better error message

pytorch_pretrained_bert/modeling.py

@@ -658,7 +658,6 @@ class BertPreTrainedModel(nn.Module):
         # redirect to the cache, if necessary
         try:
             resolved_archive_file = cached_path(archive_file, cache_dir=cache_dir)
-            resolved_config_file = cached_path(config_file, cache_dir=cache_dir)
         except EnvironmentError:
             if pretrained_model_name_or_path in PRETRAINED_MODEL_ARCHIVE_MAP:
                 logger.error(
@@ -673,6 +672,22 @@ class BertPreTrainedModel(nn.Module):
                         ', '.join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()),
                         archive_file))
             return None
+        try:
+            resolved_config_file = cached_path(config_file, cache_dir=cache_dir)
+        except EnvironmentError:
+            if pretrained_model_name_or_path in PRETRAINED_CONFIG_ARCHIVE_MAP:
+                logger.error(
+                    "Couldn't reach server at '{}' to download pretrained model configuration file.".format(
+                        config_file))
+            else:
+                logger.error(
+                    "Model name '{}' was not found in model name list ({}). "
+                    "We assumed '{}' was a path or url but couldn't find any file "
+                    "associated to this path or url.".format(
+                        pretrained_model_name_or_path,
+                        ', '.join(PRETRAINED_CONFIG_ARCHIVE_MAP.keys()),
+                        config_file))
+            return None
         if resolved_archive_file == archive_file and resolved_config_file == config_file:
             logger.info("loading weights file {}".format(archive_file))
             logger.info("loading configuration file {}".format(config_file))

pytorch_pretrained_bert/modeling_gpt2.py

@@ -493,7 +493,6 @@ class GPT2PreTrainedModel(nn.Module):
         # redirect to the cache, if necessary
         try:
             resolved_archive_file = cached_path(archive_file, cache_dir=cache_dir)
-            resolved_config_file = cached_path(config_file, cache_dir=cache_dir)
         except EnvironmentError:
             if pretrained_model_name_or_path in PRETRAINED_MODEL_ARCHIVE_MAP:
                 logger.error(
@@ -502,10 +501,27 @@ class GPT2PreTrainedModel(nn.Module):
             else:
                 logger.error(
                     "Model name '{}' was not found in model name list ({}). "
-                    "We assumed '{}' was a path or url but couldn't find files {} and {} "
+                    "We assumed '{}' was a path or url but couldn't find file {} "
                     "at this path or url.".format(
                         pretrained_model_name_or_path, ", ".join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()), pretrained_model_name_or_path,
-                        archive_file, config_file
+                        archive_file
+                    )
+                )
+            return None
+        try:
+            resolved_config_file = cached_path(config_file, cache_dir=cache_dir)
+        except EnvironmentError:
+            if pretrained_model_name_or_path in PRETRAINED_CONFIG_ARCHIVE_MAP:
+                logger.error(
+                    "Couldn't reach server at '{}' to download pretrained model configuration file.".format(
+                        config_file))
+            else:
+                logger.error(
+                    "Model name '{}' was not found in model name list ({}). "
+                    "We assumed '{}' was a path or url but couldn't find file {} "
+                    "at this path or url.".format(
+                        pretrained_model_name_or_path, ", ".join(PRETRAINED_CONFIG_ARCHIVE_MAP.keys()), pretrained_model_name_or_path,
+                        config_file
                     )
                 )
             return None

pytorch_pretrained_bert/modeling_openai.py

@@ -496,7 +496,6 @@ class OpenAIGPTPreTrainedModel(nn.Module):
         # redirect to the cache, if necessary
         try:
             resolved_archive_file = cached_path(archive_file, cache_dir=cache_dir)
-            resolved_config_file = cached_path(config_file, cache_dir=cache_dir)
         except EnvironmentError:
             if pretrained_model_name_or_path in PRETRAINED_MODEL_ARCHIVE_MAP:
                 logger.error(
@@ -505,10 +504,27 @@ class OpenAIGPTPreTrainedModel(nn.Module):
             else:
                 logger.error(
                     "Model name '{}' was not found in model name list ({}). "
-                    "We assumed '{}' was a path or url but couldn't find files {} and {} "
+                    "We assumed '{}' was a path or url but couldn't find file {} "
                     "at this path or url.".format(
                         pretrained_model_name_or_path, ", ".join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()), pretrained_model_name_or_path,
-                        archive_file, config_file
+                        archive_file
+                    )
+                )
+            return None
+        try:
+            resolved_config_file = cached_path(config_file, cache_dir=cache_dir)
+        except EnvironmentError:
+            if pretrained_model_name_or_path in PRETRAINED_CONFIG_ARCHIVE_MAP:
+                logger.error(
+                    "Couldn't reach server at '{}' to download pretrained model configuration file.".format(
+                        config_file))
+            else:
+                logger.error(
+                    "Model name '{}' was not found in model name list ({}). "
+                    "We assumed '{}' was a path or url but couldn't find file {} "
+                    "at this path or url.".format(
+                        pretrained_model_name_or_path, ", ".join(PRETRAINED_CONFIG_ARCHIVE_MAP.keys()), pretrained_model_name_or_path,
+                        config_file
                     )
                 )
             return None

pytorch_pretrained_bert/modeling_transfo_xl.py

@@ -921,7 +921,6 @@ class TransfoXLPreTrainedModel(nn.Module):
         # redirect to the cache, if necessary
         try:
             resolved_archive_file = cached_path(archive_file, cache_dir=cache_dir)
-            resolved_config_file = cached_path(config_file, cache_dir=cache_dir)
         except EnvironmentError:
             if pretrained_model_name_or_path in PRETRAINED_MODEL_ARCHIVE_MAP:
                 logger.error(
@@ -930,12 +929,29 @@ class TransfoXLPreTrainedModel(nn.Module):
             else:
                 logger.error(
                     "Model name '{}' was not found in model name list ({}). "
-                    "We assumed '{}' was a path or url but couldn't find files {} and {} "
+                    "We assumed '{}' was a path or url but couldn't find file {} "
                     "at this path or url.".format(
-                        pretrained_model_name_or_path,
-                        ', '.join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()),
-                        pretrained_model_name_or_path,
-                        archive_file, config_file))
+                        pretrained_model_name_or_path, ", ".join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()), pretrained_model_name_or_path,
+                        archive_file
+                    )
+                )
+            return None
+        try:
+            resolved_config_file = cached_path(config_file, cache_dir=cache_dir)
+        except EnvironmentError:
+            if pretrained_model_name_or_path in PRETRAINED_CONFIG_ARCHIVE_MAP:
+                logger.error(
+                    "Couldn't reach server at '{}' to download pretrained model configuration file.".format(
+                        config_file))
+            else:
+                logger.error(
+                    "Model name '{}' was not found in model name list ({}). "
+                    "We assumed '{}' was a path or url but couldn't find file {} "
+                    "at this path or url.".format(
+                        pretrained_model_name_or_path, ", ".join(PRETRAINED_CONFIG_ARCHIVE_MAP.keys()), pretrained_model_name_or_path,
+                        config_file
+                    )
+                )
             return None
         if resolved_archive_file == archive_file and resolved_config_file == config_file:
             logger.info("loading weights file {}".format(archive_file))