# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. # # 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. from __future__ import print_function import unittest import numpy as np from op_test import OpTest import paddle.fluid as fluid import paddle.tensor as tensor from paddle.fluid import compiler, Program, program_guard, core class TestUnbind(unittest.TestCase): def test_unbind(self): x_1 = fluid.data(shape=[2, 3], dtype='float32', name='x_1') [out_0, out_1] = tensor.unbind(input=x_1, axis=0) input_1 = np.random.random([2, 3]).astype("float32") axis = fluid.data(shape=[1], dtype='int32', name='axis') exe = fluid.Executor(place=fluid.CPUPlace()) [res_1, res_2] = exe.run(fluid.default_main_program(), feed={"x_1": input_1, "axis": 0}, fetch_list=[out_0, out_1]) assert np.array_equal(res_1, input_1[0, 0:100]) assert np.array_equal(res_2, input_1[1, 0:100]) class TestLayersUnbind(unittest.TestCase): def test_layers_unbind(self): x_1 = fluid.data(shape=[2, 3], dtype='float32', name='x_1') [out_0, out_1] = fluid.layers.unbind(input=x_1, axis=0) input_1 = np.random.random([2, 3]).astype("float32") axis = fluid.data(shape=[1], dtype='int32', name='axis') exe = fluid.Executor(place=fluid.CPUPlace()) [res_1, res_2] = exe.run(fluid.default_main_program(), feed={"x_1": input_1, "axis": 0}, fetch_list=[out_0, out_1]) assert np.array_equal(res_1, input_1[0, 0:100]) assert np.array_equal(res_2, input_1[1, 0:100]) class TestUnbindOp(OpTest): def initParameters(self): pass def outReshape(self): pass def setAxis(self): pass def setUp(self): self._set_op_type() self.dtype = self.get_dtype() self.axis = 0 self.num = 3 self.initParameters() x = np.arange(12).reshape(3, 2, 2).astype(self.dtype) self.out = np.split(x, self.num, self.axis) self.outReshape() self.inputs = {'X': x} self.attrs = {'axis': self.axis} self.setAxis() self.outputs = {'Out': [('out%d' % i, self.out[i]) \ for i in range(len(self.out))]} def get_dtype(self): return "float64" def _set_op_type(self): self.op_type = "unbind" def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(['X'], ['out0', 'out1', 'out2']) class TestUnbindOp1(TestUnbindOp): def initParameters(self): self.axis = 1 self.num = 2 def test_check_grad(self): self.check_grad(['X'], ['out0', 'out1']) def outReshape(self): self.out[0] = self.out[0].reshape((3, 2)) self.out[1] = self.out[1].reshape((3, 2)) class TestUnbindOp2(TestUnbindOp): def initParameters(self): self.axis = 2 self.num = 2 def test_check_grad(self): self.check_grad(['X'], ['out0', 'out1']) def outReshape(self): self.out[0] = self.out[0].reshape((3, 2)) self.out[1] = self.out[1].reshape((3, 2)) class TestUnbindOp3(TestUnbindOp): def initParameters(self): self.axis = 2 self.num = 2 def setAxis(self): self.attrs = {'axis': -1} def test_check_grad(self): self.check_grad(['X'], ['out0', 'out1']) def outReshape(self): self.out[0] = self.out[0].reshape((3, 2)) self.out[1] = self.out[1].reshape((3, 2)) class TestUnbindOp4(TestUnbindOp): def initParameters(self): self.axis = 1 self.num = 2 def setAxis(self): self.attrs = {'axis': -2} def test_check_grad(self): self.check_grad(['X'], ['out0', 'out1']) def outReshape(self): self.out[0] = self.out[0].reshape((3, 2)) self.out[1] = self.out[1].reshape((3, 2)) class TestUnbindAxisError(unittest.TestCase): def test_errors(self): with program_guard(Program(), Program()): x = fluid.data(shape=[2, 3], dtype='float32', name='x') def test_table_Variable(): tensor.unbind(input=x, axis=2.0) self.assertRaises(TypeError, test_table_Variable) if __name__ == '__main__': unittest.main()