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Add avgPool3d & maxPool3d ops to graph model executor (#375)
* Add maxPool3d & avgPool3d to executor * update version
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‎docs/supported_ops.md‎

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|Tensorflow Op Name|Tensorflow.js Op Name|
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|---|---|
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|AvgPool|avgPool|
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|AvgPool3D|avgPool3d|
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|Conv1D|conv1d|
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|Conv2D|conv2d|
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|Conv2DBackpropInput|conv2dTranspose|
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|DepthwiseConv2d|depthwiseConv2d|
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|DepthwiseConv2dNative|depthwiseConv2d|
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|MaxPool|maxPool|
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|MaxPool3D|maxPool3d|
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|Not mapped|pool|
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|Not mapped|separableConv2d|
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‎package.json‎

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},
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"license": "Apache-2.0",
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"peerDependencies": {
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"@tensorflow/tfjs-core": "1.2.7"
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"@tensorflow/tfjs-core": "1.2.8"
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},
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"devDependencies": {
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"@tensorflow/tfjs-core": "1.2.7",
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"@tensorflow/tfjs-core": "1.2.8",
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"@types/deep-equal": "^1.0.1",
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"@types/jasmine": "~2.8.6",
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"@types/long": "~3.0.32",

‎python/tensorflowjs/op_list/convolution.json‎

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}
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]
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},
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{
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"tfOpName": "AvgPool3D",
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"category": "convolution",
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"inputs": [
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{
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"start": 0,
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"name": "x",
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"type": "tensor"
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}
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],
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"attrs": [
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{
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"tfName": "strides",
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"name": "strides",
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"type": "number[]"
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},
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{
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"tfName": "padding",
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"name": "pad",
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"type": "string"
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},
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{
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"tfName": "data_format",
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"name": "dataFormat",
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"type": "string",
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"notSupported": true
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},
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{
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"tfName": "ksize",
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"name": "kernelSize",
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"type": "number[]"
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},
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{
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"tfName": "T",
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"name": "dtype",
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"type": "dtype",
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"notSupported": true
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}
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]
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},
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{
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"tfOpName": "MaxPool3D",
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"category": "convolution",
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"inputs": [
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{
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"start": 0,
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"name": "x",
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"type": "tensor"
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}
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],
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"attrs": [
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{
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"tfName": "strides",
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"name": "strides",
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"type": "number[]"
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},
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{
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"tfName": "padding",
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"name": "pad",
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"type": "string"
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},
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{
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"tfName": "data_format",
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"name": "dataFormat",
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"type": "string",
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"notSupported": true
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},
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{
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"tfName": "ksize",
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"name": "kernelSize",
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"type": "number[]"
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},
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{
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"tfName": "T",
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"name": "dtype",
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"type": "dtype",
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"notSupported": true
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}
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]
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},
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{
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"tfOpName": "Conv1D",
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"category": "convolution",

‎src/operations/executors/convolution_executor.ts‎

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@@ -119,6 +119,35 @@ export let executeOp: InternalOpExecutor =
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[kernelSize[1], kernelSize[2]], [stride[1], stride[2]],
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pad as 'valid' | 'same')];
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}
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case 'AvgPool3D': {
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const stride =
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getParamValue('strides', node, tensorMap, context) as number[];
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const pad = getParamValue('pad', node, tensorMap, context);
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const kernelSize =
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getParamValue('kernelSize', node, tensorMap, context) as number[];
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return [tfc.avgPool3d(
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getParamValue('x', node, tensorMap, context) as tfc.Tensor5D,
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[kernelSize[1], kernelSize[2], kernelSize[3]],
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[stride[1], stride[2], stride[3]],
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pad as 'valid' | 'same')];
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}
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case 'MaxPool3D': {
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const stride =
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getParamValue('strides', node, tensorMap, context) as number[];
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const pad = getParamValue('pad', node, tensorMap, context);
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const kernelSize =
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getParamValue('kernelSize', node, tensorMap, context) as number[];
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return [tfc.maxPool3d(
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getParamValue('x', node, tensorMap, context) as tfc.Tensor5D,
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[kernelSize[1], kernelSize[2], kernelSize[3]],
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[stride[1], stride[2], stride[3]],
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pad as 'valid' | 'same')];
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}
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default:
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throw TypeError(`Node type ${node.op} is not implemented`);
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}

‎src/operations/executors/convolution_executor_test.ts‎

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input1[0], input2[0], [2, 2], 'same', 'NHWC', [2, 2]);
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});
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});
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describe('AvgPool3D', () => {
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it('should call tfc.avgPool3d', () => {
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spyOn(tfc, 'avgPool3d');
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node.op = 'AvgPool3D';
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node.attrParams['strides'] = createNumericArrayAttr([1, 2, 2, 2, 1]);
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node.attrParams['pad'] = createStrAttr('same');
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node.attrParams['kernelSize'] =
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createNumericArrayAttr([1, 2, 2, 2, 1]);
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executeOp(node, {input}, context);
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expect(tfc.avgPool3d)
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.toHaveBeenCalledWith(input[0], [2, 2, 2], [2, 2, 2], 'same');
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});
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});
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describe('MaxPool3D', () => {
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it('should call tfc.maxPool3d', () => {
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spyOn(tfc, 'maxPool3d');
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node.op = 'MaxPool3D';
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node.attrParams['strides'] = createNumericArrayAttr([1, 2, 2, 2, 1]);
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node.attrParams['pad'] = createStrAttr('same');
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node.attrParams['kernelSize'] =
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createNumericArrayAttr([1, 2, 2, 2, 1]);
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executeOp(node, {input}, context);
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expect(tfc.maxPool3d)
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.toHaveBeenCalledWith(input[0], [2, 2, 2], [2, 2, 2], 'same');
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});
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});
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});
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});

‎src/operations/op_list/convolution.ts‎

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{'tfName': 'T', 'name': 'dtype', 'type': 'dtype', 'notSupported': true}
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]
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},
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{
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'tfOpName': 'AvgPool3D',
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'category': 'convolution',
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'inputs': [
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{'start': 0, 'name': 'x', 'type': 'tensor'},
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],
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'attrs': [
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{'tfName': 'strides', 'name': 'strides', 'type': 'number[]'},
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{'tfName': 'padding', 'name': 'pad', 'type': 'string'}, {
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'tfName': 'data_format',
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'name': 'dataFormat',
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'type': 'string',
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'notSupported': true
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},
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{'tfName': 'ksize', 'name': 'kernelSize', 'type': 'number[]'},
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{'tfName': 'T', 'name': 'dtype', 'type': 'dtype', 'notSupported': true}
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]
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},
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{
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'tfOpName': 'MaxPool3D',
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'category': 'convolution',
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'inputs': [
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{'start': 0, 'name': 'x', 'type': 'tensor'},
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],
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'attrs': [
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{'tfName': 'strides', 'name': 'strides', 'type': 'number[]'},
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{'tfName': 'padding', 'name': 'pad', 'type': 'string'}, {
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'tfName': 'data_format',
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'name': 'dataFormat',
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'type': 'string',
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'notSupported': true
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},
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{'tfName': 'ksize', 'name': 'kernelSize', 'type': 'number[]'},
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{'tfName': 'T', 'name': 'dtype', 'type': 'dtype', 'notSupported': true}
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]
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},
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{
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'tfOpName': 'Conv1D',
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'category': 'convolution',

‎yarn.lock‎

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resolved "https://registry.yarnpkg.com/@protobufjs/utf8/-/utf8-1.1.0.tgz#a777360b5b39a1a2e5106f8e858f2fd2d060c570"
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integrity sha1-p3c2C1s5oaLlEG+OhY8v0tBgxXA=
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"@tensorflow/tfjs-core@1.2.7":
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version "1.2.7"
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resolved "https://registry.yarnpkg.com/@tensorflow/tfjs-core/-/tfjs-core-1.2.7.tgz#522328de16470aa9f7c15b91e4b68616f425002a"
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integrity sha512-RsXavYKMc0MOcCmOyD7HE8am1tWlDGXl0nJbsdib7ubmvMuH6KnrZ302eTYV7k1RMq+/ukkioJmCcw13hopuHQ==
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"@tensorflow/tfjs-core@1.2.8":
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version "1.2.8"
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resolved "https://registry.yarnpkg.com/@tensorflow/tfjs-core/-/tfjs-core-1.2.8.tgz#d6873b88522f8cf25d34c10afd095866578d7d92"
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integrity sha512-lWV4vAnXAAmahXpCWBwdGGW9HO6iNw9pUeVYih7pDXeJahMk3OJs6SgjRNhwn+ldsGwRoorR0/RHg0yNLmqWxQ==
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dependencies:
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"@types/offscreencanvas" "~2019.3.0"
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"@types/seedrandom" "2.4.27"

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