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#
# Licensed to the Apache Software Foundation (ASF) under one
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# 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
#
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# software distributed under the License is distributed on an
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from typing import Any, Tuple, List
import sys
matx = sys.modules['matx']
from .. import ASYNC, StackOp, TransposeOp
from ._base import BaseInterfaceClass
[文档]class ToTensor(BaseInterfaceClass):
[文档] def __init__(self, device_id: int = -2, sync: int = ASYNC) -> None:
super().__init__(device_id=device_id, sync=sync)
[文档] def __call__(self, device: Any, device_str: str, sync: int) -> Any:
return ToTensorImpl(device, device_str, sync)
class ToTensorImpl:
def __init__(self,
device: Any,
device_str: str,
sync: int = ASYNC) -> None:
super().__init__()
self.stack_op: StackOp = StackOp(device)
self.transpose_op: TransposeOp = TransposeOp(
device, input_layout="NHWC", output_layout="NCHW")
self.device_str: str = device_str
self.sync: int = sync
self.name: str = "ToTensor"
def __call__(self, imgs: List[matx.NDArray], apply_index: List[int] = []) -> matx.NDArray:
stacked_img = self.stack_op(imgs)
transposed_img = self.transpose_op(stacked_img, sync=self.sync)
# res = transposed_img.torch()
res = transposed_img
return res
def __repr__(self) -> str:
return self.name + '(device={}, sync={})'.format(self.device_str, self.sync)