# Copyright 2022 ByteDance Ltd. and/or its affiliates.
#
# Licensed to the Apache Software Foundation (ASF) under one
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# 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
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# KIND, either express or implied. See the License for the
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from typing import Any, Tuple, List
import sys
matx = sys.modules['matx']
from .. import NHWC, NCHW, ASYNC, TransposeOp
from ._base import BaseInterfaceClass
class TransposeCpuOp:
def __init__(self,
device: Any,
src_fmt: str = NHWC,
dst_fmt: str = NCHW) -> None:
self.device: Any = device
self.src_fmt: str = src_fmt
self.dst_fmt: str = dst_fmt
def __call__(self, images: matx.NDArray, sync: int = 0) -> matx.NDArray:
if self.src_fmt == self.dst_fmt:
return images
if self.src_fmt == NHWC:
return images.transpose([0, 3, 1, 2]).contiguous()
else:
return images.transpose([0, 2, 3, 1]).contiguous()
[文档]class Transpose(BaseInterfaceClass):
[文档] def __init__(self,
src_fmt: str = NHWC,
dst_fmt: str = NCHW,
device_id: int = -2,
sync: int = ASYNC) -> None:
super().__init__(device_id=device_id, sync=sync)
self._src_fmt: str = src_fmt
self._dst_fmt: str = dst_fmt
[文档] def __call__(self, device: Any, device_str: str, sync: int) -> Any:
return TransposeImpl(device, device_str, self._src_fmt, self._dst_fmt, sync)
class TransposeImpl:
def __init__(self,
device: Any,
device_str: str,
src_fmt: str = NHWC,
dst_fmt: str = NCHW,
sync: int = ASYNC) -> None:
super().__init__()
if device_str == "cpu":
self.op: Any = TransposeCpuOp(device, src_fmt, dst_fmt)
else:
self.op: Any = TransposeOp(device, src_fmt, dst_fmt)
self.device_str: str = device_str
self.src_fmt: str = src_fmt
self.dst_fmt: str = dst_fmt
self.sync: int = sync
self.name: str = "Transpose"
def __call__(self, imgs: matx.NDArray, apply_index: List[int] = []) -> matx.NDArray:
assert len(apply_index) == 0, "apply_index is not supported by transpose."
return self.op(imgs, sync=self.sync)
def __repr__(self) -> str:
return self.name + '(from={0}, to={1}, device={2}, sync={3})'.format(
self.src_fmt, self.dst_fmt, self.device_str, self.sync)