remove freq from PyTorchPredictor

autoformer/estimator.py

@@ -278,7 +278,6 @@ class AutoformerEstimator(PyTorchLightningEstimator):
             input_names=PREDICTION_INPUT_NAMES,
             prediction_net=module.model,
             batch_size=self.batch_size,
-            freq=self.freq,
             prediction_length=self.prediction_length,
             device=torch.device("cuda" if torch.cuda.is_available() else "cpu"),
         )

etsformer/estimator.py

@@ -273,7 +273,6 @@ class ETSformerEstimator(PyTorchLightningEstimator):
             input_names=PREDICTION_INPUT_NAMES,
             prediction_net=module.model,
             batch_size=self.batch_size,
-            freq=self.freq,
             prediction_length=self.prediction_length,
             device=torch.device("cuda" if torch.cuda.is_available() else "cpu"),
         )

hopfield/estimator.py

@@ -274,7 +274,6 @@ class HopfieldEstimator(PyTorchLightningEstimator):
             input_names=PREDICTION_INPUT_NAMES,
             prediction_net=module.model,
             batch_size=self.batch_size,
-            freq=self.freq,
             prediction_length=self.prediction_length,
             device=torch.device("cuda" if torch.cuda.is_available() else "cpu"),
         )

hopfield/hopfield_estimator.py

@@ -256,7 +256,6 @@ class HopfieldEstimator(PyTorchEstimator):
             input_names=input_names,
             prediction_net=prediction_network,
             batch_size=self.trainer.batch_size,
-            freq=self.freq,
             prediction_length=self.prediction_length,
             device=device,
         )

informer/estimator.py

@@ -281,7 +281,6 @@ class InformerEstimator(PyTorchLightningEstimator):
             input_names=PREDICTION_INPUT_NAMES,
             prediction_net=module.model,
             batch_size=self.batch_size,
-            freq=self.freq,
             prediction_length=self.prediction_length,
             device=torch.device("cuda" if torch.cuda.is_available() else "cpu"),
         )

pyraformer/estimator.py

@@ -325,7 +325,6 @@ class PyraformerEstimator(PyTorchLightningEstimator):
             input_names=PREDICTION_INPUT_NAMES,
             prediction_net=module.model,
             batch_size=self.batch_size,
-            freq=self.freq,
             prediction_length=self.prediction_length,
             device=torch.device("cuda" if torch.cuda.is_available() else "cpu"),
         )

reformer/estimator.py

@@ -270,7 +270,6 @@ class ReformerEstimator(PyTorchLightningEstimator):
             input_names=PREDICTION_INPUT_NAMES,
             prediction_net=module.model,
             batch_size=self.batch_size,
-            freq=self.freq,
             prediction_length=self.prediction_length,
             device=torch.device("cuda" if torch.cuda.is_available() else "cpu"),
         )

switch/estimator.py

@@ -284,7 +284,6 @@ class SwitchTransformerEstimator(PyTorchLightningEstimator):
             input_names=PREDICTION_INPUT_NAMES,
             prediction_net=module.model,
             batch_size=self.batch_size,
-            freq=self.freq,
             prediction_length=self.prediction_length,
             device=torch.device("cuda" if torch.cuda.is_available() else "cpu"),
         )

template/ts-template.ipynb

@@ -544,7 +544,6 @@
     "            input_names=PREDICTION_INPUT_NAMES,\n",
     "            prediction_net=module.model,\n",
     "            batch_size=self.batch_size,\n",
-    "            freq=self.freq,\n",
     "            prediction_length=self.prediction_length,\n",
     "        )\n",
     "\n",

transformer/estimator.py

@@ -274,7 +274,6 @@ class TransformerEstimator(PyTorchLightningEstimator):
             input_names=PREDICTION_INPUT_NAMES,
             prediction_net=module.model,
             batch_size=self.batch_size,
-            freq=self.freq,
             prediction_length=self.prediction_length,
             device=torch.device("cuda" if torch.cuda.is_available() else "cpu"),
         )

xformers/xformers.ipynb

@@ -821,7 +821,6 @@
                 "            input_names=PREDICTION_INPUT_NAMES,\n",
                 "            prediction_net=module.model,\n",
                 "            batch_size=self.batch_size,\n",
-                "            freq=self.freq,\n",
                 "            prediction_length=self.prediction_length,\n",
                 "            device=torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\"),\n",
                 "        )\n",