folder creation fix

ThilinaRajapakse · Jan 29, 2020 · 36256f1 · 36256f1
1 parent 489d4f7
commit 36256f1
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Showing 4 changed files with 12 additions and 7 deletions.
diff --git a/simpletransformers/classification/classification_model.py b/simpletransformers/classification/classification_model.py
@@ -147,7 +147,9 @@ def __init__(
         if args:
             self.args.update(args)
 
-        self.tokenizer = tokenizer_class.from_pretrained(model_name, do_lower_case=self.args["do_lower_case"], **kwargs)
+        self.tokenizer = tokenizer_class.from_pretrained(model_name,
+                                                         do_lower_case=self.args["do_lower_case"],
+                                                         **kwargs)
 
         self.args["model_name"] = model_name
         self.args["model_type"] = model_type
@@ -408,7 +410,10 @@ def train(
                     ):
                         # Only evaluate when single GPU otherwise metrics may not average well
                         results, _, _ = self.eval_model(
-                            eval_df, verbose=verbose and args["evaluate_during_training_verbose"], silent=True, **kwargs
+                            eval_df,
+                            verbose=verbose and args["evaluate_during_training_verbose"],
+                            silent=True,
+                            **kwargs
                         )
                         for key, value in results.items():
                             tb_writer.add_scalar("eval_{}".format(key), value, global_step)
@@ -679,7 +684,7 @@ def load_and_cache_examples(
             output_mode = "classification"
 
         if not os.path.isdir(self.args["cache_dir"]):
-            os.mkdir(self.args["cache_dir"])
+            os.makedirs(self.args["cache_dir"])
 
         mode = "dev" if evaluate else "train"
         cached_features_file = os.path.join(

diff --git a/simpletransformers/experimental/classification/classification_model.py b/simpletransformers/experimental/classification/classification_model.py
@@ -449,7 +449,7 @@ def load_and_cache_examples(self, examples, evaluate=False, no_cache=False, mult
         args = self.args
 
         if not os.path.isdir(self.args["cache_dir"]):
-            os.mkdir(self.args["cache_dir"])
+            os.makedirs(self.args["cache_dir"])
 
         mode = "dev" if evaluate else "train"
         cached_features_file = os.path.join(args["cache_dir"], "cached_{}_{}_{}_{}_{}".format(mode, args["model_type"], args["max_seq_length"], self.num_labels, len(examples)))

diff --git a/simpletransformers/ner/ner_model.py b/simpletransformers/ner/ner_model.py
@@ -730,7 +730,7 @@ def load_and_cache_examples(
         )
 
         if not os.path.isdir(self.args["cache_dir"]):
-            os.mkdir(self.args["cache_dir"])
+            os.makedirs(self.args["cache_dir"])
 
         if os.path.exists(cached_features_file) and (
             (not args["reprocess_input_data"] and not no_cache)

diff --git a/simpletransformers/question_answering/question_answering_model.py b/simpletransformers/question_answering/question_answering_model.py
@@ -147,7 +147,7 @@ def load_and_cache_examples(
         no_cache = args['no_cache']
 
         if not os.path.isdir(self.args["cache_dir"]):
-            os.mkdir(self.args["cache_dir"])
+            os.makedirs(self.args["cache_dir"])
 
         examples = get_examples(examples, is_training=not evaluate)
 
@@ -653,7 +653,7 @@ def evaluate(self, eval_data, output_dir):
 
         prefix = "test"
         if not os.path.isdir(output_dir):
-            os.mkdir(output_dir)
+            os.makedirs(output_dir)
 
         output_prediction_file = os.path.join(
             output_dir, "predictions_{}.json".format(prefix)