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Oct 13, 2022
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auto updates #5322

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1 change: 0 additions & 1 deletion monai/apps/auto3dseg/__main__.py
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# See the License for the specific language governing permissions and
# limitations under the License.


from monai.apps.auto3dseg.auto_runner import AutoRunner
from monai.apps.auto3dseg.bundle_gen import BundleAlgo, BundleGen
from monai.apps.auto3dseg.data_analyzer import DataAnalyzer
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1 change: 0 additions & 1 deletion monai/apps/auto3dseg/ensemble_builder.py
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# See the License for the specific language governing permissions and
# limitations under the License.


import json
import os
from abc import ABC, abstractmethod
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1 change: 0 additions & 1 deletion monai/apps/deepedit/transforms.py
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logger = logging.getLogger(__name__)


distance_transform_cdt, _ = optional_import("scipy.ndimage.morphology", name="distance_transform_cdt")


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1 change: 0 additions & 1 deletion monai/apps/detection/metrics/coco.py
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# The views and conclusions contained in the software and documentation are those
# of the authors and should not be interpreted as representing official policies,
# either expressed or implied, of the FreeBSD Project.

"""
This script is almost same with https://github.com/MIC-DKFZ/nnDetection/blob/main/nndet/evaluator/detection/coco.py
The changes include 1) code reformatting, 2) docstrings.
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1 change: 0 additions & 1 deletion monai/apps/detection/metrics/matching.py
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# The views and conclusions contained in the software and documentation are those
# of the authors and should not be interpreted as representing official policies,
# either expressed or implied, of the FreeBSD Project.

"""
This script is almost same with https://github.com/MIC-DKFZ/nnDetection/blob/main/nndet/evaluator/detection/matching.py
The changes include 1) code reformatting, 2) docstrings,
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1 change: 0 additions & 1 deletion monai/apps/detection/networks/retinanet_detector.py
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# * Neither the name of the copyright holder nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.

"""
Part of this script is adapted from
https://github.com/pytorch/vision/blob/main/torchvision/models/detection/retinanet.py
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1 change: 0 additions & 1 deletion monai/apps/detection/networks/retinanet_network.py
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# * Neither the name of the copyright holder nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.

"""
Part of this script is adapted from
https://github.com/pytorch/vision/blob/main/torchvision/models/detection/retinanet.py
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1 change: 0 additions & 1 deletion monai/apps/detection/utils/ATSS_matcher.py
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# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

"""
The functions in this script are adapted from nnDetection,
https://github.com/MIC-DKFZ/nnDetection/blob/main/nndet/core/boxes/matcher.py
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1 change: 0 additions & 1 deletion monai/apps/detection/utils/anchor_utils.py
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# * Neither the name of the copyright holder nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.

"""
This script is adapted from
https://github.com/pytorch/vision/blob/release/0.12/torchvision/models/detection/anchor_utils.py
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1 change: 0 additions & 1 deletion monai/apps/detection/utils/box_coder.py
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# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

"""
This script is modified from torchvision to support N-D images,

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1 change: 0 additions & 1 deletion monai/apps/detection/utils/box_selector.py
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# * Neither the name of the copyright holder nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.

"""
Part of this script is adapted from
https://github.com/pytorch/vision/blob/main/torchvision/models/detection/retinanet.py
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1 change: 0 additions & 1 deletion monai/apps/detection/utils/hard_negative_sampler.py
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# 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.

"""
The functions in this script are adapted from nnDetection,
https://github.com/MIC-DKFZ/nnDetection/blob/main/nndet/core/boxes/sampler.py
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1 change: 0 additions & 1 deletion monai/apps/mmars/mmars.py
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# 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.

"""
Utilities for accessing Nvidia MMARs

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1 change: 0 additions & 1 deletion monai/apps/mmars/model_desc.py
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# 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.

"""
Collection of the remote MMAR descriptors
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1 change: 0 additions & 1 deletion monai/apps/reconstruction/transforms/array.py
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# See the License for the specific language governing permissions and
# limitations under the License.


from abc import abstractmethod
from typing import Sequence

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1 change: 0 additions & 1 deletion monai/apps/reconstruction/transforms/dictionary.py
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# See the License for the specific language governing permissions and
# limitations under the License.


from typing import Dict, Hashable, Mapping, Optional, Sequence

import numpy as np
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2 changes: 0 additions & 2 deletions monai/apps/tcia/label_desc.py
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# See the License for the specific language governing permissions and
# limitations under the License.


from typing import Dict

__all__ = ["TCIA_LABEL_DICT"]


TCIA_LABEL_DICT: Dict[str, Dict[str, int]] = {
"C4KC-KiTS": {"Kidney": 0, "Renal Tumor": 1},
"NSCLC-Radiomics": {
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1 change: 0 additions & 1 deletion monai/bundle/__main__.py
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# See the License for the specific language governing permissions and
# limitations under the License.


from monai.bundle.scripts import ckpt_export, download, init_bundle, run, verify_metadata, verify_net_in_out

if __name__ == "__main__":
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2 changes: 0 additions & 2 deletions monai/bundle/utils.py
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__all__ = ["ID_REF_KEY", "ID_SEP_KEY", "EXPR_KEY", "MACRO_KEY"]


ID_REF_KEY = "@" # start of a reference to a ConfigItem
ID_SEP_KEY = "#" # separator for the ID of a ConfigItem
EXPR_KEY = "$" # start of a ConfigExpression
MACRO_KEY = "%" # start of a macro of a config


_conf_values = get_config_values()

DEFAULT_METADATA = {
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1 change: 0 additions & 1 deletion monai/config/type_definitions.py
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"SequenceStr",
]


#: KeysCollection
#
# The KeyCollection type is used to for defining variables
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2 changes: 0 additions & 2 deletions monai/data/box_utils.py
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# 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.

"""
This utility module mainly supports rectangular bounding boxes with a few
different parameterizations and methods for converting between them. It
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# We support 2-D or 3-D bounding boxes
SUPPORTED_SPATIAL_DIMS = [2, 3]


# TO_REMOVE = 0.0 if the bottom-right corner pixel/voxel is not included in the boxes,
# i.e., when xmin=1., xmax=2., we have w = 1.
# TO_REMOVE = 1.0 if the bottom-right corner pixel/voxel is included in the boxes,
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1 change: 0 additions & 1 deletion monai/data/dataset.py
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# See the License for the specific language governing permissions and
# limitations under the License.


import collections.abc
import math
import pickle
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1 change: 0 additions & 1 deletion monai/data/image_writer.py
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nib, _ = optional_import("nibabel")
PILImage, _ = optional_import("PIL.Image")


__all__ = [
"ImageWriter",
"ITKWriter",
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1 change: 0 additions & 1 deletion monai/data/thread_buffer.py
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# See the License for the specific language governing permissions and
# limitations under the License.


from multiprocessing.context import SpawnContext
from queue import Empty, Full, Queue
from threading import Thread
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1 change: 0 additions & 1 deletion monai/data/utils.py
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DataFrame, _ = optional_import("pandas", name="DataFrame")
nib, _ = optional_import("nibabel")


__all__ = [
"AFFINE_TOL",
"SUPPORTED_PICKLE_MOD",
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1 change: 0 additions & 1 deletion monai/handlers/logfile_handler.py
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else:
Engine, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Engine")


__all__ = ["LogfileHandler"]


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1 change: 0 additions & 1 deletion monai/handlers/nvtx_handlers.py
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Engine, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Engine")
Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")


__all__ = ["RangeHandler", "RangePushHandler", "RangePopHandler", "MarkHandler"]


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1 change: 0 additions & 1 deletion monai/losses/contrastive.py
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class ContrastiveLoss(_Loss):

"""
Compute the Contrastive loss defined in:

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1 change: 0 additions & 1 deletion monai/losses/giou_loss.py
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class BoxGIoULoss(_Loss):

"""
Compute the generalized intersection over union (GIoU) loss of a pair of boxes.
The two inputs should have the same shape. giou_loss = 1.0 - giou
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1 change: 0 additions & 1 deletion monai/losses/ssim_loss.py
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# See the License for the specific language governing permissions and
# limitations under the License.


import torch
import torch.nn.functional as F
from torch import nn
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1 change: 0 additions & 1 deletion monai/losses/tversky.py
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class TverskyLoss(_Loss):

"""
Compute the Tversky loss defined in:

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1 change: 0 additions & 1 deletion monai/metrics/froc.py
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# See the License for the specific language governing permissions and
# limitations under the License.


from typing import List, Optional, Tuple, Union

import numpy as np
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1 change: 0 additions & 1 deletion monai/networks/blocks/backbone_fpn_utils.py
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# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

"""
This script is modified from from torchvision to support N-D images,
by overriding the definition of convolutional layers and pooling layers.
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1 change: 0 additions & 1 deletion monai/networks/blocks/dints_block.py
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# See the License for the specific language governing permissions and
# limitations under the License.


from typing import Tuple, Union

import torch
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1 change: 0 additions & 1 deletion monai/networks/blocks/feature_pyramid_network.py
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# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

"""
This script is modified from from torchvision to support N-D images,
by overriding the definition of convolutional layers and pooling layers.
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1 change: 0 additions & 1 deletion monai/networks/blocks/unetr_block.py
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# See the License for the specific language governing permissions and
# limitations under the License.


from typing import Sequence, Tuple, Union

import torch
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2 changes: 0 additions & 2 deletions monai/networks/layers/factories.py
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# 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.

"""
Defines factories for creating layers in generic, extensible, and dimensionally independent ways. A separate factory
object is created for each type of layer, and factory functions keyed to names are added to these objects. Whenever
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InstanceNorm3dNVFuser, has_nvfuser = optional_import("apex.normalization", name="InstanceNorm3dNVFuser")


__all__ = ["LayerFactory", "Dropout", "Norm", "Act", "Conv", "Pool", "Pad", "split_args"]


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1 change: 0 additions & 1 deletion monai/networks/nets/dints.py
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# See the License for the specific language governing permissions and
# limitations under the License.


import warnings
from typing import List, Optional, Tuple, Union

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1 change: 0 additions & 1 deletion monai/networks/nets/dynunet.py
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# See the License for the specific language governing permissions and
# limitations under the License.


from typing import List, Optional, Sequence, Tuple, Union

import torch
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1 change: 0 additions & 1 deletion monai/networks/nets/senet.py
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"SE_NET_MODELS",
]


SE_NET_MODELS = {
"senet154": "http://data.lip6.fr/cadene/pretrainedmodels/senet154-c7b49a05.pth",
"se_resnet50": "http://data.lip6.fr/cadene/pretrainedmodels/se_resnet50-ce0d4300.pth",
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1 change: 0 additions & 1 deletion monai/networks/nets/torchvision_fc.py
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models, _ = optional_import("torchvision.models")


__all__ = ["TorchVisionFCModel"]


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1 change: 0 additions & 1 deletion monai/networks/nets/vit.py
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# See the License for the specific language governing permissions and
# limitations under the License.


from typing import Sequence, Union

import torch
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1 change: 0 additions & 1 deletion monai/networks/nets/vitautoenc.py
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# See the License for the specific language governing permissions and
# limitations under the License.


from typing import Sequence, Union

import torch
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1 change: 0 additions & 1 deletion monai/transforms/adaptors.py
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# 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.

"""
How to use the adaptor function
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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1 change: 0 additions & 1 deletion monai/transforms/signal/array.py
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central_frequency, has_central_frequency = optional_import("pywt", name="central_frequency")
cwt, has_cwt = optional_import("pywt", name="cwt")


__all__ = [
"SignalRandDrop",
"SignalRandScale",
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1 change: 0 additions & 1 deletion monai/transforms/smooth_field/array.py
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# 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.

"""Transforms using a smooth spatial field generated by interpolating from smaller randomized fields."""

from typing import Any, Optional, Sequence, Union
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