More logger entries + better tf_gpt2 handle

aitextgen/aitextgen.py

@@ -66,7 +66,7 @@ class aitextgen:
     :param unk_token: String to override the unknown token
     """
 
-    openai_gpt2_large = False
+    openai_tf_gpt2 = None
 
     # default values for GPT2Tokenizer
     tokenizer = None
@@ -110,9 +110,7 @@ def __init__(
             logging.getLogger("transformers.modeling_utils").setLevel(logging.ERROR)
 
         if tf_gpt2:
-            if tf_gpt2 != "124M":
-                self.openai_gpt2_large = True
-                gradient_checkpointing = True
+            self.openai_tf_gpt2 = tf_gpt2
 
             # Download + convert the TF weights if a PyTorch model has not been created
             if not os.path.isfile(
@@ -188,7 +186,8 @@ def __init__(
                     cache_dir=cache_dir,
                 )
 
-        if gradient_checkpointing:
+        if gradient_checkpointing or tf_gpt2 in ["355M", "774M", "1558M"]:
+            logger.info("Gradient checkpointing enabled for model training.")
             setattr(self.model.config, "gradient_checkpointing", True)
             setattr(self.model.config, "use_cache", False)
 
@@ -597,7 +596,8 @@ def train(
                 **kwargs,
             )
 
-        if freeze_layers or self.openai_gpt2_large:
+        if freeze_layers or self.openai_tf_gpt2 == "1558M":
+            logger.info("Layer freezing enabled for model training.")
             freeze_layers = True
             if num_layers_freeze:
                 assert (