# Copyright (c) 2023 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 numpy as np
from op_test import OpTest, OpTestTool
from op_test_helper import TestCaseHelper
import paddle
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 TestBitwiseOp(OpTest):
    def setUp(self):
        print(f"\nRunning {self.__class__.__name__}: {self.case}")
        self.prepare_inputs()

    def prepare_inputs(self):
        # Test with infinite values
        if "with_inf" in self.case:
            self.x_np = np.full(
                shape=self.case["x_shape"],
                fill_value=np.inf,
                dtype=self.case["dtype"])
        # Test with nan values
        elif "with_nan" in self.case:
            self.x_np = np.full(
                shape=self.case["x_shape"],
                fill_value=np.nan,
                dtype=self.case["dtype"])
        else:
            self.x_np = self.random(
                shape=self.case["x_shape"], dtype=self.case["dtype"])
        if self.case["op_type"] != "not":
            self.y_np = self.random(
                shape=self.case["y_shape"], dtype=self.case["dtype"])

    def build_paddle_program(self, target):
        x = paddle.to_tensor(self.x_np, stop_gradient=False)
        if self.case["op_type"] != "not":
            y = paddle.to_tensor(self.y_np, stop_gradient=False)
        if self.case["op_type"] == "and":
            out = paddle.bitwise_and(x, y)
        elif self.case["op_type"] == "or":
            out = paddle.bitwise_or(x, y)
        elif self.case["op_type"] == "xor":
            out = paddle.bitwise_xor(x, y)
        elif self.case["op_type"] == "not":
            out = paddle.bitwise_not(x)
        else:
            out = paddle.assign(x)
        self.paddle_outputs = [out]

    def build_cinn_program(self, target):
        builder = NetBuilder("bitwise")
        x = builder.create_input(
            self.nptype2cinntype(self.case["dtype"]), self.case["x_shape"],
            "x")
        if self.case["op_type"] != "not":
            y = builder.create_input(
                self.nptype2cinntype(self.case["dtype"]), self.case["y_shape"],
                "y")
        if self.case["op_type"] == "and":
            out = builder.bitwise_and(x, y)
        elif self.case["op_type"] == "or":
            out = builder.bitwise_or(x, y)
        elif self.case["op_type"] == "xor":
            out = builder.bitwise_xor(x, y)
        elif self.case["op_type"] == "not":
            out = builder.bitwise_not(x)
        else:
            out = builder.identity(x)
        prog = builder.build()
        if self.case["op_type"] != "not":
            res = self.get_cinn_output(prog, target, [x, y],
                                       [self.x_np, self.y_np], [out])
        else:
            res = self.get_cinn_output(prog, target, [x], [self.x_np], [out])
        self.cinn_outputs = res

    def test_check_results(self):
        max_relative_error = self.case[
            "max_relative_error"] if "max_relative_error" in self.case else 1e-5
        self.check_outputs_and_grads(max_relative_error=max_relative_error)


class TestBitwiseOpShape(TestCaseHelper):
    def init_attrs(self):
        self.class_name = "TestBitwiseOpCase"
        self.cls = TestBitwiseOp
        self.inputs = [
            {
                "x_shape": [1],
                "y_shape": [1],
            },
            {
                "x_shape": [1024],
                "y_shape": [1024],
            },
            {
                "x_shape": [512, 256],
                "y_shape": [512, 256],
            },
            {
                "x_shape": [128, 64, 32],
                "y_shape": [128, 64, 32],
            },
            {
                "x_shape": [16, 8, 4, 2],
                "y_shape": [16, 8, 4, 2],
            },
            {
                "x_shape": [16, 8, 4, 2, 1],
                "y_shape": [16, 8, 4, 2, 1],
            },
            {
                "x_shape": [1, 1, 1, 1, 1],
                "y_shape": [1, 1, 1, 1, 1],
            },
        ]
        self.dtypes = [
            {
                "dtype": "int32"
            },
        ]
        self.attrs = [
            {
                "op_type": "and"
            },
            {
                "op_type": "or"
            },
            {
                "op_type": "xor"
            },
            {
                "op_type": "not"
            },
        ]


class TestBitwiseOpDtype(TestCaseHelper):
    def init_attrs(self):
        self.class_name = "TestBitwiseOpCase"
        self.cls = TestBitwiseOp
        self.inputs = [
            {
                "x_shape": [32, 64],
                "y_shape": [32, 64],
            },
        ]
        self.dtypes = [
            {
                "dtype": "bool"
            },
            {
                "dtype": "uint8"
            },
            {
                "dtype": "int8"
            },
            {
                "dtype": "int16"
            },
            {
                "dtype": "int32"
            },
            {
                "dtype": "int64"
            },
        ]
        self.attrs = [
            {
                "op_type": "and"
            },
            {
                "op_type": "or"
            },
            {
                "op_type": "xor"
            },
            {
                "op_type": "not"
            },
        ]


class TestBitwiseOpBroadcast(TestBitwiseOpShape):
    def init_attrs(self):
        super().init_attrs()
        self.inputs = [
            {
                "x_shape": [1024],
                "y_shape": [1],
            },
            {
                "x_shape": [512, 256],
                "y_shape": [1, 1],
            },
            {
                "x_shape": [128, 64, 32],
                "y_shape": [1, 1, 1],
            },
            {
                "x_shape": [16, 8, 4, 2],
                "y_shape": [1, 1, 1, 1],
            },
            {
                "x_shape": [16, 8, 4, 2, 1],
                "y_shape": [1, 1, 1, 1, 1],
            },
        ]


class TestBitwiseWithINF(TestBitwiseOpDtype):
    def init_attrs(self):
        super().init_attrs()
        self.inputs = [
            {
                "x_shape": [16],
                "y_shape": [16],
                "with_inf": True,
            },
        ]


class TestBitwiseWithNAN(TestBitwiseOpDtype):
    def init_attrs(self):
        super().init_attrs()
        self.inputs = [
            {
                "x_shape": [16],
                "y_shape": [16],
                "with_nan": True,
            },
        ]


if __name__ == "__main__":
    TestBitwiseOpShape().run()
    TestBitwiseOpDtype().run()
    TestBitwiseOpBroadcast().run()
    TestBitwiseWithINF().run()
    TestBitwiseWithNAN().run()