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@tensorflow/tfjs-core

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Hardware-accelerated JavaScript library for machine intelligence

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"use strict"; Object.defineProperty(exports, "__esModule", { value: true }); var tf = require("../index"); var test_util_1 = require("../test_util"); var jasmine_util_1 = require("../jasmine_util"); jasmine_util_1.describeWithFlags('resizeBilinear', test_util_1.ALL_ENVS, function () { it('simple alignCorners=false', function () { var input = tf.tensor3d([2, 2, 4, 4], [2, 2, 1]); var output = input.resizeBilinear([3, 3], false); test_util_1.expectArraysClose(output, [2, 2, 2, 10 / 3, 10 / 3, 10 / 3, 4, 4, 4]); }); it('simple alignCorners=true', function () { var input = tf.tensor3d([2, 2, 4, 4], [2, 2, 1]); var output = input.resizeBilinear([3, 3], true); test_util_1.expectArraysClose(output, [2, 2, 2, 3, 3, 3, 4, 4, 4]); }); it('matches tensorflow w/ random numbers alignCorners=false', function () { var input = tf.tensor3d([ 1.19074044, 0.91373104, 2.01611669, -0.52270832, 0.38725395, 1.30809779, 0.61835143, 3.49600659, 2.09230986, 0.56473997, 0.03823943, 1.19864896 ], [2, 3, 2]); var output = input.resizeBilinear([4, 5], false); test_util_1.expectArraysClose(output, [ 1.19074047, 0.91373104, 1.68596613, 0.05186744, 1.69034398, -0.15654698, 0.7130264, 0.94193673, 0.38725394, 1.30809784, 0.9045459, 2.20486879, 1.59434628, 0.89455694, 1.68591988, 0.26748738, 0.58103991, 1.00690198, 0.21274668, 1.25337338, 0.6183514, 3.49600649, 1.50272655, 1.73724651, 1.68149579, 0.69152176, 0.44905344, 1.07186723, 0.03823943, 1.19864893, 0.6183514, 3.49600649, 1.50272655, 1.73724651, 1.68149579, 0.69152176, 0.44905344, 1.07186723, 0.03823943, 1.19864893 ]); }); it('matches tensorflow w/ random numbers alignCorners=true', function () { var input = tf.tensor3d([ 1.56324531, 2.13817752, 1.44398421, 1.07632684, 0.59306785, -0.36970865, 1.62451879, 1.8367334, 1.13944798, 2.01993218, 2.01919952, 2.67524054 ], [2, 3, 2]); var output = input.resizeBilinear([4, 5], true); test_util_1.expectArraysClose(output, [ 1.5632453, 2.13817763, 1.50361478, 1.60725224, 1.44398427, 1.07632685, 1.01852608, 0.35330909, 0.59306782, -0.36970866, 1.58366978, 2.03769612, 1.46307099, 1.71427906, 1.3424722, 1.39086199, 1.20545864, 1.01806819, 1.06844509, 0.6452744, 1.60409427, 1.93721485, 1.42252707, 1.82130599, 1.24096, 1.70539713, 1.3923912, 1.68282723, 1.54382229, 1.66025746, 1.62451875, 1.83673346, 1.38198328, 1.92833281, 1.13944793, 2.01993227, 1.57932377, 2.34758639, 2.01919961, 2.67524052 ]); }); it('batch of 2, simple, alignCorners=true', function () { var input = tf.tensor4d([2, 2, 4, 4, 3, 3, 5, 5], [2, 2, 2, 1]); var output = input.resizeBilinear([3, 3], true); test_util_1.expectArraysClose(output, [2, 2, 2, 3, 3, 3, 4, 4, 4, 3, 3, 3, 4, 4, 4, 5, 5, 5]); }); it('throws when passed a non-tensor', function () { var e = /Argument 'images' passed to 'resizeBilinear' must be a Tensor/; expect(function () { return tf.image.resizeBilinear({}, [ 1, 1 ]); }).toThrowError(e); }); });