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Functions556 in github.com/cure-lab/LTSF-Linear

⨍ Functions 556◇ Types & classes 178
↓ 36 callersMethodabs
(self, x, y)
FEDformer/layers/utils.py:358
↓ 19 callersMethodcpu
(self)
FEDformer/layers/utils.py:317
↓ 13 callersMethodbackward
(ctx, grad_output)
Pyraformer/pyraformer/hierarchical_mm_tvm.py:264
↓ 9 callersMethod__init__
(self, c_in, d_model, embed_type='fixed', freq='h', dropout=0.1)
FEDformer/layers/Embed.py:106
↓ 9 callersMethodfit
(self, data)
Pyraformer/utils/tools.py:35
↓ 8 callersMethod__init__
(self, attn_layers, conv_layers=None, norm_layer=None)
FEDformer/layers/Autoformer_EncDec.py:123
↓ 8 callersMethod__init__
(self, opt, mask)
Pyraformer/pyraformer/Layers.py:381
↓ 8 callersMethod__init__
(self, c_in, d_model, embed_type='fixed', freq='h', dropout=0.1)
layers/Embed.py:106
↓ 7 callersMethodcuda
(self)
FEDformer/layers/utils.py:313
↓ 6 callersMethod__init__
(self, c_in, d_model, dropout=0.1)
Pyraformer/pyraformer/embed.py:82
↓ 6 callersMethod__init__
(self, attn_layers, conv_layers=None, norm_layer=None)
layers/Autoformer_EncDec.py:86
↓ 5 callersMethod_get_data
(self, flag)
FEDformer/exp/exp_main.py:39
↓ 5 callersMethod_get_data
(self, flag)
exp/exp_main.py:41
↓ 5 callersMethod_prepare_tensors
Fix `stride()` information of input tensor. This addresses some inconsistency in stride information in PyTorch. For a tensor t, if t.size(0) =
Pyraformer/pyraformer/hierarchical_mm_tvm.py:205
↓ 5 callersMethodpredict
(self, setting, load=False)
exp/exp_main.py:305
↓ 4 callersMethod__init__
(self, k=3, alpha=64, L=0, c=1, base='legendre',
FEDformer/layers/MultiWaveletCorrelation.py:297
↓ 4 callersMethod__init__
(self, attn_layers, conv_layers=None, norm_layer=None)
FEDformer/layers/Transformer_EncDec.py:54
↓ 4 callersMethod__init__
(self, attn_layers, conv_layers=None, norm_layer=None)
layers/Transformer_EncDec.py:54
↓ 4 callersMethod__init__
(self, configs)
models/Stat_models.py:103
↓ 4 callersMethod_graph_mm
Calls the compiled function after checking the input format. This function is called in three different modes. t1 x t2 = r ==> t1 and t2 are n
Pyraformer/pyraformer/hierarchical_mm_tvm.py:161
↓ 4 callersMethodfit
(self, data)
Pyraformer/data_loader.py:278
↓ 4 callersMethodinverse_transform
(self, data)
Pyraformer/data_loader.py:250
↓ 4 callersFunctionpsi
(psi1, psi2, i, inp)
FEDformer/layers/utils.py:133
↓ 4 callersFunctiontime_features
(dates, freq='h')
utils/timefeatures.py:133
↓ 4 callersMethodtrain
(self, setting)
exp/exp_main.py:99
↓ 4 callersMethodtransform
(self, data)
utils/tools.py:77
↓ 4 callersMethodtransform
(self, data)
FEDformer/utils/tools.py:72
↓ 3 callersFunctionMSE
(pred, true)
FEDformer/utils/metrics.py:18
↓ 3 callersMethod__init__
(self, d=2, p=2, size_average=True, reduction=True)
FEDformer/layers/utils.py:347
↓ 3 callersMethod__init__
(self, mask_flag=True, factor=5, scale=None, attention_dropout=0.1, output_attention=False)
FEDformer/layers/SelfAttention_Family.py:15
↓ 3 callersFunctionget_frequency_modes
get modes on frequency domain: 'random' means sampling randomly; 'else' means sampling the lowest modes;
FEDformer/layers/FourierCorrelation.py:10
↓ 3 callersFunctionget_mask
Get the attention mask of PAM-Naive
Pyraformer/pyraformer/Layers.py:12
↓ 3 callersMethodinverse_transform
(self, data)
FEDformer/data_provider/data_loader.py:371
↓ 3 callersMethodinverse_transform
(self, data)
data_provider/data_loader.py:401
↓ 3 callersMethodreturn_result
(self)
models/Stat_models.py:29
↓ 3 callersFunctionsplit
(split_start, label, cov, pred_length)
Pyraformer/data_loader.py:494
↓ 3 callersMethodtest
(self, setting, test=0)
exp/exp_stat.py:39
↓ 3 callersFunctiontime_features
(dates, freq='h')
FEDformer/utils/timefeatures.py:133
↓ 3 callersFunctiontime_features
(dates, timeenc=1, freq='h')
Pyraformer/utils/timefeatures.py:114
↓ 3 callersMethodtrain
(self, setting)
FEDformer/exp/exp_main.py:94
↓ 3 callersMethodtransform
(self, data)
Pyraformer/utils/tools.py:39
↓ 3 callersMethodwavelet_transform
(self, x)
FEDformer/layers/MultiWaveletCorrelation.py:191
↓ 2 callersFunctionMAE
(pred, true)
FEDformer/utils/metrics.py:14
↓ 2 callersFunctionMAPE
(pred, true)
FEDformer/utils/metrics.py:26
↓ 2 callersFunctionMSE
(pred, true)
utils/metrics.py:19
↓ 2 callersFunctionMSE
(pred, true)
Pyraformer/utils/tools.py:9
↓ 2 callersFunctionMSPE
(pred, true)
FEDformer/utils/metrics.py:30
↓ 2 callersFunctionRMSE
(pred, true)
FEDformer/utils/metrics.py:22
↓ 2 callersMethod__init__
(self, opt)
Pyraformer/pyraformer/graph_attention.py:185
↓ 2 callersMethod__init__
(self, mask_flag=True, factor=5, scale=None, attention_dropout=0.1, output_attention=False)
layers/SelfAttention_Family.py:15
↓ 2 callersMethod__init__
(self, configs)
models/DLinear.py:42
↓ 2 callersMethod_get_lib_filename
(dtype: str, device: str)
Pyraformer/pyraformer/hierarchical_mm_tvm.py:117
↓ 2 callersFunctiondata_provider
(args, flag)
data_provider/data_factory.py:13
↓ 2 callersFunctioneval_epoch
Epoch operation in evaluation phase.
Pyraformer/single_step_main.py:125
↓ 2 callersFunctioneval_epoch
Epoch operation in evaluation phase.
Pyraformer/long_range_main.py:199
↓ 2 callersFunctionget_filter
(base, k)
FEDformer/layers/utils.py:131
↓ 2 callersFunctionget_k_q
Get the index of the query that can attend to the given key.
Pyraformer/pyraformer/Layers.py:153
↓ 2 callersFunctionget_q_k
Get the index of the key that a given query needs to attend to.
Pyraformer/pyraformer/Layers.py:91
↓ 2 callersFunctionmetric
(pred, true)
utils/metrics.py:35
↓ 2 callersFunctionnormalize
(inputs, seq_length)
Pyraformer/preprocess_wind.py:66
↓ 2 callersFunctionnormalize
(inputs, seq_length)
Pyraformer/preprocess_flow.py:76
↓ 2 callersFunctionprep_data
Divide the training sequence into windows
Pyraformer/preprocess_elect.py:26
↓ 2 callersFunctionprepare_dataloader
Load data and prepare dataloader.
Pyraformer/single_step_main.py:16
↓ 2 callersFunctionprepare_dataloader
Load data and prepare dataloader.
Pyraformer/long_range_main.py:14
↓ 2 callersFunctionrefer_points
Gather features from PAM's pyramid sequences
Pyraformer/pyraformer/Layers.py:50
↓ 2 callersFunctionsave
(data, v, save_dir)
Pyraformer/preprocess_wind.py:80
↓ 2 callersFunctionsave
(data, v, save_dir)
Pyraformer/preprocess_flow.py:86
↓ 2 callersMethodsave_checkpoint
(self, val_loss, model, path)
utils/tools.py:58
↓ 2 callersMethodsave_checkpoint
(self, val_loss, model, path)
FEDformer/utils/tools.py:53
↓ 2 callersMethodtest
(self, setting, test=0)
FEDformer/exp/exp_main.py:219
↓ 2 callersFunctiontest_NSA
Test the time and CUDA memory consumption of normal self attention.
Pyraformer/pyraformer/graph_attention.py:451
↓ 2 callersMethodtime_delay_agg_inference
SpeedUp version of Autocorrelation (a batch-normalization style design) This is for the inference phase.
FEDformer/layers/AutoCorrelation.py:62
↓ 2 callersMethodtime_delay_agg_training
SpeedUp version of Autocorrelation (a batch-normalization style design) This is for the training phase.
FEDformer/layers/AutoCorrelation.py:38
↓ 2 callersMethodvali
(self, vali_data, vali_loader, criterion)
FEDformer/exp/exp_main.py:51
↓ 2 callersMethodvali
(self, vali_data, vali_loader, criterion)
exp/exp_main.py:53
↓ 2 callersFunctionvisual
Results visualization
utils/tools.py:84
↓ 1 callersFunctionAE_loss
(mu, labels, ignore_zero)
Pyraformer/utils/tools.py:86
↓ 1 callersFunctionCORR
(pred, true)
utils/metrics.py:8
↓ 1 callersFunctionCORR
(pred, true)
FEDformer/utils/metrics.py:8
↓ 1 callersFunctionMAE
(pred, true)
utils/metrics.py:15
↓ 1 callersFunctionMAE
(pred, true)
Pyraformer/utils/tools.py:6
↓ 1 callersFunctionMAPE
(pred, true)
utils/metrics.py:27
↓ 1 callersFunctionMAPE
(pred, true)
Pyraformer/utils/tools.py:15
↓ 1 callersFunctionMSPE
(pred, true)
utils/metrics.py:31
↓ 1 callersFunctionMSPE
(pred, true)
Pyraformer/utils/tools.py:18
↓ 1 callersFunctionRMSE
(pred, true)
utils/metrics.py:23
↓ 1 callersFunctionRMSE
(pred, true)
Pyraformer/utils/tools.py:12
↓ 1 callersFunctionRSE
(pred, true)
utils/metrics.py:4
↓ 1 callersFunctionRSE
(pred, true)
FEDformer/utils/metrics.py:4
↓ 1 callersMethod__init__
(self, in_channels, out_channels, seq_len, modes=0, mode_select_method='random')
FEDformer/layers/FourierCorrelation.py:29
↓ 1 callersMethod__init__
(self, mask_flag=True, factor=1, scale=None, attention_dropout=0.1, output_attention=False, configs=None)
FEDformer/layers/AutoCorrelation.py:26
↓ 1 callersMethod__init__
(self, topk)
Pyraformer/utils/tools.py:50
↓ 1 callersMethod__init__
(self, opt)
Pyraformer/pyraformer/Pyraformer_SS.py:59
↓ 1 callersMethod__init__
(self, n_head, d_model, d_k, d_v, dropout=0.1, normalize_before=True)
Pyraformer/pyraformer/SubLayers.py:10
↓ 1 callersMethod__init__
(self, opt)
Pyraformer/pyraformer/Pyraformer_LR.py:74
↓ 1 callersMethod__init__
(self, mask_flag=True, factor=1, scale=None, attention_dropout=0.1, output_attention=False)
layers/AutoCorrelation.py:18
↓ 1 callersMethod__read_data__
(self)
FEDformer/data_provider/data_loader.py:43
↓ 1 callersMethod__read_data__
(self)
FEDformer/data_provider/data_loader.py:131
↓ 1 callersMethod__read_data__
(self)
FEDformer/data_provider/data_loader.py:221
↓ 1 callersMethod__read_data__
(self)
FEDformer/data_provider/data_loader.py:320
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