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[FIX] Fixes 948 multivariate predict/val issues when n_series > 1024 #962

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merged 4 commits into from
Apr 10, 2024
Merged

[FIX] Fixes 948 multivariate predict/val issues when n_series > 1024 #962

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9665686
fix_issue
elephaint Apr 10, 2024
3e8468c
fix_frequency_in_unit_test
elephaint Apr 10, 2024
8b49880
fix_unit_test_comme
elephaint Apr 10, 2024
be270b5
Merge branch 'main' into 948-tsmixerx-model-batch-size-mismatch-if-nu…
elephaint Apr 10, 2024
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4 changes: 3 additions & 1 deletion nbs/common.base_multivariate.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -493,6 +493,7 @@
" return self._fit(\n",
" dataset=dataset,\n",
" batch_size=self.n_series,\n",
" valid_batch_size=self.n_series,\n",
" val_size=val_size,\n",
" test_size=test_size,\n",
" random_seed=random_seed,\n",
Expand All @@ -516,7 +517,8 @@
"\n",
" self.predict_step_size = step_size\n",
" self.decompose_forecast = False\n",
" datamodule = TimeSeriesDataModule(dataset=dataset,\n",
" datamodule = TimeSeriesDataModule(dataset=dataset, \n",
" valid_batch_size=self.n_series, \n",
" batch_size=self.n_series,\n",
" **data_module_kwargs)\n",
"\n",
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33 changes: 31 additions & 2 deletions nbs/models.tsmixerx.ipynb
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Expand Up @@ -515,9 +515,10 @@
"#| hide\n",
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"import logging\n",
"import warnings\n",
"import pandas as pd\n",
"\n",
"from neuralforecast import NeuralForecast\n",
"from neuralforecast.utils import AirPassengersPanel, AirPassengersStatic\n",
"from neuralforecast.utils import AirPassengersPanel, AirPassengersStatic, generate_series\n",
"from neuralforecast.losses.pytorch import MAE, MSE, RMSE, MAPE, SMAPE, MASE, relMSE, QuantileLoss, MQLoss, DistributionLoss,PMM, GMM, NBMM, HuberLoss, TukeyLoss, HuberQLoss, HuberMQLoss\n"
]
},
Expand Down Expand Up @@ -589,7 +590,35 @@
" )\n",
"fcst = NeuralForecast(models=[model], freq='M')\n",
"fcst.fit(df=Y_train_df_single, static_df=AirPassengersStatic_single, val_size=12)\n",
"forecasts = fcst.predict(futr_df=Y_test_df_single) "
"forecasts = fcst.predict(futr_df=Y_test_df_single) \n",
"\n",
"# Test n_series > 1024\n",
"# See issue: https://github.com/Nixtla/neuralforecast/issues/948\n",
"n_series = 1111\n",
"Y_df, S_df = generate_series(n_series=n_series, n_temporal_features=2, n_static_features=2)\n",
"\n",
"model = TSMixerx(\n",
" h=12,\n",
" input_size=24,\n",
" n_series=n_series,\n",
" stat_exog_list=['static_0', 'static_1'],\n",
" hist_exog_list=[\"temporal_0\", \"temporal_1\"],\n",
" n_block=4,\n",
" ff_dim=3,\n",
" revin=True,\n",
" scaler_type=\"standard\",\n",
" max_steps=5,\n",
" early_stop_patience_steps=-1,\n",
" val_check_steps=5,\n",
" learning_rate=1e-3,\n",
" loss=MAE(),\n",
" valid_loss=MAE(),\n",
" batch_size=32,\n",
")\n",
"\n",
"fcst = NeuralForecast(models=[model], freq=\"D\")\n",
"fcst.fit(df=Y_df, static_df=S_df, val_size=12)\n",
"forecasts = fcst.predict()"
]
},
{
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6 changes: 5 additions & 1 deletion neuralforecast/common/_base_multivariate.py
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Expand Up @@ -525,6 +525,7 @@ def fit(
return self._fit(
dataset=dataset,
batch_size=self.n_series,
valid_batch_size=self.n_series,
val_size=val_size,
test_size=test_size,
random_seed=random_seed,
Expand Down Expand Up @@ -556,7 +557,10 @@ def predict(
self.predict_step_size = step_size
self.decompose_forecast = False
datamodule = TimeSeriesDataModule(
dataset=dataset, batch_size=self.n_series, **data_module_kwargs
dataset=dataset,
valid_batch_size=self.n_series,
batch_size=self.n_series,
**data_module_kwargs,
)

# Protect when case of multiple gpu. PL does not support return preds with multiple gpu.
Expand Down
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