@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
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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 { Slice } from '../kernel_names';
import { pad } from '../ops/pad';
import { parseSliceParams } from '../ops/slice_util';
export const sliceGradConfig = {
kernelName: Slice,
inputsToSave: ['x'],
gradFunc: (dy, saved, attrs) => {
const [x] = saved;
const { begin, size } = attrs;
const inputShape = x.shape;
const [begin_, size_] = parseSliceParams(x, begin, size);
// Create an Nx2 padding where the first column represents how many
// zeros are prepended (at start) for each dimension, and the second
// column indicates how many zeros are appended (at end).
// The number of zeros to append is the shape of the input
// elementwise-subtracted by both the begin vector and sizes vector.
const paddings = [];
for (let i = 0; i < dy.rank; i++) {
paddings.push([begin_[i], inputShape[i] - begin_[i] - size_[i]]);
}
return { x: () => pad(dy, paddings) };
}
};
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