Functions — github.com/BlackHC/BatchBALD

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Functions305 in github.com/BlackHC/BatchBALD

⨍ Functions 305◇ Types & classes 28

Functionget_vip_args

(store)

src/al_notebook/results_loader.py:507

Functiongroupby_dict

(d: dict, *, key_kv=None, key_k=None, key_v=None, agg=None)

src/al_notebook/results_loader.py:141

Methodinitialize_weights

src/joint_entropy/test_matmuls.py:77

Functioninner

()

src/joint_entropy/unoptimized/test_exact_batch.py:116

Functioninner

()

src/joint_entropy/unoptimized/test_sampling_batch.py:138

Functioninner

()

src/joint_entropy/unoptimized/test_exact_joint_probs.py:130

Functioninner

()

src/joint_entropy/unoptimized/test_sampling_sample.py:164

Functioninner

(kv)

src/al_notebook/results_loader.py:84

Functionjoint_probs_M_K

(probs_N_K_C, prev_joint_probs_M_K=None)

src/joint_entropy/exact.py:23

Functionjoint_probs_M_K

(probs_N_K_C, prev_joint_probs_M_K=None)

src/joint_entropy/unoptimized/exact.py:5

Functionload_experiment_results

(*experiments, incl_current=False, incl_current_vm=False)

src/al_notebook/results_loader.py:519

Functionlog

(_)

src/ignite_utils.py:21

Functionlog_results

(engine: ignite.engine.Engine, name)

src/ignite_utils.py:31

Functionmax_entropy_acquisition_function

(logits_b_K_C)

src/acquisition_functions.py:26

Methodmc_forward_impl

(self, input: Tensor)

src/emnist_model.py:24

Methodmc_forward_impl

(self, input: Tensor)

src/mnist_model.py:20

Methodmc_forward_impl

src/torch_utils.py:112

Functionmean_stddev_acquisition_function

(logits_b_K_C)

src/acquisition_functions.py:22

Functionmnist_test

()

src/al_notebook/show_batch.py:25

Functionmnist_train

()

src/al_notebook/show_batch.py:10

Functionmutual_information

(logits_B_K_C)

src/torch_utils.py:100

Functionnan

()

src/al_notebook/results_loader.py:207

Methodnum_classes

(self)

src/dataset_enum.py:169

Functionon_complete

(_)

src/ignite_utils.py:9

Methodon_complete

(self, engine)

src/ignite_progress_bar.py:24

Methodon_completed

(self, _)

src/ignite_restoring_score_guard.py:106

Methodon_epoch_completed

(self, _)

src/ignite_restoring_score_guard.py:87

Methodon_iteration_complete

(self, engine)

src/ignite_progress_bar.py:27

Methodon_start

(self, engine)

src/ignite_progress_bar.py:17

Functionout_of_patience

()

src/train_model.py:47

Functionpandas_accuracies

Creates a pandas DataFrame from the accuracies in a dict of stores.

src/al_notebook/results_loader.py:252

Functionpartition_dataset

(dataset: np.ndarray, mask)

src/torch_utils.py:117

Functionplot_aggregated_groups

( grouped: Dict[object, rl.AggregateAccuracies], key2text=None, axes=None, show_num_trials=Tru

src/al_notebook/plots.py:90

Functionplot_aggregated_groups_sample_points

( grouped: Dict[object, rl.AggregateAccuracies], key2text=None, axes=None, show_num_trials=Tru

src/al_notebook/plots.py:69

Functionplot_save

(output_path, **kwargs)

src/al_notebook/plots.py:111

Functionprint_global_torch_tensors

(line, local_ns)

src/al_notebook/torch_utils.py:23

Functionprobs_B_K_C

(B, K, C, torch_device)

src/joint_entropy/test_matmuls.py:65

Functionprobs_B_K_C

(B, K, C, torch_device)

src/joint_entropy/unoptimized/test_exact_batch.py:86

Functionprobs_B_K_C

(B, K, C, torch_device)

src/joint_entropy/unoptimized/test_sampling_batch.py:108

Functionprobs_B_K_C

(B, K, C, torch_device)

src/joint_entropy/unoptimized/test_exact_joint_probs.py:100

Functionprobs_B_K_C

(B, K, C, torch_device)

src/joint_entropy/unoptimized/test_sampling_sample.py:134

Functionprobs_N_K_C

(N, K, C, torch_device)

src/joint_entropy/unoptimized/test_exact_batch.py:91

Functionprobs_N_K_C

(N, K, C, torch_device)

src/joint_entropy/unoptimized/test_sampling_batch.py:113

Functionprobs_N_K_C

(N, K, C, torch_device)

src/joint_entropy/unoptimized/test_exact_joint_probs.py:105

Functionprobs_N_K_C

(N, K, C, torch_device)

src/joint_entropy/unoptimized/test_sampling_sample.py:139

Functionrandom_acquisition_function

(logits_b_K_C)

src/acquisition_functions.py:9

Functionrecover_model

(laaos_store, target_iteration=None)

src/recover_model.py:71

Functionresult_B_M_C

(B, M, C, torch_device)

src/joint_entropy/test_matmuls.py:70

Functionresult_B_M_C

(B, M, C, torch_device)

src/joint_entropy/unoptimized/test_exact_batch.py:96

Functionresult_B_M_C

(B, M, C, torch_device)

src/joint_entropy/unoptimized/test_sampling_batch.py:118

Functionresult_B_M_C

(B, M, C, torch_device)

src/joint_entropy/unoptimized/test_exact_joint_probs.py:110

Functionresult_B_M_C

(B, M, C, torch_device)

src/joint_entropy/unoptimized/test_sampling_sample.py:144

Functionsample_M_K

(probs_N_K_C, S=1000)

src/joint_entropy/sampling.py:28

Functionsample_M_K

(probs_N_K_C, S=1000)

src/joint_entropy/unoptimized/sampling.py:8

Functionsample_M_K_unified

(probs_N_K_C, S=1000)

src/joint_entropy/sampling.py:9

Functionsamples_M_K

(M, K, torch_device)

src/joint_entropy/test_matmuls.py:60

Functionsamples_M_K

(M, K, torch_device)

src/joint_entropy/unoptimized/test_exact_batch.py:81

Functionsamples_M_K

(M, K, torch_device)

src/joint_entropy/unoptimized/test_sampling_batch.py:103

Functionsamples_M_K

(M, K, torch_device)

src/joint_entropy/unoptimized/test_exact_joint_probs.py:95

Functionsamples_M_K

(M, K, torch_device)

src/joint_entropy/unoptimized/test_sampling_sample.py:129

Functionsampling_module

(request)

src/joint_entropy/unoptimized/test_exact_batch.py:108

Functionsampling_module

(request)

src/joint_entropy/unoptimized/test_sampling_batch.py:130

Functionsampling_module

(request)

src/joint_entropy/unoptimized/test_exact_joint_probs.py:122

Functionsampling_module

(request)

src/joint_entropy/unoptimized/test_sampling_sample.py:156

Methodscorer

(self)

src/acquisition_functions.py:42

Functionset_dropout_p

(bayesian_net: Module, p)

src/mc_dropout.py:8

Functionshould_reduce_batch_size

(exception)

src/torch_utils.py:69

Functionshow_indices

(dataset, indices, **kwargs)

src/al_notebook/show_batch.py:45

Functionsort_dict

(d: dict, *, reverse=False, kv=None, k=None, v=None)

src/al_notebook/results_loader.py:136

Functiontest_acquisition_functions

(acquisition_function: acquisition_functions.AcquisitionFunction)

src/test_acquisition_functions.py:46

Functiontest_batch

(B, M, K, C, benchmark, probs_B_K_C, samples_M_K, exact_module: exact)

src/joint_entropy/unoptimized/test_exact_batch.py:113

Functiontest_batch

(B, M, K, C, benchmark, probs_B_K_C, samples_M_K, sampling_module: sampling)

src/joint_entropy/unoptimized/test_sampling_batch.py:135

Functiontest_batch_matmul

(B, K, M, benchmark, samples_M_K, probs_B_K_C, result_B_M_C)

src/joint_entropy/test_matmuls.py:74

Functiontest_check_input_permutation

(af_type: acquisition_functions.AcquisitionFunction)

src/test_acquisition_functions.py:75

Functiontest_exact_joint_entropy

()

src/joint_entropy/test_joint_entropy.py:42

Functiontest_find_additional_labels

()

src/test_torch_mnist.py:14

Functiontest_get_balanced_samples

()

src/test_torch_utils.py:8

Functiontest_joint_probs

(N, M, K, C, benchmark, probs_N_K_C, samples_M_K, exact_module: exact)

src/joint_entropy/unoptimized/test_exact_joint_probs.py:127

Functiontest_looped_matmul

(B, K, M, benchmark, samples_M_K, probs_B_K_C, result_B_M_C)

src/joint_entropy/test_matmuls.py:86

Functiontest_partition_dataset

()

src/test_torch_utils.py:17

Functiontest_random_acquistion_function

()

src/test_acquisition_functions.py:19

Functiontest_sample_M_K

(S, N, K, C, benchmark, probs_N_K_C, sampling_module: sampling)

src/joint_entropy/unoptimized/test_sampling_sample.py:161

Functiontest_sampling_joint_entropy

()

src/joint_entropy/test_joint_entropy.py:55

Functiontest_unified_sampling_joint_entropy

()

src/joint_entropy/test_joint_entropy.py:73

Functionto_namedtuple

(obj, name)

src/al_notebook/results_loader.py:53

Functiontorch_device

(request)

src/joint_entropy/test_matmuls.py:30

Functiontorch_device

(request)

src/joint_entropy/unoptimized/test_exact_batch.py:41

Functiontorch_device

(request)

src/joint_entropy/unoptimized/test_sampling_batch.py:63

Functiontorch_device

(request)

src/joint_entropy/unoptimized/test_exact_joint_probs.py:55

Functiontorch_device

(request)

src/joint_entropy/unoptimized/test_sampling_sample.py:89

Functionvariation_ratios

(logits_b_K_C)

src/acquisition_functions.py:15

Functionvgg11

VGG 11-layer model (configuration "A") Args: pretrained (bool): If True, returns a model pre-trained on ImageNet progress (bool):

src/vgg_model.py:128

Functionvgg11_bn

VGG 11-layer model (configuration "A") with batch normalization Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

src/vgg_model.py:137

Functionvgg13

VGG 13-layer model (configuration "B") Args: pretrained (bool): If True, returns a model pre-trained on ImageNet progress (bool):

src/vgg_model.py:146

Functionvgg13_bn

VGG 13-layer model (configuration "B") with batch normalization Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

src/vgg_model.py:155

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