@tensorflow/tfjs-core
Version:
Hardware-accelerated JavaScript library for machine intelligence
47 lines • 1.8 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 { Sub } from '../kernel_names';
import * as broadcast_util from '../ops/broadcast_util';
import { neg } from '../ops/neg';
import { reshape } from '../ops/reshape';
import { sum } from '../ops/sum';
export const subGradConfig = {
kernelName: Sub,
inputsToSave: ['a', 'b'],
gradFunc: (dy, saved) => {
const [a, b] = saved;
const outShape = broadcast_util.assertAndGetBroadcastShape(a.shape, b.shape);
const derA = () => {
let res = dy;
const reduceAxes = broadcast_util.getReductionAxes(a.shape, outShape);
if (reduceAxes.length > 0) {
res = sum(res, reduceAxes);
}
return reshape(res, a.shape);
};
const derB = () => {
let res = dy;
const reduceAxes = broadcast_util.getReductionAxes(b.shape, outShape);
if (reduceAxes.length > 0) {
res = sum(res, reduceAxes);
}
return reshape(neg(res), b.shape);
};
return { a: derA, b: derB };
}
};
//# sourceMappingURL=Sub_grad.js.map