set max length to 120

flairNLP · Dec 14, 2021 · f6f9f42 · f6f9f42
1 parent 819417f
commit f6f9f42
Show file tree

Hide file tree

Showing 59 changed files with 1,586 additions and 4,781 deletions.
diff --git a/examples/ner/run_ner.py b/examples/ner/run_ner.py
@@ -28,58 +28,38 @@ class ModelArguments:
         default="first",
         metadata={"help": "Subtoken pooling strategy used for fine-tuned."},
     )
-    hidden_size: int = field(
-        default=256, metadata={"help": "Hidden size for NER model."}
-    )
-    use_crf: bool = field(
-        default=False, metadata={"help": "Whether to use a CRF on-top or not."}
-    )
+    hidden_size: int = field(default=256, metadata={"help": "Hidden size for NER model."})
+    use_crf: bool = field(default=False, metadata={"help": "Whether to use a CRF on-top or not."})
 
 
 @dataclass
 class TrainingArguments:
-    num_epochs: int = field(
-        default=10, metadata={"help": "The number of training epochs."}
-    )
-    batch_size: int = field(
-        default=8, metadata={"help": "Batch size used for training."}
-    )
+    num_epochs: int = field(default=10, metadata={"help": "The number of training epochs."})
+    batch_size: int = field(default=8, metadata={"help": "Batch size used for training."})
     mini_batch_chunk_size: int = field(
         default=1,
         metadata={"help": "If smaller than batch size, batches will be chunked."},
     )
     learning_rate: float = field(default=5e-05, metadata={"help": "Learning rate"})
-    seed: int = field(
-        default=42, metadata={"help": "Seed used for reproducible fine-tuning results."}
-    )
+    seed: int = field(default=42, metadata={"help": "Seed used for reproducible fine-tuning results."})
     device: str = field(default="cuda:0", metadata={"help": "CUDA device string."})
-    weight_decay: float = field(
-        default=0.0, metadata={"help": "Weight decay for optimizer."}
-    )
-    embeddings_storage_mode: str = field(
-        default="none", metadata={"help": "Defines embedding storage method."}
-    )
+    weight_decay: float = field(default=0.0, metadata={"help": "Weight decay for optimizer."})
+    embeddings_storage_mode: str = field(default="none", metadata={"help": "Defines embedding storage method."})
 
 
 @dataclass
 class FlertArguments:
-    context_size: int = field(
-        default=0, metadata={"help": "Context size when using FLERT approach."}
-    )
+    context_size: int = field(default=0, metadata={"help": "Context size when using FLERT approach."})
     respect_document_boundaries: bool = field(
         default=False,
-        metadata={
-            "help": "Whether to respect document boundaries or not when using FLERT."
-        },
+        metadata={"help": "Whether to respect document boundaries or not when using FLERT."},
     )
 
 
 @dataclass
 class DataArguments:
     dataset_name: str = field(metadata={"help": "Flair NER dataset name."})
-    dataset_arguments: str = field(
-        default="", metadata={"help": "Dataset arguments for Flair NER dataset."}
-    )
+    dataset_arguments: str = field(default="", metadata={"help": "Dataset arguments for Flair NER dataset."})
     output_dir: str = field(
         default="resources/taggers/ner",
         metadata={"help": "Defines output directory for final fine-tuned model."},
@@ -91,11 +71,7 @@ def get_flair_corpus(data_args):
 
     for name, obj in inspect.getmembers(flair.datasets.sequence_labeling):
         if inspect.isclass(obj):
-            if (
-                name.startswith("NER")
-                or name.startswith("CONLL")
-                or name.startswith("WNUT")
-            ):
+            if name.startswith("NER") or name.startswith("CONLL") or name.startswith("WNUT"):
                 ner_task_mapping[name] = obj
 
     dataset_args = {}
@@ -105,17 +81,13 @@ def get_flair_corpus(data_args):
         dataset_args = json.loads(data_args.dataset_arguments)
 
     if not dataset_name in ner_task_mapping:
-        raise ValueError(
-            f"Dataset name {dataset_name} is not a valid Flair datasets name!"
-        )
+        raise ValueError(f"Dataset name {dataset_name} is not a valid Flair datasets name!")
 
     return ner_task_mapping[dataset_name](**dataset_args)
 
 
 def main():
-    parser = HfArgumentParser(
-        (ModelArguments, TrainingArguments, FlertArguments, DataArguments)
-    )
+    parser = HfArgumentParser((ModelArguments, TrainingArguments, FlertArguments, DataArguments))
 
     if len(sys.argv) == 2 and sys.argv[1].endswith(".json"):
         (

diff --git a/flair/__init__.py b/flair/__init__.py
@@ -41,9 +41,7 @@
                 "stream": "ext://sys.stdout",
             }
         },
-        "loggers": {
-            "flair": {"handlers": ["console"], "level": "INFO", "propagate": False}
-        },
+        "loggers": {"flair": {"handlers": ["console"], "level": "INFO", "propagate": False}},
     }
 )