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[FEAT] DeepNPTS model #990

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merged 12 commits into from
May 7, 2024
Merged

[FEAT] DeepNPTS model #990

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18cae4c
deepnpts_firststab
elephaint Apr 18, 2024
17d1ef0
deepnpts_simple
elephaint Apr 22, 2024
7bfe7bc
update_model_files
elephaint May 6, 2024
012a8c2
deepnpts_firststab
elephaint Apr 18, 2024
54b2f0a
deepnpts_simple
elephaint Apr 22, 2024
d702d63
update_model_files
elephaint May 6, 2024
8c18ab3
merge_conflicts
elephaint May 6, 2024
5002fbd
add_deepnpts_to_eval
elephaint May 6, 2024
237be0d
add_deepnpts_to_eval
elephaint May 6, 2024
df82264
fix_conflicts
elephaint May 6, 2024
90960f1
test
jmoralez May 6, 2024
d3bf75b
remove_eval_false_from_usage_example
elephaint May 6, 2024
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2 changes: 1 addition & 1 deletion action_files/test_models/src/evaluation.py
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Expand Up @@ -43,7 +43,7 @@ def evaluate(model: str, dataset: str, group: str):
groups = ['Monthly']
models = ['AutoDilatedRNN', 'RNN', 'TCN', 'DeepAR',
'NHITS', 'TFT', 'AutoMLP', 'DLinear', 'VanillaTransformer',
'BiTCN', 'TiDE']
'BiTCN', 'TiDE', 'DeepNPTS']
datasets = ['M3']
evaluation = [evaluate(model, dataset, group) for model, group in product(models, groups) for dataset in datasets]
evaluation = [eval_ for eval_ in evaluation if eval_ is not None]
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2 changes: 2 additions & 0 deletions action_files/test_models/src/models.py
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Expand Up @@ -28,6 +28,7 @@
from neuralforecast.models.dlinear import DLinear
from neuralforecast.models.bitcn import BiTCN
from neuralforecast.models.tide import TiDE
from neuralforecast.models.deepnpts import DeepNPTS

from neuralforecast.auto import (
AutoMLP,
Expand Down Expand Up @@ -76,6 +77,7 @@ def main(dataset: str = 'M3', group: str = 'Monthly') -> None:
DeepAR(h=horizon, input_size=2 * horizon, scaler_type='minmax1', max_steps=1000),
BiTCN(h=horizon, input_size=2 * horizon, loss=MAE(), dropout=0.0, max_steps=1000, val_check_steps=500),
TiDE(h=horizon, input_size=2 * horizon, loss=MAE(), max_steps=1000, val_check_steps=500),
DeepNPTS(h=horizon, input_size=2 * horizon, loss=MAE(), max_steps=1000, val_check_steps=500),
]

# Models
Expand Down
4 changes: 2 additions & 2 deletions nbs/common.scalers.ipynb
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Expand Up @@ -567,8 +567,8 @@
" shape = list(x.shape)\n",
" shape[dim] = 1\n",
"\n",
" x_shift = torch.zeros(shape)\n",
" x_scale = torch.ones(shape)\n",
" x_shift = torch.zeros(shape, device=x.device)\n",
" x_scale = torch.ones(shape, device=x.device)\n",
"\n",
" return x_shift, x_scale"
]
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4 changes: 3 additions & 1 deletion nbs/core.ipynb
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Expand Up @@ -91,7 +91,7 @@
" Informer, Autoformer, FEDformer,\n",
" StemGNN, PatchTST, TimesNet, TimeLLM, TSMixer, TSMixerx,\n",
" MLPMultivariate, iTransformer,\n",
" BiTCN, TiDE\n",
" BiTCN, TiDE, DeepNPTS,\n",
")"
]
},
Expand Down Expand Up @@ -239,6 +239,8 @@
" 'itransformer': iTransformer, 'autoitransformer': iTransformer,\n",
" 'bitcn': BiTCN, 'autobitcn': BiTCN,\n",
" 'tide': TiDE, 'autotide': TiDE,\n",
" 'deepnpts': DeepNPTS, 'autodeepnpts': DeepNPTS,\n",
"\n",
"}"
]
},
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2 changes: 1 addition & 1 deletion nbs/losses.pytorch.ipynb
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Expand Up @@ -67,7 +67,7 @@
" Normal, \n",
" StudentT, \n",
" Poisson,\n",
" NegativeBinomial\n",
" NegativeBinomial,\n",
")\n",
"\n",
"from torch.distributions import constraints"
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373 changes: 373 additions & 0 deletions nbs/models.deepnpts.ipynb
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397 changes: 142 additions & 255 deletions nbs/models.ipynb
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11 changes: 11 additions & 0 deletions neuralforecast/_modidx.py
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Expand Up @@ -24,6 +24,11 @@
'neuralforecast/auto.py'),
'neuralforecast.auto.AutoDeepAR.get_default_config': ( 'models.html#autodeepar.get_default_config',
'neuralforecast/auto.py'),
'neuralforecast.auto.AutoDeepNPTS': ('models.html#autodeepnpts', 'neuralforecast/auto.py'),
'neuralforecast.auto.AutoDeepNPTS.__init__': ( 'models.html#autodeepnpts.__init__',
'neuralforecast/auto.py'),
'neuralforecast.auto.AutoDeepNPTS.get_default_config': ( 'models.html#autodeepnpts.get_default_config',
'neuralforecast/auto.py'),
'neuralforecast.auto.AutoDilatedRNN': ('models.html#autodilatedrnn', 'neuralforecast/auto.py'),
'neuralforecast.auto.AutoDilatedRNN.__init__': ( 'models.html#autodilatedrnn.__init__',
'neuralforecast/auto.py'),
Expand Down Expand Up @@ -512,6 +517,12 @@
'neuralforecast/models/deepar.py'),
'neuralforecast.models.deepar.DeepAR.validation_step': ( 'models.deepar.html#deepar.validation_step',
'neuralforecast/models/deepar.py')},
'neuralforecast.models.deepnpts': { 'neuralforecast.models.deepnpts.DeepNPTS': ( 'models.deepnpts.html#deepnpts',
'neuralforecast/models/deepnpts.py'),
'neuralforecast.models.deepnpts.DeepNPTS.__init__': ( 'models.deepnpts.html#deepnpts.__init__',
'neuralforecast/models/deepnpts.py'),
'neuralforecast.models.deepnpts.DeepNPTS.forward': ( 'models.deepnpts.html#deepnpts.forward',
'neuralforecast/models/deepnpts.py')},
'neuralforecast.models.dilated_rnn': { 'neuralforecast.models.dilated_rnn.AttentiveLSTMLayer': ( 'models.dilated_rnn.html#attentivelstmlayer',
'neuralforecast/models/dilated_rnn.py'),
'neuralforecast.models.dilated_rnn.AttentiveLSTMLayer.__init__': ( 'models.dilated_rnn.html#attentivelstmlayer.__init__',
Expand Down
103 changes: 87 additions & 16 deletions neuralforecast/auto.py
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Expand Up @@ -2,9 +2,10 @@

# %% auto 0
__all__ = ['AutoRNN', 'AutoLSTM', 'AutoGRU', 'AutoTCN', 'AutoDeepAR', 'AutoDilatedRNN', 'AutoBiTCN', 'AutoMLP', 'AutoNBEATS',
'AutoNBEATSx', 'AutoNHITS', 'AutoDLinear', 'AutoNLinear', 'AutoTiDE', 'AutoTFT', 'AutoVanillaTransformer',
'AutoInformer', 'AutoAutoformer', 'AutoFEDformer', 'AutoPatchTST', 'AutoiTransformer', 'AutoTimesNet',
'AutoStemGNN', 'AutoHINT', 'AutoTSMixer', 'AutoTSMixerx', 'AutoMLPMultivariate']
'AutoNBEATSx', 'AutoNHITS', 'AutoDLinear', 'AutoNLinear', 'AutoTiDE', 'AutoDeepNPTS', 'AutoTFT',
'AutoVanillaTransformer', 'AutoInformer', 'AutoAutoformer', 'AutoFEDformer', 'AutoPatchTST',
'AutoiTransformer', 'AutoTimesNet', 'AutoStemGNN', 'AutoHINT', 'AutoTSMixer', 'AutoTSMixerx',
'AutoMLPMultivariate']

# %% ../nbs/models.ipynb 2
from os import cpu_count
Expand All @@ -31,6 +32,7 @@
from .models.dlinear import DLinear
from .models.nlinear import NLinear
from .models.tide import TiDE
from .models.deepnpts import DeepNPTS

from .models.tft import TFT
from .models.vanillatransformer import VanillaTransformer
Expand Down Expand Up @@ -1033,7 +1035,76 @@ def get_default_config(cls, h, backend, n_series=None):

return config

# %% ../nbs/models.ipynb 71
# %% ../nbs/models.ipynb 70
class AutoDeepNPTS(BaseAuto):

default_config = {
"input_size_multiplier": [1, 2, 3, 4, 5],
"h": None,
"hidden_size": tune.choice([16, 32, 64]),
"dropout": tune.uniform(0.0, 0.99),
"n_layers": tune.choice([1, 2, 4]),
"learning_rate": tune.loguniform(1e-4, 1e-1),
"scaler_type": tune.choice([None, "robust", "standard"]),
"max_steps": tune.quniform(lower=500, upper=1500, q=100),
"batch_size": tune.choice([32, 64, 128, 256]),
"windows_batch_size": tune.choice([128, 256, 512, 1024]),
"loss": None,
"random_seed": tune.randint(lower=1, upper=20),
}

def __init__(
self,
h,
loss=MAE(),
valid_loss=None,
config=None,
search_alg=BasicVariantGenerator(random_state=1),
num_samples=10,
refit_with_val=False,
cpus=cpu_count(),
gpus=torch.cuda.device_count(),
verbose=False,
alias=None,
backend="ray",
callbacks=None,
):

# Define search space, input/output sizes
if config is None:
config = self.get_default_config(h=h, backend=backend)

super(AutoDeepNPTS, self).__init__(
cls_model=DeepNPTS,
h=h,
loss=loss,
valid_loss=valid_loss,
config=config,
search_alg=search_alg,
num_samples=num_samples,
refit_with_val=refit_with_val,
cpus=cpus,
gpus=gpus,
verbose=verbose,
alias=alias,
backend=backend,
callbacks=callbacks,
)

@classmethod
def get_default_config(cls, h, backend, n_series=None):
config = cls.default_config.copy()
config["input_size"] = tune.choice(
[h * x for x in config["input_size_multiplier"]]
)
config["step_size"] = tune.choice([1, h])
del config["input_size_multiplier"]
if backend == "optuna":
config = cls._ray_config_to_optuna(config)

return config

# %% ../nbs/models.ipynb 75
class AutoTFT(BaseAuto):

default_config = {
Expand Down Expand Up @@ -1101,7 +1172,7 @@ def get_default_config(cls, h, backend, n_series=None):

return config

# %% ../nbs/models.ipynb 75
# %% ../nbs/models.ipynb 79
class AutoVanillaTransformer(BaseAuto):

default_config = {
Expand Down Expand Up @@ -1169,7 +1240,7 @@ def get_default_config(cls, h, backend, n_series=None):

return config

# %% ../nbs/models.ipynb 79
# %% ../nbs/models.ipynb 83
class AutoInformer(BaseAuto):

default_config = {
Expand Down Expand Up @@ -1237,7 +1308,7 @@ def get_default_config(cls, h, backend, n_series=None):

return config

# %% ../nbs/models.ipynb 83
# %% ../nbs/models.ipynb 87
class AutoAutoformer(BaseAuto):

default_config = {
Expand Down Expand Up @@ -1305,7 +1376,7 @@ def get_default_config(cls, h, backend, n_series=None):

return config

# %% ../nbs/models.ipynb 87
# %% ../nbs/models.ipynb 91
class AutoFEDformer(BaseAuto):

default_config = {
Expand Down Expand Up @@ -1372,7 +1443,7 @@ def get_default_config(cls, h, backend, n_series=None):

return config

# %% ../nbs/models.ipynb 91
# %% ../nbs/models.ipynb 95
class AutoPatchTST(BaseAuto):

default_config = {
Expand Down Expand Up @@ -1442,7 +1513,7 @@ def get_default_config(cls, h, backend, n_series=None):

return config

# %% ../nbs/models.ipynb 95
# %% ../nbs/models.ipynb 99
class AutoiTransformer(BaseAuto):

default_config = {
Expand Down Expand Up @@ -1527,7 +1598,7 @@ def get_default_config(cls, h, backend, n_series):

return config

# %% ../nbs/models.ipynb 100
# %% ../nbs/models.ipynb 104
class AutoTimesNet(BaseAuto):

default_config = {
Expand Down Expand Up @@ -1595,7 +1666,7 @@ def get_default_config(cls, h, backend, n_series=None):

return config

# %% ../nbs/models.ipynb 105
# %% ../nbs/models.ipynb 109
class AutoStemGNN(BaseAuto):

default_config = {
Expand Down Expand Up @@ -1680,7 +1751,7 @@ def get_default_config(cls, h, backend, n_series):

return config

# %% ../nbs/models.ipynb 109
# %% ../nbs/models.ipynb 113
class AutoHINT(BaseAuto):

def __init__(
Expand Down Expand Up @@ -1752,7 +1823,7 @@ def _fit_model(
def get_default_config(cls, h, backend, n_series=None):
raise Exception("AutoHINT has no default configuration.")

# %% ../nbs/models.ipynb 114
# %% ../nbs/models.ipynb 118
class AutoTSMixer(BaseAuto):

default_config = {
Expand Down Expand Up @@ -1838,7 +1909,7 @@ def get_default_config(cls, h, backend, n_series):

return config

# %% ../nbs/models.ipynb 118
# %% ../nbs/models.ipynb 122
class AutoTSMixerx(BaseAuto):

default_config = {
Expand Down Expand Up @@ -1924,7 +1995,7 @@ def get_default_config(cls, h, backend, n_series):

return config

# %% ../nbs/models.ipynb 122
# %% ../nbs/models.ipynb 126
class AutoMLPMultivariate(BaseAuto):

default_config = {
Expand Down
4 changes: 2 additions & 2 deletions neuralforecast/common/_scalers.py
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Expand Up @@ -313,8 +313,8 @@ def identity_statistics(x, mask, dim=-1, eps=1e-6):
shape = list(x.shape)
shape[dim] = 1

x_shift = torch.zeros(shape)
x_scale = torch.ones(shape)
x_shift = torch.zeros(shape, device=x.device)
x_scale = torch.ones(shape, device=x.device)

return x_shift, x_scale

Expand Down
3 changes: 3 additions & 0 deletions neuralforecast/core.py
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Expand Up @@ -58,6 +58,7 @@
iTransformer,
BiTCN,
TiDE,
DeepNPTS,
)

# %% ../nbs/core.ipynb 5
Expand Down Expand Up @@ -173,6 +174,8 @@ def _insample_times(
"autobitcn": BiTCN,
"tide": TiDE,
"autotide": TiDE,
"deepnpts": DeepNPTS,
"autodeepnpts": DeepNPTS,
}

# %% ../nbs/core.ipynb 8
Expand Down
8 changes: 7 additions & 1 deletion neuralforecast/losses/pytorch.py
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Expand Up @@ -13,7 +13,13 @@

import torch.nn.functional as F
from torch.distributions import Distribution
from torch.distributions import Bernoulli, Normal, StudentT, Poisson, NegativeBinomial
from torch.distributions import (
Bernoulli,
Normal,
StudentT,
Poisson,
NegativeBinomial,
)

from torch.distributions import constraints

Expand Down
4 changes: 2 additions & 2 deletions neuralforecast/models/__init__.py
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Expand Up @@ -2,7 +2,7 @@
'MLP', 'NHITS', 'NBEATS', 'NBEATSx', 'DLinear', 'NLinear',
'TFT', 'VanillaTransformer', 'Informer', 'Autoformer', 'PatchTST', 'FEDformer',
'StemGNN', 'HINT', 'TimesNet', 'TimeLLM', 'TSMixer', 'TSMixerx', 'MLPMultivariate',
'iTransformer', 'BiTCN', 'TiDE',
'iTransformer', 'BiTCN', 'TiDE', 'DeepNPTS'
]

from .rnn import RNN
Expand Down Expand Up @@ -33,4 +33,4 @@
from .itransformer import iTransformer
from .bitcn import BiTCN
from .tide import TiDE

from .deepnpts import DeepNPTS
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