/**
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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 {KernelConfig, LRNGrad, LRNGradAttrs, LRNGradInputs} from '@tensorflow/tfjs';
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import {createTensorsTypeOpAttr, NodeJSKernelBackend} from '../nodejs_kernel_backend';
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// tslint:disable-next-line: variable-name
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export const LRNGradConfig: KernelConfig = {
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kernelName: LRNGrad,
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backendName: 'tensorflow',
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kernelFunc: (args) => {
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const {x, y, dy} = args.inputs as LRNGradInputs;
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const backend = args.backend as NodeJSKernelBackend;
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const {depthRadius, bias, alpha, beta} =
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args.attrs as unknown as LRNGradAttrs;
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const opAttrs = [
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createTensorsTypeOpAttr('T', dy.dtype),
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{
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name: 'depth_radius',
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type: backend.binding.TF_ATTR_INT,
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value: depthRadius
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},
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{name: 'bias', type: backend.binding.TF_ATTR_FLOAT, value: bias},
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{name: 'alpha', type: backend.binding.TF_ATTR_FLOAT, value: alpha},
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{name: 'beta', type: backend.binding.TF_ATTR_FLOAT, value: beta},
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];
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return backend.executeSingleOutput(LRNGrad, opAttrs, [dy, x, y]);
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}
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};
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