@tensorflow/tfjs-node
Version:
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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JavaScript
;
/**
* @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.rangeConfig = void 0;
var tfjs_1 = require("@tensorflow/tfjs");
var nodejs_kernel_backend_1 = require("../nodejs_kernel_backend");
exports.rangeConfig = {
kernelName: tfjs_1.Range,
backendName: 'tensorflow',
kernelFunc: function (args) {
var backend = args.backend;
var _a = args.attrs, start = _a.start, stop = _a.stop, dtype = _a.dtype;
var step = args.attrs.step;
// TensorFlow.js specific allowances
var sameStartStop = start === stop;
var increasingRangeNegativeStep = start < stop && step < 0;
var decreasingRangePositiveStep = stop < start && step > 1;
if (sameStartStop || increasingRangeNegativeStep ||
decreasingRangePositiveStep) {
return (0, tfjs_1.zeros)([0], dtype);
}
if (stop < start && step === 1) {
// Auto adjust the step's sign if it hasn't been set
// (or was set to 1)
step = -1;
}
var opAttrs = [(0, nodejs_kernel_backend_1.createTensorsTypeOpAttr)('Tidx', dtype)];
var startTensor = (0, tfjs_1.scalar)(start, dtype);
var stopTensor = (0, tfjs_1.scalar)(stop, dtype);
var stepTensor = (0, tfjs_1.scalar)(step, dtype);
var res = backend.executeSingleOutput(tfjs_1.Range, opAttrs, [startTensor, stopTensor, stepTensor]);
startTensor.dispose();
stopTensor.dispose();
stepTensor.dispose();
return res;
}
};