#!/usr/bin/env python3

# Copyright (c) 2022 CINN 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, OpTestTool
import paddle
import paddle.nn.functional as F
import cinn
from cinn.frontend import *
from cinn.common import *


@OpTestTool.skip_if(not is_compiled_with_cuda(),
                    "x86 test will be skipped due to timeout.")
class TestModOp(OpTest):
    def setUp(self):
        self.init_case()

    def init_case(self):
        self.inputs = {
            "x": np.array([7]).astype('float32'),
            "y": np.array([-3]).astype('float32')
        }

    def build_paddle_program(self, target):
        x = paddle.to_tensor(self.inputs["x"], stop_gradient=False)
        y = paddle.to_tensor(self.inputs["y"], stop_gradient=False)

        out = paddle.mod(x, y)

        self.paddle_outputs = [out]

    def build_cinn_program(self, target):
        builder = NetBuilder("pow")
        x = builder.create_input(
            self.nptype2cinntype(self.inputs["x"].dtype),
            self.inputs["x"].shape, "x")
        y = builder.create_input(
            self.nptype2cinntype(self.inputs["y"].dtype),
            self.inputs["y"].shape, "y")
        out = builder.mod(x, y)

        prog = builder.build()
        res = self.get_cinn_output(prog, target, [x, y],
                                   [self.inputs["x"], self.inputs["y"]], [out])

        self.cinn_outputs = [res[0]]

    def test_check_results(self):
        self.check_outputs_and_grads()


class TestModCase1(TestModOp):
    def init_case(self):
        self.inputs = {
            "x": self.random([32, 64], "float32", 20, 100),
            "y": self.random([32, 64], "float32", 1, 20),
        }


class TestModCase2(TestModOp):
    def init_case(self):
        self.inputs = {
            "x": self.random([32, 64], "int32", 20, 100),
            "y": self.random([32, 64], "int32", 1, 20),
        }


class TestModCase3(TestModOp):
    def init_case(self):
        self.inputs = {
            "x": self.random([32, 64], "float32", 20, 100),
            "y": self.random([32, 64], "float32", -20, -1),
        }


class TestModCase4(TestModOp):
    def init_case(self):
        self.inputs = {
            "x": self.random([32, 64], "int32", 20, 100),
            "y": self.random([32, 64], "int32", -20, -1),
        }


class TestModCase5(TestModOp):
    def init_case(self):
        self.inputs = {
            "x": self.random([32, 64], "float32", -100, -20),
            "y": self.random([32, 64], "float32", 1, 20),
        }


class TestModCase6(TestModOp):
    def init_case(self):
        self.inputs = {
            "x": self.random([32, 64], "float32", -100, -20),
            "y": self.random([32, 64], "float32", -20, -1),
        }


class TestModCase7(TestModOp):
    def init_case(self):
        self.inputs = {
            "x": self.random([32, 64], "int32", -100, -20),
            "y": self.random([32, 64], "int32", 1, 20),
        }


class TestModCase8(TestModOp):
    def init_case(self):
        self.inputs = {
            "x": self.random([32, 64], "int32", -100, -20),
            "y": self.random([32, 64], "int32", -20, -1),
        }


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