@tensorflow/tfjs-converter - npm Package Compare versions

Comparing version 0.5.2 to 0.5.3

dist/executor/frozen_model.js

@@ -188,4 +188,4 @@ "use strict";
         }
-        if (this.executor.isControlFlowModel) {
-            throw new Error('The model contains control flow ops, ' +
+        if (this.executor.isControlFlowModel || this.executor.isDynamicShapeModel) {
+            throw new Error('The model contains control flow or dynamic shape ops, ' +
                 'please use executeAsync method');
@@ -205,4 +205,5 @@ }
                     case 0:
-                        if (!this.executor.isControlFlowModel) {
-                            throw new Error('The model does not contain control flow ops, ' +
+                        if (!(this.executor.isControlFlowModel &&
+                            this.executor.isDynamicShapeModel)) {
+                            throw new Error('The model does not contain control flow or dynamic shape ops, ' +
                                 'please use execute method for better performance.');
@@ -209,0 +210,0 @@ }

dist/executor/graph_executor.d.ts

@@ -17,2 +17,3 @@ import { NamedTensorMap, NamedTensorsMap, TensorInfo } from '../data/types';
     readonly isControlFlowModel: boolean;
+    readonly isDynamicShapeModel: boolean;
     private compile();
@@ -19,0 +20,0 @@ execute(inputs: NamedTensorsMap, outputs?: string | string[]): NamedTensorMap;

dist/executor/graph_executor.js

@@ -122,4 +122,11 @@ "use strict";
     });
+    Object.defineProperty(GraphExecutor.prototype, "isDynamicShapeModel", {
+        get: function () {
+            return this.graph.withDynamicShape;
+        },
+        enumerable: true,
+        configurable: true
+    });
     GraphExecutor.prototype.compile = function () {
-        if (this.graph.withControlFlow) {
+        if (this.graph.withControlFlow || this.graph.withDynamicShape) {
             return;
@@ -126,0 +133,0 @@ }

dist/operations/executors/transformation_executor.js

@@ -24,2 +24,12 @@ "use strict";
         }
+        case 'spaceToBatchND': {
+            var blockShape = utils_1.getParamValue('blockShape', node, tensorMap, context);
+            var paddings = utils_1.split(utils_1.getParamValue('paddings', node, tensorMap, context), 2);
+            return [tfc.spaceToBatchND(utils_1.getParamValue('x', node, tensorMap, context), blockShape, paddings)];
+        }
+        case 'batchToSpaceND': {
+            var blockShape = utils_1.getParamValue('blockShape', node, tensorMap, context);
+            var crops = utils_1.split(utils_1.getParamValue('crops', node, tensorMap, context), 2);
+            return [tfc.batchToSpaceND(utils_1.getParamValue('x', node, tensorMap, context), blockShape, crops)];
+        }
         default:
@@ -26,0 +36,0 @@ throw TypeError("Node type " + node.op + " is not implemented");

dist/operations/op_list/image.json

@@ -57,3 +57,62 @@ [
     ]
+  },
+  {
+    "tfOpName": "NonMaxSuppressionV2",
+    "dlOpName": "nonMaxSuppression",
+    "category": "image",
+    "params": [
+      {
+        "tfInputIndex": 0,
+        "dlParamName": "boxes",
+        "type": "tensor"
+      },
+      {
+        "tfInputIndex": 1,
+        "dlParamName": "scores",
+        "type": "tensor"
+      },
+      {
+        "tfInputIndex": 2,
+        "dlParamName": "maxOutputSize",
+        "type": "number"
+      },
+      {
+        "tfInputIndex": 3,
+        "dlParamName": "iouThreshold",
+        "type": "number"
+      }
+    ]
+  },
+  {
+    "tfOpName": "NonMaxSuppressionV3",
+    "dlOpName": "nonMaxSuppression",
+    "category": "image",
+    "params": [
+      {
+        "tfInputIndex": 0,
+        "dlParamName": "boxes",
+        "type": "tensor"
+      },
+      {
+        "tfInputIndex": 1,
+        "dlParamName": "scores",
+        "type": "tensor"
+      },
+      {
+        "tfInputIndex": 2,
+        "dlParamName": "maxOutputSize",
+        "type": "number"
+      },
+      {
+        "tfInputIndex": 3,
+        "dlParamName": "iouThreshold",
+        "type": "number"
+      },
+      {
+        "tfInputIndex": 4,
+        "dlParamName": "scoreThreshold",
+        "type": "number"
+      }
+    ]
   }
 ]

dist/operations/op_list/transformation.json

@@ -118,3 +118,45 @@ [
     ]
+  },
+  {
+    "tfOpName": "SpaceToBatchND",
+    "dlOpName": "spaceToBatchND",
+    "category": "transformation",
+    "params": [{
+        "tfInputIndex": 0,
+        "dlParamName": "x",
+        "type": "tensor"
+      },
+      {
+        "tfInputIndex": 1,
+        "dlParamName": "blockShape",
+        "type": "number[]"
+      },
+      {
+        "tfInputIndex": 2,
+        "dlParamName": "paddings",
+        "type": "number[]"
+      }
+    ]
+  },
+  {
+    "tfOpName": "BatchToSpaceND",
+    "dlOpName": "batchToSpaceND",
+    "category": "transformation",
+    "params": [{
+        "tfInputIndex": 0,
+        "dlParamName": "x",
+        "type": "tensor"
+      },
+      {
+        "tfInputIndex": 1,
+        "dlParamName": "blockShape",
+        "type": "number[]"
+      },
+      {
+        "tfInputIndex": 2,
+        "dlParamName": "crops",
+        "type": "number[]"
+      }
+    ]
   }
 ]

dist/operations/operation_executor.js

@@ -8,2 +8,4 @@ "use strict";
 var creation = require("./executors/creation_executor");
+var dynamic = require("./executors/dynamic_executor");
+var evaluation = require("./executors/evaluation_executor");
 var graph = require("./executors/graph_executor");
@@ -29,2 +31,6 @@ var image = require("./executors/image_executor");
             return creation.executeOp(node, tensorMap, context);
+        case 'dynamic':
+            return dynamic.executeOp(node, tensorMap, context);
+        case 'evaluation':
+            return evaluation.executeOp(node, tensorMap, context);
         case 'image':
@@ -31,0 +37,0 @@ return image.executeOp(node, tensorMap, context);

dist/operations/operation_mapper.d.ts

@@ -9,2 +9,3 @@ import { tensorflow } from '../data/compiled_api';
     private isControlFlow(node);
+    private isDynamicShape(node);
     transformGraph(graph: tensorflow.IGraphDef): Graph;
@@ -11,0 +12,0 @@ private mapNode(node);

dist/operations/operation_mapper.js

@@ -10,2 +10,4 @@ "use strict";
 var creation = require("./op_list/creation.json");
+var dynamic = require("./op_list/dynamic.json");
+var evaluation = require("./op_list/evaluation.json");
 var graph = require("./op_list/graph.json");
@@ -20,7 +22,9 @@ var image = require("./op_list/image.json");
 var CONTROL_FLOW_OPS = ['Switch', 'Merge', 'Enter', 'Exit', 'NextIteration'];
+var DYNAMIC_SHAPE_OPS = ['NonMaxSuppressionV2', 'NonMaxSuppressionV3', 'Where'];
 var OperationMapper = (function () {
     function OperationMapper() {
         var ops = [
-            arithmetic, basicMath, control, convolution, creation, logical, image,
-            graph, matrices, normalization, reduction, sliceJoin, transformation
+            arithmetic, basicMath, control, convolution, creation, dynamic,
+            evaluation, logical, image, graph, matrices, normalization, reduction,
+            sliceJoin, transformation
         ];
@@ -43,2 +47,5 @@ var mappersJson = [].concat.apply([], ops.map(function (op) { return op.default ? op.default : op; }));
     };
+    OperationMapper.prototype.isDynamicShape = function (node) {
+        return DYNAMIC_SHAPE_OPS.some(function (op) { return op === node.op; });
+    };
     OperationMapper.prototype.transformGraph = function (graph) {
@@ -48,2 +55,3 @@ var _this = this;
         var withControlFlow = false;
+        var withDynamicShape = false;
         var placeholders = [];
@@ -54,2 +62,4 @@ var nodes = tfNodes.reduce(function (map, node) {
                 withControlFlow = true;
+            if (_this.isDynamicShape(node))
+                withDynamicShape = true;
             if (node.op === 'Placeholder')
@@ -76,3 +86,10 @@ placeholders.push(map[node.name]);
         });
-        return { nodes: nodes, inputs: inputs, outputs: outputs, placeholders: placeholders, withControlFlow: withControlFlow };
+        return {
+            nodes: nodes,
+            inputs: inputs,
+            outputs: outputs,
+            placeholders: placeholders,
+            withControlFlow: withControlFlow,
+            withDynamicShape: withDynamicShape
+        };
     };
@@ -189,3 +206,5 @@ OperationMapper.prototype.mapNode = function (node) {
         if (param && param.shape) {
-            return param.shape.dim.map(function (dim) { return dim.size; });
+            return param.shape.dim.map(function (dim) {
+                return (typeof dim.size === 'number') ? dim.size : dim.size['toInt']();
+            });
         }
@@ -192,0 +211,0 @@ return def;

dist/operations/types.d.ts

 import { Tensor } from '@tensorflow/tfjs-core';
 export declare type ParamTypes = 'number' | 'string' | 'number[]' | 'bool' | 'shape' | 'tensor' | 'tensors' | 'dtype';
-export declare type Category = 'arithmetic' | 'basic_math' | 'control' | 'convolution' | 'image' | 'creation' | 'graph' | 'logical' | 'matrices' | 'normalization' | 'reduction' | 'slice_join' | 'transformation';
+export declare type Category = 'arithmetic' | 'basic_math' | 'control' | 'convolution' | 'dynamic' | 'evaluation' | 'image' | 'creation' | 'graph' | 'logical' | 'matrices' | 'normalization' | 'reduction' | 'slice_join' | 'transformation';
 export interface ParamMapper {
@@ -41,4 +41,5 @@ tfParamName?: string;
     withControlFlow: boolean;
+    withDynamicShape: boolean;
 }
-export declare type ValueType = string | string[] | number | number[] | boolean | boolean[] | Tensor | Tensor[];
+export declare type ValueType = string | string[] | number | number[] | number[][] | boolean | boolean[] | Tensor | Tensor[];
 export interface ParamValue {
@@ -45,0 +46,0 @@ value?: ValueType;

dist/version.d.ts

@@ -1,2 +0,2 @@
-declare const version = "0.5.2";
+declare const version = "0.5.3";
 export { version };

dist/version.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
-var version = '0.5.2';
+var version = '0.5.3';
 exports.version = version;
 //# sourceMappingURL=version.js.map

package.json

 {
   "name": "@tensorflow/tfjs-converter",
-  "version": "0.5.2",
+  "version": "0.5.3",
   "description": "Tensorflow model converter for javascript",
@@ -17,6 +17,6 @@ "main": "dist/index.js",
   "peerDependencies": {
-    "@tensorflow/tfjs-core": "~0.12.4"
+    "@tensorflow/tfjs-core": "~0.12.5"
   },
   "devDependencies": {
-    "@tensorflow/tfjs-core": "~0.12.4",
+    "@tensorflow/tfjs-core": "~0.12.5",
     "@types/jasmine": "~2.8.6",
@@ -23,0 +23,0 @@ "@types/node-fetch": "1.6.9",

README.md

@@ -92,2 +92,3 @@ [![Build Status](https://travis-ci.org/tensorflow/tfjs-converter.svg?branch=master)](https://travis-ci.org/tensorflow/tfjs-converter)
 |`--signature_name`   | Only applicable to TensorFlow Hub module conversion, signature to load. Defaults to `default`. See https://www.tensorflow.org/hub/common_signatures/.|
+|`--strip_debug_ops`   | Strips out TensorFlow debug operations `Print`, `Assert`, `CheckNumerics`. Defaults to `True`.|
 
@@ -94,0 +95,0 @@

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License

This package is not allowed per your license policy. Review the package's license to ensure compliance.

Found 1 instance in 1 package

Fixed alerts

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Improved metrics

Total package byte prevSize

968506

increased by3.11%

Number of package files

82

increased by7.89%

Lines of code

19637

increased by3.49%

Number of lines in readme file

256

increased by0.39%

No dependency changes