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@tensorflow/tfjs-core

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Hardware-accelerated JavaScript library for machine intelligence

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/** * @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. * ============================================================================= */ import {Atan2} from '../kernel_names'; import {GradConfig} from '../kernel_registry'; import {add} from '../ops/add'; import {assertAndGetBroadcastShape, getReductionAxes} from '../ops/broadcast_util'; import {div} from '../ops/div'; import {mul} from '../ops/mul'; import {neg} from '../ops/neg'; import {reshape} from '../ops/reshape'; import {square} from '../ops/square'; import {sum} from '../ops/sum'; import {Tensor} from '../tensor'; export const atan2GradConfig: GradConfig = { kernelName: Atan2, inputsToSave: ['a', 'b'], gradFunc: (dy: Tensor, saved: Tensor[]) => { const [a, b] = saved; const outShape = assertAndGetBroadcastShape(a.shape, b.shape); const derA = () => { const d = add(square(a), square(b)); let res = mul(dy, div(b, d)); const reduceAxes = getReductionAxes(a.shape, outShape); if (reduceAxes.length > 0) { res = sum(res, reduceAxes); } return reshape(res, a.shape); }; const derB = () => { const d = add(square(a), square(b)); let res = neg(mul(dy, div(a, d))); const reduceAxes = getReductionAxes(b.shape, outShape); if (reduceAxes.length > 0) { res = sum(res, reduceAxes); } return reshape(res, b.shape); }; return {a: derA, b: derB}; } };