| # Licensed to the Apache Software Foundation (ASF) under one |
| # or more contributor license agreements. See the NOTICE file |
| # distributed with this work for additional information |
| # regarding copyright ownership. The ASF licenses this file |
| # to you 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. |
| # ============================================================================= |
| from __future__ import division |
| |
| import math |
| import unittest |
| import numpy as np |
| |
| |
| from singa import tensor |
| from singa.proto import core_pb2 |
| |
| |
| class TestTensorMethods(unittest.TestCase): |
| |
| def setUp(self): |
| self.shape = (2, 3) |
| self.t = tensor.Tensor(self.shape) |
| self.s = tensor.Tensor(self.shape) |
| self.t.set_value(0) |
| self.s.set_value(0) |
| |
| def test_tensor_fields(self): |
| t = self.t |
| shape = self.shape |
| self.assertTupleEqual(t.shape, shape) |
| self.assertEqual(t.shape[0], shape[0]) |
| self.assertEqual(t.shape[1], shape[1]) |
| self.assertEqual(tensor.product(shape), 2*3) |
| self.assertEqual(t.ndim(), 2) |
| self.assertEqual(t.size(), 2*3) |
| self.assertEqual(t.memsize(), 2*3*tensor.sizeof(core_pb2.kFloat32)) |
| self.assertFalse(t.is_transpose()) |
| |
| def test_unary_operators(self): |
| t = self.t |
| self.assertAlmostEqual(tensor.to_numpy(t)[0, 0], 0.0) |
| t += 1.23 |
| self.assertAlmostEqual(tensor.to_numpy(t)[0, 0], 1.23) |
| t -= 0.23 |
| self.assertAlmostEqual(tensor.to_numpy(t)[0, 0], 1.23-0.23) |
| t *= 2.5 |
| self.assertAlmostEqual(tensor.to_numpy(t)[0, 0], (1.23-0.23)*2.5) |
| t /= 2 |
| self.assertAlmostEqual(tensor.to_numpy(t)[0, 0], (1.23-0.23)*2.5/2) |
| |
| def test_binary_operators(self): |
| t = self.t |
| t += 3.2 |
| s = self.s |
| s += 2.1 |
| a = t + s |
| self.assertAlmostEqual(tensor.to_numpy(a)[0, 0], 3.2+2.1, 5) |
| a = t - s |
| self.assertAlmostEqual(tensor.to_numpy(a)[0, 0], 3.2-2.1, 5) |
| a = t * s |
| self.assertAlmostEqual(tensor.to_numpy(a)[0, 0], 3.2*2.1, 5) |
| ''' not implemented yet |
| a = t / s |
| self.assertAlmostEqual(tensor.to_numpy(a)[0,0], 3.2/2.1, 5) |
| ''' |
| |
| def test_comparison_operators(self): |
| t = self.t |
| t += 3.45 |
| a = t < 3.45 |
| self.assertEqual(tensor.to_numpy(a)[0, 0], 0) |
| a = t <= 3.45 |
| self.assertEqual(tensor.to_numpy(a)[0, 0], 1) |
| a = t > 3.45 |
| self.assertEqual(tensor.to_numpy(a)[0, 0], 0) |
| a = t >= 3.45 |
| self.assertEqual(tensor.to_numpy(a)[0, 0], 1) |
| a = tensor.lt(t, 3.45) |
| self.assertEqual(tensor.to_numpy(a)[0, 0], 0) |
| a = tensor.le(t, 3.45) |
| self.assertEqual(tensor.to_numpy(a)[0, 0], 1) |
| a = tensor.gt(t, 3.45) |
| self.assertEqual(tensor.to_numpy(a)[0, 0], 0) |
| a = tensor.ge(t, 3.45) |
| self.assertEqual(tensor.to_numpy(a)[0, 0], 1) |
| |
| def test_tensor_copy(self): |
| t = tensor.Tensor((2, 3)) |
| t += 1.23 |
| self.assertAlmostEqual(tensor.to_numpy(t)[0, 0], 1.23) |
| tc = t.copy() |
| tdc = t.deepcopy() |
| self.assertAlmostEqual(tensor.to_numpy(tc)[0, 0], 1.23) |
| self.assertAlmostEqual(tensor.to_numpy(tdc)[0, 0], 1.23) |
| t += 1.23 |
| self.assertAlmostEqual(tensor.to_numpy(t)[0, 0], 2.46) |
| self.assertAlmostEqual(tensor.to_numpy(tc)[0, 0], 2.46) |
| self.assertAlmostEqual(tensor.to_numpy(tdc)[0, 0], 1.23) |
| |
| def test_copy_data(self): |
| t = self.t |
| t += 1.23 |
| s = self.s |
| s += 5.43 |
| self.assertAlmostEqual(tensor.to_numpy(t)[0, 0], 1.23) |
| tensor.copy_data_to_from(t, s, 2) |
| self.assertAlmostEqual(tensor.to_numpy(t)[0, 0], 5.43, 5) |
| self.assertAlmostEqual(tensor.to_numpy(t)[0, 1], 5.43, 5) |
| self.assertAlmostEqual(tensor.to_numpy(t)[0, 2], 1.23) |
| |
| def test_global_method(self): |
| t = self.t |
| t += 12.34 |
| a = tensor.log(t) |
| self.assertAlmostEqual(tensor.to_numpy(a)[0, 0], math.log(12.34)) |
| |
| def test_random(self): |
| x = tensor.Tensor((1000,)) |
| x.gaussian(1, 0.01) |
| self.assertAlmostEqual(tensor.average(x), 1, 3) |
| |
| def test_radd(self): |
| x = tensor.Tensor((3,)) |
| x.set_value(1) |
| y = 1 + x |
| self.assertEqual(tensor.average(y), 2.) |
| |
| def test_rsub(self): |
| x = tensor.Tensor((3,)) |
| x.set_value(1) |
| y = 1 - x |
| self.assertEqual(tensor.average(y), 0.) |
| |
| def test_rmul(self): |
| x = tensor.Tensor((3,)) |
| x.set_value(1) |
| y = 2 * x |
| self.assertEqual(tensor.average(y), 2.) |
| |
| def test_rdiv(self): |
| x = tensor.Tensor((3,)) |
| x.set_value(1) |
| y = 2 / x |
| self.assertEqual(tensor.average(y), 2.) |
| |
| def test_numpy_convert(self): |
| a = np.asarray([[1, 0, 0], [0, 1, 0]], dtype=np.int) |
| t = tensor.from_numpy(a) |
| b = tensor.to_numpy(t) |
| self.assertEqual(np.sum(a-b), 0) |
| |
| a = np.asarray([[1, 0, 0], [0, 1, 0]], dtype=np.float32) |
| t = tensor.from_numpy(a) |
| b = tensor.to_numpy(t) |
| self.assertEqual(np.sum(a-b), 0.) |
| |
| def test_transpose(self): |
| a = np.array([1.1,1.1,1.1,1.1,1.4,1.3,1.1,1.6,1.1,1.1,1.1,1.2]) |
| a = np.reshape(a,(2,3,2)) |
| ta = tensor.from_numpy(a) |
| |
| A1 = np.transpose(a) |
| tA1 = tensor.transpose(ta) |
| TA1 = tensor.to_numpy(tA1) |
| A2 = np.transpose(a,[0,2,1]) |
| tA2 = tensor.transpose(ta,[0,2,1]) |
| TA2 = tensor.to_numpy(tA2) |
| |
| self.assertAlmostEqual(np.sum(TA1 - A1), 0.,places=3) |
| self.assertAlmostEqual(np.sum(TA2 - A2), 0.,places=3) |
| |
| def test_einsum(self): |
| |
| a = np.array([1.1,1.1,1.1,1.1,1.4,1.3,1.1,1.6,1.1,1.1,1.1,1.2]) |
| a = np.reshape(a,(2,3,2)) |
| ta = tensor.from_numpy(a) |
| |
| res1 = np.einsum('kij,kij->kij', a, a) |
| tres1 = tensor.einsum('kij,kij->kij', ta, ta) |
| Tres1 = tensor.to_numpy(tres1) |
| res2 = np.einsum('kij,kih->kjh', a, a) |
| tres2 = tensor.einsum('kij,kih->kjh', ta, ta) |
| Tres2 = tensor.to_numpy(tres2) |
| |
| self.assertAlmostEqual(np.sum(Tres1 - res1), 0.,places=3) |
| self.assertAlmostEqual(np.sum(Tres2 - res2), 0.,places=3) |
| |
| def test_repeat(self): |
| |
| a = np.array([1.1,1.1,1.1,1.1,1.4,1.3,1.1,1.6,1.1,1.1,1.1,1.2]) |
| a = np.reshape(a,(2,3,2)) |
| ta = tensor.from_numpy(a) |
| |
| ta_repeat1 = tensor.repeat(ta,2,axis = None) |
| a_repeat1 = np.repeat(a,2,axis = None) |
| Ta_repeat1 = tensor.to_numpy(ta_repeat1) |
| ta_repeat2 = tensor.repeat(ta, 4, axis = 1) |
| a_repeat2 = np.repeat(a, 4, axis = 1) |
| Ta_repeat2 = tensor.to_numpy(ta_repeat2) |
| |
| self.assertAlmostEqual(np.sum(Ta_repeat1 - a_repeat1), 0., places=3) |
| self.assertAlmostEqual(np.sum(Ta_repeat2 - a_repeat2), 0., places=3) |
| |
| def test_sum(self): |
| a = np.array([1.1,1.1,1.1,1.1,1.4,1.3,1.1,1.6,1.1,1.1,1.1,1.2]) |
| a = np.reshape(a,(2,3,2)) |
| ta = tensor.from_numpy(a) |
| |
| a_sum0 = np.sum(a) |
| ta_sum0 = tensor.sum(ta) |
| Ta_sum0 = tensor.to_numpy(ta_sum0) |
| a_sum1 = np.sum(a, axis = 1) |
| ta_sum1 = tensor.sum(ta, axis = 1) |
| Ta_sum1 = tensor.to_numpy(ta_sum1) |
| a_sum2 = np.sum(a, axis = 2) |
| ta_sum2 = tensor.sum(ta, axis = 2) |
| Ta_sum2 = tensor.to_numpy(ta_sum2) |
| |
| self.assertAlmostEqual(np.sum(a_sum0 - Ta_sum0), 0., places=3) |
| self.assertAlmostEqual(np.sum(a_sum1 - Ta_sum1), 0., places=3) |
| self.assertAlmostEqual(np.sum(a_sum2 - Ta_sum2), 0., places=3) |
| |
| def test_tensordot(self): |
| a = np.array([1.1,1.1,1.1,1.1,1.4,1.3,1.1,1.6,1.1,1.1,1.1,1.2]) |
| a = np.reshape(a,(2,3,2)) |
| |
| ta = tensor.from_numpy(a) |
| |
| res1 = np.tensordot(a, a, axes = 1) |
| tres1 = tensor.tensordot(ta, ta, axes = 1) |
| Tres1 = tensor.to_numpy(tres1) |
| res2 = np.tensordot(a, a, axes = ([0,1],[2,1])) |
| tres2 = tensor.tensordot(ta, ta, axes = ([0,1],[2,1])) |
| Tres2 = tensor.to_numpy(tres2) |
| |
| self.assertAlmostEqual(np.sum(Tres1 - res1), 0., places=3) |
| self.assertAlmostEqual(np.sum(Tres2 - res2), 0., places=3) |
| |
| |
| if __name__ == '__main__': |
| unittest.main() |
