"use strict";
|
/**
|
* @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.
|
* =============================================================================
|
*/
|
Object.defineProperty(exports, "__esModule", { value: true });
|
exports.concatConfig = void 0;
|
var tfjs_1 = require("@tensorflow/tfjs");
|
var nodejs_kernel_backend_1 = require("../nodejs_kernel_backend");
|
exports.concatConfig = {
|
kernelName: tfjs_1.Concat,
|
backendName: 'tensorflow',
|
kernelFunc: function (args) {
|
var tensors = args.inputs;
|
var backend = args.backend;
|
var axis = args.attrs.axis;
|
var opAttrs = [
|
{ name: 'N', type: backend.binding.TF_ATTR_INT, value: tensors.length }, {
|
name: 'Tidx',
|
type: backend.binding.TF_ATTR_TYPE,
|
value: backend.binding.TF_INT32
|
},
|
(0, nodejs_kernel_backend_1.createTensorsTypeOpAttr)('T', tensors)
|
];
|
var inputs = Array.from(tensors);
|
var axisTensor = (0, tfjs_1.scalar)(axis, 'int32');
|
inputs.push(axisTensor);
|
var res = backend.executeSingleOutput('ConcatV2', opAttrs, inputs);
|
axisTensor.dispose();
|
return res;
|
}
|
};
|