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!_TAG_PROGRAM_AUTHOR	Darren Hiebert	/dhiebert@users.sourceforge.net/
!_TAG_PROGRAM_NAME	Exuberant Ctags	//
!_TAG_PROGRAM_URL	http://ctags.sourceforge.net	/official site/
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ACCURACY_METRIC	vis_models/training/supervised.py	/^ACCURACY_METRIC = "accuracy"$/;"	v
ACTIVATION	vis_models/architectures/simple_conv.py	/^ACTIVATION = "act"$/;"	v
ARTIFACTS_DIR_KEY	vis_models/io/dirs.py	/^ARTIFACTS_DIR_KEY = "ARTIFACTS_DIR"$/;"	v
AdvInferenceRecord	vis_models/training/adversarial.py	/^class AdvInferenceRecord(InferenceRecord):$/;"	c
AdversarialTraining	vis_models/training/adversarial.py	/^class AdversarialTraining(torch.nn.Module):$/;"	c
AdversarialTrainingConfig	vis_models/training/adversarial.py	/^class AdversarialTrainingConfig:$/;"	c
AttackConstraint	vis_models/training/adversarial.py	/^AttackConstraint = Literal["2", "inf", "unconstrained", "fourier"]$/;"	v
AttackerModel	vis_models/training/adversarial.py	/^from robustness.attacker import AttackerModel$/;"	i
BATCH_NORM	vis_models/architectures/simple_conv.py	/^BATCH_NORM = "bn"$/;"	v
BasicBlock	vis_models/architectures/cifar/resnet.py	/^class BasicBlock(nn.Module):$/;"	c
Bottleneck	vis_models/architectures/cifar/densenet.py	/^class Bottleneck(nn.Module):$/;"	c
Bottleneck	vis_models/architectures/cifar/resnet.py	/^class Bottleneck(nn.Module):$/;"	c
CLASSWISE_ACCURACY_METRIC	vis_models/training/supervised.py	/^CLASSWISE_ACCURACY_METRIC = "classwise_accuracy"$/;"	v
CONFUSION_MATRIX_METRIC	vis_models/training/supervised.py	/^CONFUSION_MATRIX_METRIC = "confusion_matrix"$/;"	v
CONV	vis_models/architectures/simple_conv.py	/^CONV = "conv"$/;"	v
Callable	vis_models/architectures/access.py	/^from typing import Callable, cast$/;"	i
Callable	vis_models/inference_recording/with_intermediate.py	/^from typing import Callable, Iterator$/;"	i
DataLoader	tests/test_training.py	/^from torch.utils.data import DataLoader, Dataset$/;"	i
DataSample	vis_models/inference_recording/with_intermediate.py	/^from vis_datasets.wrappers.data_sample import DataSample$/;"	i
Dataset	tests/test_training.py	/^from torch.utils.data import DataLoader, Dataset$/;"	i
DatasetStats	vis_models/training/adversarial.py	/^class DatasetStats:$/;"	c
DenseNet	vis_models/architectures/cifar/densenet.py	/^class DenseNet(nn.Module):$/;"	c
DenseNet121	vis_models/architectures/cifar/densenet.py	/^def DenseNet121(num_classes: int):$/;"	f
DenseNet161	vis_models/architectures/cifar/densenet.py	/^def DenseNet161(num_classes: int):$/;"	f
DenseNet169	vis_models/architectures/cifar/densenet.py	/^def DenseNet169(num_classes: int):$/;"	f
DenseNet201	vis_models/architectures/cifar/densenet.py	/^def DenseNet201(num_classes: int):$/;"	f
F	vis_models/architectures/cifar/densenet.py	/^import torch.nn.functional as F$/;"	i
F	vis_models/architectures/cifar/resnet.py	/^import torch.nn.functional as F$/;"	i
F	vis_models/training/supervised.py	/^import torch.nn.functional as F$/;"	i
FLATTEN	vis_models/architectures/simple_conv.py	/^FLATTEN = "fl"$/;"	v
InferenceRecord	vis_models/architectures/lib/recorded_sequential.py	/^from ..definitions import Model, InferenceRecord$/;"	i
InferenceRecord	vis_models/architectures/simple_conv.py	/^from ..wrapping import WrappedModel, InferenceRecord$/;"	i
InferenceRecord	vis_models/inference_recording/__init__.py	/^from .inference_record import InferenceRecord, to_inference_record, concatenate$/;"	i
InferenceRecord	vis_models/inference_recording/inference_record.py	/^class InferenceRecord:$/;"	c
InferenceRecord	vis_models/inference_recording/with_intermediate.py	/^from .inference_record import InferenceRecord, to_inference_record$/;"	i
InferenceRecord	vis_models/inference_recording/wrappers.py	/^from .inference_record import InferenceRecord, to_inference_record$/;"	i
InferenceRecord	vis_models/training/adversarial.py	/^from ..inference_recording import InferenceRecord$/;"	i
Iterable	vis_models/inference_recording/inference_record.py	/^from typing import Iterable, Optional, Union$/;"	i
Iterator	vis_models/inference_recording/with_intermediate.py	/^from typing import Callable, Iterator$/;"	i
LINEAR	vis_models/architectures/simple_conv.py	/^LINEAR = "fc"$/;"	v
LOSS_METRIC	vis_models/training/supervised.py	/^LOSS_METRIC = "loss"$/;"	v
LayerAccessor	vis_models/architectures/access.py	/^LayerAccessor = Callable[[Module], Module]$/;"	v
LayerRepresentations	vis_models/inference_recording/inference_record.py	/^LayerRepresentations = dict[str, torch.Tensor]$/;"	v
List	vis_models/metrics/representation_similarity/cka/cka_minibatch.py	/^from typing import List$/;"	i
Literal	vis_models/architectures/create.py	/^from typing import Literal$/;"	i
Literal	vis_models/training/adversarial.py	/^from typing import Literal, Optional$/;"	i
MAX_POOL	vis_models/architectures/simple_conv.py	/^MAX_POOL = "mp"$/;"	v
MinibatchCKA	tests/test_CKA_minibatch.py	/^from ..CKA_minibatch import MinibatchCKA$/;"	i
MinibatchCKA	vis_models/metrics/representation_similarity/cka/__init__.py	/^from .cka_minibatch import MinibatchCKA$/;"	i
MinibatchCKA	vis_models/metrics/representation_similarity/cka/cka_minibatch.py	/^class MinibatchCKA:$/;"	c
Model	vis_models/architectures/lib/recorded_sequential.py	/^from ..definitions import Model, InferenceRecord$/;"	i
ModelConfig	vis_models/architectures/__init__.py	/^from .create import ModelConfig, create_model$/;"	i
ModelConfig	vis_models/architectures/access.py	/^from .create import ModelConfig$/;"	i
ModelConfig	vis_models/architectures/create.py	/^class ModelConfig:$/;"	c
ModelConfig	vis_models/architectures/utils/fine_tuning.py	/^from ..create import ModelConfig$/;"	i
Module	vis_models/architectures/access.py	/^from torch.nn import Module$/;"	i
Module	vis_models/architectures/create.py	/^from torch.nn import Module$/;"	i
Optional	vis_models/inference_recording/inference_record.py	/^from typing import Iterable, Optional, Union$/;"	i
Optional	vis_models/io/dirs.py	/^from typing import Optional, Union$/;"	i
Optional	vis_models/io/persistence.py	/^from typing import Optional, Union$/;"	i
Optional	vis_models/metrics/representation_similarity/cka/cka.py	/^from typing import Optional$/;"	i
Optional	vis_models/training/adversarial.py	/^from typing import Literal, Optional$/;"	i
Optional	vis_models/training/supervised.py	/^from typing import Optional, Union$/;"	i
OrderedDict	vis_models/architectures/simple_conv.py	/^from collections import OrderedDict$/;"	i
Path	tests/test_training.py	/^from pathlib import Path$/;"	i
Path	vis_models/io/dirs.py	/^from pathlib import Path$/;"	i
Path	vis_models/io/logging.py	/^from pathlib import Path$/;"	i
Path	vis_models/io/persistence.py	/^from pathlib import Path$/;"	i
RecordedSequential	vis_models/architectures/lib/recorded_sequential.py	/^class RecordedSequential(Model):$/;"	c
RecordedSequential	vis_models/architectures/simple_conv.py	/^from .lib.recorded_sequential import RecordedSequential$/;"	i
ResNet	vis_models/architectures/cifar/resnet.py	/^class ResNet(nn.Module):$/;"	c
ResNet101	vis_models/architectures/cifar/resnet.py	/^def ResNet101(num_classes: int):$/;"	f
ResNet152	vis_models/architectures/cifar/resnet.py	/^def ResNet152(num_classes: int):$/;"	f
ResNet18	vis_models/architectures/cifar/resnet.py	/^def ResNet18(num_classes: int):$/;"	f
ResNet34	vis_models/architectures/cifar/resnet.py	/^def ResNet34(num_classes: int):$/;"	f
ResNet50	vis_models/architectures/cifar/resnet.py	/^def ResNet50(num_classes: int):$/;"	f
SimpleConv	tests/test_training.py	/^from models.architectures.simple_conv import SimpleConvConfig, SimpleConv$/;"	i
SimpleConv	vis_models/architectures/simple_conv.py	/^class SimpleConv(WrappedModel):$/;"	c
SimpleConvConfig	tests/test_training.py	/^from models.architectures.simple_conv import SimpleConvConfig, SimpleConv$/;"	i
SimpleConvConfig	vis_models/architectures/simple_conv.py	/^class SimpleConvConfig:$/;"	c
SimpleConvTraining	tests/test_training.py	/^    class SimpleConvTraining(SupervisedTraining):$/;"	c	function:test_training
SupervisedLearning	vis_models/training/supervised.py	/^class SupervisedLearning(pl.LightningModule):$/;"	c
SupervisedTraining	tests/test_training.py	/^from models.training.supervised import SupervisedTraining$/;"	i
TestDataset	tests/test_training.py	/^class TestDataset(Dataset):$/;"	c
Trainer	vis_models/training/__init__.py	/^from .trainer import Trainer$/;"	i
Trainer	vis_models/training/trainer.py	/^class Trainer(pl.Trainer):$/;"	c
Transition	vis_models/architectures/cifar/densenet.py	/^class Transition(nn.Module):$/;"	c
Union	vis_models/inference_recording/inference_record.py	/^from typing import Iterable, Optional, Union$/;"	i
Union	vis_models/io/dirs.py	/^from typing import Optional, Union$/;"	i
Union	vis_models/io/logging.py	/^from typing import Union$/;"	i
Union	vis_models/io/persistence.py	/^from typing import Optional, Union$/;"	i
Union	vis_models/training/supervised.py	/^from typing import Optional, Union$/;"	i
Union	vis_models/training/trainer.py	/^from typing import Union$/;"	i
VGG	vis_models/architectures/cifar/vgg.py	/^class VGG(nn.Module):$/;"	c
VGG11	vis_models/architectures/cifar/vgg.py	/^def VGG11(num_classes: int) -> VGG:$/;"	f
WrappedModel	vis_models/architectures/simple_conv.py	/^from ..wrapping import WrappedModel, InferenceRecord$/;"	i
__getitem__	tests/test_training.py	/^    def __getitem__(self, idx: int) -> tuple[torch.Tensor, torch.Tensor]:$/;"	m	class:TestDataset	file:
__init__	vis_models/architectures/cifar/densenet.py	/^    def __init__(self, block, nblocks, growth_rate=12, reduction=0.5, num_classes=10):$/;"	m	class:DenseNet
__init__	vis_models/architectures/cifar/densenet.py	/^    def __init__(self, in_planes, growth_rate):$/;"	m	class:Bottleneck
__init__	vis_models/architectures/cifar/densenet.py	/^    def __init__(self, in_planes, out_planes):$/;"	m	class:Transition
__init__	vis_models/architectures/cifar/resnet.py	/^    def __init__(self, block, num_blocks, num_classes=10):$/;"	m	class:ResNet
__init__	vis_models/architectures/cifar/resnet.py	/^    def __init__(self, in_planes, planes, stride=1):$/;"	m	class:BasicBlock
__init__	vis_models/architectures/cifar/resnet.py	/^    def __init__(self, in_planes, planes, stride=1):$/;"	m	class:Bottleneck
__init__	vis_models/architectures/cifar/vgg.py	/^    def __init__(self, vgg_name: str, num_classes: int = 10):$/;"	m	class:VGG
__init__	vis_models/architectures/lib/recorded_sequential.py	/^    def __init__($/;"	m	class:RecordedSequential
__init__	vis_models/architectures/simple_conv.py	/^    def __init__(self, config: SimpleConvConfig) -> None:$/;"	m	class:SimpleConv
__init__	vis_models/metrics/representation_similarity/cka/cka_minibatch.py	/^    def __init__(self) -> None:$/;"	m	class:MinibatchCKA
__init__	vis_models/training/adversarial.py	/^    def __init__($/;"	m	class:AdversarialTraining
__init__	vis_models/training/supervised.py	/^    def __init__($/;"	m	class:SupervisedLearning
__init__	vis_models/training/trainer.py	/^    def __init__($/;"	m	class:Trainer
__len__	tests/test_training.py	/^    def __len__(self) -> int:$/;"	m	class:TestDataset	file:
__len__	vis_models/inference_recording/inference_record.py	/^    def __len__(self) -> int:$/;"	m	class:InferenceRecord	file:
_append_directories	vis_models/io/dirs.py	/^def _append_directories($/;"	f
_create_metric	vis_models/training/supervised.py	/^def _create_metric($/;"	f
_make_dense_layers	vis_models/architectures/cifar/densenet.py	/^    def _make_dense_layers(self, block, in_planes, nblock):$/;"	m	class:DenseNet
_make_layer	vis_models/architectures/cifar/resnet.py	/^    def _make_layer(self, block, planes, num_blocks, stride):$/;"	m	class:ResNet
_make_layers	vis_models/architectures/cifar/vgg.py	/^    def _make_layers(self, cfg):$/;"	m	class:VGG
activation_monitor_hook	vis_models/inference_recording/with_intermediate.py	/^    def activation_monitor_hook($/;"	f	function:intermediate_representations
add_minibatch	vis_models/metrics/representation_similarity/cka/cka_minibatch.py	/^    def add_minibatch(self, X: torch.Tensor, Y: torch.Tensor) -> None:$/;"	m	class:MinibatchCKA
approx_equal	tests/test_CKA_minibatch.py	/^def approx_equal(x: float, y: float) -> bool:$/;"	f
asdict	vis_models/training/adversarial.py	/^from dataclasses import dataclass, asdict$/;"	i
callbacks	tests/test_training.py	/^        callbacks=[$/;"	v	class:test_training.SimpleConvTraining
cast	vis_models/architectures/access.py	/^from typing import Callable, cast$/;"	i
cast	vis_models/architectures/cifar/densenet.py	/^from typing import cast$/;"	i
cast	vis_models/architectures/cifar/resnet.py	/^from typing import cast$/;"	i
cast	vis_models/architectures/cifar/vgg.py	/^from typing import cast$/;"	i
cast	vis_models/architectures/utils/fine_tuning.py	/^from typing import cast$/;"	i
centering	vis_models/metrics/representation_similarity/cka/cka.py	/^def centering(K: torch.Tensor) -> torch.Tensor:$/;"	f
cfg	vis_models/architectures/cifar/vgg.py	/^cfg = {$/;"	v
cifar_last_getters	vis_models/architectures/access.py	/^cifar_last_getters = {$/;"	v
cifar_last_setters	vis_models/architectures/access.py	/^cifar_last_setters = {$/;"	v
cifar_models	vis_models/architectures/create.py	/^cifar_models = {$/;"	v
cifar_penultimate_getters	vis_models/architectures/access.py	/^cifar_penultimate_getters = {$/;"	v
cka	vis_models/metrics/representation_similarity/cka/cka_minibatch.py	/^from . import cka$/;"	i
compat_forward	vis_models/training/adversarial.py	/^        def compat_forward($/;"	f	function:AdversarialTraining.__init__
concatenate	vis_models/inference_recording/__init__.py	/^from .inference_record import InferenceRecord, to_inference_record, concatenate$/;"	i
concatenate	vis_models/inference_recording/inference_record.py	/^def concatenate(maps: Iterable[LayerRepresentations]) -> LayerRepresentations:$/;"	f
configure_optimizers	tests/test_training.py	/^        def configure_optimizers(self):$/;"	m	class:test_training.SimpleConvTraining
configure_optimizers	vis_models/training/supervised.py	/^    def configure_optimizers(self):$/;"	m	class:SupervisedLearning
contextmanager	vis_models/inference_recording/with_intermediate.py	/^from contextlib import contextmanager$/;"	i
conv_layer_filters	tests/test_training.py	/^        conv_layer_filters=[16, 32, 64],$/;"	v	class:test_training.SimpleConvTraining
create_model	vis_models/architectures/__init__.py	/^from .create import ModelConfig, create_model$/;"	i
create_model	vis_models/architectures/create.py	/^def create_model($/;"	f
dataclass	vis_models/architectures/create.py	/^from dataclasses import dataclass$/;"	i
dataclass	vis_models/architectures/simple_conv.py	/^from dataclasses import dataclass$/;"	i
dataclass	vis_models/inference_recording/inference_record.py	/^from dataclasses import dataclass$/;"	i
dataclass	vis_models/training/adversarial.py	/^from dataclasses import dataclass, asdict$/;"	i
datetime	vis_models/io/logging.py	/^import datetime$/;"	i
densenet	vis_models/architectures/create.py	/^from .cifar import resnet, densenet, vgg$/;"	i
densenet_cifar	vis_models/architectures/cifar/densenet.py	/^def densenet_cifar(num_classes: int):$/;"	f
densenet_set_last	vis_models/architectures/access.py	/^def densenet_set_last(model: Module, layer: Module) -> Module:$/;"	f
disable_gradients	vis_models/architectures/utils/fine_tuning.py	/^def disable_gradients(model: nn.Module) -> nn.Module:$/;"	f
expansion	vis_models/architectures/cifar/resnet.py	/^    expansion = 1$/;"	v	class:BasicBlock
expansion	vis_models/architectures/cifar/resnet.py	/^    expansion = 4$/;"	v	class:Bottleneck
fc_layer_units	tests/test_training.py	/^        fc_layer_units=[1024, 512, 10],$/;"	v	class:test_training.SimpleConvTraining
forward	vis_models/architectures/cifar/densenet.py	/^    def forward(self, x):$/;"	m	class:Bottleneck
forward	vis_models/architectures/cifar/densenet.py	/^    def forward(self, x):$/;"	m	class:DenseNet
forward	vis_models/architectures/cifar/densenet.py	/^    def forward(self, x):$/;"	m	class:Transition
forward	vis_models/architectures/cifar/resnet.py	/^    def forward(self, x):$/;"	m	class:BasicBlock
forward	vis_models/architectures/cifar/resnet.py	/^    def forward(self, x):$/;"	m	class:Bottleneck
forward	vis_models/architectures/cifar/resnet.py	/^    def forward(self, x):$/;"	m	class:ResNet
forward	vis_models/architectures/cifar/vgg.py	/^    def forward(self, x):$/;"	m	class:VGG
forward	vis_models/architectures/lib/recorded_sequential.py	/^    def forward(self, x: torch.Tensor) -> InferenceRecord:$/;"	m	class:RecordedSequential
forward	vis_models/architectures/simple_conv.py	/^    def forward(self, x: torch.Tensor) -> InferenceRecord:$/;"	m	class:SimpleConv
forward	vis_models/training/adversarial.py	/^    def forward($/;"	m	class:AdversarialTraining
get_artifacts_dir	vis_models/io/dirs.py	/^def get_artifacts_dir() -> Path:$/;"	f
get_best_checkpoint_path	vis_models/io/persistence.py	/^def get_best_checkpoint_path($/;"	f
get_checkpoints_callback	tests/test_training.py	/^from models.utils import get_tb_logger, get_checkpoints_callback$/;"	i
get_checkpoints_callback	vis_models/io/persistence.py	/^def get_checkpoints_callback($/;"	f
get_checkpoints_callback	vis_models/training/trainer.py	/^from ..io.persistence import get_checkpoints_callback$/;"	i
get_checkpoints_dir	vis_models/io/dirs.py	/^def get_checkpoints_dir($/;"	f
get_checkpoints_dir	vis_models/io/persistence.py	/^from .dirs import get_checkpoints_dir, recreate_dir$/;"	i
get_last_layer	vis_models/architectures/access.py	/^def get_last_layer(model_config: ModelConfig, model: Module) -> Module:$/;"	f
get_last_layer	vis_models/architectures/cifar/densenet.py	/^def get_last_layer(model: nn.Module) -> nn.Module:$/;"	f
get_last_layer	vis_models/architectures/cifar/resnet.py	/^def get_last_layer(model: nn.Module) -> nn.Module:$/;"	f
get_last_layer	vis_models/architectures/cifar/vgg.py	/^def get_last_layer(model: nn.Module) -> nn.Module:$/;"	f
get_last_layer	vis_models/architectures/utils/fine_tuning.py	/^from ..access import get_last_layer, set_last_layer$/;"	i
get_logging_dir	vis_models/io/dirs.py	/^def get_logging_dir($/;"	f
get_logging_dir	vis_models/io/logging.py	/^from .dirs import get_logging_dir, recreate_dir$/;"	i
get_penultimate_layer	vis_models/architectures/access.py	/^def get_penultimate_layer(model_config: ModelConfig, model: Module) -> Module:$/;"	f
get_penultimate_layer	vis_models/architectures/cifar/densenet.py	/^def get_penultimate_layer(model: nn.Module) -> nn.Module:$/;"	f
get_penultimate_layer	vis_models/architectures/cifar/resnet.py	/^def get_penultimate_layer(model: nn.Module) -> nn.Module:$/;"	f
get_penultimate_layer	vis_models/architectures/cifar/vgg.py	/^def get_penultimate_layer(model: nn.Module) -> nn.Module:$/;"	f
get_results_dir	vis_models/io/dirs.py	/^def get_results_dir($/;"	f
get_tb_logger	tests/test_training.py	/^from models.utils import get_tb_logger, get_checkpoints_callback$/;"	i
get_tb_logger	vis_models/io/logging.py	/^def get_tb_logger($/;"	f
get_tb_logger	vis_models/training/trainer.py	/^from ..io.logging import get_tb_logger$/;"	i
gpus	tests/test_training.py	/^        gpus=0,$/;"	v	class:test_training.SimpleConvTraining
hook	vis_models/inference_recording/with_intermediate.py	/^        def hook($/;"	f	function:intermediate_representations.activation_monitor_hook
id	tests/test_training.py	/^        id="test",$/;"	v	class:test_training.SimpleConvTraining
imagenet_last_getters	vis_models/architectures/access.py	/^imagenet_last_getters = {$/;"	v
imagenet_last_setters	vis_models/architectures/access.py	/^imagenet_last_setters = {$/;"	v
imagenet_models	vis_models/architectures/create.py	/^imagenet_models = {$/;"	v
imagenet_penultimate_getters	vis_models/architectures/access.py	/^imagenet_penultimate_getters = {$/;"	v
input_size	tests/test_training.py	/^        input_size=32,$/;"	v	class:test_training.SimpleConvTraining
intermediate_representations	vis_models/inference_recording/__init__.py	/^from .with_intermediate import intermediate_representations$/;"	i
intermediate_representations	vis_models/inference_recording/with_intermediate.py	/^def intermediate_representations($/;"	f
kernel_CKA	vis_models/metrics/representation_similarity/cka/cka.py	/^def kernel_CKA($/;"	f
kernel_HSIC	vis_models/metrics/representation_similarity/cka/cka.py	/^def kernel_HSIC($/;"	f
limit_train_batches	tests/test_training.py	/^        limit_train_batches=1,$/;"	v	class:test_training.SimpleConvTraining
linear_CKA	vis_models/metrics/representation_similarity/cka/__init__.py	/^from .cka import linear_CKA$/;"	i
linear_CKA	vis_models/metrics/representation_similarity/cka/cka.py	/^def linear_CKA(X: torch.Tensor, Y: torch.Tensor) -> torch.Tensor:$/;"	f
linear_HSIC	vis_models/metrics/representation_similarity/cka/cka.py	/^def linear_HSIC(X: torch.Tensor, Y: torch.Tensor) -> torch.Tensor:$/;"	f
ln	vis_models/architectures/simple_conv.py	/^from ..wrapping import layer_names as ln$/;"	i
logger	tests/test_training.py	/^        logger=get_tb_logger(tmp_path \/ "artifacts\/logs\/test_training"),$/;"	v	class:test_training.SimpleConvTraining
math	vis_models/architectures/cifar/densenet.py	/^import math$/;"	i
math	vis_models/architectures/simple_conv.py	/^import math$/;"	i
max_epochs	tests/test_training.py	/^        max_epochs=1,$/;"	v	class:test_training.SimpleConvTraining
monitored_forward	vis_models/inference_recording/with_intermediate.py	/^    def monitored_forward(batch: DataSample) -> InferenceRecord:$/;"	f	function:intermediate_representations
nn	vis_models/architectures/cifar/densenet.py	/^import torch.nn as nn$/;"	i
nn	vis_models/architectures/cifar/densenet.py	/^import torch.nn.functional as F$/;"	i
nn	vis_models/architectures/cifar/resnet.py	/^import torch.nn as nn$/;"	i
nn	vis_models/architectures/cifar/resnet.py	/^import torch.nn.functional as F$/;"	i
nn	vis_models/architectures/cifar/vgg.py	/^import torch.nn as nn$/;"	i
nn	vis_models/architectures/lib/recorded_sequential.py	/^import torch.nn as nn$/;"	i
nn	vis_models/architectures/simple_conv.py	/^import torch.nn as nn$/;"	i
nn	vis_models/architectures/utils/fine_tuning.py	/^from torch import nn$/;"	i
nn	vis_models/inference_recording/with_intermediate.py	/^from torch import nn$/;"	i
nn	vis_models/training/supervised.py	/^import torch.nn.functional as F$/;"	i
os	vis_models/io/dirs.py	/^import os$/;"	i
pl	tests/test_training.py	/^import pytorch_lightning as pl$/;"	i
pl	vis_models/training/supervised.py	/^import pytorch_lightning as pl$/;"	i
pl	vis_models/training/trainer.py	/^import pytorch_lightning as pl$/;"	i
pl_callbacks	vis_models/io/persistence.py	/^from pytorch_lightning import callbacks as pl_callbacks$/;"	i
pl_loggers	vis_models/io/logging.py	/^from pytorch_lightning import loggers as pl_loggers$/;"	i
predictions	vis_models/inference_recording/inference_record.py	/^    def predictions(self) -> torch.Tensor:$/;"	m	class:InferenceRecord
prepare_torchvision_finetuning	vis_models/architectures/utils/fine_tuning.py	/^def prepare_torchvision_finetuning($/;"	f
rbf	vis_models/metrics/representation_similarity/cka/cka.py	/^def rbf(X: torch.Tensor, sigma: Optional[torch.Tensor] = None) -> torch.Tensor:$/;"	f
recreate_dir	vis_models/io/dirs.py	/^def recreate_dir(directory: Path) -> None:$/;"	f
recreate_dir	vis_models/io/logging.py	/^from .dirs import get_logging_dir, recreate_dir$/;"	i
recreate_dir	vis_models/io/persistence.py	/^from .dirs import get_checkpoints_dir, recreate_dir$/;"	i
reset	vis_models/metrics/representation_similarity/cka/cka_minibatch.py	/^    def reset(self) -> None:$/;"	m	class:MinibatchCKA
resnet	vis_models/architectures/create.py	/^from .cifar import resnet, densenet, vgg$/;"	i
resnet_set_last	vis_models/architectures/access.py	/^def resnet_set_last(model: Module, layer: Module) -> Module:$/;"	f
set_artifacts_dir	vis_models/io/dirs.py	/^def set_artifacts_dir(dir: Union[str, Path]):$/;"	f
set_last_layer	vis_models/architectures/access.py	/^def set_last_layer($/;"	f
set_last_layer	vis_models/architectures/cifar/densenet.py	/^def set_last_layer(model: nn.Module, layer: nn.Module) -> nn.Module:$/;"	f
set_last_layer	vis_models/architectures/cifar/resnet.py	/^def set_last_layer(model: nn.Module, layer: nn.Module) -> nn.Module:$/;"	f
set_last_layer	vis_models/architectures/cifar/vgg.py	/^def set_last_layer(model: nn.Module, layer: nn.Module) -> nn.Module:$/;"	f
set_last_layer	vis_models/architectures/utils/fine_tuning.py	/^from ..access import get_last_layer, set_last_layer$/;"	i
test	vis_models/architectures/cifar/densenet.py	/^def test():$/;"	f
test	vis_models/architectures/cifar/resnet.py	/^def test():$/;"	f
test	vis_models/architectures/cifar/vgg.py	/^def test():$/;"	f
test_different_activations	tests/test_CKA_minibatch.py	/^def test_different_activations():$/;"	f
test_reset_different	tests/test_CKA_minibatch.py	/^def test_reset_different():$/;"	f
test_same_activations	tests/test_CKA_minibatch.py	/^def test_same_activations():$/;"	f
test_step	vis_models/training/supervised.py	/^    def test_step(self, batch, batch_idx: int) -> None:$/;"	m	class:SupervisedLearning
test_training	tests/test_training.py	/^def test_training(tmp_path: Path):$/;"	f
to_inference_record	vis_models/inference_recording/__init__.py	/^from .inference_record import InferenceRecord, to_inference_record, concatenate$/;"	i
to_inference_record	vis_models/inference_recording/inference_record.py	/^def to_inference_record($/;"	f
to_inference_record	vis_models/inference_recording/with_intermediate.py	/^from .inference_record import InferenceRecord, to_inference_record$/;"	i
to_inference_record	vis_models/inference_recording/wrappers.py	/^from .inference_record import InferenceRecord, to_inference_record$/;"	i
to_inference_record	vis_models/training/supervised.py	/^from ..inference_recording import to_inference_record$/;"	i
torch	tests/test_CKA_minibatch.py	/^import torch$/;"	i
torch	tests/test_training.py	/^import torch$/;"	i
torch	vis_models/architectures/cifar/densenet.py	/^import torch$/;"	i
torch	vis_models/architectures/cifar/densenet.py	/^import torch.nn as nn$/;"	i
torch	vis_models/architectures/cifar/densenet.py	/^import torch.nn.functional as F$/;"	i
torch	vis_models/architectures/cifar/resnet.py	/^import torch$/;"	i
torch	vis_models/architectures/cifar/resnet.py	/^import torch.nn as nn$/;"	i
torch	vis_models/architectures/cifar/resnet.py	/^import torch.nn.functional as F$/;"	i
torch	vis_models/architectures/cifar/vgg.py	/^import torch$/;"	i
torch	vis_models/architectures/cifar/vgg.py	/^import torch.nn as nn$/;"	i
torch	vis_models/architectures/lib/recorded_sequential.py	/^import torch$/;"	i
torch	vis_models/architectures/lib/recorded_sequential.py	/^import torch.nn as nn$/;"	i
torch	vis_models/architectures/simple_conv.py	/^import torch$/;"	i
torch	vis_models/architectures/simple_conv.py	/^import torch.nn as nn$/;"	i
torch	vis_models/inference_recording/inference_record.py	/^import torch$/;"	i
torch	vis_models/inference_recording/with_intermediate.py	/^import torch$/;"	i
torch	vis_models/inference_recording/wrappers.py	/^import torch$/;"	i
torch	vis_models/metrics/representation_similarity/cka/cka.py	/^import torch$/;"	i
torch	vis_models/metrics/representation_similarity/cka/cka_minibatch.py	/^import torch$/;"	i
torch	vis_models/training/adversarial.py	/^import torch$/;"	i
torch	vis_models/training/supervised.py	/^import torch$/;"	i
torch	vis_models/training/supervised.py	/^import torch.nn.functional as F$/;"	i
torchmetrics	vis_models/training/supervised.py	/^import torchmetrics$/;"	i
torchvision	vis_models/architectures/create.py	/^import torchvision$/;"	i
training_step	vis_models/training/supervised.py	/^    def training_step(self, batch) -> torch.Tensor:$/;"	m	class:SupervisedLearning
transforms	tests/test_training.py	/^from torchvision import transforms$/;"	i
unbiased_linear_HSIC	vis_models/metrics/representation_similarity/cka/cka_minibatch.py	/^def unbiased_linear_HSIC(X: torch.Tensor, Y: torch.Tensor) -> torch.Tensor:$/;"	f
validation_step	vis_models/training/supervised.py	/^    def validation_step(self, batch, batch_idx: int) -> torch.Tensor:$/;"	m	class:SupervisedLearning
value	vis_models/metrics/representation_similarity/cka/cka_minibatch.py	/^    def value(self, reset: bool = False) -> torch.Tensor:$/;"	m	class:MinibatchCKA
vgg	vis_models/architectures/create.py	/^from .cifar import resnet, densenet, vgg$/;"	i
vgg_set_last	vis_models/architectures/access.py	/^def vgg_set_last(model: Module, layer: Module) -> Module:$/;"	f
with_wrappers	vis_models/inference_recording/__init__.py	/^from .wrappers import with_wrappers$/;"	i
with_wrappers	vis_models/inference_recording/wrappers.py	/^def with_wrappers(model: torch.nn.Module) -> torch.nn.Module:$/;"	f
wrapped_forward	vis_models/inference_recording/wrappers.py	/^    def wrapped_forward(batch) -> InferenceRecord:$/;"	f	function:with_wrappers
