# Copyright (c) 2020 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 unittest
import numpy as np
from inference_pass_test import InferencePassTest
import paddle.fluid as fluid
import paddle.fluid.core as core
from paddle.fluid.core import AnalysisConfig
"""Test for fusion of conv and elementwise_add."""


class ConvElementwiseAddFusePassTest(InferencePassTest):
    def setUp(self):
        with fluid.program_guard(self.main_program, self.startup_program):
            data = fluid.data(
                name="data", shape=[-1, 3, 100, 100], dtype="float32")
            param_attr = fluid.ParamAttr(
                initializer=fluid.initializer.Xavier(uniform=False),
                learning_rate=0.001)
            conv_out = fluid.layers.conv2d(
                input=data, num_filters=3, filter_size=3, bias_attr=param_attr)

        self.feeds = {
            "data": np.random.random((1, 3, 100, 100)).astype("float32")
        }
        self.fetch_list = [conv_out]
        self.enable_mkldnn = False

    def test_check_output(self):
        if core.is_compiled_with_cuda():
            use_gpu = True
            self.check_output_with_option(use_gpu)


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