# 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 import paddle.fluid as fluid def gather_numpy(x, index, axis): x_transpose = np.swapaxes(x, 0, axis) tmp_gather = x_transpose[index, ...] gather = np.swapaxes(tmp_gather, 0, axis) return gather class TestGatherOp(OpTest): def setUp(self): self.op_type = "gather" self.config() xnp = np.random.random(self.x_shape).astype(self.x_type) self.inputs = { 'X': xnp, 'Index': np.array(self.index).astype(self.index_type) } self.outputs = {'Out': self.inputs["X"][self.inputs["Index"]]} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(['X'], 'Out') def config(self): """ For multi-dimension input """ self.x_shape = (10, 20) self.x_type = "float64" self.index = [1, 3, 5] self.index_type = "int32" class TestCase1(TestGatherOp): def config(self): """ For one dimension input """ self.x_shape = (100) self.x_type = "float64" self.index = [1, 3, 5] self.index_type = "int32" class TestCase2(TestGatherOp): def config(self): """ For int64_t index type """ self.x_shape = (100) self.x_type = "float64" self.index = [1, 3, 5] self.index_type = "int64" class TestCase3(TestGatherOp): def config(self): """ For other input type """ self.x_shape = (10, 20) self.x_type = "float64" self.index = [1, 3, 5] self.index_type = "int64" class TestCase4(TestGatherOp): def config(self): self.x_shape = (10, 20) self.attrs = {'overwrite': False} self.x_type = "double" self.index = [1, 1] self.index_type = "int32" class TestCase5(TestGatherOp): def config(self): self.x_shape = (10, 20) self.attrs = {'overwrite': False} self.x_type = "float64" self.index = [1, 1, 3] self.index_type = "int32" class TestCase6(TestGatherOp): def config(self): self.x_shape = (10, 20) self.attrs = {'overwrite': True} self.x_type = "float64" self.index = [1, 3] self.index_type = "int32" class TestGatherOp1(OpTest): def setUp(self): self.op_type = "gather" self.config() xnp = np.random.random(self.x_shape).astype(self.x_type) axis_np = np.array(self.axis).astype(self.index_type) index_np = np.array(self.index).astype(self.index_type) out = gather_numpy(xnp, index_np, axis_np[0]) self.inputs = {'X': xnp, 'Index': index_np, 'Axis': axis_np} self.outputs = {'Out': out} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(['X'], 'Out') def config(self): """ For multi-dimension input """ self.x_shape = (3, 88, 3) self.x_type = "float64" self.index = [1, 3, 5] self.index_type = "int32" self.axis = [1] self.axis_type = "int32" class TestGatherOp2(TestGatherOp1): def config(self): """ For multi-dimension input """ self.x_shape = (10, 88, 10) self.x_type = "float64" self.index = [1, 3, 5] self.index_type = "int64" self.axis = [0] self.axis_type = "int32" class TestGatherOp3(TestGatherOp1): def config(self): """ For multi-dimension input """ self.x_shape = (10, 88, 10) self.x_type = "float64" self.index = [1, 3, 5] self.index_type = "int64" self.axis = [2] self.axis_type = "int32" class TestGatherOp4(TestGatherOp1): def config(self): """ For multi-dimension input """ self.x_shape = (3, 100, 10) self.x_type = "float64" self.index = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1] self.index_type = "int64" self.axis = [0] self.axis_type = "int32" class API_TestGather(unittest.TestCase): def test_out1(self): with fluid.program_guard(fluid.Program(), fluid.Program()): data1 = fluid.layers.data('data1', shape=[-1, 2], dtype='float64') index = fluid.layers.data('index', shape=[-1, 1], dtype='int32') out = paddle.fluid.layers.gather(data1, index) place = fluid.CPUPlace() exe = fluid.Executor(place) input = np.array([[1, 2], [3, 4], [5, 6]]) index_1 = np.array([1, 2]) result, = exe.run(feed={"data1": input, "index": index_1}, fetch_list=[out]) expected_output = np.array([[3, 4], [5, 6]]) self.assertTrue(np.allclose(result, expected_output)) def test_out2(self): with paddle.static.program_guard(paddle.static.Program(), paddle.static.Program()): x = paddle.data('x', shape=[-1, 2], dtype='float64') index = paddle.data('index', shape=[-1, 1], dtype='int32') axis = paddle.data('axis', shape=[1], dtype='int32') out = paddle.gather(x, index, axis) place = paddle.CPUPlace() exe = paddle.static.Executor(place) x_np = np.array([[1, 2], [3, 4], [5, 6]]).astype('float64') index_np = np.array([1, 1]).astype('int32') axis_np = np.array([1]).astype('int32') result, = exe.run( feed={"x": x_np, "index": index_np, 'axis': axis_np}, fetch_list=[out]) expected_output = gather_numpy(x_np, index_np, axis_np) self.assertTrue(np.allclose(result, expected_output)) class API_TestDygraphGather(unittest.TestCase): def test_out1(self): paddle.disable_static() input_1 = np.array([[1, 2], [3, 4], [5, 6]]) index_1 = np.array([1, 2]) input = paddle.to_tensor(input_1) index = paddle.to_tensor(index_1) output = paddle.fluid.layers.gather(input, index) output_np = output.numpy() expected_output = np.array([[3, 4], [5, 6]]) self.assertTrue(np.allclose(output_np, expected_output)) paddle.enable_static() def test_out12(self): paddle.disable_static() input_1 = np.array([[1, 2], [3, 4], [5, 6]]) index_1 = np.array([1, 2]) x = paddle.to_tensor(input_1) index = paddle.to_tensor(index_1) output = paddle.gather(x, index, axis=0) output_np = output.numpy() expected_output = gather_numpy(input_1, index_1, axis=0) self.assertTrue(np.allclose(output_np, expected_output)) paddle.enable_static() class TestGathertError(unittest.TestCase): def test_error1(self): with paddle.static.program_guard(paddle.static.Program(), paddle.static.Program()): shape = [8, 9, 6] x = paddle.data(shape=shape, dtype='int8', name='x') axis = paddle.data(shape=[1], dtype='float32', name='axis') index = paddle.data(shape=shape, dtype='int32', name='index') index_float = paddle.data( shape=shape, dtype='float32', name='index_float') def test_x_type(): paddle.gather(x, index) self.assertRaises(TypeError, test_x_type) def test_index_type(): paddle.gather(x, index_float) self.assertRaises(TypeError, test_index_type) def test_axis_dtype(): paddle.gather(x, index, axis=1.11) self.assertRaises(TypeError, test_axis_dtype) def test_axis_dtype(): paddle.gather(x, index, axis=axis) self.assertRaises(TypeError, test_axis_dtype) def test_error2(self): with fluid.program_guard(fluid.Program(), fluid.Program()): shape = [8, 9, 6] x = fluid.data(shape=shape, dtype='int8', name='x') index = fluid.data(shape=shape, dtype='int32', name='mask') index_float = fluid.data( shape=shape, dtype='float32', name='index_float') def test_x_type(): paddle.fluid.layers.gather(x, index) self.assertRaises(TypeError, test_x_type) def test_index_type(): paddle.fluid.layers.gather(x, index_float) self.assertRaises(TypeError, test_index_type) if __name__ == "__main__": unittest.main()