| 1 | /**
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| 2 | * @license
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| 3 | * Copyright 2020 Google LLC. All Rights Reserved.
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| 4 | * Licensed under the Apache License, Version 2.0 (the "License");
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| 5 | * you may not use this file except in compliance with the License.
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| 6 | * You may obtain a copy of the License at
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| 7 | *
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| 8 | * http://www.apache.org/licenses/LICENSE-2.0
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| 9 | *
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| 10 | * Unless required by applicable law or agreed to in writing, software
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| 11 | * distributed under the License is distributed on an "AS IS" BASIS,
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| 12 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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| 13 | * See the License for the specific language governing permissions and
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| 14 | * limitations under the License.
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| 15 | * =============================================================================
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| 16 | */
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| 17 | import * as tf from '../index';
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| 18 | import { ALL_ENVS, describeWithFlags } from '../jasmine_util';
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| 19 | import { expectArraysClose } from '../test_util';
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| 20 | import { backend } from '../index';
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| 21 | describeWithFlags('neg', ALL_ENVS, () => {
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| 22 | it('basic', async () => {
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| 23 | const a = tf.tensor1d([1, -3, 2, 7, -4]);
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| 24 | const result = tf.neg(a);
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| 25 | expectArraysClose(await result.data(), [-1, 3, -2, -7, 4]);
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| 26 | });
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| 27 | it('int32', async () => {
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| 28 | if (backend() && backend().floatPrecision() === 32) {
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| 29 | // TODO: Use skip() instead when it is implemented
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| 30 | const a = tf.tensor1d([1, -3, 12345678, -12345678], 'int32');
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| 31 | const result = tf.neg(a);
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| 32 | expect(result.dtype).toEqual('int32');
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| 33 | expectArraysClose(await result.data(), [-1, 3, -12345678, 12345678]);
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| 34 | }
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| 35 | });
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| 36 | it('propagate NaNs', async () => {
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| 37 | const a = tf.tensor1d([1, -3, 2, 7, NaN]);
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| 38 | const result = tf.neg(a);
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| 39 | const expected = [-1, 3, -2, -7, NaN];
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| 40 | expectArraysClose(await result.data(), expected);
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| 41 | });
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| 42 | it('gradients: Scalar', async () => {
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| 43 | const a = tf.scalar(4);
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| 44 | const dy = tf.scalar(8);
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| 45 | const da = tf.grad(a => tf.neg(a))(a, dy);
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| 46 | expect(da.shape).toEqual(a.shape);
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| 47 | expect(da.dtype).toEqual('float32');
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| 48 | expectArraysClose(await da.data(), [8 * -1]);
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| 49 | });
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| 50 | it('gradients: Scalar', async () => {
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| 51 | const a = tf.scalar(4);
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| 52 | const dy = tf.scalar(8);
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| 53 | const da = tf.grad(a => tf.neg(a.clone()).clone())(a, dy);
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| 54 | expect(da.shape).toEqual(a.shape);
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| 55 | expect(da.dtype).toEqual('float32');
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| 56 | expectArraysClose(await da.data(), [8 * -1]);
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| 57 | });
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| 58 | it('gradients: Tensor1D', async () => {
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| 59 | const a = tf.tensor1d([1, 2, -3, 5]);
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| 60 | const dy = tf.tensor1d([1, 2, 3, 4]);
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| 61 | const da = tf.grad(a => tf.neg(a))(a, dy);
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| 62 | expect(da.shape).toEqual(a.shape);
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| 63 | expect(da.dtype).toEqual('float32');
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| 64 | expectArraysClose(await da.data(), [1 * -1, 2 * -1, 3 * -1, 4 * -1]);
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| 65 | });
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| 66 | it('gradients: Tensor2D', async () => {
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| 67 | const a = tf.tensor2d([3, -1, -2, 3], [2, 2]);
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| 68 | const dy = tf.tensor2d([1, 2, 3, 4], [2, 2]);
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| 69 | const da = tf.grad(a => tf.neg(a))(a, dy);
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| 70 | expect(da.shape).toEqual(a.shape);
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| 71 | expect(da.dtype).toEqual('float32');
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| 72 | expectArraysClose(await da.data(), [1 * -1, 2 * -1, 3 * -1, 4 * -1]);
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| 73 | });
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| 74 | it('throws when passed a non-tensor', () => {
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| 75 | expect(() => tf.neg({}))
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| 76 | .toThrowError(/Argument 'x' passed to 'neg' must be a Tensor/);
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| 77 | });
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| 78 | it('accepts a tensor-like object', async () => {
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| 79 | const result = tf.neg([1, -3, 2, 7, -4]);
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| 80 | expectArraysClose(await result.data(), [-1, 3, -2, -7, 4]);
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| 81 | });
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| 82 | it('throws for string tensor', () => {
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| 83 | expect(() => tf.neg('q'))
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| 84 | .toThrowError(/Argument 'x' passed to 'neg' must be numeric/);
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| 85 | });
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| 86 | });
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| 87 | //# sourceMappingURL=data:application/json;base64,{"version":3,"file":"neg_test.js","sourceRoot":"","sources":["../../../../../../tfjs-core/src/ops/neg_test.ts"],"names":[],"mappings":"AAAA;;;;;;;;;;;;;;;GAeG;AAEH,OAAO,KAAK,EAAE,MAAM,UAAU,CAAC;AAC/B,OAAO,EAAC,QAAQ,EAAE,iBAAiB,EAAC,MAAM,iBAAiB,CAAC;AAC5D,OAAO,EAAC,iBAAiB,EAAC,MAAM,cAAc,CAAC;AAC/C,OAAO,EAAC,OAAO,EAAC,MAAM,UAAU,CAAC;AAEjC,iBAAiB,CAAC,KAAK,EAAE,QAAQ,EAAE,GAAG,EAAE;IACtC,EAAE,CAAC,OAAO,EAAE,KAAK,IAAI,EAAE;QACrB,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC,CAAC;QACzC,MAAM,MAAM,GAAG,EAAE,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC;QACzB,iBAAiB,CAAC,MAAM,MAAM,CAAC,IAAI,EAAE,EAAE,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;IAC7D,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,OAAO,EAAE,KAAK,IAAI,EAAE;QACrB,IAAI,OAAO,EAAE,IAAI,OAAO,EAAE,CAAC,cAAc,EAAE,KAAK,EAAE,EAAE;YAClD,kDAAkD;YAClD,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,QAAQ,EAAE,CAAC,QAAQ,CAAC,EAAE,OAAO,CAAC,CAAC;YAC7D,MAAM,MAAM,GAAG,EAAE,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC;YACzB,MAAM,CAAC,MAAM,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,OAAO,CAAC,CAAC;YACtC,iBAAiB,CAAC,MAAM,MAAM,CAAC,IAAI,EAAE,EAAE,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,QAAQ,EAAE,QAAQ,CAAC,CAAC,CAAC;SACtE;IACH,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,gBAAgB,EAAE,KAAK,IAAI,EAAE;QAC9B,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,GAAG,CAAC,CAAC,CAAC;QAC1C,MAAM,MAAM,GAAG,EAAE,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC;QACzB,MAAM,QAAQ,GAAG,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,GAAG,CAAC,CAAC;QACtC,iBAAiB,CAAC,MAAM,MAAM,CAAC,IAAI,EAAE,EAAE,QAAQ,CAAC,CAAC;IACnD,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,mBAAmB,EAAE,KAAK,IAAI,EAAE;QACjC,MAAM,CAAC,GAAG,EAAE,CAAC,MAAM,CAAC,CAAC,CAAC,CAAC;QACvB,MAAM,EAAE,GAAG,EAAE,CAAC,MAAM,CAAC,CAAC,CAAC,CAAC;QAExB,MAAM,EAAE,GAAG,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,EAAE,EAAE,CAAC,CAAC;QAE1C,MAAM,CAAC,EAAE,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,CAAC,CAAC,KAAK,CAAC,CAAC;QAClC,MAAM,CAAC,EAAE,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,SAAS,CAAC,CAAC;QACpC,iBAAiB,CAAC,MAAM,EAAE,CAAC,IAAI,EAAE,EAAE,CAAC,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC;IAC/C,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,mBAAmB,EAAE,KAAK,IAAI,EAAE;QACjC,MAAM,CAAC,GAAG,EAAE,CAAC,MAAM,CAAC,CAAC,CAAC,CAAC;QACvB,MAAM,EAAE,GAAG,EAAE,CAAC,MAAM,CAAC,CAAC,CAAC,CAAC;QAExB,MAAM,EAAE,GAAG,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,GAAG,CAAC,CAAC,CAAC,KAAK,EAAE,CAAC,CAAC,KAAK,EAAE,CAAC,CAAC,CAAC,EAAE,EAAE,CAAC,CAAC;QAE1D,MAAM,CAAC,EAAE,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,CAAC,CAAC,KAAK,CAAC,CAAC;QAClC,MAAM,CAAC,EAAE,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,SAAS,CAAC,CAAC;QACpC,iBAAiB,CAAC,MAAM,EAAE,CAAC,IAAI,EAAE,EAAE,CAAC,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC;IAC/C,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,qBAAqB,EAAE,KAAK,IAAI,EAAE;QACnC,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QACrC,MAAM,EAAE,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QAErC,MAAM,EAAE,GAAG,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,EAAE,EAAE,CAAC,CAAC;QAE1C,MAAM,CAAC,EAAE,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,CAAC,CAAC,KAAK,CAAC,CAAC;QAClC,MAAM,CAAC,EAAE,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,SAAS,CAAC,CAAC;QACpC,iBAAiB,CAAC,MAAM,EAAE,CAAC,IAAI,EAAE,EAAE,CAAC,CAAC,GAAG,CAAC,CAAC,EAAE,CAAC,GAAG,CAAC,CAAC,EAAE,CAAC,GAAG,CAAC,CAAC,EAAE,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC;IACvE,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,qBAAqB,EAAE,KAAK,IAAI,EAAE;QACnC,MAAM,CAAC,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QAC9C,MAAM,EAAE,GAAG,EAAE,CAAC,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;QAE7C,MAAM,EAAE,GAAG,EAAE,CAAC,IAAI,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC,EAAE,EAAE,CAAC,CAAC;QAE1C,MAAM,CAAC,EAAE,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,CAAC,CAAC,KAAK,CAAC,CAAC;QAClC,MAAM,CAAC,EAAE,CAAC,KAAK,CAAC,CAAC,OAAO,CAAC,SAAS,CAAC,CAAC;QACpC,iBAAiB,CAAC,MAAM,EAAE,CAAC,IAAI,EAAE,EAAE,CAAC,CAAC,GAAG,CAAC,CAAC,EAAE,CAAC,GAAG,CAAC,CAAC,EAAE,CAAC,GAAG,CAAC,CAAC,EAAE,CAAC,GAAG,CAAC,CAAC,CAAC,CAAC,CAAC;IACvE,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,iCAAiC,EAAE,GAAG,EAAE;QACzC,MAAM,CAAC,GAAG,EAAE,CAAC,EAAE,CAAC,GAAG,CAAC,EAAe,CAAC,CAAC;aAChC,YAAY,CAAC,+CAA+C,CAAC,CAAC;IACrE,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,8BAA8B,EAAE,KAAK,IAAI,EAAE;QAC5C,MAAM,MAAM,GAAG,EAAE,CAAC,GAAG,CAAC,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC,CAAC;QACzC,iBAAiB,CAAC,MAAM,MAAM,CAAC,IAAI,EAAE,EAAE,CAAC,CAAC,CAAC,EAAE,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC,CAAC;IAC7D,CAAC,CAAC,CAAC;IAEH,EAAE,CAAC,0BAA0B,EAAE,GAAG,EAAE;QAClC,MAAM,CAAC,GAAG,EAAE,CAAC,EAAE,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;aACpB,YAAY,CAAC,8CAA8C,CAAC,CAAC;IACpE,CAAC,CAAC,CAAC;AACL,CAAC,CAAC,CAAC","sourcesContent":["/**\n * @license\n * Copyright 2020 Google LLC. All Rights Reserved.\n * Licensed under the Apache License, Version 2.0 (the \"License\");\n * you may not use this file except in compliance with the License.\n * You may obtain a copy of the License at\n *\n * http://www.apache.org/licenses/LICENSE-2.0\n *\n * Unless required by applicable law or agreed to in writing, software\n * distributed under the License is distributed on an \"AS IS\" BASIS,\n * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n * See the License for the specific language governing permissions and\n * limitations under the License.\n * =============================================================================\n */\n\nimport * as tf from '../index';\nimport {ALL_ENVS, describeWithFlags} from '../jasmine_util';\nimport {expectArraysClose} from '../test_util';\nimport {backend} from '../index';\n\ndescribeWithFlags('neg', ALL_ENVS, () => {\n  it('basic', async () => {\n    const a = tf.tensor1d([1, -3, 2, 7, -4]);\n    const result = tf.neg(a);\n    expectArraysClose(await result.data(), [-1, 3, -2, -7, 4]);\n  });\n\n  it('int32', async () => {\n    if (backend() && backend().floatPrecision() === 32) {\n      // TODO: Use skip() instead when it is implemented\n      const a = tf.tensor1d([1, -3, 12345678, -12345678], 'int32');\n      const result = tf.neg(a);\n      expect(result.dtype).toEqual('int32');\n      expectArraysClose(await result.data(), [-1, 3, -12345678, 12345678]);\n    }\n  });\n\n  it('propagate NaNs', async () => {\n    const a = tf.tensor1d([1, -3, 2, 7, NaN]);\n    const result = tf.neg(a);\n    const expected = [-1, 3, -2, -7, NaN];\n    expectArraysClose(await result.data(), expected);\n  });\n\n  it('gradients: Scalar', async () => {\n    const a = tf.scalar(4);\n    const dy = tf.scalar(8);\n\n    const da = tf.grad(a => tf.neg(a))(a, dy);\n\n    expect(da.shape).toEqual(a.shape);\n    expect(da.dtype).toEqual('float32');\n    expectArraysClose(await da.data(), [8 * -1]);\n  });\n\n  it('gradients: Scalar', async () => {\n    const a = tf.scalar(4);\n    const dy = tf.scalar(8);\n\n    const da = tf.grad(a => tf.neg(a.clone()).clone())(a, dy);\n\n    expect(da.shape).toEqual(a.shape);\n    expect(da.dtype).toEqual('float32');\n    expectArraysClose(await da.data(), [8 * -1]);\n  });\n\n  it('gradients: Tensor1D', async () => {\n    const a = tf.tensor1d([1, 2, -3, 5]);\n    const dy = tf.tensor1d([1, 2, 3, 4]);\n\n    const da = tf.grad(a => tf.neg(a))(a, dy);\n\n    expect(da.shape).toEqual(a.shape);\n    expect(da.dtype).toEqual('float32');\n    expectArraysClose(await da.data(), [1 * -1, 2 * -1, 3 * -1, 4 * -1]);\n  });\n\n  it('gradients: Tensor2D', async () => {\n    const a = tf.tensor2d([3, -1, -2, 3], [2, 2]);\n    const dy = tf.tensor2d([1, 2, 3, 4], [2, 2]);\n\n    const da = tf.grad(a => tf.neg(a))(a, dy);\n\n    expect(da.shape).toEqual(a.shape);\n    expect(da.dtype).toEqual('float32');\n    expectArraysClose(await da.data(), [1 * -1, 2 * -1, 3 * -1, 4 * -1]);\n  });\n\n  it('throws when passed a non-tensor', () => {\n    expect(() => tf.neg({} as tf.Tensor))\n        .toThrowError(/Argument 'x' passed to 'neg' must be a Tensor/);\n  });\n\n  it('accepts a tensor-like object', async () => {\n    const result = tf.neg([1, -3, 2, 7, -4]);\n    expectArraysClose(await result.data(), [-1, 3, -2, -7, 4]);\n  });\n\n  it('throws for string tensor', () => {\n    expect(() => tf.neg('q'))\n        .toThrowError(/Argument 'x' passed to 'neg' must be numeric/);\n  });\n});\n"]} |
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