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* @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';\n\ndescribeWithFlags('stack', ALL_ENVS, () => {\n it('scalars 3, 5 and 7', async () => {\n const a = tf.scalar(3);\n const b = tf.scalar(5);\n const c = tf.scalar(7);\n const res = tf.stack([a, b, c]);\n expect(res.shape).toEqual([3]);\n expectArraysClose(await res.data(), [3, 5, 7]);\n });\n\n it('scalars 3, 5 and 7 along axis=1 throws error', () => {\n const a = tf.scalar(3);\n const b = tf.scalar(5);\n const c = tf.scalar(7);\n const f = () => tf.stack([a, b, c], 1);\n expect(f).toThrowError();\n });\n\n it('non matching shapes throws error', () => {\n const a = tf.scalar(3);\n const b = tf.tensor1d([5]);\n const f = () => tf.stack([a, b]);\n expect(f).toThrowError();\n });\n\n it('non matching dtypes throws error', () => {\n const a = tf.scalar(3);\n const b = tf.scalar(5, 'bool');\n const f = () => tf.stack([a, b]);\n expect(f).toThrowError();\n });\n\n it('2d but axis=3 throws error', () => {\n const a = tf.zeros([2, 2]);\n const b = tf.zeros([2, 2]);\n const f = () => tf.stack([a, b], 3 /* axis */);\n expect(f).toThrowError();\n });\n\n it('[1,2], [3,4] and [5,6], axis=0', async () => {\n const a = tf.tensor1d([1, 2]);\n const b = tf.tensor1d([3, 4]);\n const c = tf.tensor1d([5, 6]);\n const res = tf.stack([a, b, c], 0 /* axis */);\n expect(res.shape).toEqual([3, 2]);\n expectArraysClose(await res.data(), [1, 2, 3, 4, 5, 6]);\n });\n\n it('[1,2], [3,4] and [5,6], axis=1', async () => {\n const a = tf.tensor1d([1, 2]);\n const b = tf.tensor1d([3, 4]);\n const c = tf.tensor1d([5, 6]);\n const res = tf.stack([a, b, c], 1 /* axis */);\n expect(res.shape).toEqual([2, 3]);\n expectArraysClose(await res.data(), [1, 3, 5, 2, 4, 6]);\n });\n\n it('[[1,2],[3,4]] and [[5, 6], [7, 8]], axis=0', async () => {\n const a = tf.tensor2d([[1, 2], [3, 4]]);\n const b = tf.tensor2d([[5, 6], [7, 8]]);\n const res = tf.stack([a, b], 0 /* axis */);\n expect(res.shape).toEqual([2, 2, 2]);\n expectArraysClose(await res.data(), [1, 2, 3, 4, 5, 6, 7, 8]);\n });\n\n it('[[1,2],[3,4]] and [[5, 6], [7, 8]], axis=2', async () => {\n const a = tf.tensor2d([[1, 2], [3, 4]]);\n const b = tf.tensor2d([[5, 6], [7, 8]]);\n const c = tf.tensor2d([[9, 10], [11, 12]]);\n const res = tf.stack([a, b, c], 2 /* axis */);\n expect(res.shape).toEqual([2, 2, 3]);\n expectArraysClose(\n await res.data(), [1, 5, 9, 2, 6, 10, 3, 7, 11, 4, 8, 12]);\n });\n\n it('single tensor', async () => {\n const a = tf.tensor2d([[1, 2], [3, 4]]);\n const res = tf.stack([a], 2 /* axis */);\n expect(res.shape).toEqual([2, 2, 1]);\n expectArraysClose(await res.data(), [1, 2, 3, 4]);\n });\n\n it('throws when passed a non-tensor', () => {\n expect(() => tf.stack([{} as tf.Tensor]))\n .toThrowError(\n /Argument 'tensors\\[0\\]' passed to 'stack' must be a Tensor/);\n });\n\n it('accepts a tensor-like object', async () => {\n const a = [[1, 2], [3, 4]];\n const res = tf.stack([a], 2 /* axis */);\n expect(res.shape).toEqual([2, 2, 1]);\n expectArraysClose(await res.data(), [1, 2, 3, 4]);\n });\n\n it('accepts string.', async () => {\n const a = tf.scalar('three', 'string');\n const b = tf.scalar('five', 'string');\n const c = tf.scalar('seven', 'string');\n const res = tf.stack([a, b, c]);\n expect(res.shape).toEqual([3]);\n expectArraysClose(await res.data(), ['three', 'five', 'seven']);\n });\n\n it('chain api', async () => {\n const a = tf.tensor([1, 2]);\n const res = a.stack(tf.tensor([3, 4]));\n expect(res.shape).toEqual([2, 2]);\n expectArraysClose(await res.data(), [1, 2, 3, 4]);\n });\n});\n"]} |