ppbrown commited on
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eb222a6
1 Parent(s): 075cee0

Upload generate-distances.py

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Files changed (1) hide show
  1. generate-distances.py +19 -3
generate-distances.py CHANGED
@@ -21,24 +21,40 @@ device=torch.device("cuda")
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  print("read in words from json now",file=sys.stderr)
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  with open("fullword.json","r") as f:
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  tokendict = json.load(f)
 
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  print("read in embeddingsnow",file=sys.stderr)
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  model = safe_open(embed_file,framework="pt",device="cuda")
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  embs=model.get_tensor("embeddings")
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-
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  embs.to(device)
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  print("Shape of loaded embeds =",embs.shape)
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-
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-
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  print("calculate distances now")
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  distances = torch.cdist(embs, embs, p=2)
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  print("distances shape is",distances.shape)
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  """
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  import torch.nn.functional as F
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  pos=0
 
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  print("read in words from json now",file=sys.stderr)
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  with open("fullword.json","r") as f:
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  tokendict = json.load(f)
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+ wordlist = list(tokendict.keys())
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  print("read in embeddingsnow",file=sys.stderr)
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  model = safe_open(embed_file,framework="pt",device="cuda")
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  embs=model.get_tensor("embeddings")
 
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  embs.to(device)
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  print("Shape of loaded embeds =",embs.shape)
 
 
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  print("calculate distances now")
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  distances = torch.cdist(embs, embs, p=2)
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  print("distances shape is",distances.shape)
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+ targetword="cat"
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+ targetindex=wordlist.index(targetword)
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+ print("index of cat is",targetindex)
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+ targetdistances=distances[targetindex]
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+
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+ smallest_distances, smallest_indices = torch.topk(targetdistances, 5, largest=False)
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+
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+ smallest_distances=smallest_distances.tolist()
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+ smallest_indices=smallest_indices.tolist()
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+
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+ print("The smallest distance values are",smallest_distances)
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+ print("The smallest index values are",smallest_indices)
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+
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+ for t in smallest_indices:
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+ print(wordlist[t])
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+
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+
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+
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  """
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  import torch.nn.functional as F
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  pos=0