FM / segformer

/usr/local/lib/python3.6/site-packages/transformers/models/segformer/

/usr/local/lib/python3.6/site-packages/transformers/models/segformer

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
configuration_segformer.py	7049	0644	edit dl rm
convert_segformer_original_to_pytorch.py	17096	0644	edit dl rm
feature_extraction_segformer.py	9475	0644	edit dl rm
modeling_segformer.py	34990	0644	edit dl rm
__init__.py	2172	0644	edit dl rm

Edit: /usr/local/lib/python3.6/site-packages/transformers/models/segformer/__init__.py (2172B)

# flake8: noqa
# There's no way to ignore "F401 '...' imported but unused" warnings in this
# module, but to preserve other warnings. So, don't check this module at all.

# Copyright 2021 The HuggingFace Team. 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.
from typing import TYPE_CHECKING

from ...utils import _LazyModule, is_torch_available, is_vision_available

_import_structure = {
    "configuration_segformer": ["SEGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "SegformerConfig"],
}

if is_vision_available():
    _import_structure["feature_extraction_segformer"] = ["SegformerFeatureExtractor"]

if is_torch_available():
    _import_structure["modeling_segformer"] = [
        "SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
        "SegformerDecodeHead",
        "SegformerForImageClassification",
        "SegformerForSemanticSegmentation",
        "SegformerLayer",
        "SegformerModel",
        "SegformerPreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_segformer import SEGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, SegformerConfig

if is_vision_available():
        from .feature_extraction_segformer import SegformerFeatureExtractor

if is_torch_available():
        from .modeling_segformer import (
            SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            SegformerDecodeHead,
            SegformerForImageClassification,
            SegformerForSemanticSegmentation,
            SegformerLayer,
            SegformerModel,
            SegformerPreTrainedModel,
        )

else:
    import sys

sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

# flake8: noqa # There's no way to ignore "F401 '...' imported but unused" warnings in this # module, but to preserve other warnings. So, don't check this module at all. # Copyright 2021 The HuggingFace Team. 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. from typing import TYPE_CHECKING from ...utils import _LazyModule, is_torch_available, is_vision_available _import_structure = { "configuration_segformer": ["SEGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "SegformerConfig"], } if is_vision_available(): _import_structure["feature_extraction_segformer"] = ["SegformerFeatureExtractor"] if is_torch_available(): _import_structure["modeling_segformer"] = [ "SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST", "SegformerDecodeHead", "SegformerForImageClassification", "SegformerForSemanticSegmentation", "SegformerLayer", "SegformerModel", "SegformerPreTrainedModel", ] if TYPE_CHECKING: from .configuration_segformer import SEGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, SegformerConfig if is_vision_available(): from .feature_extraction_segformer import SegformerFeatureExtractor if is_torch_available(): from .modeling_segformer import ( SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST, SegformerDecodeHead, SegformerForImageClassification, SegformerForSemanticSegmentation, SegformerLayer, SegformerModel, SegformerPreTrainedModel, ) else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)