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@tensorflow/tfjs-core

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Hardware-accelerated JavaScript library for machine intelligence

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/** * @license * Copyright 2019 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, SYNC_BACKEND_ENVS } from './jasmine_util'; import { convertToTensor } from './tensor_util_env'; import { expectArraysClose } from './test_util'; describeWithFlags('debug on', SYNC_BACKEND_ENVS, () => { beforeAll(() => { // Silence debug warnings. spyOn(console, 'warn'); tf.enableDebugMode(); }); it('debug mode does not error when no nans', async () => { const a = tf.tensor1d([2, -1, 0, 3]); const res = tf.relu(a); expectArraysClose(await res.data(), [2, 0, 0, 3]); }); it('debug mode errors when nans in tensor construction, float32', () => { const a = () => tf.tensor1d([2, NaN], 'float32'); expect(a).toThrowError(); }); it('debug mode errors when nans in tensor construction, int32', () => { const a = () => tf.tensor1d([2, NaN], 'int32'); expect(a).toThrowError(); }); it('debug mode errors when Infinity in tensor construction', () => { const a = () => tf.tensor1d([2, Infinity], 'float32'); expect(a).toThrowError(); }); it('debug mode errors when nans in tensor created from TypedArray', () => { const a = () => tf.tensor1d(new Float32Array([1, 2, NaN]), 'float32'); expect(a).toThrowError(); }); it('debug mode errors when infinities in op output', async () => { const a = tf.tensor1d([1, 2, 3, 4]); const b = tf.tensor1d([2, -1, 0, 3]); const c = async () => { const result = a.div(b); // Must await result so we know exception would have happened by the // time we call `expect`. await result.data(); }; await c(); expect(console.warn).toHaveBeenCalled(); }); it('debug mode errors when nans in op output', async () => { const a = tf.tensor1d([-1, 2]); const b = tf.tensor1d([0.5, 1]); const c = async () => { const result = a.pow(b); await result.data(); }; await c(); expect(console.warn).toHaveBeenCalled(); }); it('debug mode errors when nans in oneHot op (tensorlike), int32', () => { const f = () => tf.oneHot([2, NaN], 3); expect(f).toThrowError(); }); it('debug mode errors when nan in convertToTensor, int32', () => { const a = () => convertToTensor(NaN, 'a', 'test', 'int32'); expect(a).toThrowError(); }); it('debug mode errors when nan in convertToTensor array input, int32', () => { const a = () => convertToTensor([NaN], 'a', 'test', 'int32'); expect(a).toThrowError(); }); // tslint:disable-next-line: ban xit('A x B', async () => { const a = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]); const b = tf.tensor2d([0, 1, -3, 2, 2, 1], [3, 2]); const c = tf.matMul(a, b); expect(c.shape).toEqual([2, 2]); expectArraysClose(await c.data(), [0, 8, -3, 20]); }); }); describeWithFlags('debug off', ALL_ENVS, () => { beforeAll(() => { tf.env().set('DEBUG', false); }); it('no errors where there are nans, and debug mode is disabled', async () => { const a = tf.tensor1d([2, NaN]); const res = tf.relu(a); expectArraysClose(await res.data(), [2, NaN]); }); }); //# sourceMappingURL=debug_mode_test.js.map