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github.com/SPOClab-ca/dn3
/ functions
Functions
482 in github.com/SPOClab-ca/dn3
⨍
Functions
482
◇
Types & classes
87
Method
features_forward
(self, x, **kwargs)
dn3/trainable/models.py:256
Method
features_forward
(self, x)
dn3/trainable/models.py:316
Method
features_forward
(self, x)
dn3/trainable/models.py:376
Method
features_forward
(self, x)
dn3/trainable/models.py:425
Method
forward
(self, pred, target)
dn3/utils.py:143
Method
forward
(self, x)
dn3/trainable/layers.py:13
Method
forward
(self, x)
dn3/trainable/layers.py:21
Method
forward
(self, x)
dn3/trainable/layers.py:26
Method
forward
(self, x)
dn3/trainable/layers.py:35
Method
forward
(self, *x)
dn3/trainable/layers.py:40
Method
forward
(self, *x)
dn3/trainable/layers.py:57
Method
forward
(self, x)
dn3/trainable/layers.py:66
Method
forward
(self, input, **kwargs)
dn3/trainable/layers.py:92
Method
forward
(self, x)
dn3/trainable/layers.py:140
Method
forward
(self, x)
dn3/trainable/layers.py:172
Method
forward
(self, x)
dn3/trainable/layers.py:196
Method
forward
(self, x)
dn3/trainable/layers.py:242
Method
forward
(self, x)
dn3/trainable/layers.py:330
Method
forward
(self, x, mask_t=None, mask_c=None)
dn3/trainable/layers.py:360
Method
forward
(self, x)
dn3/trainable/layers.py:390
Method
forward
(self, x, mask_t=None, mask_c=None)
dn3/trainable/layers.py:461
Method
forward
(self, x)
dn3/trainable/models.py:32
Method
forward
(self, *x)
dn3/trainable/models.py:113
Method
forward
(self, *inputs)
dn3/trainable/experimental.py:126
Method
forward
(self, *inputs)
dn3/trainable/processes.py:645
Method
forward
(self, *inputs)
dn3/trainable/processes.py:912
Method
forward
(self, *inputs)
dn3/trainable/processes.py:998
Method
forward
(self, x)
tests/testTrainables.py:20
Method
found_best
()
dn3/trainable/processes.py:396
Method
freeze_features
(self, unfreeze=False)
dn3/trainable/layers.py:265
Method
freeze_features
(self, unfreeze=False, finetuning=False)
dn3/trainable/layers.py:491
Method
freeze_features
(self, unfreeze=False)
dn3/trainable/models.py:52
Method
from_dataset
(cls, dataset: DN3ataset, **modelargs)
dn3/trainable/models.py:57
Method
from_precollected_statistics
(dataset, precollected)
dn3/data/utils.py:172
Method
get_all
(self)
dn3/data/dataset.py:201
Function
get_dataset_max_and_min
This utility function is used early on to determine the *data_max* and *data_min* parameters that are added to the configuratron to properly
dn3/data/utils.py:74
Function
get_largest_trial_id
This utility is for determining the largest trial id from a dataset. Parameters ---------- dataset: Dataset trial_id_offset: int
dn3/data/utils.py:112
Method
get_pop
(key, default=None)
dn3/configuratron/config.py:188
Method
get_raw
(self, pseudo_path)
dn3/configuratron/extensions.py:48
Method
get_start_end
(tid, sid, trial_id)
dn3/data/utils.py:328
Method
get_targets
(self)
dn3/data/dataset.py:432
Method
get_targets
Collect all the targets (i.e. labels) that this Thinker's data is annotated with. Returns ------- targets: np.ndarra
dn3/data/dataset.py:1135
Method
get_thinkers
(self)
dn3/data/dataset.py:1240
Method
init_bert_params
(self, module)
dn3/trainable/layers.py:446
Method
init_from_contextualizer
(self, filename)
dn3/trainable/layers.py:377
Function
init_seed
Set a constant random seed to have reproducible runs Parameters ---------- seed hard: bool If you are having trouble rep
dn3/utils.py:12
Method
internal_loss
(self, forward_pass_tensors)
dn3/trainable/models.py:35
Method
is_nested
(split: list)
dn3/data/dataset.py:1093
Function
kappa
(y_t, y_p)
dn3/metrics/base.py:80
Method
keep_window
Rejects any statistics that lie outside the specified windown limits of low and high. If one is not specified, one side of the window
dn3/data/utils.py:272
Method
load
(self, filename, strict=True)
dn3/trainable/layers.py:497
Method
load
(self, filename, strict=True)
dn3/trainable/models.py:45
Method
load_and_prepare
(sess)
dn3/configuratron/config.py:562
Method
make_new_classification_layer
(self)
dn3/trainable/models.py:204
Method
make_new_classification_layer
(self)
dn3/trainable/experimental.py:48
Method
new_channels
This is an optional method that indicates the transformation modifies the representation and/or presence of channels. Parame
dn3/transforms/instance.py:54
Method
new_channels
(self, old_channels: np.ndarray)
dn3/transforms/instance.py:375
Method
new_channels
(self, old_channels)
dn3/transforms/instance.py:391
Method
new_channels
(self, old_channels)
dn3/transforms/instance.py:534
Method
new_channels
(self, old_channels)
dn3/trainable/experimental.py:154
Method
new_sequence_length
This is an optional method that indicates the transformation modifies the length of the acquired extracts, specified in number of sam
dn3/transforms/instance.py:88
Method
new_sequence_length
(self, old_sequence_length)
dn3/transforms/instance.py:168
Method
new_sequence_length
(self, old_sequence_length)
dn3/transforms/instance.py:212
Method
new_sequence_length
(self, old_sequence_length)
dn3/transforms/instance.py:232
Method
new_sequence_length
(self, old_sequence_length)
dn3/transforms/instance.py:299
Method
new_sequence_length
(self, old_sequence_length)
dn3/transforms/instance.py:546
Method
new_sfreq
(self, old_sfreq)
dn3/transforms/instance.py:215
Method
new_sfreq
(self, old_sfreq)
dn3/transforms/instance.py:540
Method
num_features_for_classification
(self)
dn3/trainable/models.py:159
Method
num_features_for_classification
(self)
dn3/trainable/models.py:219
Method
num_features_for_classification
(self)
dn3/trainable/models.py:253
Method
num_features_for_classification
(self)
dn3/trainable/models.py:313
Method
num_features_for_classification
(self)
dn3/trainable/models.py:373
Method
num_features_for_classification
(self)
dn3/trainable/models.py:417
Method
num_features_for_classification
(self)
dn3/trainable/experimental.py:73
Method
package_multiple_tensors
(batches: list)
dn3/trainable/processes.py:348
Method
pop_session
(self, session_id, apply_thinker_transform=True)
dn3/data/dataset.py:537
Method
pop_thinker
(self, person_id, apply_ds_transforms=False)
dn3/data/dataset.py:836
Method
preprocess
(self, preprocessor, apply_transform=True)
dn3/configuratron/config.py:798
Method
preprocess
Applies a preprocessor to the dataset Parameters ---------- preprocessor : Preprocessor A pre
dn3/data/dataset.py:116
Method
preprocess
(self, preprocessor: Preprocessor, apply_transform=True)
dn3/data/dataset.py:345
Method
preprocess
(self, preprocessor: Preprocessor, apply_transform=True, **kwargs)
dn3/data/dataset.py:414
Method
preprocess
Applies a preprocessor to the dataset Parameters ---------- preprocessor : Preprocessor A pre
dn3/data/dataset.py:892
Method
preprocess
(self, preprocessor: Preprocessor, apply_transform=True)
dn3/data/dataset.py:1243
Method
print_training_metrics
(epoch, iteration=None)
dn3/trainable/processes.py:534
Method
raw
(self)
dn3/configuratron/config.py:792
Method
reject
(self, thinker=None, session=None, trial=None, bulk=None)
dn3/data/utils.py:301
Method
rejected_stats
(self)
dn3/data/utils.py:206
Method
reset
(self)
dn3/trainable/models.py:110
Method
safe_mode
This allows switching *safe_mode* on or off. When safe_mode is on, if data is ever NaN, it is captured before being returned and a re
dn3/data/dataset.py:880
Method
save
(self, filename)
dn3/trainable/layers.py:501
Method
save
(self, filename)
dn3/trainable/models.py:49
Method
save
(self, filename, ignore_classifier=True)
dn3/trainable/experimental.py:65
Method
sequence_length
Returns ------- sequence_length: int, list The length of each instance in number of samples
dn3/data/dataset.py:58
Method
sequence_length
(self)
dn3/data/dataset.py:220
Method
sequence_length
(self)
dn3/data/dataset.py:513
Method
sequence_length
(self)
dn3/data/dataset.py:939
Method
sequence_length
(self)
dn3/data/dataset.py:1237
Method
sess_cb
(session: RawTorchRecording)
tests/testConfig.py:171
Method
setUp
(self)
tests/testConfig.py:65
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