gx

chenyc

2025-06-12 7b72ac13a83764a662159d4a49b7fffb90476ecb

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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 { GatherV2 } from '../kernel_names';
import { getUndoAxesPermutation } from '../ops/axis_util';
import { reshape } from '../ops/reshape';
import { stack } from '../ops/stack';
import { transpose } from '../ops/transpose';
import { unsortedSegmentSum } from '../ops/unsorted_segment_sum';
import { parseAxisParam } from '../util';
export const gatherGradConfig = {
    kernelName: GatherV2,
    inputsToSave: ['x', 'indices'],
    gradFunc: (dy, saved, attrs) => {
        const [x, indices] = saved;
        const { axis, batchDims } = attrs;
        const parsedAxis = parseAxisParam(axis, x.shape)[0];
        const derXBatch = (x, indices, dy) => {
            return () => {
                const paramsShape = x.shape;
                const indicesSize = indices.size;
                const outerShape = paramsShape.slice(0, parsedAxis);
                const outerDims = outerShape.length;
                const innerShape = paramsShape.slice(axis, paramsShape.length).slice(1);
                const innerDims = innerShape.length;
                const outerAxesIndices = arrayRange(0, outerDims);
                const innerAxesIndices = arrayRange(outerDims + 1, outerDims + 1 + innerDims);
                const valuesShape = arrayConcat([outerShape, [indicesSize],
                    innerShape]);
                const values = reshape(dy, valuesShape);
                const reshapedIndices = reshape(indices, [indicesSize]);
                const transposeDims = arrayConcat([[outerDims], outerAxesIndices, innerAxesIndices]);
                const valuesTranspose = transpose(values, transposeDims);
                let paramsGrad = unsortedSegmentSum(valuesTranspose, reshapedIndices, x.shape[parsedAxis]);
                const invertTransposeDims = getUndoAxesPermutation(transposeDims);
                paramsGrad = transpose(paramsGrad, invertTransposeDims);
                return paramsGrad;
            };
        };
        if (batchDims === 1) {
            const batchSize = x.shape[0];
            const xBatch = x.split(batchSize, 0);
            const derXBatched = () => {
                const stacked = stack(xBatch.map((x, i) => {
                    return derXBatch(x, indices.slice(i, 1), dy.slice(i, 1))();
                }));
                return stacked.reshape(x.shape);
            };
            return { x: derXBatched, indices: () => indices };
        }
        else {
            return { x: derXBatch(x, indices, dy), indices: () => indices };
        }
    }
};
function arrayRange(start, stop) {
    const result = [];
    for (let i = start; i < stop; ++i) {
        result.push(i);
    }
    return result;
}
function arrayConcat(arrays) {
    const result = [];
    for (let i = 0; i < arrays.length; ++i) {
        for (let j = 0; j < arrays[i].length; ++j) {
            result.push(arrays[i][j]);
        }
    }
    return result;
}
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All Rights Reserved.\n * Licensed under the Apache License, Version 2.0 (the \"License\");\n * you may not use this file except in compliance with the License.\n * You may obtain a copy of the License at\n *\n * http://www.apache.org/licenses/LICENSE-2.0\n *\n * Unless required by applicable law or agreed to in writing, software\n * distributed under the License is distributed on an \"AS IS\" BASIS,\n * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n * See the License for the specific language governing permissions and\n * limitations under the License.\n * =============================================================================\n */\n\nimport {GatherV2, GatherV2Attrs} from '../kernel_names';\nimport {GradConfig, NamedAttrMap} from '../kernel_registry';\nimport {getUndoAxesPermutation} from '../ops/axis_util';\nimport {reshape} from '../ops/reshape';\nimport {stack} from '../ops/stack';\nimport {transpose} from '../ops/transpose';\nimport {unsortedSegmentSum} from '../ops/unsorted_segment_sum';\nimport {Tensor, Tensor1D} from '../tensor';\nimport {parseAxisParam} from '../util';\n\nexport const gatherGradConfig: GradConfig = {\n  kernelName: GatherV2,\n  inputsToSave: ['x', 'indices'],\n  gradFunc: (dy: Tensor, saved: Tensor[], attrs: NamedAttrMap) => {\n    const [x, indices] = saved;\n    const {axis, batchDims} = attrs as unknown as GatherV2Attrs;\n\n    const parsedAxis = parseAxisParam(axis, x.shape)[0];\n\n    const derXBatch = (x: Tensor, indices: Tensor, dy: Tensor) => {\n      return (): Tensor => {\n        const paramsShape = x.shape;\n        const indicesSize = indices.size;\n\n        const outerShape = paramsShape.slice(0, parsedAxis);\n        const outerDims = outerShape.length;\n        const innerShape = paramsShape.slice(axis, paramsShape.length).slice(1);\n        const innerDims = innerShape.length;\n\n        const outerAxesIndices = arrayRange(0, outerDims);\n        const innerAxesIndices =\n            arrayRange(outerDims + 1, outerDims + 1 + innerDims);\n\n        const valuesShape = arrayConcat([outerShape, [indicesSize],\n                                         innerShape]);\n\n        const values = reshape(dy, valuesShape);\n        const reshapedIndices = reshape(indices, [indicesSize]);\n\n        const transposeDims =\n            arrayConcat([[outerDims], outerAxesIndices, innerAxesIndices]);\n        const valuesTranspose = transpose(values, transposeDims);\n        let paramsGrad = unsortedSegmentSum(\n            valuesTranspose, reshapedIndices as Tensor1D, x.shape[parsedAxis]);\n        const invertTransposeDims = getUndoAxesPermutation(transposeDims);\n        paramsGrad = transpose(paramsGrad, invertTransposeDims);\n        return paramsGrad;\n      };\n    };\n\n    if (batchDims === 1) {\n      const batchSize = x.shape[0];\n      const xBatch = x.split(batchSize, 0);\n      const derXBatched = () => {\n        const stacked = stack(\n          xBatch.map((x, i) => {\n            return derXBatch(x, indices.slice(i,1), dy.slice(i,1))();\n          }));\n        return stacked.reshape(x.shape);\n      };\n      return {x: derXBatched, indices: () => indices};\n    } else {\n      return {x: derXBatch(x, indices, dy), indices: () => indices};\n    }\n  }\n};\n\nfunction arrayRange(start: number, stop: number): number[] {\n  const result = [];\n  for (let i = start; i < stop; ++i) {\n    result.push(i);\n  }\n  return result;\n}\n\nfunction arrayConcat(arrays: number[][]): number[] {\n  const result = [];\n  for (let i = 0; i < arrays.length; ++i) {\n    for (let j = 0; j < arrays[i].length; ++j) {\n      result.push(arrays[i][j]);\n    }\n  }\n  return result;\n}\n"]}