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@tensorflow/tfjs-core

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Hardware-accelerated JavaScript library for machine intelligence

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/** * @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. * ============================================================================= */ import * as tf from '../index'; import { ALL_ENVS, describeWithFlags } from '../jasmine_util'; import { expectArraysClose } from '../test_util'; describeWithFlags('elu', ALL_ENVS, () => { it('calculate elu', async () => { const a = tf.tensor1d([1, -1, 0]); const result = tf.elu(a); expect(result.shape).toEqual(a.shape); expectArraysClose(await result.data(), [1, -0.6321, 0]); }); it('elu propagates NaN', async () => { const a = tf.tensor1d([1, NaN]); const result = tf.elu(a); expect(result.shape).toEqual(a.shape); expectArraysClose(await result.data(), [1, NaN]); }); it('derivative', async () => { const x = tf.tensor1d([1, 3, -2]); const dy = tf.tensor1d([5, 50, 500]); const gradients = tf.grad(a => tf.elu(a))(x, dy); expect(gradients.shape).toEqual(x.shape); expect(gradients.dtype).toEqual('float32'); expectArraysClose(await gradients.data(), [5, 50, 500 * Math.exp(-2)]); }); it('gradient with clones', async () => { const x = tf.tensor1d([1, 3, -2]); const dy = tf.tensor1d([5, 50, 500]); const gradients = tf.grad(a => tf.elu(a.clone()).clone())(x, dy); expect(gradients.shape).toEqual(x.shape); expect(gradients.dtype).toEqual('float32'); expectArraysClose(await gradients.data(), [5, 50, 500 * Math.exp(-2)]); }); it('throws when passed a non-tensor', () => { expect(() => tf.elu({})) .toThrowError(/Argument 'x' passed to 'elu' must be a Tensor/); }); it('accepts a tensor-like object', async () => { const result = tf.elu([1, -1, 0]); expect(result.shape).toEqual(result.shape); expectArraysClose(await result.data(), [1, -0.6321, 0]); }); it('throws for string tensor', () => { expect(() => tf.elu('q')) .toThrowError(/Argument 'x' passed to 'elu' must be numeric/); }); }); //# sourceMappingURL=elu_test.js.map