rename models -> arch

nndet/core/retina.py

@@ -4,12 +4,12 @@ import torch.nn as nn
 from torch import Tensor
 from typing import List, Tuple, Dict, Any, Optional, Union
 
-from nndet.models.abstract import AbstractModel
+from nndet.arch.abstract import AbstractModel
 from nndet.core import boxes as box_utils
-from nndet.models.encoder.abstract import EncoderType
-from nndet.models.decoder.base import DecoderType
-from nndet.models.heads.segmenter import SegmenterType
-from nndet.models.heads.comb import HeadType
+from nndet.arch.encoder.abstract import EncoderType
+from nndet.arch.decoder.base import DecoderType
+from nndet.arch.heads.segmenter import SegmenterType
+from nndet.arch.heads.comb import HeadType
 
 
 class BaseRetinaNet(AbstractModel):

nndet/inference/predictor.py

@@ -25,7 +25,7 @@ from typing import Hashable, List, Sequence, Dict, Union, Any, Optional, Callabl
 from pathlib import Path
 
 from nndet.io.load import save_pickle
-from nndet.models.abstract import AbstractModel
+from nndet.arch.abstract import AbstractModel
 from nndet.io.transforms import NoOp
 from nndet.inference.patching import save_get_crop, create_grid
 from nndet.utils import to_device, maybe_verbose_iterable

nndet/models/blocks/__init__.py

-from nndet.models.blocks.basic import AbstractBlock, StackedConvBlock, \
-    StackedResidualBlock, StackedConvBlock2
-from nndet.models.blocks.res import ResBasic, ResBottleneck

nndet/models/decoder/__init__.py

-from nndet.models.decoder.fpn import FPN, UFPN, FPN2

nndet/models/encoder/__init__.py

-from nndet.models.encoder.abstract import AbstractEncoder
-from nndet.models.encoder.modular import Encoder

nndet/models/heads/__init__.py

-from nndet.models.heads.classifier import ClassifierType, Classifier
-from nndet.models.heads.comb import HeadType, AbstractHead
-from nndet.models.heads.regressor import RegressorType, Regressor
-from nndet.models.heads.segmenter import SegmenterType, Segmenter

nndet/ptmodule/retinaunet/base.py

@@ -41,15 +41,15 @@ from nndet.core.boxes.utils import box_iou
 
 from nndet.ptmodule.base_module import LightningBaseModuleSWA, LightningBaseModule
 
-from nndet.models.conv import Generator, ConvInstanceRelu, ConvGroupRelu
-from nndet.models.blocks.basic import StackedConvBlock2
-from nndet.models.encoder.abstract import EncoderType
-from nndet.models.encoder.modular import Encoder
-from nndet.models.decoder.base import DecoderType, BaseUFPN, UFPNModular
-from nndet.models.heads.classifier import ClassifierType, CEClassifier
-from nndet.models.heads.regressor import RegressorType, L1Regressor
-from nndet.models.heads.comb import HeadType, DetectionHeadHNM
-from nndet.models.heads.segmenter import SegmenterType, DiCESegmenter
+from nndet.arch.conv import Generator, ConvInstanceRelu, ConvGroupRelu
+from nndet.arch.blocks.basic import StackedConvBlock2
+from nndet.arch.encoder.abstract import EncoderType
+from nndet.arch.encoder.modular import Encoder
+from nndet.arch.decoder.base import DecoderType, BaseUFPN, UFPNModular
+from nndet.arch.heads.classifier import ClassifierType, CEClassifier
+from nndet.arch.heads.regressor import RegressorType, L1Regressor
+from nndet.arch.heads.comb import HeadType, DetectionHeadHNM
+from nndet.arch.heads.segmenter import SegmenterType, DiCESegmenter
 
 from nndet.training.optimizer import get_params_no_wd_on_norm
 from nndet.training.learning_rate import LinearWarmupPolyLR

nndet/ptmodule/retinaunet/v001.py

@@ -17,12 +17,11 @@ limitations under the License.
 from nndet.ptmodule.retinaunet.base import RetinaUNetModule
 
 from nndet.core.boxes.matcher import ATSSMatcher
-from nndet.models.heads.classifier import BCECLassifier
-from nndet.models.heads.regressor import GIoURegressor
-from nndet.models.heads.comb import DetectionHeadHNMNative
-from nndet.models.heads.segmenter import DiCESegmenterFgBg
-
-from nndet.models.conv import ConvInstanceRelu, ConvGroupRelu
+from nndet.arch.heads.classifier import BCECLassifier
+from nndet.arch.heads.regressor import GIoURegressor
+from nndet.arch.heads.comb import DetectionHeadHNMNative
+from nndet.arch.heads.segmenter import DiCESegmenterFgBg
+from nndet.arch.conv import ConvInstanceRelu, ConvGroupRelu
 
 from nndet.ptmodule import MODULE_REGISTRY
 

nndet/training/optimizer/utils.py

@@ -19,7 +19,7 @@ from typing import Dict, Sequence
 import torch
 import torch.nn as nn
 
-import nndet.models.layers.norm as an
+import nndet.arch.layers.norm as an
 
 NORM_TYPES = [nn.BatchNorm1d, nn.BatchNorm2d, nn.BatchNorm3d,
               nn.InstanceNorm1d, nn.InstanceNorm2d, nn.InstanceNorm3d,