#!/usr/bin/env python3

# Copyright (c) 2021 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 paddle
import paddle.nn.functional as F
from cinn.frontend import *
from cinn.common import *
from op_test import OpTest, OpTestTool
from op_test_helper import TestCaseHelper


@OpTestTool.skip_if(not is_compiled_with_cuda(),
                    "x86 test will be skipped due to timeout.")
class TestReluOp(OpTest):
    def setUp(self):
        print(f"\nRunning {self.__class__.__name__}: {self.case}")
        self.inputs = {}
        self.prepare_inputs()

    def prepare_inputs(self):
        self.inputs = {
            "x": self.random(self.case["shape"], self.case["dtype"], -1.0,
                             1.0),
            "dout": self.random(self.case["shape"], self.case["dtype"], -1.0,
                                1.0)
        }

    def build_paddle_program(self, target):
        x = paddle.to_tensor(self.inputs["x"], stop_gradient=False)
        out = F.relu(x)
        self.paddle_outputs = [out]
        self.paddle_grads = self.get_paddle_grads([out], [x],
                                                  [self.inputs["dout"]])

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

        dout = builder.create_input(
            self.nptype2cinntype(self.inputs["dout"].dtype),
            self.inputs["dout"].shape, "dout")
        x_grad = builder.relu_grad(dout, out)

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

        self.cinn_outputs = [res[0]]
        self.cinn_grads = [res[1]]

    def test_check_results(self):
        self.check_outputs_and_grads()


class TestReluOpShape(TestCaseHelper):
    def init_attrs(self):
        self.class_name = "TestReluOpShape"
        self.cls = TestReluOp
        self.inputs = [
            {
                "shape": [10],
            },
            {
                "shape": [8, 5],
            },
            {
                "shape": [10, 3, 5],
            },
            {
                "shape": [80, 40, 5, 7],
            },
            {
                "shape": [80, 1, 5, 7],
            },
            {
                "shape": [80, 3, 1024, 7],
            },
            {
                "shape": [10, 5, 1024, 2048],
            },
            {
                "shape": [1],
            },
            {
                "shape": [512],
            },
            {
                "shape": [1024],
            },
            {
                "shape": [2048],
            },
            {
                "shape": [1, 1, 1, 1],
            },
        ]
        self.dtypes = [
            {
                "dtype": "float32"
            },
        ]
        self.attrs = []


class TestReluOpDtype(TestCaseHelper):
    def init_attrs(self):
        self.class_name = "TestReluOpDtype"
        self.cls = TestReluOp
        self.inputs = [
            {
                "shape": [1],
            },
            {
                "shape": [5],
            },
            {
                "shape": [80, 40, 5, 7],
            },
        ]
        self.dtypes = [
            {
                "dtype": "float16"
            },
            {
                "dtype": "float32"
            },
            {
                "dtype": "float64"
            },
        ]
        self.attrs = []


if __name__ == "__main__":
    TestReluOpShape().run()
    TestReluOpDtype().run()
