@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.fusedConv2DConfig = void 0;
var tfjs_1 = require("@tensorflow/tfjs");
var Conv2D_1 = require("./Conv2D");
exports.fusedConv2DConfig = {
kernelName: tfjs_1.FusedConv2D,
backendName: 'tensorflow',
kernelFunc: function (args) {
var _a = args.inputs, x = _a.x, filter = _a.filter, bias = _a.bias, preluActivationWeights = _a.preluActivationWeights;
var backend = args.backend;
var _b = args.attrs, strides = _b.strides, pad = _b.pad, dataFormat = _b.dataFormat, dilations = _b.dilations, dimRoundingMode = _b.dimRoundingMode, activation = _b.activation, leakyreluAlpha = _b.leakyreluAlpha;
if (dataFormat !== 'NHWC') {
throw new Error("Node backend FusedConv2D does not support dataFormat:'" +
"".concat(dataFormat, "'. Please use 'NHWC'."));
}
var $dataFormat = tfjs_1.backend_util.convertConv2DDataFormat(dataFormat);
var convInfo = tfjs_1.backend_util.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad, dimRoundingMode, false /* depthwise */, $dataFormat);
var result = (0, Conv2D_1.conv2dImpl)(x, filter, convInfo, backend);
var toDispose = [];
if (bias != null) {
toDispose.push(result);
result = (0, tfjs_1.add)(result, bias);
}
var temp = result;
result = backend.applyActivation(result, activation, preluActivationWeights, leakyreluAlpha);
if (temp !== result) {
toDispose.push(temp);
}
toDispose.forEach(function (t) { return t.dispose(); });
return result;
}
};