@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
48 lines • 6.44 kB
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.
* =============================================================================
*/
import { Multiply } from '../kernel_names';
import { assertAndGetBroadcastShape, getReductionAxes } from '../ops/broadcast_util';
import { cast } from '../ops/cast';
import { mul } from '../ops/mul';
import { reshape } from '../ops/reshape';
import { sum } from '../ops/sum';
export const multiplyGradConfig = {
kernelName: Multiply,
inputsToSave: ['a', 'b'],
gradFunc: (dy, saved) => {
const [a, b] = saved;
const outShape = assertAndGetBroadcastShape(a.shape, b.shape);
const derA = () => {
const res = mul(dy, cast(b, 'float32'));
const reduceAxes = getReductionAxes(a.shape, outShape);
if (reduceAxes.length > 0) {
return reshape(sum(res, reduceAxes), a.shape);
}
return res;
};
const derB = () => {
const res = mul(dy, cast(a, 'float32'));
const reduceAxes = getReductionAxes(b.shape, outShape);
if (reduceAxes.length > 0) {
return reshape(sum(res, reduceAxes), b.shape);
}
return res;
};
return { a: derA, b: derB };
}
};
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