTensorArrayDesc = class DenseTensorArrayDesc {
 
     static decode(reader, position) {
-        const $ = new paddle.lite.fbs.proto.VarType_.LoDTensorArrayDesc();
+        const $ = new paddle.lite.fbs.proto.VarType_.DenseTensorArrayDesc();
         $.tensor = reader.table(position, 4, paddle.lite.fbs.proto.VarType_.TensorDesc);
         $.lod_level = reader.int32_(position, 6, 0);
         return $;
     }
 
     static decodeText(reader, json) {
-        const $ = new paddle.lite.fbs.proto.VarType_.LoDTensorArrayDesc();
+        const $ = new paddle.lite.fbs.proto.VarType_.DenseTensorArrayDesc();
         $.tensor = reader.object(json.tensor, paddle.lite.fbs.proto.VarType_.TensorDesc);
         $.lod_level = reader.value(json.lod_level, 0);
         return $;
@@ -319,13 +319,13 @@ paddle.lite.fbs.proto.VarType_.ReaderDesc = class ReaderDesc {
 
     static decode(reader, position) {
         const $ = new paddle.lite.fbs.proto.VarType_.ReaderDesc();
-        $.lod_tensor = reader.tables(position, 4, paddle.lite.fbs.proto.VarType_.LoDTensorDesc);
+        $.dense_tensor = reader.tables(position, 4, paddle.lite.fbs.proto.VarType_.DenseTensorDesc);
         return $;
     }
 
     static decodeText(reader, json) {
         const $ = new paddle.lite.fbs.proto.VarType_.ReaderDesc();
-        $.lod_tensor = reader.objects(json.lod_tensor, paddle.lite.fbs.proto.VarType_.LoDTensorDesc);
+        $.dense_tensor = reader.objects(json.dense_tensor, paddle.lite.fbs.proto.VarType_.DenseTensorDesc);
         return $;
     }
 };
@@ -464,10 +464,10 @@ paddle.lite.fbs.proto = paddle.lite.fbs.proto || {};
 
 paddle.lite.fbs.proto.ParamDesc_ = paddle.lite.fbs.proto.ParamDesc_ || {};
 
-paddle.lite.fbs.proto.ParamDesc_.LoDTensorDesc = class LoDTensorDesc {
+paddle.lite.fbs.proto.ParamDesc_.DenseTensorDesc = class DenseTensorDesc {
 
     static decode(reader, position) {
-        const $ = new paddle.lite.fbs.proto.ParamDesc_.LoDTensorDesc();
+        const $ = new paddle.lite.fbs.proto.ParamDesc_.DenseTensorDesc();
         $.lod_level = reader.int32_(position, 4, 0);
         $.lod = reader.int64s_(position, 6);
         $.dim = reader.int64s_(position, 8);
@@ -477,7 +477,7 @@ paddle.lite.fbs.proto.ParamDesc_.LoDTensorDesc = class LoDTensorDesc {
     }
 
     static decodeText(reader, json) {
-        const $ = new paddle.lite.fbs.proto.ParamDesc_.LoDTensorDesc();
+        const $ = new paddle.lite.fbs.proto.ParamDesc_.DenseTensorDesc();
         $.lod_level = reader.value(json.lod_level, 0);
         $.lod = reader.array(json.lod);
         $.dim = reader.array(json.dim);
@@ -508,14 +508,14 @@ paddle.lite.fbs.proto.ParamDesc_.VariableDesc = class {
 
     static decode(reader, position, type) {
         switch (type) {
-            case 1: return paddle.lite.fbs.proto.ParamDesc_.LoDTensorDesc.decode(reader, position);
+            case 1: return paddle.lite.fbs.proto.ParamDesc_.DenseTensorDesc.decode(reader, position);
             default: return undefined;
         }
     }
 
     static decodeText(reader, json, type) {
         switch (type) {
-            case 'LoDTensorDesc': return paddle.lite.fbs.proto.ParamDesc_.LoDTensorDesc.decodeText(reader, json);
+            case 'DenseTensorDesc': return paddle.lite.fbs.proto.ParamDesc_.DenseTensorDesc.decodeText(reader, json);
             default: return undefined;
         }
     }

source/paddle.js

@@ -285,7 +285,7 @@ paddle.Graph = class {
             this.name = block.idx.toString();
             const values = new Map();
             for (const variable of block.vars) {
-                const type = variable.type && variable.type.type && variable.type.lod_tensor && variable.type.lod_tensor.tensor ? paddle.Utility.createTensorType(variable.type.lod_tensor.tensor.data_type, variable.type.lod_tensor.tensor.dims) : null;
+                const type = variable.type && variable.type.type && variable.type.dense_tensor && variable.type.dense_tensor.tensor ? paddle.Utility.createTensorType(variable.type.dense_tensor.tensor.data_type, variable.type.dense_tensor.tensor.dims) : null;
                 const tensor = variable.persistable && variable.type && variable.type.type !== paddle.DataType.FETCH_LIST && variable.type.type !== paddle.DataType.FEED_MINIBATCH ? (tensors.get(variable.name) || new paddle.Tensor(type)) : null;
                 values.set(variable.name, new paddle.Value(variable.name, type, tensor));
             }
@@ -847,13 +847,13 @@ paddle.DataType = {
     FP16: 4,
     FP32: 5,
     FP64: 6,
-    LOD_TENSOR: 7,
+    DENSE_TENSOR: 7,
     SELECTED_ROWS: 8,
     FEED_MINIBATCH: 9,
     FETCH_LIST: 10,
     STEP_SCOPES: 11,
     LOD_RANK_TABLE: 12,
-    LOD_TENSOR_ARRAY: 13,
+    DENSE_TENSOR_ARRAY: 13,
     PLACE_LIST: 14,
     READER: 15,
     RAW: 17,