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Functions365 in github.com/BorealisAI/scaleformer

Method__init__
N: the order of the HiPPO projection dt: discretization step size - should be roughly inverse to the length of the sequence
models/FiLM.py:79
Method__init__
(self, in_channels, out_channels,seq_len, modes1,compression=0,ratio=0.5,mode_type=0)
models/FiLM.py:125
Method__init__
(self)
models/AutoformerMS.py:22
Method__init__
(self)
models/ReformerMS.py:23
Method__init__
(self)
models/PerformerMS.py:23
Method__init__
(self, configs)
models/Performer.py:28
Method__init__
(self)
models/FiLMMS.py:25
Method__init__
N: the order of the HiPPO projection dt: discretization step size - should be roughly inverse to the length of the sequence
models/FiLMMS.py:93
Method__init__
(self, in_channels, out_channels,seq_len, modes1,compression=0,ratio=0.5,mode_type=0)
models/FiLMMS.py:139
Method__init__
(self, configs)
models/Informer.py:37
Method__init__
(self, configs)
models/FEDformer.py:29
Method__init__
(self)
models/FEDformerMS.py:25
Method__init__
(self, configs)
models/Reformer.py:39
Method__init__
(self)
models/InformerMS.py:22
Method__init__
(self, configs)
models/Autoformer.py:35
Method__len__
(self)
data_provider/data_loader.py:107
Method__len__
(self)
data_provider/data_loader.py:197
Method__len__
(self)
data_provider/data_loader.py:316
Method__len__
(self)
data_provider/data_loader.py:410
Method__len__
(self)
data_provider/data_loader.py:516
Method__repr__
(self)
utils/timefeatures.py:38
Method_build_model
(self)
exp/exp_main.py:135
Method_get_data
(self)
exp/exp_basic.py:43
Function_init_weights
(module, initialization)
models/NHits.py:277
Function_init_weights
(module, initialization)
models/NHitsMS.py:291
Methodadd_outliers
(signal, perc=0.00001)
data_provider/data_loader.py:229
Functionaffine_sigmoid
Maps reals to (lo, hi), where 0 maps to (lo+hi)/2.
robust_loss_pytorch/util.py:64
Functionaffine_softplus
Maps real numbers to (lo, infinity), where 0 maps to ref.
robust_loss_pytorch/util.py:86
Functionanalytical_base_partition_function
r"""Accurately approximate the partition function Z(numer / denom). This uses the analytical formulation of the true partition function Z(alpha),
robust_loss_pytorch/distribution.py:38
Functioncollapse
Collapses a wavelet decomposition made by construct() back into an image. Args: pyr: A numpy or TF tensor of single or double precision floats
robust_loss_pytorch/wavelet.py:342
Methodcompl_mul1d
(self, input, weights)
layers/FourierCorrelation.py:110
Functioncompute_jacobian
Computes the Jacobian of function `f` with respect to input `x`.
robust_loss_pytorch/util.py:189
Functionconstruct
num_levels a wavelet decomposition of an image. Args: im: A numpy or TF tensor of single or double precision floats of size (batch_size,
robust_loss_pytorch/wavelet.py:294
Methodcpu
(self)
layers/utils.py:317
Methodcuda
(self)
layers/utils.py:313
Methoddecode
(self, x, sample_idx=None)
layers/utils.py:297
Methoddecode
(self, x, sample_idx=None)
layers/utils.py:335
Methoddecode
(self, x)
layers/utils.py:365
Methoddraw_samples
r"""Draw samples from the robust distribution. This function implements Algorithm 1 the paper. This code is written to allow for sampling
robust_loss_pytorch/distribution.py:212
Methodencode
(self, x)
layers/utils.py:293
Methodencode
(self, x)
layers/utils.py:331
Methodencode
(self, x)
layers/utils.py:358
Functionexp_safe
The same as torch.exp(x), but clamps the input to prevent NaNs.
robust_loss_pytorch/util.py:40
Functionexpm1_safe
The same as tf.math.expm1(x), but clamps the input to prevent NaNs.
robust_loss_pytorch/util.py:46
Methodforward
(self, queries, keys, values, attn_mask)
layers/MultiWaveletCorrelation.py:55
Methodforward
(self, q, k, v, mask=None)
layers/MultiWaveletCorrelation.py:130
Methodforward
(self, q, k, v, mask)
layers/MultiWaveletCorrelation.py:232
Methodforward
(self, x)
layers/MultiWaveletCorrelation.py:289
Methodforward
(self, x)
layers/MultiWaveletCorrelation.py:345
Methodforward
(self, x)
layers/Autoformer_EncDec.py:37
Methodforward
(self, x)
layers/Autoformer_EncDec.py:52
Methodforward
(self, x)
layers/Autoformer_EncDec.py:70
Methodforward
(self, x)
layers/Autoformer_EncDec.py:85
Methodforward
(self, x)
layers/Autoformer_EncDec.py:101
Methodforward
(self, x, attn_mask=None)
layers/Autoformer_EncDec.py:126
Methodforward
(self, x, attn_mask=None)
layers/Autoformer_EncDec.py:150
Methodforward
(self, x, cross, x_mask=None, cross_mask=None)
layers/Autoformer_EncDec.py:197
Methodforward
(self, x, cross, x_mask=None, cross_mask=None, trend=None)
layers/Autoformer_EncDec.py:230
Methodforward
(self, x)
layers/Embed.py:33
Methodforward
(self, x, scale=1)
layers/Embed.py:52
Methodforward
(self, x)
layers/Embed.py:65
Methodforward
(self, x)
layers/Embed.py:86
Methodforward
(self, x)
layers/Embed.py:108
Methodforward
(self, x)
layers/Embed.py:128
Methodforward
(self, x, scale=1)
layers/Embed.py:140
Methodforward
(self, x, x_mark)
layers/Embed.py:160
Methodforward
(self, x, x_mark, scale, first_scale, label_len)
layers/Embed.py:175
Methodforward
(self, x, x_mark)
layers/Embed.py:202
Methodforward
(self, q, k, v, mask)
layers/FourierCorrelation.py:71
Methodforward
(self, q, k, v, mask)
layers/FourierCorrelation.py:114
Methodforward
(self, queries, keys, values, attn_mask)
layers/SelfAttention_Family.py:31
Methodforward
(self, queries, keys, values, attn_mask)
layers/SelfAttention_Family.py:115
Methodforward
(self, queries, keys, values, attn_mask)
layers/SelfAttention_Family.py:158
Methodforward
(self, queries, keys, values, attn_mask)
layers/SelfAttention_Family.py:201
Methodforward
(self, queries, keys, values, attn_mask)
layers/SelfAttention_Family.py:217
Methodforward
(self, x)
layers/Transformer_EncDec.py:39
Methodforward
(self, x, attn_mask=None)
layers/Transformer_EncDec.py:60
Methodforward
(self, x, attn_mask=None)
layers/Transformer_EncDec.py:81
Methodforward
(self, x, cross, x_mask=None, cross_mask=None)
layers/Transformer_EncDec.py:117
Methodforward
(self, x, cross, x_mask=None, cross_mask=None)
layers/Transformer_EncDec.py:143
Methodforward
(self, queries, keys, values, attn_mask)
layers/AutoCorrelation.py:120
Methodforward
(self, queries, keys, values, attn_mask)
layers/AutoCorrelation.py:164
Methodforward
(self, x, kernel_size)
exp/exp_main.py:116
Methodforward
(self, x)
models/NHits.py:53
Methodforward
(self, x)
models/NHits.py:80
Methodforward
(self, x)
models/NHits.py:100
Methodforward
(self, x)
models/NHits.py:113
Methodforward
(self, x)
models/NHits.py:128
Methodforward
(self, x)
models/NHits.py:139
Methodforward
(self, x)
models/NHits.py:152
Methodforward
(self, theta: t.Tensor, insample_x_t: t.Tensor, outsample_x_t: t.Tensor)
models/NHits.py:167
Methodforward
(self, theta: t.Tensor, insample_x_t: t.Tensor, outsample_x_t: t.Tensor)
models/NHits.py:196
Methodforward
(self, theta: t.Tensor, insample_x_t: t.Tensor, outsample_x_t: t.Tensor)
models/NHits.py:243
Methodforward
(self, theta: t.Tensor, insample_x_t: t.Tensor, outsample_x_t: t.Tensor)
models/NHits.py:268
Methodforward
(self, insample_y: t.Tensor, insample_x_t: t.Tensor, outsample_x_t: t.Tensor, x_s: t.Tensor)
models/NHits.py:362
Methodforward
(self, x_enc, x_mark_enc, x_dec, x_mark_dec, return_decomposition=False, **kwargs)
models/NHits.py:497
Methodforward
(self, x, scale=1)
models/NHitsMS.py:28
Methodforward
(self, x)
models/NHitsMS.py:67
Methodforward
(self, x)
models/NHitsMS.py:94
Methodforward
(self, x)
models/NHitsMS.py:114
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