#   Copyright (c) 2019 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 paddle
import paddle.fluid as fluid
import paddle.fluid.core as core
from paddle.fluid import Program, program_guard
import paddle.compat as cpt
import unittest
import numpy as np
from op_test import OpTest


class TestFillAnyLikeOp(OpTest):
    def setUp(self):
        self.op_type = "fill_any_like"
        self.dtype = np.int32
        self.value = 0.0
        self.init()
        self.inputs = {'X': np.random.random((219, 232)).astype(self.dtype)}
        self.attrs = {'value': self.value}
        self.outputs = {'Out': self.value * np.ones_like(self.inputs["X"])}

    def init(self):
        pass

    def test_check_output(self):
        self.check_output()


class TestFillAnyLikeOpFloat32(TestFillAnyLikeOp):
    def init(self):
        self.dtype = np.float32
        self.value = 0.0


class TestFillAnyLikeOpValue1(TestFillAnyLikeOp):
    def init(self):
        self.value = 1.0


class TestFillAnyLikeOpValue2(TestFillAnyLikeOp):
    def init(self):
        self.value = 1e-10


class TestFillAnyLikeOpValue3(TestFillAnyLikeOp):
    def init(self):
        self.value = 1e-100


class TestFillAnyLikeOpType(TestFillAnyLikeOp):
    def setUp(self):
        self.op_type = "fill_any_like"
        self.dtype = np.int32
        self.value = 0.0
        self.init()
        self.inputs = {'X': np.random.random((219, 232)).astype(self.dtype)}
        self.attrs = {
            'value': self.value,
            'dtype': int(core.VarDesc.VarType.FP32)
        }
        self.outputs = {
            'Out':
            self.value * np.ones_like(self.inputs["X"]).astype(np.float32)
        }


class TestFillAnyLikeOpOverflow(TestFillAnyLikeOp):
    def init(self):
        self.value = 1e100

    def test_check_output(self):
        exception = None
        try:
            self.check_output(check_dygraph=False)
        except core.EnforceNotMet as ex:
            exception = ex
        self.assertIsNotNone(exception)


class TestFillAnyLikeOpFloat16(TestFillAnyLikeOp):
    def init(self):
        self.dtype = np.float16


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