@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
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text/typescript
/**
* @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};
}
};