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Functions193 in github.com/KimMeen/Time-LLM

⨍ Functions 193◇ Types & classes 64
Method__init__
(self, c_in, d_model)
layers/Embed.py:47
Method__init__
(self, d_model, embed_type='fixed', freq='h')
layers/Embed.py:68
Method__init__
(self, d_model, embed_type='timeF', freq='h')
layers/Embed.py:98
Method__init__
(self, c_in, d_model, embed_type='fixed', freq='h', dropout=0.1)
layers/Embed.py:131
Method__init__
(self, padding)
layers/Embed.py:150
Method__init__
(self, d_model, patch_len, stride, dropout)
layers/Embed.py:161
Method__init__
(self, c_in, d_model, embed_type='fixed', freq='h', dropout=0.1)
layers/Embed.py:189
Method__init__
(self, mask_flag=True, factor=5, scale=None, attention_dropout=0.1, output_attention=False)
layers/SelfAttention_Family.py:48
Method__init__
(self, mask_flag=True, factor=5, scale=None, attention_dropout=0.1, output_attention=False)
layers/SelfAttention_Family.py:78
Method__init__
(self, attention, d_model, n_heads, d_keys=None, d_values=None)
layers/SelfAttention_Family.py:179
Method__init__
(self, attention, d_model, n_heads, d_keys=None, d_values=None, causal=False, bucket_size=4,
layers/SelfAttention_Family.py:216
Method__init__
(self, c_in)
layers/Transformer_EncDec.py:7
Method__init__
(self, attention, d_model, d_ff=None, dropout=0.1, activation="relu")
layers/Transformer_EncDec.py:28
Method__init__
(self, self_attention, cross_attention, d_model, d_ff=None, dropout=0.1, activation="relu")
layers/Transformer_EncDec.py:84
Method__init__
(self, layers, norm_layer=None, projection=None)
layers/Transformer_EncDec.py:120
Method__init__
:param num_features: the number of features or channels :param eps: a value added for numerical stability :param affine: if T
layers/StandardNorm.py:6
Method__init__
(self, correlation, d_model, n_heads, d_keys=None, d_values=None)
layers/AutoCorrelation.py:132
Method__init__
(self, root_path, flag='train', size=None, features='S', data_path='ETTh1.csv',
data_provider/data_loader.py:14
Method__init__
(self, root_path, flag='train', size=None, features='S', data_path='ETTm1.csv',
data_provider/data_loader.py:112
Method__init__
(self, root_path, flag='train', size=None, features='S', data_path='ETTh1.csv',
data_provider/data_loader.py:210
Method__init__
(self, root_path, flag='pred', size=None, features='S', data_path='ETTh1.csv',
data_provider/data_loader.py:315
Method__init__
(self, root_path, flag='train', size=None, features='S', data_path='ETTh1.csv',
data_provider_pretrain/data_loader.py:12
Method__init__
(self, root_path, flag='train', size=None, features='S', data_path='ETTm1.csv',
data_provider_pretrain/data_loader.py:116
Method__init__
(self, n_vars, nf, target_window, head_dropout=0)
models/TimeLLM.py:16
Method__init__
(self, d_model, n_heads, d_keys=None, d_llm=None, attention_dropout=0.1)
models/TimeLLM.py:268
Method__init__
individual: Bool, whether shared model among different variates.
models/DLinear.py:12
Method__init__
(self, configs)
models/Autoformer.py:18
Method__len__
(self)
data_provider/data_loader.py:104
Method__len__
(self)
data_provider/data_loader.py:202
Method__len__
(self)
data_provider/data_loader.py:307
Method__len__
(self)
data_provider/data_loader.py:369
Method__len__
(self)
data_provider_pretrain/data_loader.py:108
Method__len__
(self)
data_provider_pretrain/data_loader.py:217
Method__repr__
(self)
utils/timefeatures.py:16
Functionadjustment
(gt, pred)
utils/tools.py:105
Functioncal_accuracy
(y_pred, y_true)
utils/tools.py:129
Functiondata_provider
(args, data, data_path, pretrain=True, flag='train')
data_provider_pretrain/data_factory.py:13
Functiondownload
Download a file to the given path. :param url: URL to download :param file_path: Where to download the content.
data_provider/m4.py:39
Methodforward
MAPE loss as defined in: https://en.wikipedia.org/wiki/Mean_absolute_percentage_error :param forecast: Forecast values. Shape: batch
utils/losses.py:39
Methodforward
sMAPE loss as defined in https://robjhyndman.com/hyndsight/smape/ (Makridakis 1993) :param forecast: Forecast values. Shape: batch,
utils/losses.py:57
Methodforward
MASE loss as defined in "Scaled Errors" https://robjhyndman.com/papers/mase.pdf :param insample: Insample values. Shape: batch, time
utils/losses.py:75
Methodforward
(self, x)
layers/Autoformer_EncDec.py:15
Methodforward
(self, x)
layers/Autoformer_EncDec.py:31
Methodforward
(self, x)
layers/Autoformer_EncDec.py:50
Methodforward
(self, x)
layers/Autoformer_EncDec.py:66
Methodforward
(self, x, attn_mask=None)
layers/Autoformer_EncDec.py:95
Methodforward
(self, x, attn_mask=None)
layers/Autoformer_EncDec.py:120
Methodforward
(self, x, cross, x_mask=None, cross_mask=None)
layers/Autoformer_EncDec.py:161
Methodforward
(self, x, cross, x_mask=None, cross_mask=None, trend=None)
layers/Autoformer_EncDec.py:193
Methodforward
(self, x)
layers/Conv_Blocks.py:25
Methodforward
(self, x)
layers/Conv_Blocks.py:55
Methodforward
(self, x)
layers/Embed.py:26
Methodforward
(self, x)
layers/Embed.py:41
Methodforward
(self, x)
layers/Embed.py:63
Methodforward
(self, x)
layers/Embed.py:85
Methodforward
(self, x)
layers/Embed.py:106
Methodforward
(self, x, x_mark)
layers/Embed.py:121
Methodforward
(self, x, x_mark)
layers/Embed.py:141
Methodforward
(self, input: Tensor)
layers/Embed.py:154
Methodforward
(self, x)
layers/Embed.py:177
Methodforward
(self, x)
layers/Embed.py:196
Methodforward
(self, queries, keys, values, attn_mask, tau=None, delta=None)
layers/SelfAttention_Family.py:19
Methodforward
(self, queries, keys, values, attn_mask, tau=None, delta=None)
layers/SelfAttention_Family.py:55
Methodforward
(self, queries, keys, values, attn_mask, tau=None, delta=None)
layers/SelfAttention_Family.py:146
Methodforward
(self, queries, keys, values, attn_mask, tau=None, delta=None)
layers/SelfAttention_Family.py:193
Methodforward
(self, queries, keys, values, attn_mask, tau, delta)
layers/SelfAttention_Family.py:238
Methodforward
(self, x)
layers/Transformer_EncDec.py:18
Methodforward
(self, x, attn_mask=None, tau=None, delta=None)
layers/Transformer_EncDec.py:39
Methodforward
(self, x, attn_mask=None, tau=None, delta=None)
layers/Transformer_EncDec.py:61
Methodforward
(self, x, cross, x_mask=None, cross_mask=None, tau=None, delta=None)
layers/Transformer_EncDec.py:98
Methodforward
(self, x, cross, x_mask=None, cross_mask=None, tau=None, delta=None)
layers/Transformer_EncDec.py:126
Methodforward
(self, x, mode: str)
layers/StandardNorm.py:21
Methodforward
(self, queries, keys, values, attn_mask)
layers/AutoCorrelation.py:102
Methodforward
(self, queries, keys, values, attn_mask)
layers/AutoCorrelation.py:146
Methodforward
(self, x)
models/TimeLLM.py:23
Methodforward
(self, x_enc, x_mark_enc, x_dec, x_mark_dec, mask=None)
models/TimeLLM.py:194
Methodforward
(self, target_embedding, source_embedding, value_embedding)
models/TimeLLM.py:280
Methodforward
(self, x_enc, x_mark_enc, x_dec, x_mark_dec, mask=None)
models/DLinear.py:94
Methodforward
(self, x_enc, x_mark_enc, x_dec, x_mark_dec, mask=None)
models/Autoformer.py:144
Methodgroup_count
(group_name)
utils/m4_summary.py:121
Methodinverse_transform
(self, data)
utils/tools.py:102
Methodinverse_transform
(self, data)
data_provider/data_loader.py:107
Methodinverse_transform
(self, data)
data_provider/data_loader.py:205
Methodinverse_transform
(self, data)
data_provider/data_loader.py:310
Methodinverse_transform
(self, data)
data_provider_pretrain/data_loader.py:220
Functionload_m4_info
Load M4Info file. :return: Pandas DataFrame of M4Info.
data_provider/m4.py:126
Methodmask
(self)
utils/masking.py:11
Methodmask
(self)
utils/masking.py:25
Functionmetric
(pred, true)
utils/metrics.py:34
Functionprogress
(count, block_size, total_size)
data_provider/m4.py:47
Methodround_all
(d)
utils/m4_summary.py:107
Methodtime_delay_agg_full
Standard version of Autocorrelation
layers/AutoCorrelation.py:78
Functionurl_file_name
Extract file name from url. :param url: URL to extract file name from. :return: File name.
data_provider/m4.py:29
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