Functions — github.com/Graph-and-Geometric-Learning/hyperbolic-transformer

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Functions650 in github.com/Graph-and-Geometric-Learning/hyperbolic-transformer

⨍ Functions 650◇ Types & classes 92

↓ 1 callersFunction_expmap

(x, u, *, k: torch.Tensor, dim: int = -1)

large/manifolds/lorentz_math.py:312

↓ 1 callersFunction_expmap

(x, u, *, k: torch.Tensor, dim: int = -1)

medium/manifolds/lorentz_math.py:318

↓ 1 callersFunction_expmap

(x, u, *, k: torch.Tensor, dim: int = -1)

Hypformer/manifolds/lorentz_math.py:318

↓ 1 callersFunction_expmap0

(u, k: torch.Tensor, dim: int = -1)

large/manifolds/lorentz_math.py:343

↓ 1 callersFunction_expmap0

(u, k: torch.Tensor, dim: int = -1)

medium/manifolds/lorentz_math.py:349

↓ 1 callersFunction_expmap0

(u, k: torch.Tensor, dim: int = -1)

Hypformer/manifolds/lorentz_math.py:349

↓ 1 callersFunction_geodesic_unit

(t, x, u, k)

large/manifolds/lorentz_math.py:628

↓ 1 callersFunction_geodesic_unit

(t, x, u, k)

medium/manifolds/lorentz_math.py:618

↓ 1 callersFunction_geodesic_unit

(t, x, u, k)

Hypformer/manifolds/lorentz_math.py:618

↓ 1 callersFunction_logmap

(x, y, k, dim: int = -1)

large/manifolds/lorentz_math.py:392

↓ 1 callersFunction_logmap0

(y, k, dim: int = -1)

large/manifolds/lorentz_math.py:419

↓ 1 callersFunction_logmap0back

(x, k, dim: int = -1)

large/manifolds/lorentz_math.py:448

↓ 1 callersFunction_parallel_transport

(x, y, v, k, dim: int = -1)

large/manifolds/lorentz_math.py:515

↓ 1 callersFunction_parallel_transport

(x, y, v, k, dim: int = -1)

medium/manifolds/lorentz_math.py:521

↓ 1 callersFunction_parallel_transport

(x, y, v, k, dim: int = -1)

Hypformer/manifolds/lorentz_math.py:521

↓ 1 callersFunction_parallel_transport0

(y, v, k, dim: int = -1)

large/manifolds/lorentz_math.py:550

↓ 1 callersFunction_parallel_transport0

(y, v, k, dim: int = -1)

medium/manifolds/lorentz_math.py:552

↓ 1 callersFunction_parallel_transport0

(y, v, k, dim: int = -1)

Hypformer/manifolds/lorentz_math.py:552

↓ 1 callersFunction_parallel_transport0back

(x, v, k, dim: int = -1)

large/manifolds/lorentz_math.py:588

↓ 1 callersFunction_parallel_transport0back

(x, v, k, dim: int = -1)

medium/manifolds/lorentz_math.py:584

↓ 1 callersFunction_parallel_transport0back

(x, v, k, dim: int = -1)

Hypformer/manifolds/lorentz_math.py:584

↓ 1 callersFunction_project

(x, k: torch.Tensor, dim: int = -1)

large/manifolds/lorentz_math.py:172

↓ 1 callersFunction_project

(x, k: torch.Tensor, dim: int = -1)

medium/manifolds/lorentz_math.py:178

↓ 1 callersFunction_project

(x, k: torch.Tensor, dim: int = -1)

Hypformer/manifolds/lorentz_math.py:178

↓ 1 callersFunction_project_polar

(x, k: torch.Tensor, dim: int = -1)

large/manifolds/lorentz_math.py:205

↓ 1 callersFunction_project_polar

(x, k: torch.Tensor, dim: int = -1)

medium/manifolds/lorentz_math.py:211

↓ 1 callersFunction_project_polar

(x, k: torch.Tensor, dim: int = -1)

Hypformer/manifolds/lorentz_math.py:211

↓ 1 callersFunction_project_u

(x, v, k: torch.Tensor, dim: int = -1)

large/manifolds/lorentz_math.py:245

↓ 1 callersFunction_project_u

(x, v, k: torch.Tensor, dim: int = -1)

medium/manifolds/lorentz_math.py:251

↓ 1 callersFunction_project_u

(x, v, k: torch.Tensor, dim: int = -1)

Hypformer/manifolds/lorentz_math.py:251

↓ 1 callersMethodadd_result

(self, run, result)

medium/logger.py:10

↓ 1 callersMethodbackward

(ctx: Any, grad_output: torch.Tensor)

medium/manifolds/manifold_utils.py:257

↓ 1 callersFunctionbin_feat

(feat, bins)

medium/dataset.py:167

↓ 1 callersMethodcinner

Compute the Lorentzian inner product. Parameters ---------- x : torch.Tensor First tensor. y : t

medium/manifolds/lorentz.py:327

↓ 1 callersMethodcinner

(self, x, y)

medium/manifolds/hyp_layer.py:138

↓ 1 callersMethodcinner

(self, x, y)

Hypformer/manifolds/hyp_layer.py:132

↓ 1 callersFunctionclass_rand_splits

(label, label_num_per_class, valid_num=500, test_num=1000)

large/data_utils.py:61

↓ 1 callersFunctionclass_rand_splits

use all remaining data points as test data, so test_num will not be used

medium/data_utils.py:39

↓ 1 callersFunctioncompute_and_print_degrees

(dataset)

large/main.py:95

↓ 1 callersFunctioncompute_and_print_degrees

(dataset)

large/main-batch.py:94

↓ 1 callersFunctioncompute_loss

(out, criterion, train_idx, true_label, args)

large/main.py:222

↓ 1 callersFunctioncompute_loss

(args, criterion, out_i, train_mask_i, y_i)

large/main-batch.py:230

↓ 1 callersFunctionconvert_labels_to_one_hot

(dataset, args)

large/main-batch.py:148

↓ 1 callersFunctiondisplay_evaluation_results

(epoch, result, split_idx, degrees, threshold, loss)

large/main.py:241

↓ 1 callersFunctiondisplay_evaluation_results

(epoch, result, split_idx, degrees, threshold, loss)

large/main-batch.py:256

↓ 1 callersFunctionevaluate

(model, dataset, split_idx, eval_func, criterion, args, result=None)

medium/data_utils.py:87

↓ 1 callersFunctionevaluate_and_log

(epoch, args, model, dataset, split_idx, eval_func, criterion, degrees, threshold, device, logger,

large/main.py:230

↓ 1 callersFunctionevaluate_batch

(model, dataset, split_idx, args, device, n, true_label)

large/eval.py:87

↓ 1 callersFunctionevaluate_epoch

(epoch, args, model, dataset, split_idx, eval_func, criterion, degrees, threshold, device, logger,

large/main-batch.py:238

↓ 1 callersFunctionfix_seed

(seed)

large/main.py:29

↓ 1 callersFunctionfix_seed

(seed)

large/main-batch.py:26

↓ 1 callersFunctionfix_seed

(seed)

medium/main.py:29

↓ 1 callersMethodget_attentions

(self, x)

large/hypformer.py:250

↓ 1 callersMethodget_attentions

(self, x)

Hypformer/hypformer.py:223

↓ 1 callersFunctionget_data_splits

(args, dataset)

large/main.py:66

↓ 1 callersFunctionget_data_splits

(args, dataset)

large/main-batch.py:62

↓ 1 callersFunctionget_device

(use_cpu, device_id)

large/main.py:43

↓ 1 callersFunctionget_device

(use_cpu, device_id)

large/main-batch.py:40

↓ 1 callersMethodget_idx_split

train_prop: The proportion of dataset for train split. Between 0 and 1. valid_prop: The proportion of dataset for validation split. B

medium/dataset.py:51

↓ 1 callersMethodget_results_string

(best_result)

large/logger.py:24

↓ 1 callersFunctionget_true_label

(dataset, args)

large/main.py:215

↓ 1 callersFunctionidx2sign

Unify idx to be negative or positive, that helps in cases of broadcasting. Parameters ---------- idx : int current index

large/manifolds/utils.py:92

↓ 1 callersFunctionidx2sign

Unify idx to be negative or positive, that helps in cases of broadcasting. Parameters ---------- idx : int current index

medium/manifolds/manifold_utils.py:93

↓ 1 callersFunctionidx2sign

Unify idx to be negative or positive, that helps in cases of broadcasting. Parameters ---------- idx : int current index

Hypformer/manifolds/utils.py:92

↓ 1 callersFunctioninitialize_wandb

(args, run)

large/main.py:133

↓ 1 callersFunctioninitialize_wandb

(args, run)

large/main-batch.py:155

↓ 1 callersFunctionload_20news

(n_remove=0)

medium/dataset.py:376

↓ 1 callersFunctionload_airport_dataset

()

medium/dataset.py:135

↓ 1 callersFunctionload_amazon2m_dataset

(data_dir)

large/dataset.py:275

↓ 1 callersFunctionload_amazon_dataset

(data_dir, name)

large/dataset.py:496

↓ 1 callersFunctionload_and_preprocess_data

(args, device)

large/main.py:53

↓ 1 callersFunctionload_and_preprocess_data

(args)

large/main-batch.py:50

↓ 1 callersFunctionload_arxiv_year_dataset

(data_dir, nclass=5)

large/dataset.py:262

↓ 1 callersFunctionload_coauthor_dataset

(data_dir, name)

large/dataset.py:522

↓ 1 callersFunctionload_deezer_dataset

(data_dir)

large/dataset.py:242

↓ 1 callersFunctionload_deezer_dataset

()

medium/dataset.py:116

↓ 1 callersFunctionload_disease_dataset

()

medium/dataset.py:324

↓ 1 callersFunctionload_fb100_dataset

(data_dir, filename)

large/dataset.py:201

↓ 1 callersFunctionload_fixed_splits

(dataset, name, protocol)

medium/data_utils.py:124

↓ 1 callersFunctionload_geom_gcn_dataset

(data_dir, name)

large/dataset.py:548

↓ 1 callersFunctionload_geom_gcn_dataset

(name)

medium/dataset.py:204

↓ 1 callersFunctionload_mini_imagenet

()

medium/dataset.py:424

↓ 1 callersFunctionload_nc_dataset

Loader for NCDataset Returns NCDataset

medium/dataset.py:78

↓ 1 callersFunctionload_ogb_dataset

(data_dir, name)

large/dataset.py:354

↓ 1 callersFunctionload_planetoid_dataset

(data_dir, name)

large/dataset.py:470

↓ 1 callersFunctionload_planetoid_dataset

(name, no_feat_norm=False)

medium/dataset.py:172

↓ 1 callersFunctionload_pokec_mat

requires pokec.mat

large/dataset.py:371

↓ 1 callersFunctionload_proteins_dataset

(data_dir)

large/dataset.py:331

↓ 1 callersFunctionload_snap_patents_mat

(data_dir, nclass=5)

large/dataset.py:419

↓ 1 callersFunctionload_twitch_dataset

(data_dir, lang)

large/dataset.py:140

↓ 1 callersFunctionload_wiki_new

(name, no_feat_norm=False)

medium/dataset.py:295

↓ 1 callersFunctionload_yelpchi_dataset

(data_dir)

large/dataset.py:446

↓ 1 callersFunctionmain

()

large/main.py:257

↓ 1 callersFunctionmain

()

large/main-batch.py:270

↓ 1 callersFunctionmake_tuple

(obj: Union[Tuple, List, Any])

large/manifolds/utils.py:66

↓ 1 callersFunctionmake_tuple

(obj: Union[Tuple, List, Any])

medium/manifolds/manifold_utils.py:66

↓ 1 callersFunctionmake_tuple

(obj: Union[Tuple, List, Any])

Hypformer/manifolds/utils.py:66

↓ 1 callersFunctionmkdirs

(path)

large/logger.py:7

↓ 1 callersFunctionmkdirs

(path)

medium/main.py:23

↓ 1 callersFunctionparse_args

()

large/main.py:37

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