@tensorflow/tfjs-node
Version:
This repository provides native TensorFlow execution in backend JavaScript applications under the Node.js runtime, accelerated by the TensorFlow C binary under the hood. It provides the same API as [TensorFlow.js](https://js.tensorflow.org/api/latest/).
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JavaScript
;
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
Object.defineProperty(exports, "__esModule", { value: true });
exports.conv2DBackpropInputConfig = void 0;
var tfjs_1 = require("@tensorflow/tfjs");
var nodejs_kernel_backend_1 = require("../nodejs_kernel_backend");
exports.conv2DBackpropInputConfig = {
kernelName: tfjs_1.Conv2DBackpropInput,
backendName: 'tensorflow',
kernelFunc: function (args) {
var _a = args.inputs, dy = _a.dy, filter = _a.filter;
var backend = args.backend;
var _b = args.attrs, strides = _b.strides, pad = _b.pad, dataFormat = _b.dataFormat, dimRoundingMode = _b.dimRoundingMode, inputShape = _b.inputShape;
var $dataFormat = tfjs_1.backend_util.convertConv2DDataFormat(dataFormat);
var convInfo = tfjs_1.backend_util.computeConv2DInfo(inputShape, filter.shape, strides, 1 /* dilations */, pad, dimRoundingMode, false, $dataFormat);
return conv2DBackpropInputImpl(dy, filter, convInfo, backend);
}
};
function conv2DBackpropInputImpl(dy, filter, convInfo, backend) {
if (convInfo.padInfo.type !== 'VALID' && convInfo.padInfo.type !== 'SAME') {
throw new Error("TF Backend supports only 'valid' and 'same' padding " +
"while padding was ".concat(convInfo.padInfo.type));
}
var strides = [1, convInfo.strideHeight, convInfo.strideWidth, 1];
var padding = convInfo.padInfo.type;
var dataFormat = convInfo.dataFormat === 'channelsLast' ? 'NHWC' : 'NCHW';
var dilations = [1, convInfo.dilationHeight, convInfo.dilationWidth, 1];
var opAttrs = [
(0, nodejs_kernel_backend_1.createTensorsTypeOpAttr)('T', 'float32'),
{ name: 'strides', type: backend.binding.TF_ATTR_INT, value: strides },
{ name: 'padding', type: backend.binding.TF_ATTR_STRING, value: padding }, {
name: 'data_format',
type: backend.binding.TF_ATTR_STRING,
value: dataFormat
},
{ name: 'use_cudnn_on_gpu', type: backend.binding.TF_ATTR_BOOL, value: true },
{ name: 'dilations', type: backend.binding.TF_ATTR_INT, value: dilations }
];
var inputSizes = (0, tfjs_1.tensor1d)(convInfo.inShape, 'int32');
var res = backend.executeSingleOutput(tfjs_1.Conv2DBackpropInput, opAttrs, [inputSizes, filter, dy]);
inputSizes.dispose();
return res;
}