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| /**
| * @license
| * Copyright 2022 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 * as tf from '../index';
| import { ALL_ENVS, describeWithFlags } from '../jasmine_util';
| import { expectArraysClose } from '../test_util';
| describeWithFlags('upperBound', ALL_ENVS, () => {
| it('test1D', async () => {
| // Tests against numpy generated data.
| const NUMPY_DATA = {
| 'float32': [
| [
| -725.0505981445312, -721.4473266601562, -669.2916259765625,
| -460.14422607421875, -304.4682922363281, -302.20330810546875,
| -204.64633178710938, -143.817626953125, 243.3914337158203,
| 247.34442138671875, 326.88299560546875, 451.9959716796875,
| 501.62420654296875, 501.8848571777344, 614.7825927734375,
| 766.6121826171875, 791.7724609375, 806.8038330078125,
| 855.0171508789062, 929.6801147460938
| ],
| [
| -795.3311157226562, -171.88803100585938, 388.8003234863281,
| -171.64146423339844, -900.0930786132812, 71.79280853271484,
| 327.58929443359375, 29.77822494506836, 889.1895141601562,
| 173.11007690429688
| ],
| [0, 7, 11, 7, 0, 8, 11, 8, 19, 8]
| ],
| 'int32': [
| [
| -968, -867, -751, -725, -655, -346, -285, 54, 246, 381,
| 393, 423, 507, 510, 771, 817, 846, 858, 865, 994
| ],
| [-770, 898, -100, 156, -183, -525, 806, 147, -994, 234],
| [2, 19, 7, 8, 7, 5, 15, 8, 0, 8]
| ]
| };
| for (const dtype of ['float32', 'int32']) {
| const [sortedSequence, values, npAns] = NUMPY_DATA[dtype];
| const result = tf.upperBound(sortedSequence, values);
| expectArraysClose(await result.data(), npAns);
| }
| });
| it('upperBound2D', async () => {
| for (const dtype of ['float32', 'int32']) {
| const sortedSequence = tf.tensor2d([[0, 3, 9, 9, 10], [1, 2, 3, 4, 5]], undefined, dtype);
| const values = tf.tensor2d([[2, 4, 9], [0, 2, 6]], undefined, dtype);
| const correctAns = [[1, 2, 4], [0, 2, 5]];
| const result = tf.upperBound(sortedSequence, values);
| expectArraysClose(await result.data(), correctAns);
| }
| });
| });
| //# 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|
|
