fix back

Author: lostella

scripts/evaluation/configs/zero-shot.yaml

@@ -1,137 +1,137 @@
 # Backtest configs for the 27 "zero-shot" datasets.
 # These datasets were not seen by Chronos models during training.
-- name: monash_traffic
-  hf_repo: autogluon/chronos_datasets
-  offset: -24
-  prediction_length: 24
-  num_rolls: 1
-- name: monash_australian_electricity
-  hf_repo: autogluon/chronos_datasets
-  offset: -48
-  prediction_length: 48
-  num_rolls: 1
-- name: ercot
-  hf_repo: autogluon/chronos_datasets
-  offset: -24
-  prediction_length: 24
-  num_rolls: 1
-- name: ETTm
-  hf_repo: autogluon/chronos_datasets_extra
-  offset: -96
-  prediction_length: 24
-  num_rolls: 1
-- name: ETTh
-  hf_repo: autogluon/chronos_datasets_extra
-  offset: -24
-  prediction_length: 24
-  num_rolls: 1
-- name: exchange_rate
-  hf_repo: autogluon/chronos_datasets
-  offset: -30
-  prediction_length: 30
-  num_rolls: 1
-- name: nn5
-  hf_repo: autogluon/chronos_datasets
-  offset: -56
-  prediction_length: 56
-  num_rolls: 1
-- name: monash_nn5_weekly
-  hf_repo: autogluon/chronos_datasets
-  offset: -8
-  prediction_length: 8
-  num_rolls: 1
-- name: monash_weather
-  hf_repo: autogluon/chronos_datasets
-  offset: -30
-  prediction_length: 30
-  num_rolls: 1
-- name: monash_covid_deaths
-  hf_repo: autogluon/chronos_datasets
-  offset: -30
-  prediction_length: 30
-  num_rolls: 1
-- name: monash_fred_md
-  hf_repo: autogluon/chronos_datasets
-  offset: -12
-  prediction_length: 12
-  num_rolls: 1
-- name: m4_quarterly
-  hf_repo: autogluon/chronos_datasets
-  offset: -8
-  prediction_length: 8
-  num_rolls: 1
-- name: m4_yearly
-  hf_repo: autogluon/chronos_datasets
-  offset: -6
-  prediction_length: 6
-  num_rolls: 1
-- name: dominick
-  hf_repo: autogluon/chronos_datasets
-  offset: -8
-  prediction_length: 8
-  num_rolls: 1
-- name: m5
-  hf_repo: autogluon/chronos_datasets
-  offset: -28
-  prediction_length: 28
-  num_rolls: 1
-- name: monash_tourism_monthly
-  hf_repo: autogluon/chronos_datasets
-  offset: -24
-  prediction_length: 24
-  num_rolls: 1
-- name: monash_tourism_quarterly
-  hf_repo: autogluon/chronos_datasets
-  offset: -8
-  prediction_length: 8
-  num_rolls: 1
-- name: monash_tourism_yearly
-  hf_repo: autogluon/chronos_datasets
-  offset: -4
-  prediction_length: 4
-  num_rolls: 1
-- name: monash_car_parts
-  hf_repo: autogluon/chronos_datasets
-  offset: -12
-  prediction_length: 12
-  num_rolls: 1
+# - name: monash_traffic
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -24
+#   prediction_length: 24
+#   num_rolls: 1
+# - name: monash_australian_electricity
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -48
+#   prediction_length: 48
+#   num_rolls: 1
+# - name: ercot
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -24
+#   prediction_length: 24
+#   num_rolls: 1
+# - name: ETTm
+#   hf_repo: autogluon/chronos_datasets_extra
+#   offset: -96
+#   prediction_length: 24
+#   num_rolls: 1
+# - name: ETTh
+#   hf_repo: autogluon/chronos_datasets_extra
+#   offset: -24
+#   prediction_length: 24
+#   num_rolls: 1
+# - name: exchange_rate
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -30
+#   prediction_length: 30
+#   num_rolls: 1
+# - name: nn5
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -56
+#   prediction_length: 56
+#   num_rolls: 1
+# - name: monash_nn5_weekly
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -8
+#   prediction_length: 8
+#   num_rolls: 1
+# - name: monash_weather
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -30
+#   prediction_length: 30
+#   num_rolls: 1
+# - name: monash_covid_deaths
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -30
+#   prediction_length: 30
+#   num_rolls: 1
+# - name: monash_fred_md
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -12
+#   prediction_length: 12
+#   num_rolls: 1
+# - name: m4_quarterly
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -8
+#   prediction_length: 8
+#   num_rolls: 1
+# - name: m4_yearly
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -6
+#   prediction_length: 6
+#   num_rolls: 1
+# - name: dominick
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -8
+#   prediction_length: 8
+#   num_rolls: 1
+# - name: m5
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -28
+#   prediction_length: 28
+#   num_rolls: 1
+# - name: monash_tourism_monthly
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -24
+#   prediction_length: 24
+#   num_rolls: 1
+# - name: monash_tourism_quarterly
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -8
+#   prediction_length: 8
+#   num_rolls: 1
+# - name: monash_tourism_yearly
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -4
+#   prediction_length: 4
+#   num_rolls: 1
+# - name: monash_car_parts
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -12
+#   prediction_length: 12
+#   num_rolls: 1
 - name: monash_hospital
   hf_repo: autogluon/chronos_datasets
   offset: -12
   prediction_length: 12
   num_rolls: 1
-- name: monash_cif_2016
-  hf_repo: autogluon/chronos_datasets
-  offset: -12
-  prediction_length: 12
-  num_rolls: 1
-- name: monash_m1_yearly
-  hf_repo: autogluon/chronos_datasets
-  offset: -6
-  prediction_length: 6
-  num_rolls: 1
-- name: monash_m1_quarterly
-  hf_repo: autogluon/chronos_datasets
-  offset: -8
-  prediction_length: 8
-  num_rolls: 1
-- name: monash_m1_monthly
-  hf_repo: autogluon/chronos_datasets
-  offset: -18
-  prediction_length: 18
-  num_rolls: 1
-- name: monash_m3_monthly
-  hf_repo: autogluon/chronos_datasets
-  offset: -18
-  prediction_length: 18
-  num_rolls: 1
-- name: monash_m3_yearly
-  hf_repo: autogluon/chronos_datasets
-  offset: -6
-  prediction_length: 6
-  num_rolls: 1
-- name: monash_m3_quarterly
-  hf_repo: autogluon/chronos_datasets
-  offset: -8
-  prediction_length: 8
-  num_rolls: 1
+# - name: monash_cif_2016
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -12
+#   prediction_length: 12
+#   num_rolls: 1
+# - name: monash_m1_yearly
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -6
+#   prediction_length: 6
+#   num_rolls: 1
+# - name: monash_m1_quarterly
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -8
+#   prediction_length: 8
+#   num_rolls: 1
+# - name: monash_m1_monthly
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -18
+#   prediction_length: 18
+#   num_rolls: 1
+# - name: monash_m3_monthly
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -18
+#   prediction_length: 18
+#   num_rolls: 1
+# - name: monash_m3_yearly
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -6
+#   prediction_length: 6
+#   num_rolls: 1
+# - name: monash_m3_quarterly
+#   hf_repo: autogluon/chronos_datasets
+#   offset: -8
+#   prediction_length: 8
+#   num_rolls: 1

scripts/evaluation/evaluate.py

@@ -239,7 +239,7 @@ def generate_sample_forecasts(
     # Generate forecast samples
     forecast_samples = []
     for batch in tqdm(batcher(test_data_input, batch_size=batch_size)):
-        context = [torch.tensor(entry["target"], torch.float32) for entry in batch]
+        context = [torch.tensor(entry["target"]) for entry in batch]
         forecast_samples.append(
             pipeline.predict(
                 context,

src/chronos/chronos.py

@@ -371,13 +371,10 @@ def left_pad_and_stack_1D(tensors: List[torch.Tensor]) -> torch.Tensor:
         assert isinstance(c, torch.Tensor)
         assert c.ndim == 1
         padding = torch.full(
-            size=(max_len - len(c),),
-            fill_value=torch.nan,
-            device=c.device,
-            dtype=c.dtype,
+            size=(max_len - len(c),), fill_value=torch.nan, device=c.device
         )
         padded.append(torch.concat((padding, c), dim=-1))
-    return torch.stack(padded)
+    return torch.stack(padded).to(tensors[0])
 
 
 @dataclass