# Copyright (c) 2023 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 hypothesis.strategies as st
from auto_scan_test import PassAutoScanTest
from program_config import OpConfig, ProgramConfig, TensorConfig


class TestDeleteDropoutOpPass(PassAutoScanTest):
    def sample_predictor_configs(self, program_config):
        config = self.create_inference_config(use_xpu=True)
        yield config, ["elementwise_add", "relu", "relu6"], (1e-5, 1e-5)

    def sample_program_config(self, draw):
        add_op = OpConfig(
            "elementwise_add",
            inputs={"X": ["add_x"], "Y": ["add_y"]},
            outputs={"Out": ["add_out"]},
            axis=-1,
        )
        dropout_op = OpConfig(
            "dropout",
            inputs={"X": ["add_out"]},
            outputs={"Out": ["dropout_out"], "Mask": ["dropout_mask"]},
            dropout_implementation="upscale_in_train",
            dropout_prob=0.1,
            fix_seed=False,
            is_test=True,
            seed=0,
        )
        relu_op = OpConfig(
            "relu",
            inputs={"X": ["dropout_out"]},
            outputs={"Out": ["relu_out"]},
        )
        relu6_op = OpConfig(
            "relu6",
            inputs={"X": ["dropout_out"]},
            outputs={"Out": ["relu6_out"]},
        )
        ops = [add_op, dropout_op, relu_op, relu6_op]

        add_x_shape = draw(
            st.lists(
                st.integers(min_value=1, max_value=4), min_size=2, max_size=4
            )
        )
        program_config = ProgramConfig(
            ops=ops,
            weights={},
            inputs={
                "add_x": TensorConfig(shape=add_x_shape),
                "add_y": TensorConfig(shape=add_x_shape),
            },
            outputs=["relu_out", "relu6_out"],
        )
        return program_config

    def test(self):
        self.run_and_statis(
            quant=False,
            max_examples=1,
            min_success_num=1,
            passes=["delete_dropout_op_pass"],
        )


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