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@tensorflow/tfjs-core

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Hardware-accelerated JavaScript library for machine intelligence

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"use strict"; Object.defineProperty(exports, "__esModule", { value: true }); /** * @license * Copyright 2020 Google Inc. 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. * ============================================================================= */ var kernel_names_1 = require("../kernel_names"); var broadcast_util = require("../ops/broadcast_util"); exports.addGradConfig = { kernelName: kernel_names_1.Add, inputsToSave: ['a', 'b'], gradFunc: function (dy, saved) { var a = saved[0], b = saved[1]; var outShape = broadcast_util.assertAndGetBroadcastShape(a.shape, b.shape); var derA = function () { var res = dy; var reduceAxes = broadcast_util.getReductionAxes(a.shape, outShape); if (reduceAxes.length > 0) { res = res.sum(reduceAxes); } return res.reshape(a.shape); }; var derB = function () { var res = dy; var reduceAxes = broadcast_util.getReductionAxes(b.shape, outShape); if (reduceAxes.length > 0) { res = res.sum(reduceAxes); } return res.reshape(b.shape); }; return { a: derA, b: derB }; } }; //# sourceMappingURL=Add_grad.js.map