@tensorflow/tfjs-converter - npm Package Compare versions

Comparing version 0.6.5 to 0.6.6

dist/src/executor/graph_executor.d.ts

@@ -21,5 +21,7 @@ import { NamedTensorMap, NamedTensorsMap, TensorInfo } from '../data/types';
     execute(inputs: NamedTensorsMap, strictInputCheck?: boolean, outputs?: string | string[]): NamedTensorMap;
+    private getFrozenTensorIds(tensorMap);
+    private checkTensorForDisposal(nodeName, node, tensorMap, context, tensorsToKeep, intermediateTensorConsumerCount);
     executeAsync(inputs: NamedTensorsMap, outputs?: string | string[]): Promise<NamedTensorMap>;
     private executeWithControlFlow(inputs, context);
-    private processStack(inputNodes, stack, context, tensorMap, added);
+    private processStack(inputNodes, stack, context, tensorMap, added, tensorsToKeep, intermediateTensorConsumerCount);
     private processChildNodes(node, stack, context, tensorMap, added);
@@ -26,0 +28,0 @@ private calculateOutputs(outputs?);

dist/src/executor/graph_executor.js

@@ -171,2 +171,4 @@ "use strict";
             var tensorMap = __assign({}, _this.weightMap, inputs);
+            var tensorsToKeep = _this.getFrozenTensorIds(tensorMap);
+            var intermediateTensorConsumerCount = {};
             var compiledNodes = _this.compiledMap.get(names.join(_this.SEPERATOR));
@@ -178,2 +180,3 @@ for (var i = 0; i < compiledNodes.length; i++) {
                         operation_executor_1.executeOp(node, tensorMap, context);
+                    _this.checkTensorForDisposal(node.name, node, tensorMap, context, tensorsToKeep, intermediateTensorConsumerCount);
                 }
@@ -188,2 +191,39 @@ if (outputNames.every(function (name) { return !!tensorMap[name]; })) {
     };
+    GraphExecutor.prototype.getFrozenTensorIds = function (tensorMap) {
+        var ids = Object.keys(tensorMap)
+            .map(function (key) { return tensorMap[key]; })
+            .map(function (tensors) { return tensors.map(function (tensor) { return tensor.id; }); });
+        return new (Set.bind.apply(Set, [void 0].concat(ids)))();
+    };
+    GraphExecutor.prototype.checkTensorForDisposal = function (nodeName, node, tensorMap, context, tensorsToKeep, intermediateTensorConsumerCount) {
+        if (node.category === 'control') {
+            return;
+        }
+        tensorMap[nodeName].forEach(function (tensor) {
+            if (tensor != null) {
+                intermediateTensorConsumerCount[tensor.id] =
+                    (intermediateTensorConsumerCount[tensor.id] || 0) +
+                        node.children.length;
+            }
+        });
+        node.inputs.forEach(function (input) {
+            if (input.category !== 'control') {
+                var tensors = utils_1.getTensorsForCurrentContenxt(input.name, tensorMap, context);
+                if (tensors != null) {
+                    tensors.forEach(function (tensor) {
+                        if (tensor && !tensorsToKeep.has(tensor.id)) {
+                            var count = intermediateTensorConsumerCount[tensor.id];
+                            if (count === 1) {
+                                tensor.dispose();
+                                delete intermediateTensorConsumerCount[tensor.id];
+                            }
+                            else if (count != null) {
+                                intermediateTensorConsumerCount[tensor.id]--;
+                            }
+                        }
+                    });
+                }
+            }
+        });
+    };
     GraphExecutor.prototype.executeAsync = function (inputs, outputs) {
@@ -225,3 +265,3 @@ return __awaiter(this, void 0, void 0, function () {
             var _this = this;
-            var names, inputNodes, stack, tensorMap, added, promises;
+            var names, inputNodes, stack, tensorMap, intermediateTensorConsumerCount, tensorsToKeep, added, promises;
             return __generator(this, function (_a) {
@@ -236,2 +276,4 @@ switch (_a.label) {
                         tensorMap = __assign({}, this.weightMap, inputs);
+                        intermediateTensorConsumerCount = {};
+                        tensorsToKeep = this.getFrozenTensorIds(tensorMap);
                         added = {};
@@ -241,3 +283,3 @@ _a.label = 1;
                         if (!(stack.length > 0)) return [3, 3];
-                        promises = this.processStack(inputNodes, stack, context, tensorMap, added);
+                        promises = this.processStack(inputNodes, stack, context, tensorMap, added, tensorsToKeep, intermediateTensorConsumerCount);
                         return [4, Promise.all(promises)];
@@ -252,3 +294,3 @@ case 2:
     };
-    GraphExecutor.prototype.processStack = function (inputNodes, stack, context, tensorMap, added) {
+    GraphExecutor.prototype.processStack = function (inputNodes, stack, context, tensorMap, added, tensorsToKeep, intermediateTensorConsumerCount) {
         var _this = this;
@@ -274,2 +316,3 @@ var promises = [];
                         context.currentContext = currentContext_1;
+                        _this.checkTensorForDisposal(nodeName, item.node, tensorMap, context, tensorsToKeep, intermediateTensorConsumerCount);
                         _this.processChildNodes(item.node, stack, context, tensorMap, added);
@@ -281,2 +324,3 @@ return t;
                     tensorMap[nodeName] = tensors;
+                    this_1.checkTensorForDisposal(nodeName, item.node, tensorMap, context, tensorsToKeep, intermediateTensorConsumerCount);
                     this_1.processChildNodes(item.node, stack, context, tensorMap, added);
@@ -283,0 +327,0 @@ }

dist/src/operations/executors/basic_math_executor.js

@@ -83,2 +83,4 @@ "use strict";
             return [tfc.div(tfc.scalar(1.0, 'float32'), tfc.sqrt(utils_1.getTensor(node.inputNames[0], tensorMap, context)))];
+        case 'prod':
+            return [tfc.prod(utils_1.getParamValue('x', node, tensorMap, context), utils_1.getParamValue('axes', node, tensorMap, context))];
         default:
@@ -85,0 +87,0 @@ throw TypeError("Node type " + node.op + " is not implemented");

dist/src/operations/executors/control_executor.js

@@ -66,3 +66,5 @@ "use strict";
                     return [3, 17];
-                case 1: return [2, [utils_1.getParamValue('pred', node, tensorMap, context)]];
+                case 1: return [2, [
+                        utils_1.getParamValue('pred', node, tensorMap, context).clone()
+                    ]];
                 case 2:
@@ -72,6 +74,8 @@ pred = utils_1.getParamValue('pred', node, tensorMap, context);
                     return [4, pred.data()];
-                case 3: return [2, (_b.sent())[0] ? [undefined, data_1] : [data_1, undefined]];
+                case 3: return [2, (_b.sent())[0] ? [undefined, data_1.clone()] :
+                        [data_1.clone(), undefined]];
                 case 4:
                     inputName = node.inputNames.find(function (name) { return utils_1.getTensor(name, tensorMap, context) !== undefined; });
-                    return [2, inputName ? [utils_1.getTensor(inputName, tensorMap, context)] : undefined];
+                    return [2, inputName ? [utils_1.getTensor(inputName, tensorMap, context).clone()] :
+                            undefined];
                 case 5:
@@ -81,11 +85,11 @@ frameId = utils_1.getParamValue('frameName', node, tensorMap, context);
                     context.enterFrame(frameId);
-                    return [2, [data]];
+                    return [2, [data.clone()]];
                 case 6:
                     tensor = utils_1.getParamValue('tensor', node, tensorMap, context);
                     context.exitFrame();
-                    return [2, [tensor]];
+                    return [2, [tensor.clone()]];
                 case 7:
                     input = utils_1.getParamValue('tensor', node, tensorMap, context);
                     context.nextIteration();
-                    return [2, [input]];
+                    return [2, [input.clone()]];
                 case 8:
@@ -92,0 +96,0 @@ size = utils_1.getParamValue('size', node, tensorMap, context);

dist/src/operations/executors/graph_executor.js

@@ -16,3 +16,5 @@ "use strict";
         case 'fakeQuantWithMinMaxVars':
-            return [utils_1.getParamValue('x', node, tensorMap, context)];
+            return [
+                utils_1.getParamValue('x', node, tensorMap, context).clone()
+            ];
         case 'snapshot':
@@ -19,0 +21,0 @@ var snapshot = utils_1.getParamValue('x', node, tensorMap, context);

dist/src/operations/executors/slice_join_executor.js

@@ -80,2 +80,20 @@ "use strict";
         }
+        case 'scatterNd': {
+            var indices = utils_1.getParamValue('indices', node, tensorMap, context);
+            var values = utils_1.getParamValue('values', node, tensorMap, context);
+            var shape = utils_1.getParamValue('shape', node, tensorMap, context);
+            return [tfc.scatterND(indices, values, shape)];
+        }
+        case 'gatherNd': {
+            var x = utils_1.getParamValue('x', node, tensorMap, context);
+            var indices = utils_1.getParamValue('indices', node, tensorMap, context);
+            return [tfc.gatherND(x, indices)];
+        }
+        case 'sparseToDense': {
+            var indices = utils_1.getParamValue('sparseIndices', node, tensorMap, context);
+            var shape = utils_1.getParamValue('outputShape', node, tensorMap, context);
+            var sparseValues = utils_1.getParamValue('sparseValues', node, tensorMap, context);
+            var defaultValue = utils_1.getParamValue('defaultValue', node, tensorMap, context);
+            return [tfc.sparseToDense(indices, sparseValues, shape, defaultValue)];
+        }
         default:
@@ -82,0 +100,0 @@ throw TypeError("Node type " + node.op + " is not implemented");

dist/src/operations/executors/test_helper.d.ts

@@ -13,2 +13,2 @@ import { OpMapper, ParamValue } from '../types';
 export declare function createDtypeAttr(dtype: string): ParamValue;
-export declare function validateParam(node: Node, opMappers: OpMapper[]): boolean;
+export declare function validateParam(node: Node, opMappers: OpMapper[], tfOpName?: string): boolean;

dist/src/operations/executors/test_helper.js

@@ -43,4 +43,6 @@ "use strict";
 exports.createDtypeAttr = createDtypeAttr;
-function validateParam(node, opMappers) {
-    var opMapper = opMappers.find(function (mapper) { return mapper.dlOpName === node.op; });
+function validateParam(node, opMappers, tfOpName) {
+    var opMapper = tfOpName != null ?
+        opMappers.find(function (mapper) { return mapper.tfOpName === tfOpName; }) :
+        opMappers.find(function (mapper) { return mapper.dlOpName === node.op; });
     return Object.keys(node.params).every(function (key) {
@@ -47,0 +49,0 @@ var value = node.params[key];

dist/src/operations/executors/utils.d.ts

@@ -7,4 +7,5 @@ import * as tfc from '@tensorflow/tfjs-core';
 export declare function getTensor(name: string, tensorsMap: NamedTensorsMap, context: ExecutionContext): tfc.Tensor;
+export declare function getTensorsForCurrentContenxt(name: string, tensorsMap: NamedTensorsMap, context: ExecutionContext): tfc.Tensor[];
 export declare function getNodeNameAndIndex(inputName: string, context?: ExecutionContext): [string, number];
 export declare function parseNodeName(name: string): [string, number];
 export declare function split(arr: number[], size: number): number[][];

dist/src/operations/executors/utils.js

@@ -34,2 +34,6 @@ "use strict";
 exports.getTensor = getTensor;
+function getTensorsForCurrentContenxt(name, tensorsMap, context) {
+    return tensorsMap[getNodeNameWithContextId(name, context.currentContextId)];
+}
+exports.getTensorsForCurrentContenxt = getTensorsForCurrentContenxt;
 function getNodeNameAndIndex(inputName, context) {
@@ -36,0 +40,0 @@ var _a = parseNodeName(inputName), nodeName = _a[0], index = _a[1];

dist/src/operations/op_list/basic_math.js

@@ -464,4 +464,24 @@ "use strict";
         ]
+    },
+    {
+        'tfOpName': 'Prod',
+        'dlOpName': 'prod',
+        'category': 'basic_math',
+        'params': [
+            { 'tfInputIndex': 0, 'dlParamName': 'x', 'type': 'tensor' },
+            { 'tfInputIndex': 1, 'dlParamName': 'axes', 'type': 'number[]' }, {
+                'tfParamName': 'keep_dims',
+                'dlParamName': 'keepDims',
+                'type': 'bool',
+                'notSupported': true
+            },
+            {
+                'tfParamName': 'T',
+                'dlParamName': 'dtype',
+                'type': 'dtype',
+                'notSupported': true
+            }
+        ]
     }
 ];
 //# sourceMappingURL=basic_math.js.map

dist/src/operations/op_list/slice_join.d.ts

@@ -48,2 +48,17 @@ export declare const json: ({
         'tfInputIndex': number;
+        'dlParamName': string;
+        'type': string;
+        notSupported?: undefined;
+    } | {
+        'tfInputIndex': number;
+        'dlParamName': string;
+        'type': string;
+        'notSupported': boolean;
+    })[];
+} | {
+    'tfOpName': string;
+    'dlOpName': string;
+    'category': string;
+    'params': ({
+        'tfInputIndex': number;
         'tfInputParamLength': number;
@@ -95,2 +110,21 @@ 'dlParamName': string;
     })[];
+} | {
+    'tfOpName': string;
+    'dlOpName': string;
+    'category': string;
+    'params': ({
+        'tfInputIndex': number;
+        'dlParamName': string;
+        'type': string;
+        tfParamName?: undefined;
+        defaultValue?: undefined;
+        notSupported?: undefined;
+    } | {
+        'tfParamName': string;
+        'dlParamName': string;
+        'type': string;
+        'defaultValue': boolean;
+        'notSupported': boolean;
+        tfInputIndex?: undefined;
+    })[];
 })[];

dist/src/operations/op_list/slice_join.js

@@ -39,3 +39,3 @@ "use strict";
             { 'tfInputIndex': 1, 'dlParamName': 'indices', 'type': 'tensor' }, {
-                'tfParamName': 'axis',
+                'tfInputIndex': 2,
                 'dlParamName': 'axis',
@@ -72,4 +72,8 @@ 'type': 'number',
         'params': [
-            { 'tfInputIndex': 0, 'dlParamName': 'x', 'type': 'tensor' },
-            { 'tfInputIndex': 1, 'dlParamName': 'axis', 'type': 'number' }
+            { 'tfInputIndex': 0, 'dlParamName': 'x', 'type': 'tensor' }, {
+                'tfInputIndex': 1,
+                'dlParamName': 'dims',
+                'type': 'bool',
+                'notSupported': true
+            }
         ]
@@ -83,3 +87,3 @@ },
             { 'tfInputIndex': 0, 'dlParamName': 'x', 'type': 'tensor' },
-            { 'tfInputIndex': 1, 'dlParamName': 'axis', 'type': 'number' }
+            { 'tfInputIndex': 1, 'dlParamName': 'axis', 'type': 'number[]' }
         ]
@@ -224,4 +228,40 @@ },
         ]
+    },
+    {
+        'tfOpName': 'ScatterNd',
+        'dlOpName': 'scatterNd',
+        'category': 'slice_join',
+        'params': [
+            { 'tfInputIndex': 0, 'dlParamName': 'indices', 'type': 'tensor' },
+            { 'tfInputIndex': 1, 'dlParamName': 'values', 'type': 'tensor' },
+            { 'tfInputIndex': 2, 'dlParamName': 'shape', 'type': 'number[]' }
+        ]
+    },
+    {
+        'tfOpName': 'GatherNd',
+        'dlOpName': 'gatherNd',
+        'category': 'slice_join',
+        'params': [
+            { 'tfInputIndex': 0, 'dlParamName': 'x', 'type': 'tensor' },
+            { 'tfInputIndex': 1, 'dlParamName': 'indices', 'type': 'tensor' }
+        ]
+    },
+    {
+        'tfOpName': 'SparseToDense',
+        'dlOpName': 'sparseToDense',
+        'category': 'slice_join',
+        'params': [
+            { 'tfInputIndex': 0, 'dlParamName': 'sparseIndices', 'type': 'tensor' },
+            { 'tfInputIndex': 1, 'dlParamName': 'outputShape', 'type': 'number[]' },
+            { 'tfInputIndex': 2, 'dlParamName': 'sparseValues', 'type': 'tensor' },
+            { 'tfInputIndex': 3, 'dlParamName': 'defaultValue', 'type': 'tensor' }, {
+                'tfParamName': 'validate_indices',
+                'dlParamName': 'validateIndices',
+                'type': 'bool',
+                'defaultValue': false,
+                'notSupported': true
+            }
+        ]
     }
 ];
 //# sourceMappingURL=slice_join.js.map

dist/src/version.d.ts

@@ -1,2 +0,2 @@
-declare const version = "0.6.5";
+declare const version = "0.6.6";
 export { version };

dist/src/version.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
-var version = '0.6.5';
+var version = '0.6.6';
 exports.version = version;
 //# sourceMappingURL=version.js.map

package.json

 {
   "name": "@tensorflow/tfjs-converter",
-  "version": "0.6.5",
+  "version": "0.6.6",
   "description": "Tensorflow model converter for javascript",
@@ -17,6 +17,6 @@ "main": "dist/src/index.js",
   "peerDependencies": {
-    "@tensorflow/tfjs-core": "~0.13.8"
+    "@tensorflow/tfjs-core": "0.13.10"
   },
   "devDependencies": {
-    "@tensorflow/tfjs-core": "~0.13.8",
+    "@tensorflow/tfjs-core": "0.13.10",
     "@types/jasmine": "~2.8.6",
@@ -23,0 +23,0 @@ "@types/node-fetch": "1.6.9",

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Improved metrics

Total package byte prevSize

2804620

increased by2.33%

Lines of code

17396

increased by1.92%

No dependency changes