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chore: import upstream snapshot with attribution
2026-07-13 13:36:25 +08:00

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Python

# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you 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.
"""ROI Pool operator"""
from ..base import Expr
from . import _ffi_api
def roi_pool(
data: Expr,
rois: Expr,
pooled_size: int | tuple[int, int] | list[int],
spatial_scale: float,
layout: str = "NCHW",
):
"""ROI Pool operator.
Parameters
----------
data : relax.Expr
4-D input tensor.
rois : relax.Expr
2-D input tensor with shape `(num_roi, 5)` in
`[batch_idx, x1, y1, x2, y2]` format.
pooled_size : Union[int, Tuple[int, int], List[int]]
Output pooled size.
spatial_scale : float
Ratio of input feature map height (or width) to raw image height (or width).
layout : str, optional
Layout of the input data. Currently only `NCHW` is supported.
Returns
-------
result : relax.Expr
The computed result.
"""
if isinstance(pooled_size, int):
pooled_size = (pooled_size, pooled_size)
return _ffi_api.roi_pool(data, rois, pooled_size, spatial_scale, layout)