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Functions175 in github.com/GT-RIPL/AlwaysBeDreaming-DFCIL

⨍ Functions 175◇ Types & classes 32
↓ 53 callersMethodcuda
(self)
learners/default.py:375
↓ 29 callersMethodupdate
(self, val, n=1)
utils/metric.py:46
↓ 22 callersMethodtrain
(self, avg_metrics)
trainer.py:149
↓ 18 callersMethodtic
(self)
utils/metric.py:72
↓ 18 callersMethodvalidation
(self, dataloader, model=None, task_in = None, verbal = True)
learners/default.py:194
↓ 15 callersMethodforward
(self, x)
learners/kd.py:487
↓ 13 callersMethodcriterion
(self, logits, targets, data_weights)
learners/default.py:169
↓ 11 callersFunctionaccumulate_acc
(output, target, task, meter, topk)
learners/default.py:397
↓ 10 callersMethodload
(self)
dataloaders/loader.py:407
↓ 9 callersMethodload_dataset
(self, t, train=True)
dataloaders/loader.py:355
↓ 9 callersFunctionloss_fn_kd
Compute knowledge-distillation (KD) loss given [scores] and [target_scores]. Both [scores] and [target_scores] should be tensors, although [target
learners/default.py:401
↓ 9 callersMethodtoc
(self)
utils/metric.py:75
↓ 7 callersMethodgenerate_scores
(self, x, allowed_predictions=None, threshold=None)
learners/kd.py:758
↓ 7 callersMethodinit_optimizer
(self)
learners/default.py:290
↓ 6 callersMethoddata_weighting
(self, dataset, num_seen=None)
learners/default.py:241
↓ 6 callersMethodforward
(self, x)
learners/default.py:353
↓ 5 callersMethodload_model
(self, filename, class_only = False)
learners/kd.py:733
↓ 5 callersMethodnew_optimizer
(self, model)
learners/default.py:313
↓ 4 callersMethod__init__
(self, learner_config)
learners/kd.py:13
↓ 4 callersMethodappend_coreset
(self, only=False, interp=False)
dataloaders/loader.py:367
↓ 4 callersFunctioncheck_integrity
(fpath, md5)
dataloaders/utils.py:72
↓ 4 callersMethodcount_parameter
(self)
learners/default.py:369
↓ 3 callersMethod__init__
(self, block, num_blocks, num_classes=10)
models/resnet.py:77
↓ 3 callersMethod_conv
(self, channel_size, kernel_num, kernel_size_=4, stride_=2)
models/autoencoder.py:161
↓ 3 callersMethod_deconv
(self, channel_num, kernel_num,ReLU=True, kernel_size_=4, stride_=2)
models/autoencoder.py:180
↓ 3 callersMethod_linear
(self, in_size, out_size, relu=True)
models/autoencoder.py:216
↓ 3 callersMethod_make_layer
(self, block, planes, num_blocks, stride)
models/resnet.py:90
↓ 3 callersMethodforward
Apply gaussian filter to input. Arguments: input (torch.Tensor): Input to apply gaussian filter on. Returns:
learners/datafree_helper.py:241
↓ 3 callersMethodgenerate_scores_pen
(self, x)
learners/kd.py:779
↓ 3 callersMethodlearn_batch
(self, train_loader, train_dataset, model_save_dir, val_loader=None)
learners/kd.py:25
↓ 3 callersMethodtask_eval
(self, t_index, local=False)
trainer.py:136
↓ 3 callersMethodupdate_coreset
(self, coreset_size, seen)
dataloaders/loader.py:383
↓ 2 callersMethod__getitem__
Args: index (int): Index Returns: tuple: (image, target) where target is index of the target class
dataloaders/loader.py:110
↓ 2 callersMethod__init__
(self, zdim, in_channel, img_sz)
models/generator.py:14
↓ 2 callersMethod__init__
(self, learner_config)
learners/datafree.py:260
↓ 2 callersMethod_check_integrity
(self)
dataloaders/loader.py:515
↓ 2 callersMethodadd_valid_output_dim
(self, dim=0)
learners/default.py:361
↓ 2 callersMethodappend_coreset_ic
(self, post = False)
dataloaders/loader.py:166
↓ 2 callersMethodcombine_data
(self, data)
learners/datafree.py:205
↓ 2 callersMethodcombine_data
(self, data)
learners/dgr.py:211
↓ 2 callersMethodcount_parameter_gen
(self)
learners/datafree.py:245
↓ 2 callersMethodcount_parameter_gen
(self)
learners/dgr.py:198
↓ 2 callersMethoddecode
Pass latent variable activations through feedback connections, to give reconstructed image [image_recon].
models/autoencoder.py:140
↓ 2 callersFunctionget_data
(root_images)
dataloaders/loader.py:681
↓ 2 callersFunctionget_one_hot
(target,num_class)
learners/kd.py:794
↓ 2 callersFunctionjpg_image_to_array
Loads JPEG image into 3D Numpy array of shape (width, height, channels)
dataloaders/loader.py:670
↓ 2 callersMethodload_bic_dataset
(self, post = False)
dataloaders/loader.py:133
↓ 2 callersMethodpre_steps
(self)
learners/default.py:390
↓ 2 callersMethodsample
(self, teacher, dim, device, return_scores=True)
learners/datafree.py:255
↓ 2 callersMethodsave_model
(self, filename, class_only = False)
learners/kd.py:718
↓ 2 callersMethodupdate_coreset_ete
(self, coreset_size, seen, teacher)
dataloaders/loader.py:278
↓ 2 callersMethodupdate_coreset_ic
(self, coreset_size, seen, teacher)
dataloaders/loader.py:196
↓ 2 callersMethodupdate_model
(self, inputs, targets, target_KD = None)
learners/kd.py:167
↓ 1 callersMethod__init__
(self, solver, generator, gen_opt, img_shape, iters, class_idx, deep_inv_params, train = True, config=None)
learners/datafree_helper.py:25
↓ 1 callersMethod__init__
(self, solver)
learners/default.py:429
↓ 1 callersMethod__len__
(self)
dataloaders/loader.py:410
↓ 1 callersMethod_load_meta
(self)
dataloaders/loader.py:502
↓ 1 callersFunctionaccuracy
Computes the precision@k for the specified values of k
utils/metric.py:14
↓ 1 callersMethodcount_memory
(self, dataset_size)
learners/default.py:372
↓ 1 callersFunctioncreate_args
()
run_dfcil.py:14
↓ 1 callersMethodcreate_generator
(self)
learners/datafree.py:229
↓ 1 callersMethodcreate_generator
(self)
learners/dgr.py:182
↓ 1 callersMethodcreate_model
(self)
learners/default.py:338
↓ 1 callersMethodcuda_gen
(self)
learners/datafree.py:251
↓ 1 callersMethodcuda_gen
(self)
learners/dgr.py:204
↓ 1 callersMethoddownload
(self)
dataloaders/loader.py:489
↓ 1 callersFunctiondownload_url
(url, root, filename, md5)
dataloaders/utils.py:85
↓ 1 callersMethodencode
Pass input through feed-forward connections, to get [hE], [z_mean] and [z_logvar].
models/autoencoder.py:149
↓ 1 callersMethodevaluate
(self, avg_metrics)
trainer.py:250
↓ 1 callersMethodforward
(self, x)
models/autoencoder.py:71
↓ 1 callersMethodforward
(self, z)
models/generator.py:38
↓ 1 callersMethodforward
(self, z)
models/generator.py:86
↓ 1 callersMethodforward
(self, z)
models/generator.py:148
↓ 1 callersFunctionget_args
(argv)
run_dfcil.py:71
↓ 1 callersMethodget_images
(self, bs=256, epochs=1000, idx=-1)
learners/datafree_helper.py:118
↓ 1 callersMethodload_model
(self, filename)
learners/datafree.py:222
↓ 1 callersMethodload_model
(self, filename)
learners/default.py:282
↓ 1 callersMethodload_model
(self, filename)
learners/dgr.py:174
↓ 1 callersMethodloss_function
(self, recon_x, x, dw, mu=None, logvar=None)
models/autoencoder.py:94
↓ 1 callersMethodprint_model
(self)
learners/default.py:346
↓ 1 callersMethodq
(self, encoded)
models/autoencoder.py:157
↓ 1 callersMethodreparameterize
Perform "reparametrization trick" to make these stochastic variables differentiable.
models/autoencoder.py:65
↓ 1 callersMethodreset
(self)
utils/metric.py:40
↓ 1 callersMethodreset
(self)
utils/metric.py:65
↓ 1 callersMethodsample
(self, size, allowed_predictions=None, return_scores=False)
learners/dgr_helper.py:19
↓ 1 callersMethodsample
(self, size, device, return_scores=False)
learners/datafree_helper.py:65
↓ 1 callersMethodsummarize_acc
(self, acc_dict, acc_table, acc_table_pt)
trainer.py:224
↓ 1 callersMethodtrain_batch
Train model for one batch ([x],[y]), possibly supplemented with replayed data ([x_],[y_]). [x] <tensor> batch of inputs (could
models/autoencoder.py:116
↓ 1 callersMethodupdate_model
(self, inputs, targets, target_scores = None, dw_force = None, kd_index = None)
learners/datafree.py:165
↓ 1 callersMethodupdate_model
(self, inputs, targets, target_scores = None, dw_force = None, kd_index = None)
learners/default.py:173
↓ 1 callersMethodupdate_model
(self, inputs, targets, target_KD = None)
learners/kd.py:237
↓ 1 callersMethodupdate_model
(self, inputs, targets, target_KD = None)
learners/kd.py:496
↓ 1 callersMethodupdate_model_b
(self, inputs, targets, target_KD = None, target_KD_B = None)
learners/kd.py:261
FunctionCIFAR_GEN
(bn = False)
models/autoencoder.py:222
FunctionCIFAR_GEN
(bn = False)
models/generator.py:173
FunctionIMNET_GEN
(bn = False)
models/generator.py:179
FunctionTINYIMNET_GEN
(bn = False)
models/generator.py:176
Method__getitem__
Args: index (int): Index Returns: tuple: (image, target) where target is index of the target class
dataloaders/loader.py:570
Method__getitem__
Args: index (int): Index Returns: tuple: (image, target) where target is index of the target class
dataloaders/loader.py:647
Method__init__
(self, name)
run_dfcil.py:78
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