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Functions97 in github.com/IssamLaradji/sps

⨍ Functions 97 ◇ Types & classes 15

↓ 9 callersMethodstep

(self, closure=None, loss=None, batch=None)

↓ 8 callersMethod__init__

(self, input_size=784, hidden_sizes=[512, 256], n_classes=10,

src/base_classifiers.py:178

↓ 4 callersFunctionDenseNet121

src/base_classifiers.py:390

↓ 4 callersMethod_make_dense_layers

(self, block, in_planes, nblock)

src/base_classifiers.py:372

↓ 4 callersMethod_make_layer

(self, block, planes, num_blocks, stride)

src/base_classifiers.py:221

↓ 4 callersMethodval_on_dataset

(self, dataset, metric)

src/models.py:52

↓ 3 callersFunctionflatten_dict

(d, parent_key="")

src/utils.py:42

↓ 2 callersFunctionMlp_model

(input_size=784, hidden_sizes=[512, 256], n_classes=10, bias=True, dropout=False)

src/base_classifiers.py:103

↓ 2 callersFunctionadd_l2

src/models.py:208

↓ 2 callersFunctionget_metric_function

src/models.py:96

↓ 2 callersFunctionrbf_kernel

src/datasets.py:496

↓ 1 callersFunction_get_hparams

src/utils.py:53

↓ 1 callersFunctioncompute_grad_norm

(grad_list, centralize_grad_norm=False)

↓ 1 callersFunctiondensenet_cifar

src/base_classifiers.py:403

↓ 1 callersFunctiongenerate_synthetic_matrix_factorization_data

Generate a synthetic matrix factorization dataset as suggested by Ben Recht. See: https://github.com/benjamin-recht/shallow-linear-net/blob/m

src/datasets.py:353

↓ 1 callersFunctionget_exp_hash

src/utils.py:99

↓ 1 callersFunctionget_grad_list

(params, centralize_grad=False)

↓ 1 callersFunctionget_metric_function

src/metrics.py:6

↓ 1 callersMethodget_state_dict

src/models.py:42

↓ 1 callersFunctionload_libsvm

(name, data_dir)

src/datasets.py:398

↓ 1 callersFunctionload_pkl

Load the content of a pkl file.

src/utils.py:117

↓ 1 callersFunctionmake_binary_linear

(n, d, margin, y01=False, bias=False, separable=True, scale=1, shuffle=True, seed=None)

src/datasets.py:415

↓ 1 callersMethodset_state_dict

(self, state_dict)

src/models.py:48

↓ 1 callersFunctionsgd_update

(params, step_size, grad_current)

↓ 1 callersFunctionsoftmax_loss

(model, images, labels, backwards=False, reduction="mean", backpack=False)

src/models.py:147

↓ 1 callersFunctionsquared_hinge_loss

(model, images, labels, backwards=False, reduction="mean", backpack=False)

src/models.py:189

↓ 1 callersFunctionsquared_loss

(model, images, labels, backwards=False, reduction="mean", backpack=False)

src/models.py:171

↓ 1 callersMethodtrain_on_batch

src/models.py:72

↓ 1 callersMethodtrain_on_loader

(self, train_loader)

src/models.py:29

↓ 1 callersFunctiontrainval

(exp_dict, savedir, args)

FunctionDenseNet161

src/base_classifiers.py:400

FunctionDenseNet169

src/base_classifiers.py:394

FunctionDenseNet201

src/base_classifiers.py:397

Method__getitem__

src/datasets.py:305

Method__getitem__

src/datasets.py:322

(self, params, n_batches_per_epoch=500, init_step_size=1,

(self, input_size, hidden_sizes, output_size, bias=True)

src/base_classifiers.py:125

(self, input_dim, output_dim)

src/base_classifiers.py:167

(self, num_blocks, num_classes=10)

src/base_classifiers.py:207

(self, in_planes, planes, stride=1)

src/base_classifiers.py:244

(self, in_planes, planes, stride=1)

src/base_classifiers.py:279

(self, in_planes, growth_rate)

src/base_classifiers.py:315

(self, in_planes, out_planes)

src/base_classifiers.py:330

(self, block, nblocks, growth_rate=12, reduction=0.5, num_classes=10)

src/base_classifiers.py:341

(self, train_loader, exp_dict, device)

src/models.py:15

(self, dataset, split)

src/datasets.py:298

(self, corpus, data, bptt)

src/datasets.py:314

(self, inputSize, outputSize)

tests/test_basic.py:13

src/datasets.py:302

src/datasets.py:319

src/metrics.py:113

Functioncartesian_exp_group

src/utils.py:94

Functioncompute_fstar

(model, train_set)

src/utils.py:148

Functioncompute_max_eta_logistic_loss

src/datasets.py:330

Functioncompute_max_eta_squared_loss

src/datasets.py:341

Functioncompute_metric_on_dataset

(model, dataset, metric_name)

src/metrics.py:29

Functiondeactivate_batchnorm

src/base_classifiers.py:91

x: The input patterns/features.

src/base_classifiers.py:146

src/base_classifiers.py:171

src/base_classifiers.py:190

src/base_classifiers.py:229

src/base_classifiers.py:268

src/base_classifiers.py:305

src/base_classifiers.py:322

src/base_classifiers.py:335

src/base_classifiers.py:379

tests/test_basic.py:17

Functionget_classifier

(clf_name, train_set)

src/base_classifiers.py:8

Functionget_dataset

(dataset_name, split, datadir, exp_dict)

src/datasets.py:11

Functionget_model

(train_loader, exp_dict, device)

src/models.py:10

Functionget_optimizer

opt: name or dict params: model parameters n_batches_per_epoch: b/n

src/optimizers.py:5

Functionload_json

(fname, decode=None)

src/utils.py:122

Functionload_mnist

src/datasets.py:388

Functionlogistic_accuracy

(model, images, labels)

src/models.py:235

Functionlogistic_accuracy

(model, images, labels)

src/metrics.py:122

Functionlogistic_l2_loss

(model, images, labels, backwards=False, reduction="mean", backpack=False)

src/models.py:131

Functionlogistic_l2_loss

(model, images, labels, backwards=False)

src/metrics.py:53

Functionlogistic_loss

(model, images, labels, backwards=False, reduction="mean", backpack=False)

src/models.py:159

Functionlogistic_loss

(model, images, labels, backwards=False)

src/metrics.py:79

Functionmse_score

(model, images, labels)

src/models.py:183

Functionmse_score

(model, images, labels)

src/metrics.py:47

Functionopt_step

(name, opt, model, batch, loss_function, use_backpack, epoch)

src/utils.py:13

Functionread_text

src/utils.py:140

Functionsave_json

src/utils.py:128

Functionsave_pkl

Save data in pkl format.

src/utils.py:108

Functionsoftmax_accuracy

(model, images, labels)

src/models.py:242

Functionsoftmax_accuracy

(model, images, labels)

src/metrics.py:129

Functionsoftmax_loss

(model, images, labels, backwards=False)

src/metrics.py:69

Functionsquared_hinge_l2_loss

(model, images, labels, backwards=False, reduction="mean", backpack=False)

src/models.py:217

Functionsquared_hinge_loss

(model, images, labels, backwards=False)

src/metrics.py:99

Functionsquared_l2_loss

(model, images, labels, backwards=False, reduction="mean", backpack=False)

src/models.py:226

Functionsquared_loss

(model, images, labels, backwards=False)

src/metrics.py:89

src/base_classifiers.py:406

Methodtest_update

tests/test_basic.py:23

Functiontorch_save

Save data in torch format.

src/utils.py:132

Methodval_on_loader

src/models.py:69

Functionvisualize

(exp_group, savedir_base, name="results", x_col="epoch", y_cols=("train_loss", "val_score"))

src/utils.py:59