Fixes #396

clip/clip.py

@@ -2,8 +2,8 @@ import hashlib
 import os
 import urllib
 import warnings
-from packaging import version
+from typing import Any, Union, List
-from typing import Union, List
+from pkg_resources import packaging
 
 import torch
 from PIL import Image
@@ -20,7 +20,7 @@ except ImportError:
     BICUBIC = Image.BICUBIC
 
 
-if version.parse(torch.__version__) < version.parse("1.7.1"):
+if packaging.version.parse(torch.__version__) < packaging.version.parse("1.7.1"):
     warnings.warn("PyTorch version 1.7.1 or higher is recommended")
 
 
@@ -133,6 +133,7 @@ def load(name: str, device: Union[str, torch.device] = "cuda" if torch.cuda.is_a
             if jit:
                 warnings.warn(f"File {model_path} is not a JIT archive. Loading as a state dict instead")
                 jit = False
+            opened_file.seek(0)
             state_dict = torch.load(opened_file, map_location="cpu")
 
     if not jit:
@@ -228,7 +229,7 @@ def tokenize(texts: Union[str, List[str]], context_length: int = 77, truncate: b
     sot_token = _tokenizer.encoder["<|startoftext|>"]
     eot_token = _tokenizer.encoder["<|endoftext|>"]
     all_tokens = [[sot_token] + _tokenizer.encode(text) + [eot_token] for text in texts]
-    if version.parse(torch.__version__) < version.parse("1.8.0"):
+    if packaging.version.parse(torch.__version__) < packaging.version.parse("1.8.0"):
         result = torch.zeros(len(all_tokens), context_length, dtype=torch.long)
     else:
         result = torch.zeros(len(all_tokens), context_length, dtype=torch.int)

requirements.txt

@@ -1,5 +1,4 @@
 ftfy
-packaging
 regex
 tqdm
 torch