/**
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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 {backend_util, KernelConfig, scalar, SplitV, SplitVAttrs, SplitVInputs, Tensor, tensor1d, tidy, util} from '@tensorflow/tfjs';
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import {createTensorsTypeOpAttr, NodeJSKernelBackend} from '../nodejs_kernel_backend';
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export const splitVConfig: KernelConfig = {
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kernelName: SplitV,
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backendName: 'tensorflow',
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kernelFunc: (args) => {
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const {x} = args.inputs as SplitVInputs;
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const backend = args.backend as NodeJSKernelBackend;
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const {numOrSizeSplits, axis} = args.attrs as unknown as SplitVAttrs;
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const $axis = util.parseAxisParam(axis, x.shape)[0];
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const splitSizes = backend_util.prepareSplitSize(x, numOrSizeSplits, $axis);
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const opAttrs = [
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{
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name: 'num_split',
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type: backend.binding.TF_ATTR_INT,
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value: splitSizes.length
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},
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createTensorsTypeOpAttr('T', x as Tensor), {
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name: 'Tlen',
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type: backend.binding.TF_ATTR_TYPE,
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value: backend.binding.TF_INT32
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}
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];
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const inputs = [x];
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return tidy(() => {
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inputs.push(tensor1d(splitSizes, 'int32'));
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inputs.push(scalar($axis, 'int32'));
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return backend.executeMultipleOutputs(
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SplitV, opAttrs, inputs, splitSizes.length);
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});
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}
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};
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