Make add-new-model-like work in an env without all frameworks

src/transformers/commands/add_new_model_like.py

@@ -25,6 +25,7 @@
 import transformers.models.auto as auto_module
 from transformers.models.auto.configuration_auto import model_type_to_module_name
 
+from ..file_utils import is_flax_available, is_tf_available, is_torch_available
 from ..utils import logging
 from . import BaseTransformersCLICommand
 
@@ -501,7 +502,7 @@ def filter_framework_files(
         `List[Union[str, os.PathLike]]`: The list of filtered files.
     """
     if frameworks is None:
-        return files
+        frameworks = get_default_frameworks()
 
     framework_to_file = {}
     others = []
@@ -598,6 +599,20 @@ def find_base_model_checkpoint(
     return ""
 
 
+def get_default_frameworks():
+    """
+    Returns the list of frameworks (PyTorch, TensorFlow, Flax) that are installed in the environment.
+    """
+    frameworks = []
+    if is_torch_available():
+        frameworks.append("pt")
+    if is_tf_available():
+        frameworks.append("tf")
+    if is_flax_available():
+        frameworks.append("flax")
+    return frameworks
+
+
 _re_model_mapping = re.compile("MODEL_([A-Z_]*)MAPPING_NAMES")
 
 
@@ -616,17 +631,19 @@ def retrieve_model_classes(model_type: str, frameworks: Optional[List[str]] = No
         that framework as values.
     """
     if frameworks is None:
-        frameworks = ["pt", "tf", "flax"]
+        frameworks = get_default_frameworks()
 
     modules = {
-        "pt": auto_module.modeling_auto,
-        "tf": auto_module.modeling_tf_auto,
-        "flax": auto_module.modeling_flax_auto,
+        "pt": auto_module.modeling_auto if is_torch_available() else None,
+        "tf": auto_module.modeling_tf_auto if is_tf_available() else None,
+        "flax": auto_module.modeling_flax_auto if is_flax_available() else None,
     }
 
     model_classes = {}
     for framework in frameworks:
         new_model_classes = []
+        if modules[framework] is None:
+            raise ValueError(f"You selected {framework} in the frameworks, but it is not installed.")
         model_mappings = [attr for attr in dir(modules[framework]) if _re_model_mapping.search(attr) is not None]
         for model_mapping_name in model_mappings:
             model_mapping = getattr(modules[framework], model_mapping_name)
@@ -683,9 +700,9 @@ def retrieve_info_for_model(model_type, frameworks: Optional[List[str]] = None):
             available_frameworks.append("pt")
 
     if frameworks is None:
-        frameworks = available_frameworks.copy()
-    else:
-        frameworks = [f for f in frameworks if f in available_frameworks]
+        frameworks = get_default_frameworks()
+
+    frameworks = [f for f in frameworks if f in available_frameworks]
 
     model_classes = retrieve_model_classes(model_type, frameworks=frameworks)
 
@@ -738,7 +755,7 @@ def clean_frameworks_in_init(
             Whether or not to keep the preprocessing (tokenizer, feature extractor, processor) imports in the init.
     """
     if frameworks is None:
-        frameworks = ["pt", "tf", "flax"]
+        frameworks = get_default_frameworks()
 
     names = {"pt": "torch"}
     to_remove = [names.get(f, f) for f in ["pt", "tf", "flax"] if f not in frameworks]
@@ -1040,7 +1057,7 @@ def duplicate_doc_file(
         content = f.read()
 
     if frameworks is None:
-        frameworks = ["pt", "tf", "flax"]
+        frameworks = get_default_frameworks()
     if dest_file is None:
         dest_file = Path(doc_file).parent / f"{new_model_patterns.model_type}.mdx"
 
@@ -1302,7 +1319,7 @@ def __init__(self, config_file=None, path_to_repo=None, *args):
             self.old_model_type = config["old_model_type"]
             self.model_patterns = ModelPatterns(**config["new_model_patterns"])
             self.add_copied_from = config.get("add_copied_from", True)
-            self.frameworks = config.get("frameworks", ["pt", "tf", "flax"])
+            self.frameworks = config.get("frameworks", get_default_frameworks())
             self.old_checkpoint = config.get("old_checkpoint", None)
         else:
             (