@tensorflow/tfjs-converter - npm Package Compare versions

Comparing version 1.7.1 to 1.7.2

dist/operations/executors/convolution_executor.js

@@ -116,2 +116,10 @@ "use strict";
         }
+        case 'MaxPoolWithArgmax': {
+            var stride = utils_1.getParamValue('strides', node, tensorMap, context);
+            var pad = utils_1.getParamValue('pad', node, tensorMap, context);
+            var kernelSize = utils_1.getParamValue('kernelSize', node, tensorMap, context);
+            var includeBatchInIndex = utils_1.getParamValue('includeBatchInIndex', node, tensorMap, context);
+            var _c = tfc.maxPoolWithArgmax(utils_1.getParamValue('x', node, tensorMap, context), [kernelSize[1], kernelSize[2]], [stride[1], stride[2]], pad, includeBatchInIndex), result = _c.result, indexes = _c.indexes;
+            return [result, indexes];
+        }
         case 'AvgPool3D': {
@@ -118,0 +126,0 @@ var stride = utils_1.getParamValue('strides', node, tensorMap, context);

dist/operations/op_list/convolution.js

@@ -57,2 +57,19 @@ "use strict";
     {
+        'tfOpName': 'MaxPoolWithArgmax',
+        'category': 'convolution',
+        'inputs': [
+            { 'start': 0, 'name': 'x', 'type': 'tensor' },
+        ],
+        'attrs': [
+            { 'tfName': 'strides', 'name': 'strides', 'type': 'number[]' },
+            { 'tfName': 'padding', 'name': 'pad', 'type': 'string' },
+            { 'tfName': 'ksize', 'name': 'kernelSize', 'type': 'number[]' }, {
+                'tfName': 'include_batch_in_index',
+                'name': 'includeBatchInIndex',
+                'type': 'bool'
+            },
+            { 'tfName': 'T', 'name': 'dtype', 'type': 'dtype', 'notSupported': true }
+        ]
+    },
+    {
         'tfOpName': 'AvgPool3D',
@@ -59,0 +76,0 @@ 'category': 'convolution',

dist/operations/operation_mapper.js

@@ -298,2 +298,4 @@ "use strict";
         case tensorflow.DataType.DT_INT64:
+        case tensorflow.DataType.DT_INT8:
+        case tensorflow.DataType.DT_UINT8:
             return 'int32';
@@ -300,0 +302,0 @@ case tensorflow.DataType.DT_BOOL:

dist/version.d.ts

 /** @license See the LICENSE file. */
-declare const version = "1.7.1";
+declare const version = "1.7.2";
 export { version };

dist/version.js

@@ -5,4 +5,4 @@ "use strict";
 // This code is auto-generated, do not modify this file!
-var version = '1.7.1';
+var version = '1.7.2';
 exports.version = version;
 //# sourceMappingURL=version.js.map

package.json

 {
   "name": "@tensorflow/tfjs-converter",
-  "version": "1.7.1",
+  "version": "1.7.2",
   "description": "Tensorflow model converter for javascript",
@@ -18,6 +18,6 @@ "main": "dist/index.js",
   "peerDependencies": {
-    "@tensorflow/tfjs-core": "1.7.1"
+    "@tensorflow/tfjs-core": "1.7.2"
   },
   "devDependencies": {
-    "@tensorflow/tfjs-core": "1.7.1",
+    "@tensorflow/tfjs-core": "1.7.2",
     "@types/deep-equal": "^1.0.1",
@@ -24,0 +24,0 @@ "@types/jasmine": "~2.8.6",

src/operations/executors/convolution_executor.ts

@@ -26,202 +26,215 @@ /**
 
-export const executeOp: InternalOpExecutor =
-    (node: Node, tensorMap: NamedTensorsMap,
-     context: ExecutionContext): tfc.Tensor[] => {
-      switch (node.op) {
-        case 'Conv1D': {
-          const stride =
-              getParamValue('stride', node, tensorMap, context) as number;
-          const pad = getParamValue('pad', node, tensorMap, context);
-          const dataFormat =
-              (getParamValue('dataFormat', node, tensorMap, context) as string)
-                  .toUpperCase();
-          const dilation =
-              getParamValue('dilation', node, tensorMap, context) as number;
-          return [tfc.conv1d(
-              getParamValue('x', node, tensorMap, context) as tfc.Tensor3D,
-              getParamValue('filter', node, tensorMap, context) as tfc.Tensor3D,
-              stride, pad as 'valid' | 'same', dataFormat as 'NWC' | 'NCW',
-              dilation)];
-        }
-        case 'Conv2D': {
-          const stride =
-              getParamValue('strides', node, tensorMap, context) as number[];
-          const pad = getParamValue('pad', node, tensorMap, context);
-          const dataFormat =
-              (getParamValue('dataFormat', node, tensorMap, context) as string)
-                  .toUpperCase();
-          const dilations =
-              getParamValue('dilations', node, tensorMap, context) as number[];
-          return [tfc.conv2d(
-              getParamValue('x', node, tensorMap, context) as tfc.Tensor3D |
-                  tfc.Tensor4D,
-              getParamValue('filter', node, tensorMap, context) as tfc.Tensor4D,
-              [stride[1], stride[2]], pad as 'valid' | 'same',
-              dataFormat as 'NHWC' | 'NCHW', [dilations[1], dilations[2]])];
-        }
-        case '_FusedConv2D':
-        case 'FusedDepthwiseConv2dNative': {
-          const [extraOp, activationFunc] =
-              (getParamValue('fusedOps', node, tensorMap, context) as string[]);
+export const executeOp: InternalOpExecutor = (node: Node,
+                                              tensorMap: NamedTensorsMap,
+                                              context: ExecutionContext):
+                                                 tfc.Tensor[] => {
+  switch (node.op) {
+    case 'Conv1D': {
+      const stride =
+          getParamValue('stride', node, tensorMap, context) as number;
+      const pad = getParamValue('pad', node, tensorMap, context);
+      const dataFormat =
+          (getParamValue('dataFormat', node, tensorMap, context) as string)
+              .toUpperCase();
+      const dilation =
+          getParamValue('dilation', node, tensorMap, context) as number;
+      return [tfc.conv1d(
+          getParamValue('x', node, tensorMap, context) as tfc.Tensor3D,
+          getParamValue('filter', node, tensorMap, context) as tfc.Tensor3D,
+          stride, pad as 'valid' | 'same', dataFormat as 'NWC' | 'NCW',
+          dilation)];
+    }
+    case 'Conv2D': {
+      const stride =
+          getParamValue('strides', node, tensorMap, context) as number[];
+      const pad = getParamValue('pad', node, tensorMap, context);
+      const dataFormat =
+          (getParamValue('dataFormat', node, tensorMap, context) as string)
+              .toUpperCase();
+      const dilations =
+          getParamValue('dilations', node, tensorMap, context) as number[];
+      return [tfc.conv2d(
+          getParamValue('x', node, tensorMap, context) as tfc.Tensor3D |
+              tfc.Tensor4D,
+          getParamValue('filter', node, tensorMap, context) as tfc.Tensor4D,
+          [stride[1], stride[2]], pad as 'valid' | 'same',
+          dataFormat as 'NHWC' | 'NCHW', [dilations[1], dilations[2]])];
+    }
+    case '_FusedConv2D':
+    case 'FusedDepthwiseConv2dNative': {
+      const [extraOp, activationFunc] =
+          (getParamValue('fusedOps', node, tensorMap, context) as string[]);
 
-          const isBiasAdd = extraOp === 'biasadd';
-          const isPrelu = activationFunc === 'prelu';
-          const isBatchNorm = extraOp === 'fusedbatchnorm';
+      const isBiasAdd = extraOp === 'biasadd';
+      const isPrelu = activationFunc === 'prelu';
+      const isBatchNorm = extraOp === 'fusedbatchnorm';
 
-          const numArgs =
-              (getParamValue('numArgs', node, tensorMap, context) as number);
-          if (isBiasAdd) {
-            if (isPrelu && numArgs !== 2) {
-              throw new Error(
-                  'FusedConv2d and DepthwiseConv2d with BiasAdd and Prelu ' +
-                  'must have two extra arguments: bias and alpha.');
-            }
-            if (!isPrelu && numArgs !== 1) {
-              throw new Error(
-                  'FusedConv2d and DepthwiseConv2d with BiasAdd must have ' +
-                  'one extra argument: bias.');
-            }
-          }
-          if (isBatchNorm) {
-            throw new Error(
-                'FusedConv2d and DepthwiseConv2d with FusedBatchNorm is not supported.');
-          }
-          const stride =
-              getParamValue('strides', node, tensorMap, context) as number[];
-          const pad = getParamValue('pad', node, tensorMap, context);
-          const dataFormat =
-              (getParamValue('dataFormat', node, tensorMap, context) as string)
-                  .toUpperCase();
-          const dilations =
-              getParamValue('dilations', node, tensorMap, context) as number[];
-          const [biasArg, preluArg] =
-              getParamValue('args', node, tensorMap, context) as tfc.Tensor[];
-          const kernelMethod = node.op === '_FusedConv2D' ?
-              tfc.fused.conv2d :
-              tfc.fused.depthwiseConv2d;
-          return [kernelMethod({
-            x: getParamValue('x', node, tensorMap, context) as tfc.Tensor3D |
-                tfc.Tensor4D,
-            filter: getParamValue('filter', node, tensorMap, context) as
-                tfc.Tensor4D,
-            strides: [stride[1], stride[2]],
-            pad: pad as 'valid' | 'same',
-            dataFormat: dataFormat as 'NHWC' | 'NCHW',
-            dilations: [dilations[1], dilations[2]],
-            bias: biasArg,
-            activation: activationFunc as tfc.fused.Activation,
-            preluActivationWeights: preluArg
-          })];
+      const numArgs =
+          (getParamValue('numArgs', node, tensorMap, context) as number);
+      if (isBiasAdd) {
+        if (isPrelu && numArgs !== 2) {
+          throw new Error(
+              'FusedConv2d and DepthwiseConv2d with BiasAdd and Prelu ' +
+              'must have two extra arguments: bias and alpha.');
         }
-        case 'Conv2DBackpropInput':
-        case 'Conv2dTranspose': {
-          const shape = getParamValue(
-                            'outputShape', node, tensorMap,
-                            context) as [number, number, number] |
-              [number, number, number, number];
-          const stride =
-              getParamValue('strides', node, tensorMap, context) as number[];
-          const pad = getParamValue('pad', node, tensorMap, context);
-          return [tfc.conv2dTranspose(
-              getParamValue('x', node, tensorMap, context) as tfc.Tensor3D |
-                  tfc.Tensor4D,
-              getParamValue('filter', node, tensorMap, context) as tfc.Tensor4D,
-              shape, [stride[1], stride[2]], pad as 'valid' | 'same')];
+        if (!isPrelu && numArgs !== 1) {
+          throw new Error(
+              'FusedConv2d and DepthwiseConv2d with BiasAdd must have ' +
+              'one extra argument: bias.');
         }
-        case 'DepthwiseConv2dNative':
-        case 'DepthwiseConv2d': {
-          const stride =
-              getParamValue('strides', node, tensorMap, context) as number[];
-          const pad = getParamValue('pad', node, tensorMap, context);
-          const dilations =
-              getParamValue('dilations', node, tensorMap, context) as number[];
-          const dataFormat =
-              (getParamValue('dataFormat', node, tensorMap, context) as string)
-                  .toUpperCase();
+      }
+      if (isBatchNorm) {
+        throw new Error(
+            'FusedConv2d and DepthwiseConv2d with FusedBatchNorm is not supported.');
+      }
+      const stride =
+          getParamValue('strides', node, tensorMap, context) as number[];
+      const pad = getParamValue('pad', node, tensorMap, context);
+      const dataFormat =
+          (getParamValue('dataFormat', node, tensorMap, context) as string)
+              .toUpperCase();
+      const dilations =
+          getParamValue('dilations', node, tensorMap, context) as number[];
+      const [biasArg, preluArg] =
+          getParamValue('args', node, tensorMap, context) as tfc.Tensor[];
+      const kernelMethod = node.op === '_FusedConv2D' ?
+          tfc.fused.conv2d :
+          tfc.fused.depthwiseConv2d;
+      return [kernelMethod({
+        x: getParamValue('x', node, tensorMap, context) as tfc.Tensor3D |
+            tfc.Tensor4D,
+        filter: getParamValue('filter', node, tensorMap, context) as
+            tfc.Tensor4D,
+        strides: [stride[1], stride[2]],
+        pad: pad as 'valid' | 'same',
+        dataFormat: dataFormat as 'NHWC' | 'NCHW',
+        dilations: [dilations[1], dilations[2]],
+        bias: biasArg,
+        activation: activationFunc as tfc.fused.Activation,
+        preluActivationWeights: preluArg
+      })];
+    }
+    case 'Conv2DBackpropInput':
+    case 'Conv2dTranspose': {
+      const shape = getParamValue(
+                        'outputShape', node, tensorMap,
+                        context) as [number, number, number] |
+          [number, number, number, number];
+      const stride =
+          getParamValue('strides', node, tensorMap, context) as number[];
+      const pad = getParamValue('pad', node, tensorMap, context);
+      return [tfc.conv2dTranspose(
+          getParamValue('x', node, tensorMap, context) as tfc.Tensor3D |
+              tfc.Tensor4D,
+          getParamValue('filter', node, tensorMap, context) as tfc.Tensor4D,
+          shape, [stride[1], stride[2]], pad as 'valid' | 'same')];
+    }
+    case 'DepthwiseConv2dNative':
+    case 'DepthwiseConv2d': {
+      const stride =
+          getParamValue('strides', node, tensorMap, context) as number[];
+      const pad = getParamValue('pad', node, tensorMap, context);
+      const dilations =
+          getParamValue('dilations', node, tensorMap, context) as number[];
+      const dataFormat =
+          (getParamValue('dataFormat', node, tensorMap, context) as string)
+              .toUpperCase();
 
-          return [tfc.depthwiseConv2d(
-              getParamValue('input', node, tensorMap, context) as tfc.Tensor3D |
-                  tfc.Tensor4D,
-              getParamValue('filter', node, tensorMap, context) as tfc.Tensor4D,
-              [stride[1], stride[2]], pad as 'valid' | 'same',
-              dataFormat as 'NHWC' | 'NCHW', [dilations[1], dilations[2]])];
-        }
-        case 'Conv3D': {
-          const stride =
-              getParamValue('strides', node, tensorMap, context) as number[];
-          const pad = getParamValue('pad', node, tensorMap, context);
-          const dataFormat =
-              (getParamValue('dataFormat', node, tensorMap, context) as string)
-                  .toUpperCase();
-          const dilations =
-              getParamValue('dilations', node, tensorMap, context) as number[];
-          return [tfc.conv3d(
-              getParamValue('x', node, tensorMap, context) as tfc.Tensor4D |
-                  tfc.Tensor<tfc.Rank.R5>,
-              getParamValue('filter', node, tensorMap, context) as
-                  tfc.Tensor<tfc.Rank.R5>,
-              [stride[1], stride[2], stride[3]], pad as 'valid' | 'same',
-              dataFormat as 'NDHWC' | 'NCDHW',
-              [dilations[1], dilations[2], dilations[3]])];
-        }
+      return [tfc.depthwiseConv2d(
+          getParamValue('input', node, tensorMap, context) as tfc.Tensor3D |
+              tfc.Tensor4D,
+          getParamValue('filter', node, tensorMap, context) as tfc.Tensor4D,
+          [stride[1], stride[2]], pad as 'valid' | 'same',
+          dataFormat as 'NHWC' | 'NCHW', [dilations[1], dilations[2]])];
+    }
+    case 'Conv3D': {
+      const stride =
+          getParamValue('strides', node, tensorMap, context) as number[];
+      const pad = getParamValue('pad', node, tensorMap, context);
+      const dataFormat =
+          (getParamValue('dataFormat', node, tensorMap, context) as string)
+              .toUpperCase();
+      const dilations =
+          getParamValue('dilations', node, tensorMap, context) as number[];
+      return [tfc.conv3d(
+          getParamValue('x', node, tensorMap, context) as tfc.Tensor4D |
+              tfc.Tensor<tfc.Rank.R5>,
+          getParamValue('filter', node, tensorMap, context) as
+              tfc.Tensor<tfc.Rank.R5>,
+          [stride[1], stride[2], stride[3]], pad as 'valid' | 'same',
+          dataFormat as 'NDHWC' | 'NCDHW',
+          [dilations[1], dilations[2], dilations[3]])];
+    }
+    case 'AvgPool': {
+      const stride =
+          getParamValue('strides', node, tensorMap, context) as number[];
+      const pad = getParamValue('pad', node, tensorMap, context);
+      const kernelSize =
+          getParamValue('kernelSize', node, tensorMap, context) as number[];
 
-        case 'AvgPool': {
-          const stride =
-              getParamValue('strides', node, tensorMap, context) as number[];
-          const pad = getParamValue('pad', node, tensorMap, context);
-          const kernelSize =
-              getParamValue('kernelSize', node, tensorMap, context) as number[];
+      return [tfc.avgPool(
+          getParamValue('x', node, tensorMap, context) as tfc.Tensor3D |
+              tfc.Tensor4D,
+          [kernelSize[1], kernelSize[2]], [stride[1], stride[2]],
+          pad as 'valid' | 'same')];
+    }
+    case 'MaxPool': {
+      const stride =
+          getParamValue('strides', node, tensorMap, context) as number[];
+      const pad = getParamValue('pad', node, tensorMap, context);
+      const kernelSize =
+          getParamValue('kernelSize', node, tensorMap, context) as number[];
 
-          return [tfc.avgPool(
-              getParamValue('x', node, tensorMap, context) as tfc.Tensor3D |
-                  tfc.Tensor4D,
-              [kernelSize[1], kernelSize[2]], [stride[1], stride[2]],
-              pad as 'valid' | 'same')];
-        }
+      return [tfc.maxPool(
+          getParamValue('x', node, tensorMap, context) as tfc.Tensor3D |
+              tfc.Tensor4D,
+          [kernelSize[1], kernelSize[2]], [stride[1], stride[2]],
+          pad as 'valid' | 'same')];
+    }
+    case 'MaxPoolWithArgmax': {
+      const stride =
+          getParamValue('strides', node, tensorMap, context) as number[];
+      const pad = getParamValue('pad', node, tensorMap, context);
+      const kernelSize =
+          getParamValue('kernelSize', node, tensorMap, context) as number[];
+      const includeBatchInIndex =
+          getParamValue('includeBatchInIndex', node, tensorMap, context) as
+          boolean;
+      const {result, indexes} = tfc.maxPoolWithArgmax(
+          getParamValue('x', node, tensorMap, context) as tfc.Tensor4D,
+          [kernelSize[1], kernelSize[2]], [stride[1], stride[2]],
+          pad as 'valid' | 'same', includeBatchInIndex);
+      return [result, indexes];
+    }
+    case 'AvgPool3D': {
+      const stride =
+          getParamValue('strides', node, tensorMap, context) as number[];
+      const pad = getParamValue('pad', node, tensorMap, context);
+      const kernelSize =
+          getParamValue('kernelSize', node, tensorMap, context) as number[];
 
-        case 'MaxPool': {
-          const stride =
-              getParamValue('strides', node, tensorMap, context) as number[];
-          const pad = getParamValue('pad', node, tensorMap, context);
-          const kernelSize =
-              getParamValue('kernelSize', node, tensorMap, context) as number[];
+      return [tfc.avgPool3d(
+          getParamValue('x', node, tensorMap, context) as tfc.Tensor5D,
+          [kernelSize[1], kernelSize[2], kernelSize[3]],
+          [stride[1], stride[2], stride[3]], pad as 'valid' | 'same')];
+    }
 
-          return [tfc.maxPool(
-              getParamValue('x', node, tensorMap, context) as tfc.Tensor3D |
-                  tfc.Tensor4D,
-              [kernelSize[1], kernelSize[2]], [stride[1], stride[2]],
-              pad as 'valid' | 'same')];
-        }
+    case 'MaxPool3D': {
+      const stride =
+          getParamValue('strides', node, tensorMap, context) as number[];
+      const pad = getParamValue('pad', node, tensorMap, context);
+      const kernelSize =
+          getParamValue('kernelSize', node, tensorMap, context) as number[];
 
-        case 'AvgPool3D': {
-          const stride =
-              getParamValue('strides', node, tensorMap, context) as number[];
-          const pad = getParamValue('pad', node, tensorMap, context);
-          const kernelSize =
-              getParamValue('kernelSize', node, tensorMap, context) as number[];
+      return [tfc.maxPool3d(
+          getParamValue('x', node, tensorMap, context) as tfc.Tensor5D,
+          [kernelSize[1], kernelSize[2], kernelSize[3]],
+          [stride[1], stride[2], stride[3]], pad as 'valid' | 'same')];
+    }
 
-          return [tfc.avgPool3d(
-              getParamValue('x', node, tensorMap, context) as tfc.Tensor5D,
-              [kernelSize[1], kernelSize[2], kernelSize[3]],
-              [stride[1], stride[2], stride[3]], pad as 'valid' | 'same')];
-        }
+    default:
+      throw TypeError(`Node type ${node.op} is not implemented`);
+  }
+};
 
-        case 'MaxPool3D': {
-          const stride =
-              getParamValue('strides', node, tensorMap, context) as number[];
-          const pad = getParamValue('pad', node, tensorMap, context);
-          const kernelSize =
-              getParamValue('kernelSize', node, tensorMap, context) as number[];
-
-          return [tfc.maxPool3d(
-              getParamValue('x', node, tensorMap, context) as tfc.Tensor5D,
-              [kernelSize[1], kernelSize[2], kernelSize[3]],
-              [stride[1], stride[2], stride[3]], pad as 'valid' | 'same')];
-        }
-
-        default:
-          throw TypeError(`Node type ${node.op} is not implemented`);
-      }
-    };
-
 export const CATEGORY = 'convolution';

src/operations/op_list/convolution.ts

@@ -58,2 +58,19 @@ import {OpMapper} from '../types';
   {
+    'tfOpName': 'MaxPoolWithArgmax',
+    'category': 'convolution',
+    'inputs': [
+      {'start': 0, 'name': 'x', 'type': 'tensor'},
+    ],
+    'attrs': [
+      {'tfName': 'strides', 'name': 'strides', 'type': 'number[]'},
+      {'tfName': 'padding', 'name': 'pad', 'type': 'string'},
+      {'tfName': 'ksize', 'name': 'kernelSize', 'type': 'number[]'}, {
+        'tfName': 'include_batch_in_index',
+        'name': 'includeBatchInIndex',
+        'type': 'bool'
+      },
+      {'tfName': 'T', 'name': 'dtype', 'type': 'dtype', 'notSupported': true}
+    ]
+  },
+  {
     'tfOpName': 'AvgPool3D',
@@ -60,0 +77,0 @@ 'category': 'convolution',

src/operations/operation_mapper.ts

@@ -355,2 +355,4 @@ /**
     case tensorflow.DataType.DT_INT64:
+    case tensorflow.DataType.DT_INT8:
+    case tensorflow.DataType.DT_UINT8:
       return 'int32';
@@ -357,0 +359,0 @@ case tensorflow.DataType.DT_BOOL:

src/version.ts

 /** @license See the LICENSE file. */
 
 // This code is auto-generated, do not modify this file!
-const version = '1.7.1';
+const version = '1.7.2';
 export {version};

No alert changes

Improved metrics

Total package byte prevSize

3656536

increased by0.38%

Lines of code

25434

increased by0.39%

No dependency changes