#!/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
from cinn.common import *
from cinn.frontend 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 TestConstantOp(OpTest):
    def setUp(self):
        print(f"\nRunning {self.__class__.__name__}: {self.case}")
        self.inputs = {}
        self.prepare_inputs()

    def prepare_inputs(self):
        self.name = "x"
        dtype = self.case["dtype"]
        if "constant_value" in self.case:
            if "bool" in dtype:
                self.value = bool(self.case["constant_value"])
            elif "int" in dtype:
                self.value = int(self.case["constant_value"])
            elif "float" in dtype:
                self.value = float(self.case["constant_value"])
        else:
            self.value = self.random(self.case["shape"], dtype).tolist()
        self.dtype = dtype

    def build_paddle_program(self, target):
        x = paddle.to_tensor(self.value, dtype=self.dtype)
        self.paddle_outputs = [x]

    def build_cinn_program(self, target):
        builder = NetBuilder("constant")
        x = builder.constant(self.value, self.name, self.dtype)
        prog = builder.build()
        res = self.get_cinn_output(prog, target, [], [], [x])
        self.cinn_outputs = res

    def test_check_results(self):
        self.check_outputs_and_grads(all_equal=True)


class TestConstantOpShape(TestCaseHelper):
    def init_attrs(self):
        self.class_name = "TestConstantOpShape"
        self.cls = TestConstantOp
        self.inputs = [
            {
                "constant_value": 10,
            },
            {
                "constant_value": -5,
            },
            {
                "shape": [10],
            },
            {
                "shape": [8, 5],
            },
            {
                "shape": [10, 3, 5],
            },
            {
                "shape": [1, 2, 4, 8],
            },
            # known issue: https://github.com/PaddlePaddle/CINN/pull/1453
            # The compilation time is particularly long for AssignValue op.
            # {
            #     "shape": [16, 4, 8, 32],
            # },
            {
                "shape": [1],
            },
            {
                "shape": [512],
            },
            {
                "shape": [1024],
            },
            # very slow for the shape 2048
            {
                "shape": [2048],
            },
            {
                "shape": [1, 1, 1, 1],
            },
        ]
        self.dtypes = [
            {
                "dtype": "float32"
            },
        ]
        self.attrs = []


class TestConstantOpDtype(TestCaseHelper):
    def init_attrs(self):
        self.class_name = "TestConstantOpDtype"
        self.cls = TestConstantOp
        self.inputs = [
            {
                "constant_value": 1,
            },
            {
                "shape": [10],
            },
            {
                "shape": [8, 5],
            },
            {
                "shape": [10, 3, 5],
            },
        ]
        self.dtypes = [
            {
                "dtype": "float16"
            },
            {
                "dtype": "float32"
            },
            {
                "dtype": "float64"
            },
            {
                "dtype": "bool"
            },
            {
                "dtype": "uint8"
            },
            {
                "dtype": "int8"
            },
            {
                "dtype": "int32"
            },
            {
                "dtype": "int64"
            },
        ]
        self.attrs = []


if __name__ == "__main__":
    TestConstantOpShape().run()
    TestConstantOpDtype().run()