# Copyright (c) 2019 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. import os import unittest import numpy as np from op_test import OpTest from test_attribute_var import UnittestBase import paddle import paddle.fluid as fluid import paddle.fluid.framework as framework from paddle.fluid.framework import Program, program_guard class TestEyeOp(OpTest): def setUp(self): ''' Test eye op with specified shape ''' self.python_api = paddle.eye self.op_type = "eye" self.inputs = {} self.attrs = { 'num_rows': 219, 'num_columns': 319, 'dtype': framework.convert_np_dtype_to_dtype_(np.int32), } self.outputs = {'Out': np.eye(219, 319, dtype=np.int32)} def test_check_output(self): self.check_output(check_eager=True) class TestEyeOp1(OpTest): def setUp(self): ''' Test eye op with default parameters ''' self.python_api = paddle.eye self.op_type = "eye" self.inputs = {} self.attrs = {'num_rows': 50} self.outputs = {'Out': np.eye(50, dtype=float)} def test_check_output(self): self.check_output(check_eager=True) class TestEyeOp2(OpTest): def setUp(self): ''' Test eye op with specified shape ''' self.python_api = paddle.eye self.op_type = "eye" self.inputs = {} self.attrs = {'num_rows': 99, 'num_columns': 1} self.outputs = {'Out': np.eye(99, 1, dtype=float)} def test_check_output(self): self.check_output(check_eager=True) class API_TestTensorEye(unittest.TestCase): def test_out(self): with paddle.static.program_guard(paddle.static.Program()): data = paddle.eye(10) place = fluid.CPUPlace() exe = paddle.static.Executor(place) (result,) = exe.run(fetch_list=[data]) expected_result = np.eye(10, dtype="float32") self.assertEqual((result == expected_result).all(), True) with paddle.static.program_guard(paddle.static.Program()): data = paddle.eye(10, num_columns=7, dtype="float64") place = paddle.CPUPlace() exe = paddle.static.Executor(place) (result,) = exe.run(fetch_list=[data]) expected_result = np.eye(10, 7, dtype="float64") self.assertEqual((result == expected_result).all(), True) with paddle.static.program_guard(paddle.static.Program()): data = paddle.eye(10, dtype="int64") place = paddle.CPUPlace() exe = paddle.static.Executor(place) (result,) = exe.run(fetch_list=[data]) expected_result = np.eye(10, dtype="int64") self.assertEqual((result == expected_result).all(), True) paddle.disable_static() out = paddle.eye(10, dtype="int64") expected_result = np.eye(10, dtype="int64") paddle.enable_static() self.assertEqual((out.numpy() == expected_result).all(), True) def test_errors(self): with paddle.static.program_guard(paddle.static.Program()): def test_num_rows_type_check(): paddle.eye(-1, dtype="int64") self.assertRaises(TypeError, test_num_rows_type_check) def test_num_columns_type_check(): paddle.eye(10, num_columns=5.2, dtype="int64") self.assertRaises(TypeError, test_num_columns_type_check) def test_num_columns_type_check1(): paddle.eye(10, num_columns=10, dtype="int8") self.assertRaises(TypeError, test_num_columns_type_check1) class TestEyeRowsCol(UnittestBase): def init_info(self): self.shapes = [[2, 3, 4]] self.save_path = os.path.join(self.temp_dir.name, self.path_prefix()) def test_static(self): main_prog = Program() starup_prog = Program() with program_guard(main_prog, starup_prog): fc = paddle.nn.Linear(4, 10) x = paddle.randn([2, 3, 4]) x.stop_gradient = False feat = fc(x) # [2,3,10] tmp = self.call_func(feat) out = feat + tmp sgd = paddle.optimizer.SGD() sgd.minimize(paddle.mean(out)) self.assertTrue(self.var_prefix() in str(main_prog)) exe = paddle.static.Executor() exe.run(starup_prog) res = exe.run(fetch_list=[tmp, out]) gt = np.eye(3, 10) np.testing.assert_allclose(res[0], gt) paddle.static.save_inference_model( self.save_path, [x], [tmp, out], exe ) # Test for Inference Predictor infer_outs = self.infer_prog() np.testing.assert_allclose(infer_outs[0], gt) def path_prefix(self): return 'eye_rows_cols' def var_prefix(self): return "Var[" def call_func(self, x): rows = paddle.assign(3) cols = paddle.assign(10) out = paddle.eye(rows, cols) return out def test_error(self): with self.assertRaises(TypeError): paddle.eye(-1) if __name__ == "__main__": paddle.enable_static() unittest.main()