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AC1D,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';\n\ndescribeWithFlags('unstack', ALL_ENVS, () => {\n it('unstack by default', async () => {\n const x = tf.tensor2d([1, 2, 3, 4, 5, 6, 7, 8], [2, 4]);\n const res = tf.unstack(x);\n expect(res.length).toEqual(2);\n expect(res[0].rank).toEqual(1);\n expect(res[0].shape).toEqual([4]);\n expectArraysClose(await res[0].data(), [1, 2, 3, 4]);\n expect(res[1].rank).toEqual(1);\n expect(res[1].shape).toEqual([4]);\n expectArraysClose(await res[1].data(), [5, 6, 7, 8]);\n });\n\n it('chain api', async () => {\n const x = tf.tensor2d([1, 2, 3, 4, 5, 6, 7, 8], [2, 4]);\n const res = x.unstack();\n expect(res.length).toEqual(2);\n expect(res[0].rank).toEqual(1);\n expect(res[0].shape).toEqual([4]);\n expectArraysClose(await res[0].data(), [1, 2, 3, 4]);\n expect(res[1].rank).toEqual(1);\n expect(res[1].shape).toEqual([4]);\n expectArraysClose(await res[1].data(), [5, 6, 7, 8]);\n });\n\n it('unstack with negative integer axis', async () => {\n const x = tf.tensor2d([1, 2, 3, 4, 5, 6, 7, 8], [2, 4]);\n\n let res = tf.unstack(x, -1);\n expect(res.length).toEqual(4);\n expect(res[0].rank).toEqual(1);\n expect(res[0].shape).toEqual([2]);\n expectArraysClose(await res[0].data(), [1, 5]);\n expect(res[1].rank).toEqual(1);\n expect(res[1].shape).toEqual([2]);\n expectArraysClose(await res[1].data(), [2, 6]);\n expect(res[2].rank).toEqual(1);\n expect(res[2].shape).toEqual([2]);\n expectArraysClose(await res[2].data(), [3, 7]);\n expect(res[3].rank).toEqual(1);\n expect(res[3].shape).toEqual([2]);\n expectArraysClose(await res[3].data(), [4, 8]);\n\n res = tf.unstack(x, -2);\n expect(res.length).toEqual(2);\n expect(res[0].rank).toEqual(1);\n expect(res[0].shape).toEqual([4]);\n expectArraysClose(await res[0].data(), [1, 2, 3, 4]);\n expect(res[1].rank).toEqual(1);\n expect(res[1].shape).toEqual([4]);\n expectArraysClose(await res[1].data(), [5, 6, 7, 8]);\n });\n\n it('unstack into 3 tensors', async () => {\n const x = tf.tensor2d([1, 2, 3, 4, 5, 6], [3, 2]);\n const res = tf.unstack(x, 0);\n expect(res.length).toEqual(3);\n expect(res[0].rank).toEqual(1);\n expect(res[0].shape).toEqual([2]);\n expectArraysClose(await res[0].data(), [1, 2]);\n expect(res[1].rank).toEqual(1);\n expect(res[1].shape).toEqual([2]);\n expectArraysClose(await res[1].data(), [3, 4]);\n expect(res[2].rank).toEqual(1);\n expect(res[2].shape).toEqual([2]);\n expectArraysClose(await res[2].data(), [5, 6]);\n });\n\n it('unstack by axis=1', async () => {\n const x = tf.tensor2d([1, 2, 3, 4, 5, 6, 7, 8], [2, 4]);\n const res = tf.unstack(x, 1);\n expect(res.length).toEqual(4);\n expect(res[0].rank).toEqual(1);\n expect(res[0].shape).toEqual([2]);\n expectArraysClose(await res[0].data(), [1, 5]);\n expect(res[1].rank).toEqual(1);\n expect(res[1].shape).toEqual([2]);\n expectArraysClose(await res[1].data(), [2, 6]);\n expect(res[2].rank).toEqual(1);\n expect(res[2].shape).toEqual([2]);\n expectArraysClose(await res[2].data(), [3, 7]);\n expect(res[3].rank).toEqual(1);\n expect(res[3].shape).toEqual([2]);\n expectArraysClose(await res[3].data(), [4, 8]);\n });\n\n it('unstack rank 3 tensor', async () => {\n const x = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, 8], [2, 2, 2]);\n const res = tf.unstack(x);\n expect(res.length).toEqual(2);\n expect(res[0].rank).toEqual(2);\n expect(res[0].shape).toEqual([2, 2]);\n expectArraysClose(await res[0].data(), [1, 2, 3, 4]);\n expect(res[1].rank).toEqual(2);\n expect(res[1].shape).toEqual([2, 2]);\n expectArraysClose(await res[1].data(), [5, 6, 7, 8]);\n });\n\n it('unstack rank 3 tensor with axis=1', async () => {\n const x = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, 8], [2, 2, 2]);\n const res = tf.unstack(x, 1);\n expect(res.length).toEqual(2);\n expect(res[0].rank).toEqual(2);\n expect(res[0].shape).toEqual([2, 2]);\n expectArraysClose(await res[0].data(), [1, 2, 5, 6]);\n expect(res[1].rank).toEqual(2);\n expect(res[1].shape).toEqual([2, 2]);\n expectArraysClose(await res[1].data(), [3, 4, 7, 8]);\n });\n\n it('unstack rank 3 tensor with axis=2', async () => {\n const x = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, 8], [2, 2, 2]);\n const res = tf.unstack(x, 2);\n expect(res.length).toEqual(2);\n expect(res[0].rank).toEqual(2);\n expect(res[0].shape).toEqual([2, 2]);\n expectArraysClose(await res[0].data(), [1, 3, 5, 7]);\n expect(res[1].rank).toEqual(2);\n expect(res[1].shape).toEqual([2, 2]);\n expectArraysClose(await res[1].data(), [2, 4, 6, 8]);\n });\n\n it('unstack rank 4 tensor', async () => {\n const x = tf.tensor4d([1, 2, 3, 4, 5, 6, 7, 8], [2, 2, 2, 1]);\n const res = tf.unstack(x);\n expect(res.length).toEqual(2);\n expect(res[0].rank).toEqual(3);\n expect(res[0].shape).toEqual([2, 2, 1]);\n expectArraysClose(await res[0].data(), [1, 2, 3, 4]);\n expect(res[1].rank).toEqual(3);\n expect(res[1].shape).toEqual([2, 2, 1]);\n expectArraysClose(await res[1].data(), [5, 6, 7, 8]);\n });\n\n it('unstack rank 4 tensor with axis=1', async () => {\n const x = tf.tensor4d([1, 2, 3, 4, 5, 6, 7, 8], [2, 2, 2, 1]);\n const res = tf.unstack(x, 1);\n expect(res.length).toEqual(2);\n expect(res[0].rank).toEqual(3);\n expect(res[0].shape).toEqual([2, 2, 1]);\n expectArraysClose(await res[0].data(), [1, 2, 5, 6]);\n expect(res[1].rank).toEqual(3);\n expect(res[1].shape).toEqual([2, 2, 1]);\n expectArraysClose(await res[1].data(), [3, 4, 7, 8]);\n });\n\n it('unstack rank 4 tensor with axis=2', async () => {\n const x = tf.tensor4d([1, 2, 3, 4, 5, 6, 7, 8], [2, 2, 2, 1]);\n const res = tf.unstack(x, 2);\n expect(res.length).toEqual(2);\n expect(res[0].rank).toEqual(3);\n expect(res[0].shape).toEqual([2, 2, 1]);\n expectArraysClose(await res[0].data(), [1, 3, 5, 7]);\n expect(res[1].rank).toEqual(3);\n expect(res[1].shape).toEqual([2, 2, 1]);\n expectArraysClose(await res[1].data(), [2, 4, 6, 8]);\n });\n\n it('unstack rank 4 tensor with axis=3', async () => {\n const x = tf.tensor4d([1, 2, 3, 4, 5, 6, 7, 8], [2, 2, 2, 1]);\n const res = tf.unstack(x, 3);\n expect(res.length).toEqual(1);\n expect(res[0].rank).toEqual(3);\n expect(res[0].shape).toEqual([2, 2, 2]);\n expectArraysClose(await res[0].data(), [1, 2, 3, 4, 5, 6, 7, 8]);\n });\n\n it('throws when passed a non-tensor', () => {\n expect(() => tf.unstack({} as tf.Tensor))\n .toThrowError(/Argument 'x' passed to 'unstack' must be a Tensor/);\n });\n\n it('throws when passed an invalid axis', () => {\n expect(() => {\n const x = tf.tensor2d([1, 2, 3, 4, 5, 6, 7, 8], [2, 4]);\n tf.unstack(x, 3);\n }).toThrowError('Axis = 3 is not in [-2, 2)');\n expect(() => {\n const x = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, 8], [2, 2, 2]);\n tf.unstack(x, 3);\n }).toThrowError('Axis = 3 is not in [-3, 3)');\n expect(() => {\n const x = tf.tensor4d([1, 2, 3, 4, 5, 6, 7, 8], [2, 2, 2, 1]);\n tf.unstack(x, 5);\n }).toThrowError('Axis = 5 is not in [-4, 4)');\n });\n\n it('accepts a tensor-like object', async () => {\n const x = [[1, 2, 3, 4], [5, 6, 7, 8]];\n const res = tf.unstack(x);\n expect(res.length).toEqual(2);\n expect(res[0].rank).toEqual(1);\n expect(res[0].shape).toEqual([4]);\n expectArraysClose(await res[0].data(), [1, 2, 3, 4]);\n expect(res[1].rank).toEqual(1);\n expect(res[1].shape).toEqual([4]);\n expectArraysClose(await res[1].data(), [5, 6, 7, 8]);\n });\n\n it('accepts string', async () => {\n const x =\n [['one', 'two', 'three', 'four'], ['five', 'six', 'seven', 'eight']];\n const res = tf.unstack(x);\n expect(res.length).toEqual(2);\n expect(res[0].rank).toEqual(1);\n expect(res[0].shape).toEqual([4]);\n expectArraysClose(await res[0].data(), ['one', 'two', 'three', 'four']);\n expect(res[1].rank).toEqual(1);\n expect(res[1].shape).toEqual([4]);\n expectArraysClose(await res[1].data(), ['five', 'six', 'seven', 'eight']);\n });\n\n it('grad of unstack axis=0', async () => {\n const x = tf.tensor([[1, 2, 3], [4, 5, 6]]);\n const dx1 = tf.grad(x => tf.unstack(x)[0])(x);\n expect(dx1.shape).toEqual([2, 3]);\n expect(dx1.dtype).toBe('float32');\n expectArraysClose(await dx1.data(), [1, 1, 1, 0, 0, 0]);\n\n const dx2 = tf.grad(x => tf.unstack(x)[1])(x);\n expect(dx2.shape).toEqual([2, 3]);\n expect(dx2.dtype).toBe('float32');\n expectArraysClose(await dx2.data(), [0, 0, 0, 1, 1, 1]);\n });\n\n it('gradient with clones', async () => {\n const x = tf.tensor([[1, 2, 3], [4, 5, 6]]);\n const dx1 = tf.grad(x => tf.unstack(x.clone())[0].clone())(x);\n expect(dx1.shape).toEqual([2, 3]);\n expect(dx1.dtype).toBe('float32');\n expectArraysClose(await dx1.data(), [1, 1, 1, 0, 0, 0]);\n\n const dx2 = tf.grad(x => tf.unstack(x.clone())[1].clone())(x);\n expect(dx2.shape).toEqual([2, 3]);\n expect(dx2.dtype).toBe('float32');\n expectArraysClose(await dx2.data(), [0, 0, 0, 1, 1, 1]);\n });\n\n it('grad of unstack axis=1', async () => {\n const x = tf.tensor([[1, 2, 3], [4, 5, 6]]);\n const axis = 1;\n const dx1 = tf.grad(x => tf.unstack(x, axis)[0])(x);\n expect(dx1.shape).toEqual([2, 3]);\n expect(dx1.dtype).toBe('float32');\n expectArraysClose(await dx1.data(), [1, 0, 0, 1, 0, 0]);\n\n const dx2 = tf.grad(x => tf.unstack(x, axis)[1])(x);\n expect(dx2.shape).toEqual([2, 3]);\n expect(dx2.dtype).toBe('float32');\n expectArraysClose(await dx2.data(), [0, 1, 0, 0, 1, 0]);\n\n const dx3 = tf.grad(x => tf.unstack(x, axis)[2])(x);\n expect(dx3.shape).toEqual([2, 3]);\n expect(dx3.dtype).toBe('float32');\n expectArraysClose(await dx3.data(), [0, 0, 1, 0, 0, 1]);\n });\n});\n"]} |