# 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.

import unittest

import numpy as np
from op_test import OpTest

import paddle
import paddle.fluid as fluid
import paddle.fluid.core as core
from paddle.fluid.framework import Program, program_guard
from paddle.fluid.layer_helper import LayerHelper


# default kNCHW
class TestTransferLayoutOpkNCHWTokNHWC(OpTest):
    def setUp(self):
        ipt = np.random.random(size=[2, 3, 10, 10])
        self.inputs = {'X': ipt.astype('float32')}
        self.outputs = {'Out': ipt.transpose([0, 2, 3, 1])}
        self.attrs = {'src_layout': 0, 'dst_layout': 1}  # kNHWC
        self.op_type = 'transfer_layout'

    def test_check_output(self):
        self.check_output()


def softmax_with_data_format(x, data_format, axis=-1, dtype=None, name=None):
    helper = LayerHelper("softmax", **locals())
    outs_cast = x

    outs_softmax = helper.create_variable_for_type_inference(outs_cast.dtype)
    helper.append_op(
        type='softmax',
        inputs={'X': outs_cast},
        outputs={'Out': outs_softmax},
        attrs={'axis': axis, 'use_cudnn': True, 'data_format': data_format},
    )

    return outs_softmax


class TestTransferLayoutOpGpu(unittest.TestCase):
    def test_layout_transfer(self):
        if not core.is_compiled_with_cuda():
            return

        paddle.enable_static()

        main_program = Program()
        startup_program = Program()
        n, c, h, w = 2, 3, 4, 5
        with program_guard(main_program, startup_program):
            x = paddle.static.data(
                shape=[n, c, h, w], dtype='float32', name='x'
            )
            y = softmax_with_data_format(x, data_format='NCHW')
            z = softmax_with_data_format(y, data_format='NHWC')

        place = (
            fluid.CUDAPlace(0)
            if core.is_compiled_with_cuda()
            else fluid.CPUPlace()
        )
        exe = fluid.Executor(place)
        exe.run(startup_program)
        ret = exe.run(
            main_program,
            feed={'x': np.full((n, c, h, w), 1, np.float32)},
            fetch_list=[z.name],
        )
        assert len(ret) == 1
        assert ret[0].shape == (n, h, w, c)


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