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