#   Copyright (c) 2018 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.

import sys
import unittest

import numpy as np

sys.path.append("..")

from op_test_xpu import XPUOpTest
from xpu.get_test_cover_info import (
    XPUOpTestWrapper,
    create_test_class,
    get_xpu_op_support_types,
)

import paddle

paddle.enable_static()


def bilinear_interp_np(
    input,
    out_h,
    out_w,
    scale_w=0,
    scale_h=0,
    out_size=None,
    actual_shape=None,
    align_corners=True,
    align_mode=0,
    data_layout='NCHW',
):
    """bilinear interpolation implement in shape [N, C, H, W]"""
    if data_layout == "NHWC":
        input = np.transpose(input, (0, 3, 1, 2))  # NHWC => NCHW
    if out_size is not None:
        out_h = out_size[0]
        out_w = out_size[1]
    if actual_shape is not None:
        out_h = actual_shape[0]
        out_w = actual_shape[1]
    batch_size, channel, in_h, in_w = input.shape

    ratio_h = ratio_w = 0.0
    if out_h > 1:
        if align_corners:
            ratio_h = (in_h - 1.0) / (out_h - 1.0)
        else:
            if scale_h > 0:
                ratio_h = 1.0 / scale_h
            else:
                ratio_h = 1.0 * in_h / out_h
    if out_w > 1:
        if align_corners:
            ratio_w = (in_w - 1.0) / (out_w - 1.0)
        else:
            if scale_w > 0:
                ratio_w = 1.0 / scale_w
            else:
                ratio_w = 1.0 * in_w / out_w

    out = np.zeros((batch_size, channel, out_h, out_w))

    for i in range(out_h):
        if align_mode == 0 and not align_corners:
            h = int(ratio_h * (i + 0.5) - 0.5)
        else:
            h = int(ratio_h * i)

        h = max(0, h)
        hid = 1 if h < in_h - 1 else 0
        if align_mode == 0 and not align_corners:
            idx_src_h = max(ratio_h * (i + 0.5) - 0.5, 0)
            h1lambda = idx_src_h - h
        else:
            h1lambda = ratio_h * i - h
        h2lambda = 1.0 - h1lambda
        for j in range(out_w):
            if align_mode == 0 and not align_corners:
                w = int(ratio_w * (j + 0.5) - 0.5)
            else:
                w = int(ratio_w * j)
            w = max(0, w)
            wid = 1 if w < in_w - 1 else 0
            if align_mode == 0 and not align_corners:
                idx_src_w = max(ratio_w * (j + 0.5) - 0.5, 0)
                w1lambda = idx_src_w - w
            else:
                w1lambda = ratio_w * j - w
            w2lambda = 1.0 - w1lambda

            out[:, :, i, j] = h2lambda * (
                w2lambda * input[:, :, h, w]
                + w1lambda * input[:, :, h, w + wid]
            ) + h1lambda * (
                w2lambda * input[:, :, h + hid, w]
                + w1lambda * input[:, :, h + hid, w + wid]
            )

    if data_layout == "NHWC":
        out = np.transpose(out, (0, 2, 3, 1))  # NCHW => NHWC

    return out.astype(input.dtype)


class XPUTestBilinearInterpV2Op(XPUOpTestWrapper):
    def __init__(self):
        self.op_name = 'bilinear_interp_v2'
        self.use_dynamic_create_class = False

    class TestBilinearInterpOp(XPUOpTest):
        def setUp(self):
            self.out_size = None
            self.actual_shape = None
            self.init_place()
            self.data_layout = 'NCHW'
            self.init_test_case()
            self.dtype = self.in_type
            self.op_type = "bilinear_interp_v2"
            input_np = np.random.random(self.input_shape).astype(self.dtype)

            if self.data_layout == "NCHW":
                in_h = self.input_shape[2]
                in_w = self.input_shape[3]
            else:
                in_h = self.input_shape[1]
                in_w = self.input_shape[2]
            scale_h = 0
            scale_w = 0
            if self.scale:
                if isinstance(self.scale, float) or isinstance(self.scale, int):
                    if self.scale > 0.0:
                        scale_h = scale_w = float(self.scale)
                if isinstance(self.scale, list) and len(self.scale) == 1:
                    scale_w = scale_h = self.scale[0]
                elif isinstance(self.scale, list) and len(self.scale) > 1:
                    scale_w = self.scale[1]
                    scale_h = self.scale[0]
                out_h = int(in_h * scale_h)
                out_w = int(in_w * scale_w)
            else:
                out_h = self.out_h
                out_w = self.out_w

            output_np = bilinear_interp_np(
                input_np,
                out_h,
                out_w,
                0,
                0,
                self.out_size,
                self.actual_shape,
                self.align_corners,
                self.align_mode,
                self.data_layout,
            )
            self.inputs = {'X': input_np}
            if self.out_size is not None:
                self.inputs['OutSize'] = self.out_size
            if self.actual_shape is not None:
                self.inputs['OutSize'] = self.actual_shape

            self.attrs = {
                'out_h': self.out_h,
                'out_w': self.out_w,
                'interp_method': self.interp_method,
                'align_corners': self.align_corners,
                'align_mode': self.align_mode,
                'data_layout': self.data_layout,
            }
            if self.scale:
                if isinstance(self.scale, float) or isinstance(self.scale, int):
                    if self.scale > 0.0:
                        self.scale = [self.scale]
                if isinstance(self.scale, list) and len(self.scale) == 1:
                    self.scale = [self.scale[0], self.scale[0]]
                self.attrs['scale'] = self.scale
            self.outputs = {'Out': output_np}

        def test_check_output(self):
            self.check_output_with_place(self.place)

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

        def init_test_case(self):
            self.interp_method = 'bilinear'
            self.input_shape = [2, 3, 5, 5]
            self.out_h = 2
            self.out_w = 2
            self.scale = 0.0
            self.out_size = np.array([3, 3]).astype("int32")
            self.align_corners = True
            self.align_mode = 1

        def init_place(self):
            self.place = paddle.XPUPlace(0)

    class TestBilinearInterpCase1(TestBilinearInterpOp):
        def init_test_case(self):
            self.interp_method = 'bilinear'
            self.input_shape = [4, 1, 7, 8]
            self.out_h = 1
            self.out_w = 1
            self.scale = 0.0
            self.align_corners = True
            self.align_mode = 1

    class TestBilinearInterpCase2(TestBilinearInterpOp):
        def init_test_case(self):
            self.interp_method = 'bilinear'
            self.input_shape = [3, 3, 9, 6]
            self.out_h = 12
            self.out_w = 12
            self.scale = 0.0
            self.align_corners = True
            self.align_mode = 1

    class TestBilinearInterpCase3(TestBilinearInterpOp):
        def init_test_case(self):
            self.interp_method = 'bilinear'
            self.input_shape = [1, 1, 32, 64]
            self.out_h = 64
            self.out_w = 32
            self.scale = 0.0
            self.align_corners = True
            self.align_mode = 1

    class TestBilinearInterpCase4(TestBilinearInterpOp):
        def init_test_case(self):
            self.interp_method = 'bilinear'
            self.input_shape = [4, 1, 7, 8]
            self.out_h = 1
            self.out_w = 1
            self.scale = 0.0
            self.out_size = np.array([2, 2]).astype("int32")
            self.align_corners = True
            self.align_mode = 1

    class TestBilinearInterpCase5(TestBilinearInterpOp):
        def init_test_case(self):
            self.interp_method = 'bilinear'
            self.input_shape = [3, 3, 9, 6]
            self.out_h = 12
            self.out_w = 12
            self.scale = 0.0
            self.out_size = np.array([11, 11]).astype("int32")
            self.align_corners = True
            self.align_mode = 1

    class TestBilinearInterpCase6(TestBilinearInterpOp):
        def init_test_case(self):
            self.interp_method = 'bilinear'
            self.input_shape = [1, 1, 32, 64]
            self.out_h = 64
            self.out_w = 32
            self.scale = 0.0
            self.out_size = np.array([65, 33]).astype("int32")
            self.align_corners = True
            self.align_mode = 1

    class TestBilinearInterpCase7(TestBilinearInterpOp):
        def init_test_case(self):
            self.interp_method = 'bilinear'
            self.input_shape = [1, 1, 32, 64]
            self.out_h = 64
            self.out_w = 32
            self.scale = [2.0, 0.5]
            self.align_corners = False
            self.align_mode = 1

    class TestBilinearInterpSame(TestBilinearInterpOp):
        def init_test_case(self):
            self.interp_method = 'bilinear'
            self.input_shape = [2, 3, 32, 64]
            self.out_h = 32
            self.out_w = 64
            self.scale = 0.0
            self.align_corners = True
            self.align_mode = 1

    class TestBilinearInterpActualShape(TestBilinearInterpOp):
        def init_test_case(self):
            self.interp_method = 'bilinear'
            self.input_shape = [3, 2, 32, 16]
            self.out_h = 64
            self.out_w = 32
            self.scale = 0.0
            self.out_size = np.array([66, 40]).astype("int32")
            self.align_corners = True
            self.align_mode = 1

    class TestBilinearInterpOtherMethod1(TestBilinearInterpOp):
        def set_align_mode(self):
            self.align_corners = False
            self.align_mode = 1

    class TestBilinearInterpWithMethod2(TestBilinearInterpOp):
        def set_align_mode(self):
            self.align_corners = False
            self.align_mode = 0

    class TestBilinearInterpWithMethod3(TestBilinearInterpOp):
        def set_align_mode(self):
            self.align_corners = True
            self.align_mode = 0

    class TestBilinearInterpScale1(TestBilinearInterpOp):
        def init_test_case(self):
            self.interp_method = 'bilinear'
            self.input_shape = [2, 3, 5, 7]
            self.out_h = 60
            self.out_w = 25
            self.scale = 2.0
            self.align_corners = True
            self.align_mode = 1

    class TestBilinearInterpScale2(TestBilinearInterpOp):
        def init_test_case(self):
            self.interp_method = 'bilinear'
            self.input_shape = [2, 3, 5, 7]
            self.out_h = 60
            self.out_w = 25
            self.scale = 1.0
            self.align_corners = True
            self.align_mode = 1

    class TestBilinearInterpScale3(TestBilinearInterpOp):
        def init_test_case(self):
            self.interp_method = 'bilinear'
            self.input_shape = [2, 3, 5, 7]
            self.out_h = 60
            self.out_w = 25
            self.scale = 1.5
            self.align_corners = True
            self.align_mode = 1

    class TestBilinearInterpScale4(TestBilinearInterpOp):
        def init_test_case(self):
            self.interp_method = 'bilinear'
            self.input_shape = [2, 3, 5, 7]
            self.out_h = 60
            self.out_w = 25
            self.scale = [1.5, 0.5]
            self.align_corners = True
            self.align_mode = 1

    class TestBilinearInterpZero(TestBilinearInterpOp):
        def init_test_case(self):
            self.interp_method = 'bilinear'
            self.input_shape = [2, 3, 5, 7]
            self.out_h = 60
            self.out_w = 25
            self.scale = 0.2
            self.align_corners = False
            self.align_mode = 0

    class TestBilinearInterpOp_attr_tensor(XPUOpTest):
        def setUp(self):
            self.out_size = None
            self.actual_shape = None
            self.init_test_case()
            self.init_place()
            self.op_type = "bilinear_interp_v2"
            self.dtype = self.in_type
            self.shape_by_1Dtensor = False
            self.scale_by_1Dtensor = False
            self.attrs = {
                'interp_method': self.interp_method,
                'align_corners': self.align_corners,
            }

            input_np = np.random.random(self.input_shape).astype(self.dtype)
            self.inputs = {'X': input_np}

            if self.scale_by_1Dtensor:
                self.inputs['Scale'] = np.array([self.scale]).astype("float32")
            elif self.scale:
                if isinstance(self.scale, float) or isinstance(self.scale, int):
                    if self.scale > 0:
                        scale_h = scale_w = float(self.scale)
                if isinstance(self.scale, list) and len(self.scale) == 1:
                    scale_w = scale_h = self.scale[0]
                elif isinstance(self.scale, list) and len(self.scale) > 1:
                    scale_w = self.scale[1]
                    scale_h = self.scale[0]
                out_h = int(self.input_shape[2] * scale_h)
                out_w = int(self.input_shape[3] * scale_w)
            else:
                out_h = self.out_h
                out_w = self.out_w

            if self.shape_by_1Dtensor:
                self.inputs['OutSize'] = self.out_size
            elif self.out_size is not None:
                size_tensor = []
                for index, ele in enumerate(self.out_size):
                    size_tensor.append(
                        ("x" + str(index), np.ones((1)).astype('int32') * ele)
                    )
                self.inputs['SizeTensor'] = size_tensor

            self.attrs['out_h'] = self.out_h
            self.attrs['out_w'] = self.out_w
            if self.scale:
                if isinstance(self.scale, float) or isinstance(self.scale, int):
                    if self.scale > 0:
                        self.scale = [self.scale]
                if isinstance(self.scale, list) and len(self.scale) == 1:
                    self.scale = [self.scale[0], self.scale[0]]
                self.attrs['scale'] = self.scale
            output_np = bilinear_interp_np(
                input_np,
                out_h,
                out_w,
                0,
                0,
                self.out_size,
                self.actual_shape,
                self.align_corners,
            )
            self.outputs = {'Out': output_np}

        def test_check_output(self):
            self.check_output_with_place(self.place)

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

        def init_test_case(self):
            self.interp_method = 'bilinear'
            self.input_shape = [2, 3, 5, 5]
            self.out_h = 3
            self.out_w = 3
            self.scale = 0.0
            self.out_size = [3, 3]
            self.align_corners = True

        def init_place(self):
            self.place = paddle.XPUPlace(0)

    # out_size is a 1-D tensor
    class TestBilinearInterp_attr_tensor_Case1(
        TestBilinearInterpOp_attr_tensor
    ):
        def init_test_case(self):
            self.interp_method = 'bilinear'
            self.input_shape = [3, 3, 9, 6]
            self.out_h = 12
            self.out_w = 12
            self.scale = 0.0
            self.out_size = [8, 12]
            self.align_corners = True

    # scale is a 1-D tensor
    class TestBilinearInterp_attr_tensor_Case2(
        TestBilinearInterpOp_attr_tensor
    ):
        def init_test_case(self):
            self.interp_method = 'bilinear'
            self.input_shape = [3, 2, 32, 16]
            self.out_h = 64
            self.out_w = 32
            self.scale = 0.0
            self.out_size = np.array([66, 40]).astype("int32")
            self.align_corners = True
            self.shape_by_1Dtensor = True

    # scale is a 1-D tensor
    class TestBilinearInterp_attr_tensor_Case3(
        TestBilinearInterpOp_attr_tensor
    ):
        def init_test_case(self):
            self.interp_method = 'bilinear'
            self.input_shape = [3, 2, 32, 16]
            self.out_h = 64
            self.out_w = 32
            self.scale = 2.0
            self.out_size = None
            self.align_corners = True
            self.scale_by_1Dtensor = True


support_types = get_xpu_op_support_types('bilinear_interp_v2')
for stype in support_types:
    create_test_class(globals(), XPUTestBilinearInterpV2Op, stype)

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