matx.vision.tv_transforms.to_tensor 源代码

# Copyright 2022 ByteDance Ltd. and/or its affiliates.
#
# 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.

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)