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Functions365 in github.com/BorealisAI/scaleformer

⨍ Functions 365◇ Types & classes 119
↓ 1 callersMethodtransform
(self, insample_x_t, outsample_x_t)
models/NHitsMS.py:244
↓ 1 callersMethodtransform
(self, insample_x_t, outsample_x_t)
models/NHitsMS.py:271
↓ 1 callersFunctiontransition
A, B transition matrices for different measures. measure: the type of measure legt - Legendre (translated) legs - Legendre (scaled)
models/FiLM.py:21
↓ 1 callersFunctiontransition
A, B transition matrices for different measures. measure: the type of measure legt - Legendre (translated) legs - Legendre (scaled)
models/FiLMMS.py:35
↓ 1 callersMethodwavelet_transform
(self, x)
layers/MultiWaveletCorrelation.py:370
FunctionCORR
(pred, true)
utils/metrics.py:30
MethodMackey_Glass
(N, T)
data_provider/data_loader.py:210
FunctionRSE
(pred, true)
utils/metrics.py:26
Method__call__
(self, val_loss, model, path)
utils/tools.py:56
Method__call__
(self, index: pd.DatetimeIndex)
utils/timefeatures.py:35
Method__call__
(self, index: pd.DatetimeIndex)
utils/timefeatures.py:45
Method__call__
(self, index: pd.DatetimeIndex)
utils/timefeatures.py:52
Method__call__
(self, index: pd.DatetimeIndex)
utils/timefeatures.py:59
Method__call__
(self, index: pd.DatetimeIndex)
utils/timefeatures.py:66
Method__call__
(self, index: pd.DatetimeIndex)
utils/timefeatures.py:73
Method__call__
(self, index: pd.DatetimeIndex)
utils/timefeatures.py:80
Method__call__
(self, index: pd.DatetimeIndex)
utils/timefeatures.py:87
Method__call__
(self, index: pd.DatetimeIndex)
utils/timefeatures.py:94
Method__call__
(self, x, y)
layers/utils.py:414
Method__getitem__
(self, index)
data_provider/data_loader.py:94
Method__getitem__
(self, index)
data_provider/data_loader.py:184
Method__getitem__
(self, index)
data_provider/data_loader.py:304
Method__getitem__
(self, index)
data_provider/data_loader.py:397
Method__getitem__
(self, index)
data_provider/data_loader.py:500
Method__init__
(self, B, L, device="cpu")
utils/masking.py:27
Method__init__
(self, B, H, L, index, scores, device="cpu")
utils/masking.py:38
Method__init__
(self, patience=7, verbose=False, delta=0)
utils/tools.py:47
Method__init__
(self, mean, std)
utils/tools.py:86
Method__init__
(self)
utils/timefeatures.py:32
Method__init__
Sets up the adaptive loss for a matrix of inputs. Args: num_dims: The number of dimensions of the input to come. float_dtype: The flo
robust_loss_pytorch/adaptive.py:211
Method__init__
Sets up the adaptive form of the robust loss on a set of images. This function is a wrapper around AdaptiveLossFunction. It requires inputs o
robust_loss_pytorch/adaptive.py:345
Method__init__
(self)
robust_loss_pytorch/distribution.py:132
Method__init__
(self, ich=1, k=8, alpha=16, c=128, nCZ=1, L=0, base='legendre', attention_dropout=0.1)
layers/MultiWaveletCorrelation.py:42
Method__init__
(self, in_channels, out_channels, seq_len_q, seq_len_kv, modes, c=64, k=8, ich=512,
layers/MultiWaveletCorrelation.py:83
Method__init__
(self, in_channels, out_channels, modes=16, activation='tanh')
layers/MultiWaveletCorrelation.py:224
Method__init__
(self, k, alpha, c=1, nl=1, initializer=None,
layers/MultiWaveletCorrelation.py:272
Method__init__
(self, x, eps=0.00001)
layers/utils.py:285
Method__init__
(self, x, eps=0.00001)
layers/utils.py:324
Method__init__
(self, x, low=0.0, high=1.0)
layers/utils.py:350
Method__init__
(self, channels)
layers/Autoformer_EncDec.py:33
Method__init__
(self, kernel_size, stride)
layers/Autoformer_EncDec.py:47
Method__init__
(self, kernel_size)
layers/Autoformer_EncDec.py:66
Method__init__
(self, kernel_size)
layers/Autoformer_EncDec.py:80
Method__init__
(self)
layers/Autoformer_EncDec.py:97
Method__init__
(self, attention, d_model, d_ff=None, moving_avg=25, dropout=0.1, activation="relu")
layers/Autoformer_EncDec.py:109
Method__init__
(self, self_attention, cross_attention, d_model, c_out, d_ff=None, moving_avg=25, dropout=0.1
layers/Autoformer_EncDec.py:174
Method__init__
(self, layers, norm_layer=None, projection=None)
layers/Autoformer_EncDec.py:224
Method__init__
(self, d_model, max_len=5000)
layers/Embed.py:18
Method__init__
(self, d_model, max_len=5000)
layers/Embed.py:37
Method__init__
(self, c_in, d_model)
layers/Embed.py:56
Method__init__
(self, c_in, d_model)
layers/Embed.py:71
Method__init__
(self, d_model, embed_type='fixed', freq='h')
layers/Embed.py:91
Method__init__
(self, d_model, embed_type='timeF', freq='h')
layers/Embed.py:121
Method__init__
(self, d_model, embed_type='timeF', freq='h')
layers/Embed.py:132
Method__init__
(self, c_in, d_model, embed_type='fixed', freq='h', dropout=0.1, is_decoder=False)
layers/Embed.py:165
Method__init__
(self, c_in, d_model, embed_type='fixed', freq='h', dropout=0.1)
layers/Embed.py:192
Method__init__
(self, in_channels, out_channels, seq_len_q, seq_len_kv, modes=64, mode_select_method='random',
layers/FourierCorrelation.py:88
Method__init__
(self, mask_flag=True, factor=5, scale=None, attention_dropout=0.1, output_attention=False)
layers/SelfAttention_Family.py:54
Method__init__
(self, attention, d_model, n_heads, d_keys=None, d_values=None)
layers/SelfAttention_Family.py:144
Method__init__
(self, attention, d_model, n_heads, d_keys=None, d_values=None, causal=False, bucket_size=4,
layers/SelfAttention_Family.py:179
Method__init__
(self, attention, d_model, n_heads, d_keys=None, d_values=None, causal=False)
layers/SelfAttention_Family.py:208
Method__init__
(self, c_in)
layers/Transformer_EncDec.py:28
Method__init__
(self, attention, d_model, d_ff=None, dropout=0.1, activation="relu")
layers/Transformer_EncDec.py:49
Method__init__
(self, self_attention, cross_attention, d_model, d_ff=None, dropout=0.1, activation="relu")
layers/Transformer_EncDec.py:103
Method__init__
(self, layers, norm_layer=None, projection=None)
layers/Transformer_EncDec.py:137
Method__init__
(self, correlation, d_model, n_heads, d_keys=None, d_values=None)
layers/AutoCorrelation.py:150
Method__init__
(self, args)
exp/exp_basic.py:26
Method__init__
(self, x, loc, scale)
exp/exp_main.py:44
Method__init__
(self)
exp/exp_main.py:114
Method__init__
(self, root_path, flag='train', size=None, features='S', data_path='ETTh1.csv',
data_provider/data_loader.py:27
Method__init__
(self, root_path, flag='train', size=None, features='S', data_path='ETTm1.csv',
data_provider/data_loader.py:115
Method__init__
(self, root_path, flag='train', size=None, features='S', data_path='ETTh1.csv',
data_provider/data_loader.py:204
Method__init__
(self, root_path, flag='train', size=None, features='S', data_path='ETTh1.csv',
data_provider/data_loader.py:320
Method__init__
(self, root_path, flag='pred', size=None, features='S', data_path='ETTh1.csv',
data_provider/data_loader.py:418
Method__init__
(self, in_channels, out_channels, kernel_size, padding, dilation, activation, stride:int=1, w
models/NHits.py:39
Method__init__
(self, n_inputs, n_outputs, kernel_size, stride, dilation, padding, dropout=0.2)
models/NHits.py:57
Method__init__
(self, num_inputs, num_channels, kernel_size=2, dropout=0.2)
models/NHits.py:87
Method__init__
(self, repeats)
models/NHits.py:109
Method__init__
(self, chomp_size)
models/NHits.py:124
Method__init__
(self, in_features, out_features)
models/NHits.py:132
Method__init__
(self, in_features, out_features, n_time_in)
models/NHits.py:144
Method__init__
(self, backcast_size: int, forecast_size: int, interpolation_mode: str)
models/NHits.py:160
Method__init__
(self)
models/NHits.py:193
Method__init__
(self, out_features, in_features, num_levels=4, kernel_size=3, dropout_prob=0)
models/NHits.py:206
Method__init__
(self, out_features, in_features, num_levels = 4, kernel_size=2, dropout_prob=0)
models/NHits.py:252
Method__init__
models/NHits.py:307
Method__init__
(self)
models/NHitsMS.py:25
Method__init__
(self, in_channels, out_channels, kernel_size, padding, dilation, activation, stride:int=1, w
models/NHitsMS.py:53
Method__init__
(self, n_inputs, n_outputs, kernel_size, stride, dilation, padding, dropout=0.2)
models/NHitsMS.py:71
Method__init__
(self, num_inputs, num_channels, kernel_size=2, dropout=0.2)
models/NHitsMS.py:101
Method__init__
(self, repeats)
models/NHitsMS.py:123
Method__init__
(self, chomp_size)
models/NHitsMS.py:138
Method__init__
(self, in_features, out_features)
models/NHitsMS.py:146
Method__init__
(self, in_features, out_features, n_time_in)
models/NHitsMS.py:158
Method__init__
(self, backcast_size: int, forecast_size: int, interpolation_mode: str)
models/NHitsMS.py:174
Method__init__
(self)
models/NHitsMS.py:207
Method__init__
(self, out_features, in_features, num_levels=4, kernel_size=3, dropout_prob=0)
models/NHitsMS.py:220
Method__init__
(self, out_features, in_features, num_levels = 4, kernel_size=2, dropout_prob=0)
models/NHitsMS.py:266
Method__init__
models/NHitsMS.py:321
Method__init__
(self, configs)
models/Transformer.py:34
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