Code
Hub
Workspaces
Following
Trending
Connect
MCP
copy
Create free account
hub
/
github.com/M-Nauta/ProtoTree
/ functions
Functions
180 in github.com/M-Nauta/ProtoTree
⨍
Functions
180
◇
Types & classes
17
Method
__init__
(self, num_input_features, num_output_features)
features/densenet_features.py:75
Method
__init__
(self, growth_rate=32, block_config=(6, 12, 24, 16), num_init_features=64, bn_size=4, drop_ra
features/densenet_features.py:101
Method
__init__
(self, inplanes, planes, stride=1, downsample=None)
features/resnet_features.py:79
Method
__init__
(self, block, layers, num_classes=1000, zero_init_residual=False)
features/resnet_features.py:130
Method
__init__
(self, inp, oup, stride, expand_ratio)
features/mobilenet_features.py:19
Method
__init__
(self, num_features=20, num_classes=10, width_mult=1.0)
features/mobilenet_features.py:48
Method
__init__
(self, index: int, num_classes: int, args: argparse.Name
prototree/leaf.py:13
Method
__init__
(self, index: int)
prototree/node.py:8
Method
__init__
(self, index: int, l: Node, r: Node, a
prototree/branch.py:15
Method
__init__
(self, num_classes: int, feature_net: torch.nn.Module, a
prototree/prototree.py:23
Method
__init__
(self, log_dir: str)
util/log.py:12
Method
__init__
Create a new L2Conv2D layer :param num_prototypes: The number of prototypes in the layer :param num_features: The number o
util/l2conv.py:13
Method
__repr__
(self)
features/vgg_features.py:97
Method
__repr__
(self)
features/densenet_features.py:173
Method
__repr__
(self)
features/resnet_features.py:226
Method
_assign_depths
(node, d)
prototree/prototree.py:249
Method
_init_tree_recursive
(i: int, d: int)
prototree/prototree.py:301
Method
_set_parents_recursively
(node: Node)
prototree/prototree.py:321
Method
add_on_layers_require_grad
(self)
prototree/prototree.py:97
Method
block_conv_info
(self)
features/densenet_features.py:83
Method
block_conv_info
(self)
features/resnet_features.py:116
Method
branches
(self)
prototree/leaf.py:96
Method
branches
(self)
prototree/node.py:32
Method
branches
(self)
prototree/branch.py:102
Method
branches
(self)
prototree/prototree.py:258
Method
checkpoint_dir
(self)
util/log.py:31
Method
conv_info
(self)
features/vgg_features.py:88
Method
conv_info
(self)
features/densenet_features.py:167
Method
conv_info
(self)
features/resnet_features.py:210
Method
depth
(self)
prototree/leaf.py:112
Method
depth
(self)
prototree/node.py:48
Method
depth
(self)
prototree/branch.py:122
Method
depth
(self)
prototree/prototree.py:230
Method
features_require_grad
(self)
prototree/prototree.py:88
Method
forward
(self, x)
features/vgg_features.py:40
Method
forward
(self, x)
features/densenet_features.py:34
Method
forward
(self, x)
features/densenet_features.py:164
Method
forward
(self, x)
features/resnet_features.py:47
Method
forward
(self, x)
features/resnet_features.py:94
Method
forward
(self, x)
features/resnet_features.py:197
Method
forward
(self, x)
features/mobilenet_features.py:40
Method
forward
(self, x)
features/mobilenet_features.py:101
Method
forward
(self, *args, **kwargs)
prototree/node.py:12
Method
forward
(self, xs: torch.Tensor, **kwargs)
prototree/branch.py:28
Method
forward
(self, xs: torch.Tensor, sampling_strategy: str = SAMPLING_STRATEGIES[0], #
prototree/prototree.py:105
Method
index
(self)
prototree/node.py:16
Function
init_weights_kaiming
(m)
util/init.py:72
Function
init_weights_xavier
(m)
util/init.py:68
Method
leaves
(self)
prototree/leaf.py:92
Method
leaves
(self)
prototree/node.py:28
Method
leaves
(self)
prototree/branch.py:98
Method
leaves
(self)
prototree/prototree.py:262
Method
leaves_require_grad
(self)
prototree/prototree.py:71
Function
load_args
Load the pickled arguments from the specified directory :param directory_path: The path to the directory from which the arguments should be
util/args.py:180
Function
load_state
(directory_path: str, device)
util/init.py:7
Method
log_args
(self, args: argparse.Namespace)
util/log.py:76
Method
log_dir
(self)
util/log.py:27
Method
metadata_dir
(self)
util/log.py:35
Function
mobilenet_v2
Constructs a MobileNetV2 architecture from `"MobileNetV2: Inverted Residuals and Linear Bottlenecks" <https://arxiv.org/abs/1801.04381>`_.
features/mobilenet_features.py:107
Method
node_depths
(self)
prototree/prototree.py:247
Method
nodes
(self)
prototree/node.py:24
Method
nodes
(self)
prototree/prototree.py:239
Method
nodes_by_index
(self)
prototree/leaf.py:100
Method
nodes_by_index
(self)
prototree/node.py:36
Method
nodes_by_index
(self)
prototree/branch.py:108
Method
nodes_by_index
(self)
prototree/prototree.py:243
Method
num_branches
(self)
prototree/leaf.py:104
Method
num_branches
(self)
prototree/node.py:40
Method
num_branches
(self)
prototree/branch.py:114
Method
num_branches
(self)
prototree/prototree.py:266
Method
num_leaves
(self)
prototree/leaf.py:108
Method
num_leaves
(self)
prototree/node.py:44
Method
num_leaves
(self)
prototree/branch.py:118
Method
num_leaves
(self)
prototree/prototree.py:270
Function
project
(tree: ProtoTree, project_loader: DataLoader, device, args: argparse.Na
prototree/project.py:10
Method
prototypes_require_grad
(self)
prototree/prototree.py:80
Method
requires_grad
(self)
prototree/leaf.py:80
Function
resnet50_features_inat
Constructs a ResNet-50 model. Args: pretrained (bool): If True, returns a model pre-trained on Inaturalist2017
features/resnet_features.py:270
Method
root
(self)
prototree/prototree.py:67
Method
size
(self)
prototree/node.py:20
← previous
101–180 of 180, ranked by callers