Add PyTorch Hub configuration file (#259)

hubconf.py

@@ -0,0 +1,42 @@
+from clip.clip import tokenize as _tokenize, load as _load, available_models as _available_models
+import re
+import string
+
+dependencies = ["torch", "torchvision", "ftfy", "regex", "tqdm"]
+
+# For compatibility (cannot include special characters in function name)
+model_functions = { model: re.sub(f'[{string.punctuation}]', '_', model) for model in _available_models()}
+
+def _create_hub_entrypoint(model):
+    def entrypoint(**kwargs):      
+        return _load(model, **kwargs)
+    
+    entrypoint.__doc__ = f"""Loads the {model} CLIP model
+
+        Parameters
+        ----------
+        device : Union[str, torch.device]
+            The device to put the loaded model
+
+        jit : bool
+            Whether to load the optimized JIT model or more hackable non-JIT model (default).
+
+        download_root: str
+            path to download the model files; by default, it uses "~/.cache/clip"
+
+        Returns
+        -------
+        model : torch.nn.Module
+            The {model} CLIP model
+
+        preprocess : Callable[[PIL.Image], torch.Tensor]
+            A torchvision transform that converts a PIL image into a tensor that the returned model can take as its input
+        """
+    return entrypoint
+
+def tokenize():
+    return _tokenize
+
+_entrypoints = {model_functions[model]: _create_hub_entrypoint(model) for model in _available_models()}
+
+globals().update(_entrypoints)