#  Copyright (c) 2021 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 numpy as np
import unittest
import sys
sys.path.append("..")
from op_test import OpTest
import paddle
import paddle.fluid as fluid
from test_matmul_v2_op import reference_matmul

paddle.enable_static()
SEED = 2021


class TestMatMulV2Op(OpTest):
    """
    case 1
    """

    def set_npu(self):
        self.__class__.use_npu = True
        self.place = paddle.NPUPlace(0)

    def config(self):
        self.x_shape = (100, )
        self.y_shape = (100, )
        self.trans_x = False
        self.trans_y = False

    def init_kernel_type(self):
        self.dtype = "float32"

    def setUp(self):
        self.set_npu()
        self.init_kernel_type()
        self.config()
        self.op_type = "matmul_v2"
        x = np.random.random(self.x_shape).astype(self.dtype)
        y = np.random.random(self.y_shape).astype(self.dtype)
        # -0.1 ~ 0.1
        x = -0.1 + 0.2 * x
        y = -0.1 + 0.2 * y
        result = reference_matmul(x, y, self.trans_x, self.trans_y)
        result = result.astype(self.dtype)
        self.inputs = {
            'X': x,
            'Y': y,
        }
        self.attrs = {'trans_x': self.trans_x, 'trans_y': self.trans_y}
        self.outputs = {'Out': result}

    def test_check_output(self):
        self.check_output_with_place(self.place, atol=1e-7)

    def test_check_grad(self):
        self.check_grad_with_place(self.place, ['X', 'Y'], 'Out')


class TestMatMulOp2(TestMatMulV2Op):
    """
    case 2
    """

    def config(self):
        self.x_shape = (100, )
        self.y_shape = (1, 3, 2, 100)
        self.trans_x = False
        self.trans_y = True


class TestMatMulOp3(TestMatMulV2Op):
    """
    case 3
    """

    def config(self):
        self.x_shape = (100, )
        self.y_shape = (1, 1, 100, 2)
        self.trans_x = False
        self.trans_y = False


class TestMatMulOp4(TestMatMulV2Op):
    """
    case 4
    """

    def config(self):
        self.x_shape = (100, )
        self.y_shape = (1, 2, 100, 2)
        self.trans_x = False
        self.trans_y = False


class TestMatMulOp5(TestMatMulV2Op):
    """
    case 5
    """

    def config(self):
        self.x_shape = (1, 1, 100, 1)
        self.y_shape = (100, )
        self.trans_x = True
        self.trans_y = False


class TestMatMulOp6(TestMatMulV2Op):
    """
    case 6
    """

    def config(self):
        self.x_shape = (1, 2, 102, 1)
        self.y_shape = (102, )
        self.trans_x = True
        self.trans_y = False


class TestMatMulOp7(TestMatMulV2Op):
    """
    case 7
    """

    def config(self):
        self.x_shape = (1, 2, 1, 100)
        self.y_shape = (100, )
        self.trans_x = False
        self.trans_y = False


class TestMatMulOp8(TestMatMulV2Op):
    """
    case 8
    """

    def config(self):
        self.x_shape = (1, 1, 2, 100)
        self.y_shape = (1, 1, 100, 2)
        self.trans_x = False
        self.trans_y = False


class TestMatMulOp9(TestMatMulV2Op):
    """
    case 9
    """

    def config(self):
        self.x_shape = (1, 1, 1, 100)
        self.y_shape = (2, 1, 2, 100)
        self.trans_x = False
        self.trans_y = True


class TestMatMulOp10(TestMatMulV2Op):
    """
    case 10
    """

    def config(self):
        self.x_shape = (1, 1, 25, 4)
        self.y_shape = (1, 2, 4, 25)
        self.trans_x = False
        self.trans_y = False


class TestMatMulOp11(TestMatMulV2Op):
    """
    case 11
    """

    def config(self):
        self.x_shape = (2, 1, 2, 100)
        self.y_shape = (1, 1, 100, 2)
        self.trans_x = False
        self.trans_y = False


class TestMatMulOp12(TestMatMulV2Op):
    """
    case 12
    """

    def config(self):
        self.x_shape = (2, 1, 4, 25)
        self.y_shape = (1, 1, 4, 25)
        self.trans_x = True
        self.trans_y = False


class TestMatMulOp13(TestMatMulV2Op):
    """
    case 13
    """

    def config(self):
        self.x_shape = (2, 2, 10, 10)
        self.y_shape = (2, 2, 10, 10)
        self.trans_x = True
        self.trans_y = False


class TestMatMulOp14(TestMatMulV2Op):
    """
    case 14_1
    """

    def config(self):
        self.x_shape = (3, 1, 6, 6)
        self.y_shape = (1, 2, 6, 9)
        self.trans_x = True
        self.trans_y = False


class TestMatMulOp15(TestMatMulV2Op):
    """
    case 14_2
    """

    def config(self):
        self.x_shape = (3, 1, 6, 6)
        self.y_shape = (1, 2, 6, 9)
        self.trans_x = False
        self.trans_y = False


class TestMatMulOp16(TestMatMulV2Op):
    """
    case 16 : to check the gradient for special case
    """

    def config(self):
        self.x_shape = (100)
        self.y_shape = (1, 2, 2, 100, 2)
        self.trans_x = False
        self.trans_y = False


class TestMatMulOp17(TestMatMulV2Op):
    """
    case 17 : to check the gradient for special case
    """

    def config(self):
        self.x_shape = (2, 1, 100)
        self.y_shape = (100)
        self.trans_x = False
        self.trans_y = False


class TestMatMulOpBroadcast1(TestMatMulV2Op):
    """
    case 14_3
    """

    def config(self):
        self.x_shape = (3, 1, 10, 10)
        self.y_shape = (1, 2, 10, 10)
        self.trans_x = True
        self.trans_y = True


class TestMatMulOpBroadcast2(TestMatMulV2Op):
    """
    case 14_4
    """

    def config(self):
        self.x_shape = (3, 1, 10, 10)
        self.y_shape = (1, 2, 10, 10)
        self.trans_x = False
        self.trans_y = True


#--------------------test matmul fp16--------------------


def create_test_fp16_class(parent, atol=0.001, max_relative_error=2.5):
    class TestMatMulOpFp16Case(parent):
        def init_kernel_type(self):
            self.dtype = np.float16

        def test_check_output(self):
            self.check_output_with_place(self.place, atol=atol)

        def test_check_grad(self):
            self.check_grad_with_place(
                self.place, ['X', 'Y'],
                'Out',
                max_relative_error=max_relative_error)

    cls_name = "{0}_{1}".format(parent.__name__, "Fp16")
    TestMatMulOpFp16Case.__name__ = cls_name
    globals()[cls_name] = TestMatMulOpFp16Case


create_test_fp16_class(TestMatMulV2Op)
create_test_fp16_class(TestMatMulOp2)
create_test_fp16_class(TestMatMulOp3)
create_test_fp16_class(TestMatMulOp4)
create_test_fp16_class(TestMatMulOp5)
create_test_fp16_class(TestMatMulOp6)
create_test_fp16_class(TestMatMulOp7)
create_test_fp16_class(TestMatMulOp8)
create_test_fp16_class(TestMatMulOp9)
create_test_fp16_class(TestMatMulOp10)
create_test_fp16_class(TestMatMulOp11)
create_test_fp16_class(TestMatMulOp12)
create_test_fp16_class(TestMatMulOp13)
create_test_fp16_class(TestMatMulOp14)
create_test_fp16_class(TestMatMulOp15)
create_test_fp16_class(TestMatMulOp16)
create_test_fp16_class(TestMatMulOp17)


class TestMatMulV2API(unittest.TestCase):
    def setUp(self):
        self.places = [paddle.CPUPlace()]
        if paddle.is_compiled_with_npu():
            self.places.append(paddle.NPUPlace(0))

    def check_static_result(self, place):
        with fluid.program_guard(fluid.Program(), fluid.Program()):
            input_x = fluid.data(name="input_x", shape=[4, 3], dtype="float32")
            input_y = fluid.data(name="input_y", shape=[3, 4], dtype="float32")

            result = paddle.matmul(input_x, input_y)

            x_np = np.random.random([4, 3]).astype("float32")
            y_np = np.random.random([3, 4]).astype("float32")

            exe = fluid.Executor(place)
            fetches = exe.run(fluid.default_main_program(),
                              feed={"input_x": x_np,
                                    "input_y": y_np},
                              fetch_list=[result])

    def test_static(self):
        for place in self.places:
            self.check_static_result(place=place)

    def test_dygraph(self):
        for place in self.places:
            with fluid.dygraph.guard(place):
                input_x = np.random.random([4, 3]).astype("float32")
                input_y = np.random.random([3, 4]).astype("float32")
                x = paddle.to_tensor(input_x)
                y = paddle.to_tensor(input_y)
                result = paddle.matmul(x, y)

    def test_dygraph_fp16(self):
        if paddle.is_compiled_with_npu():
            place = paddle.NPUPlace(0)
            with fluid.dygraph.guard(place):
                input_x = np.random.random([4, 3]).astype("float16")
                input_y = np.random.random([3, 4]).astype("float16")
                x = paddle.to_tensor(input_x)
                y = paddle.to_tensor(input_y)
                result = paddle.matmul(x, y)


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