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@tensorflow/tfjs-node

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This repository provides native TensorFlow execution in backend JavaScript applications under the Node.js runtime, accelerated by the TensorFlow C binary under the hood. It provides the same API as [TensorFlow.js](https://js.tensorflow.org/api/latest/).

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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 {KernelConfig, MirrorPad, MirrorPadAttrs, MirrorPadInputs, tensor2d} from '@tensorflow/tfjs'; import {createTensorsTypeOpAttr, NodeJSKernelBackend} from '../nodejs_kernel_backend'; export const mirrorPadConfig: KernelConfig = { kernelName: MirrorPad, backendName: 'tensorflow', kernelFunc: ({inputs, backend, attrs}) => { const {x} = inputs as MirrorPadInputs; const {paddings, mode} = attrs as unknown as MirrorPadAttrs; const nodeBackend = backend as NodeJSKernelBackend; const paddingsTensor = tensor2d(paddings, [paddings.length, 2], 'int32'); const opAttrs = [ createTensorsTypeOpAttr('T', x.dtype), createTensorsTypeOpAttr('Tpaddings', paddingsTensor.dtype), { name: 'mode', type: nodeBackend.binding.TF_ATTR_STRING, value: mode.toUpperCase() } ]; const output = nodeBackend.executeSingleOutput( 'MirrorPad', opAttrs, [x, paddingsTensor]); paddingsTensor.dispose(); return output; } };