#  Copyright (c) 2021 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 numpy as np
import unittest
import sys
sys.path.append("..")
from op_test import OpTest
import paddle
import paddle.fluid as fluid
import paddle.fluid.core as core
from paddle.fluid import compiler, Program, program_guard

paddle.enable_static()
SEED = 2021


@unittest.skipIf(not paddle.is_compiled_with_npu(),
                 "core is not compiled with NPU")
class TestMemcpy_FillConstant(unittest.TestCase):
    def get_prog(self):
        paddle.enable_static()
        main_program = Program()
        with program_guard(main_program):
            cpu_var_name = "tensor@Cpu"
            npu_var_name = "tensor@Npu"
            cpu_var = main_program.global_block().create_var(
                name=cpu_var_name,
                shape=[10, 10],
                dtype='float32',
                persistable=False,
                stop_gradient=True)
            npu_var = main_program.global_block().create_var(
                name=npu_var_name,
                shape=[10, 10],
                dtype='float32',
                persistable=False,
                stop_gradient=True)
            main_program.global_block().append_op(
                type="fill_constant",
                outputs={"Out": npu_var_name},
                attrs={
                    "shape": [10, 10],
                    "dtype": npu_var.dtype,
                    "value": 1.0,
                    "place_type": 1
                })
            main_program.global_block().append_op(
                type="fill_constant",
                outputs={"Out": cpu_var_name},
                attrs={
                    "shape": [10, 10],
                    "dtype": cpu_var.dtype,
                    "value": 0.0,
                    "place_type": 2
                })
        return main_program, npu_var, cpu_var

    def test_npu_cpoy_to_cpu(self):
        main_program, npu_var, cpu_var = self.get_prog()
        main_program.global_block().append_op(
            type='memcpy',
            inputs={'X': npu_var},
            outputs={'Out': cpu_var},
            attrs={'dst_place_type': 0})
        place = fluid.NPUPlace(0)
        exe = fluid.Executor(place)
        npu_, cpu_ = exe.run(main_program,
                             feed={},
                             fetch_list=[npu_var.name, cpu_var.name])
        self.assertTrue(np.allclose(npu_, cpu_))
        self.assertTrue(np.allclose(cpu_, np.ones((10, 10))))

    def test_cpu_cpoy_npu(self):
        main_program, npu_var, cpu_var = self.get_prog()
        main_program.global_block().append_op(
            type='memcpy',
            inputs={'X': cpu_var},
            outputs={'Out': npu_var},
            attrs={'dst_place_type': 4})
        place = fluid.NPUPlace(0)
        exe = fluid.Executor(place)
        npu_, cpu_ = exe.run(main_program,
                             feed={},
                             fetch_list=[npu_var.name, cpu_var.name])
        self.assertTrue(np.allclose(npu_, cpu_))
        self.assertTrue(np.allclose(npu_, np.zeros((10, 10))))


if __name__ == '__main__':
    unittest.main()
