@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;
}
};