# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve. # #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 paddle.v2.fluid.core as core import unittest import numpy class TestTensor(unittest.TestCase): def test_int_tensor(self): scope = core.Scope() var = scope.var("test_tensor") place = core.CPUPlace() tensor = var.get_tensor() tensor.set_dims([1000, 784]) tensor.alloc_int(place) tensor_array = numpy.array(tensor) self.assertEqual((1000, 784), tensor_array.shape) tensor_array[3, 9] = 1 tensor_array[19, 11] = 2 tensor.set(tensor_array, place) tensor_array_2 = numpy.array(tensor) self.assertEqual(1, tensor_array_2[3, 9]) self.assertEqual(2, tensor_array_2[19, 11]) def test_float_tensor(self): scope = core.Scope() var = scope.var("test_tensor") place = core.CPUPlace() tensor = var.get_tensor() tensor.set_dims([1000, 784]) tensor.alloc_float(place) tensor_array = numpy.array(tensor) self.assertEqual((1000, 784), tensor_array.shape) tensor_array[3, 9] = 1.0 tensor_array[19, 11] = 2.0 tensor.set(tensor_array, place) tensor_array_2 = numpy.array(tensor) self.assertAlmostEqual(1.0, tensor_array_2[3, 9]) self.assertAlmostEqual(2.0, tensor_array_2[19, 11]) def test_int_lod_tensor(self): place = core.CPUPlace() scope = core.Scope() var_lod = scope.var("test_lod_tensor") lod_tensor = var_lod.get_tensor() lod_tensor.set_dims([4, 4, 6]) lod_tensor.alloc_int(place) array = numpy.array(lod_tensor) array[0, 0, 0] = 3 array[3, 3, 5] = 10 lod_tensor.set(array, place) lod_tensor.set_lod([[0, 2, 4]]) lod_v = numpy.array(lod_tensor) self.assertTrue(numpy.alltrue(array == lod_v)) lod = lod_tensor.lod() self.assertEqual(0, lod[0][0]) self.assertEqual(2, lod[0][1]) self.assertEqual(4, lod[0][2]) def test_float_lod_tensor(self): place = core.CPUPlace() scope = core.Scope() var_lod = scope.var("test_lod_tensor") lod_tensor = var_lod.get_tensor() lod_tensor.set_dims([5, 2, 3, 4]) lod_tensor.alloc_float(place) tensor_array = numpy.array(lod_tensor) self.assertEqual((5, 2, 3, 4), tensor_array.shape) tensor_array[0, 0, 0, 0] = 1.0 tensor_array[0, 0, 0, 1] = 2.0 lod_tensor.set(tensor_array, place) lod_v = numpy.array(lod_tensor) self.assertAlmostEqual(1.0, lod_v[0, 0, 0, 0]) self.assertAlmostEqual(2.0, lod_v[0, 0, 0, 1]) self.assertEqual(len(lod_tensor.lod()), 0) lod_py = [[0, 2, 5], [0, 2, 4, 5]] lod_tensor.set_lod(lod_py) lod = lod_tensor.lod() self.assertListEqual(lod_py, lod) def test_lod_tensor_init(self): scope = core.Scope() place = core.CPUPlace() lod_py = [[0, 2, 5], [0, 2, 4, 5]] lod_tensor = core.LoDTensor(lod_py) lod_tensor.set_dims([5, 2, 3, 4]) lod_tensor.alloc_float(place) tensor_array = numpy.array(lod_tensor) tensor_array[0, 0, 0, 0] = 1.0 tensor_array[0, 0, 0, 1] = 2.0 lod_tensor.set(tensor_array, place) lod_v = numpy.array(lod_tensor) self.assertAlmostEqual(1.0, lod_v[0, 0, 0, 0]) self.assertAlmostEqual(2.0, lod_v[0, 0, 0, 1]) self.assertListEqual(lod_py, lod_tensor.lod()) if __name__ == '__main__': unittest.main()