Update modeling_emotion_classifier.py

modeling_emotion_classifier.py

@@ -1,8 +1,20 @@
-from transformers import PreTrainedModel, HubertConfig, HubertModel,PretrainedConfig
-import torch.nn as nn
+import os
 import torch
+import torch.nn as nn
+from transformers import PreTrainedModel, HubertConfig, HubertModel
+from transformers.file_utils import (
+    WEIGHTS_NAME,
+    TF2_WEIGHTS_NAME,
+    TF_WEIGHTS_NAME,
+    cached_path,
+    hf_bucket_url,
+    is_remote_url,
+)
+from transformers.utils import logging
 from .configuration_emotion_classifier import EmotionClassifierConfig
 
+logger = logging.get_logger(__name__)
+
 class EmotionClassifierHuBERT(PreTrainedModel):
     config_class = EmotionClassifierConfig
 
@@ -47,7 +59,7 @@ class EmotionClassifierHuBERT(PreTrainedModel):
         mirror = kwargs.pop("mirror", None)
 
         # Load config if we don't provide a configuration
-        if not isinstance(config, PretrainedConfig):
+        if not isinstance(config, EmotionClassifierConfig):
             config_path = config if config is not None else pretrained_model_name_or_path
             config, model_kwargs = cls.config_class.from_pretrained(
                 config_path,
@@ -156,4 +168,4 @@ class EmotionClassifierHuBERT(PreTrainedModel):
             loading_info = {"missing_keys": missing_keys, "unexpected_keys": unexpected_keys}
             return model, loading_info
 
-        return model
+        return model