- Development

configuration_norbert.py

@@ -0,0 +1,35 @@
+# Taken from https://huggingface.co/ltg/norbert3-large/blob/main/configuration_norbert.py
+from transformers.configuration_utils import PretrainedConfig
+
+class NorbertConfig(PretrainedConfig):
+    """Configuration class to store the configuration of a `NorbertModel`.
+    """
+    def __init__(
+        self,
+        vocab_size=50000,
+        attention_probs_dropout_prob=0.1,
+        hidden_dropout_prob=0.1,
+        hidden_size=768,
+        intermediate_size=2048,
+        max_position_embeddings=512,
+        position_bucket_size=32,
+        num_attention_heads=12,
+        num_hidden_layers=12,
+        layer_norm_eps=1.0e-7,
+        output_all_encoded_layers=True,
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+
+        self.vocab_size = vocab_size
+        self.hidden_size = hidden_size
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads
+        self.intermediate_size = intermediate_size
+        self.hidden_dropout_prob = hidden_dropout_prob
+        self.attention_probs_dropout_prob = attention_probs_dropout_prob
+        self.max_position_embeddings = max_position_embeddings
+        self.output_all_encoded_layers = output_all_encoded_layers
+        self.position_bucket_size = position_bucket_size
+        self.layer_norm_eps = layer_norm_eps
+

modeling_humit_tagger.py

@@ -43,15 +43,16 @@ class HumitTaggerModel(torch.nn.Module):
         spec.loader.exec_module(lemma_rules)
 
         # Download base_model files into cache
-        base_config_file = hf_hub_download(repo_id=kwargs["this_model_config"]["base_model"], filename=kwargs["this_model_config"]["base_model_config_file"])
+#        base_config_file = hf_hub_download(repo_id=kwargs["this_model_config"]["base_model"], filename=kwargs["this_model_config"]["base_model_config_file"])
+        base_config_file = hf_hub_download(repo_id=repo_name, filename=kwargs["this_model_config"]["base_model_config_file"])
 #        base_model_file = hf_hub_download(repo_id=kwargs["this_model_config"]["base_model"], filename=kwargs["this_model_config"]["base_model_model_file"])
         base_model_file = hf_hub_download(repo_id=repo_name, filename=kwargs["this_model_config"]["base_model_model_file"])
         base_model_config_json_file = hf_hub_download(repo_id=kwargs["this_model_config"]["base_model"], filename=kwargs["this_model_config"]["base_model_config_json_file"])
         fullformlist_file = hf_hub_download(repo_id=repo_name, filename=kwargs["this_model_config"]["fullformlist_file"])
 
         # Copy base model's configuration python file into our working directory
-        config_file_path = os.path.join(os.path.dirname(os.path.abspath(__file__)) , os.path.basename(base_config_file))
-        shutil.copyfile(base_config_file, config_file_path)
+#        config_file_path = os.path.join(os.path.dirname(os.path.abspath(__file__)) , os.path.basename(base_config_file))
+#        shutil.copyfile(base_config_file, config_file_path)
 
         # HACK: Modify base model main file since __init.py__ has already been read and the new file must not contain relative imports
 #        base_model_file_path = os.path.join(os.path.dirname(os.path.abspath(__file__)) , os.path.basename(base_model_file))
@@ -62,8 +63,11 @@ class HumitTaggerModel(torch.nn.Module):
         
         # Register the new files:
         # First register the base model config file
-        sys.path.append(os.path.dirname(config_file_path))
-        spec = importlib.util.spec_from_file_location("base_config", config_file_path)
+#        sys.path.append(os.path.dirname(config_file_path))
+#        spec = importlib.util.spec_from_file_location("base_config", config_file_path)
+        sys.path.append(os.path.dirname(base_config_file))
+        spec = importlib.util.spec_from_file_location("base_config", base_config_file)
+
         base_config = importlib.util.module_from_spec(spec)
         sys.modules["base_config"] = base_config
         spec.loader.exec_module(base_config)