# Copyright (c) 2020  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 paddle
from paddle import _C_ops
from paddle import in_dynamic_mode
from paddle.common_ops_import import Variable, LayerHelper, check_variable_and_dtype, check_type, check_dtype


@paddle.jit.not_to_static
def roi_align(input,
              rois,
              pooled_height,
              pooled_width,
              spatial_scale=1.0,
              sampling_ratio=-1,
              rois_num=None,
              aligned=True,
              name=None):
    if in_dynamic_mode():
        assert rois_num is not None, "rois_num should not be None in dygraph mode."
        align_out = _C_ops.roi_align(
            input, rois, rois_num, "pooled_height", pooled_height,
            "pooled_width", pooled_width, "spatial_scale", spatial_scale,
            "sampling_ratio", sampling_ratio, "aligned", aligned)
        return align_out

    else:
        check_variable_and_dtype(input, 'input', ['float32', 'float64'],
                                 'roi_align')
        check_variable_and_dtype(rois, 'rois', ['float32', 'float64'],
                                 'roi_align')
        helper = LayerHelper('roi_align', **locals())
        dtype = helper.input_dtype()
        align_out = helper.create_variable_for_type_inference(dtype)
        inputs = {
            "X": input,
            "ROIs": rois,
        }
        if rois_num is not None:
            inputs['RoisNum'] = rois_num
        helper.append_op(
            type="roi_align",
            inputs=inputs,
            outputs={"Out": align_out},
            attrs={
                "pooled_height": pooled_height,
                "pooled_width": pooled_width,
                "spatial_scale": spatial_scale,
                "sampling_ratio": sampling_ratio,
                "aligned": aligned,
            })
        return align_out


class ROIAlign(object):
    def __init__(self, pooled_height, pooled_width, spatial_scale,
                 sampling_ratio):
        self.roialign_layer_attrs = {
            "pooled_height": pooled_height,
            "pooled_width": pooled_width,
            "spatial_scale": spatial_scale,
            'sampling_ratio': sampling_ratio,
        }

    def __call__(self, x0, x1, x2):
        out = roi_align(
            input=x0, rois=x1, rois_num=x2, **self.roialign_layer_attrs)
        return out