/**
 * @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 { backend_util, GatherV2, util, env } from '@tensorflow/tfjs-core';
import { GatherProgram } from '../gather_gpu';
import { gatherV2ImplCPU } from '../kernel_utils/shared';
import { reshape } from './Reshape';
export function gatherV2(args) {
    const { inputs, backend, attrs } = args;
    const { x, indices } = inputs;
    const { axis, batchDims } = attrs;
    const parsedAxis = util.parseAxisParam(axis, x.shape)[0];
    if (env().get('DEBUG')) {
        // In debug mode, throw error when any index is out of bound.
        // Otherwise, just fill out of bounds with zeroes.
        const indicesVals = backend.readSync(indices.dataId);
        const axisDim = x.shape[parsedAxis];
        for (let i = 0; i < indicesVals.length; ++i) {
            const index = indicesVals[i];
            util.assert(index <= axisDim - 1 && index >= 0, () => `GatherV2: the index value ${index} is not in [0, ${axisDim - 1}]`);
        }
    }
    const shapeInfo = backend_util.segment_util.collectGatherOpShapeInfo(x, indices, parsedAxis, batchDims);
    const indicesSize = util.sizeFromShape(indices.shape);
    const toDispose = [];
    const flattenX = reshape({
        inputs: { x },
        backend,
        attrs: {
            shape: [
                shapeInfo.batchSize, shapeInfo.outerSize, shapeInfo.dimSize,
                shapeInfo.sliceSize
            ]
        }
    });
    const flattenIndex = reshape({
        inputs: { x: indices },
        backend,
        attrs: { shape: [shapeInfo.batchSize, indicesSize / shapeInfo.batchSize] }
    });
    toDispose.push(flattenX);
    toDispose.push(flattenIndex);
    const flattenOutputShape = [
        shapeInfo.batchSize, shapeInfo.outerSize, indicesSize / shapeInfo.batchSize,
        shapeInfo.sliceSize
    ];
    if (backend.shouldExecuteOnCPU([x, indices]) || x.dtype === 'string') {
        const indicesBuf = backend.bufferSync(flattenIndex);
        const xBuf = backend.bufferSync(flattenX);
        const outBuf = gatherV2ImplCPU(xBuf, indicesBuf, flattenOutputShape);
        toDispose.forEach(t => backend.disposeIntermediateTensorInfo(t));
        return backend.makeTensorInfo(shapeInfo.outputShape, outBuf.dtype, outBuf.values);
    }
    const program = new GatherProgram(flattenX.shape, flattenOutputShape);
    const res = backend.runWebGLProgram(program, [flattenX, flattenIndex], flattenX.dtype);
    toDispose.push(res);
    const reshaped = reshape({ inputs: { x: res }, backend, attrs: { shape: shapeInfo.outputShape } });
    toDispose.forEach(t => backend.disposeIntermediateTensorInfo(t));
    return reshaped;
}
export const gatherV2Config = {
    kernelName: GatherV2,
    backendName: 'webgl',
    kernelFunc: gatherV2
};
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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 {backend_util, GatherV2, GatherV2Attrs, GatherV2Inputs, KernelConfig, KernelFunc, TensorInfo, TypedArray, util, env} from '@tensorflow/tfjs-core';\n\nimport {MathBackendWebGL} from '../backend_webgl';\nimport {GatherProgram, GatherShape} from '../gather_gpu';\nimport {gatherV2ImplCPU} from '../kernel_utils/shared';\n\nimport {reshape} from './Reshape';\n\nexport function gatherV2(args: {\n  inputs: GatherV2Inputs,\n  backend: MathBackendWebGL,\n  attrs: GatherV2Attrs\n}): TensorInfo {\n  const {inputs, backend, attrs} = args;\n  const {x, indices} = inputs;\n  const {axis, batchDims} = attrs;\n\n  const parsedAxis = util.parseAxisParam(axis, x.shape)[0];\n  if (env().get('DEBUG')) {\n    // In debug mode, throw error when any index is out of bound.\n    // Otherwise, just fill out of bounds with zeroes.\n    const indicesVals = backend.readSync(indices.dataId) as TypedArray;\n    const axisDim = x.shape[parsedAxis];\n    for (let i = 0; i < indicesVals.length; ++i) {\n      const index = indicesVals[i];\n      util.assert(\n        index <= axisDim - 1 && index >= 0,\n        () =>\n          `GatherV2: the index value ${index} is not in [0, ${axisDim - 1}]`);\n    }\n  }\n\n  const shapeInfo = backend_util.segment_util.collectGatherOpShapeInfo(\n      x, indices, parsedAxis, batchDims);\n\n  const indicesSize = util.sizeFromShape(indices.shape);\n\n  const toDispose = [];\n\n  const flattenX = reshape({\n    inputs: {x},\n    backend,\n    attrs: {\n      shape: [\n        shapeInfo.batchSize, shapeInfo.outerSize, shapeInfo.dimSize,\n        shapeInfo.sliceSize\n      ]\n    }\n  });\n\n  const flattenIndex = reshape({\n    inputs: {x: indices},\n    backend,\n    attrs: {shape: [shapeInfo.batchSize, indicesSize / shapeInfo.batchSize]}\n  });\n\n  toDispose.push(flattenX);\n  toDispose.push(flattenIndex);\n\n  const flattenOutputShape = [\n    shapeInfo.batchSize, shapeInfo.outerSize, indicesSize / shapeInfo.batchSize,\n    shapeInfo.sliceSize\n  ];\n\n  if (backend.shouldExecuteOnCPU([x, indices]) || x.dtype === 'string') {\n    const indicesBuf = backend.bufferSync(flattenIndex);\n    const xBuf = backend.bufferSync(flattenX);\n    const outBuf = gatherV2ImplCPU(xBuf, indicesBuf, flattenOutputShape);\n\n    toDispose.forEach(t => backend.disposeIntermediateTensorInfo(t));\n\n    return backend.makeTensorInfo(\n        shapeInfo.outputShape, outBuf.dtype, outBuf.values as TypedArray);\n  }\n\n  const program = new GatherProgram(flattenX.shape as GatherShape,\n                                    flattenOutputShape as GatherShape);\n  const res = backend.runWebGLProgram(\n      program, [flattenX, flattenIndex], flattenX.dtype);\n  toDispose.push(res);\n\n  const reshaped = reshape(\n      {inputs: {x: res}, backend, attrs: {shape: shapeInfo.outputShape}});\n  toDispose.forEach(t => backend.disposeIntermediateTensorInfo(t));\n  return reshaped;\n}\n\nexport const gatherV2Config: KernelConfig = {\n  kernelName: GatherV2,\n  backendName: 'webgl',\n  kernelFunc: gatherV2 as unknown as KernelFunc\n};\n"]}