/**
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* @license
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* Copyright 2020 Google LLC. All Rights Reserved.
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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* =============================================================================
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*/
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import {SquaredDifference, SquaredDifferenceInputs} from '../../../kernel_names';
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import {KernelConfig} from '../../../kernel_registry';
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import {TypedArray} from '../../../types';
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import {MathBackendCPU} from '../backend_cpu';
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import {assertNotComplex} from '../cpu_util';
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import {broadcastedBinaryOp} from '../utils/kernel_utils';
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export const squaredDifferenceConfig: KernelConfig = {
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kernelName: SquaredDifference,
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backendName: 'cpu',
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kernelFunc: ({inputs, backend}) => {
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const {a, b} = inputs as SquaredDifferenceInputs;
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const cpuBackend = backend as MathBackendCPU;
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assertNotComplex([a, b], SquaredDifference);
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const aVals = cpuBackend.data.get(a.dataId).values as TypedArray;
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const bVals = cpuBackend.data.get(b.dataId).values as TypedArray;
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const [resultData, resultShape] = broadcastedBinaryOp(
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a.shape, b.shape, aVals, bVals, a.dtype, (aVal, bVal) => {
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const diff = aVal - bVal;
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return diff * diff;
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});
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const dataId = cpuBackend.write(resultData, resultShape, a.dtype);
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return {dataId, shape: resultShape, dtype: a.dtype};
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}
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};
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