# 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. import unittest import numpy as np import op_test from op_test import get_device_place import paddle from paddle import base from paddle.base import framework def wrap_assign_value_wrapper(dtype=paddle.float32): def assign_value_wrapper(shape=[], dtype=dtype, values=0.0): if paddle.framework.in_dynamic_mode(): tensor = paddle.Tensor() else: tensor = paddle.zeros(list(shape), dtype) return paddle._C_ops.assign_value_( tensor, shape, dtype, values, framework._current_expected_place() ) return assign_value_wrapper class TestAssignValueOp(op_test.OpTest): def setUp(self): self.op_type = "assign_value" self.inputs = {} self.attrs = {} self.init_data() self.attrs["shape"] = self.value.shape self.attrs["dtype"] = framework.convert_nptype_to_datatype_or_vartype( self.value.dtype ) self.python_api = wrap_assign_value_wrapper(self.attrs["dtype"]) self.outputs = {"Out": self.value} def init_data(self): self.value = np.random.random(size=(2, 5)).astype(np.float32) self.attrs["values"] = [float(v) for v in self.value.flat] def test_forward(self): self.check_output(check_cinn=True, check_pir=True) class TestAssignValueOp2(TestAssignValueOp): def init_data(self): self.value = np.random.random(size=(2, 5)).astype(np.int32) self.attrs["values"] = [int(v) for v in self.value.flat] class TestAssignValueOp3(TestAssignValueOp): def init_data(self): self.value = np.random.random(size=(2, 5)).astype(np.int64) self.attrs["values"] = [int(v) for v in self.value.flat] class TestAssignValueOp4(TestAssignValueOp): def init_data(self): self.value = np.random.choice(a=[False, True], size=(2, 5)).astype( np.bool_ ) self.attrs["values"] = [int(v) for v in self.value.flat] class TestAssignValueOp5(TestAssignValueOp): def init_data(self): self.value = np.random.random(size=(2, 5)).astype(np.float64) self.attrs["values"] = [float(v) for v in self.value.flat] class TestAssignValueOp6(TestAssignValueOp): def init_data(self): self.value = ( np.random.random(size=(2, 5)) + 1j * np.random.random(size=(2, 5)) ).astype(np.complex64) self.attrs["values"] = list(self.value.flat) class TestAssignValueOp7(TestAssignValueOp): def init_data(self): self.value = ( np.random.random(size=(2, 5)) + 1j * np.random.random(size=(2, 5)) ).astype(np.complex128) self.attrs["values"] = list(self.value.flat) class TestAssignApi(unittest.TestCase): def setUp(self): with op_test.paddle_static_guard(): self.init_dtype() self.value = (-100 + 200 * np.random.random(size=(2, 5))).astype( self.dtype ) self.place = get_device_place() def init_dtype(self): self.dtype = "float32" def test_assign(self): with op_test.paddle_static_guard(): main_program = base.Program() with base.program_guard(main_program): x = paddle.assign(self.value) exe = base.Executor(self.place) [fetched_x] = exe.run(main_program, feed={}, fetch_list=[x]) np.testing.assert_array_equal(fetched_x, self.value) self.assertEqual(fetched_x.dtype, self.value.dtype) def test_pir_assign(self): with paddle.pir_utils.IrGuard(): main_program = paddle.pir.Program() with paddle.static.program_guard(main_program): x = paddle.zeros(shape=[1], dtype=self.dtype) paddle.assign(self.value, output=x) exe = base.Executor(self.place) [fetched_x] = exe.run(main_program, feed={}, fetch_list=[x]) np.testing.assert_array_equal(fetched_x, self.value) self.assertEqual(fetched_x.dtype, self.value.dtype) class TestAssignApi2(TestAssignApi): def init_dtype(self): self.dtype = "int32" class TestAssignApi3(TestAssignApi): def init_dtype(self): self.dtype = "int64" class TestAssignApi4(TestAssignApi): def setUp(self): with op_test.paddle_static_guard(): self.init_dtype() self.value = np.random.choice(a=[False, True], size=(2, 5)).astype( np.bool_ ) self.place = get_device_place() def init_dtype(self): self.dtype = "bool" class TestAssignApi5(TestAssignApi): def init_dtype(self): self.dtype = "float64" class TestAssignApi6(TestAssignApi): def setUp(self): with op_test.paddle_static_guard(): self.init_dtype() self.value = ( np.random.random(size=(2, 5)) + 1j * (np.random.random(size=(2, 5))) ).astype(np.complex64) self.place = get_device_place() def init_dtype(self): self.dtype = "complex64" class TestAssignApi7(TestAssignApi): def setUp(self): with op_test.paddle_static_guard(): self.init_dtype() self.value = ( np.random.random(size=(2, 5)) + 1j * (np.random.random(size=(2, 5))) ).astype(np.complex128) self.place = get_device_place() def init_dtype(self): self.dtype = "complex128" if __name__ == '__main__': unittest.main()