35 lines
1.2 KiB
35 lines
1.2 KiB
import os, pathlib
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from examples.llama3 import Tokenizer
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from tabulate import tabulate
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from tinygrad import fetch
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from tinygrad.helpers import flatten
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# llama 3 tokenizer
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tokenizer = Tokenizer(fetch("https://huggingface.co/bofenghuang/Meta-Llama-3-8B/resolve/main/original/tokenizer.model").as_posix())
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def read_code(base_path):
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ret = []
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for path, _, files in os.walk(os.path.join(base_path, "tinygrad")):
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for name in files:
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if not name.endswith(".py"): continue
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if 'tinygrad/runtime/autogen' in path.replace('\\', '/'): continue
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fullpath = os.path.join(path, name)
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code = pathlib.Path(fullpath).read_text()
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ret += [(fullpath.split("tinygrad/", 1)[1], code)]
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return ret
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if __name__ == "__main__":
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ret = read_code(".")
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table = []
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for name,code in ret:
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table.append([name, len(tokenizer.encode(name+"\x00"+code))])
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print(tabulate([["name", "llm tokens"]]+sorted(table, key=lambda x: -x[1]), headers="firstrow"))
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code_str = '\x00'.join(flatten(ret))
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print(f"code has {len(code_str)} chars")
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newline_count = code_str.count('\n')
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print(f"code has {newline_count} newlines")
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encoded = tokenizer.encode(code_str)
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print(f"code has {len(encoded)} tokens")
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