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https://github.com/YerbaPage/LongCodeZip.git
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clean up
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1
.gitignore
vendored
1
.gitignore
vendored
@@ -165,7 +165,6 @@ crosscodeeval/
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temp/
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*.jsonl
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*.out
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*.txt
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datasets/
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repositories/
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*.ipynb
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Before Width: | Height: | Size: 234 KiB After Width: | Height: | Size: 551 KiB |
@@ -676,8 +676,6 @@ class CodeCompressor:
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rate: float = 0.5,
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target_token: float = -1,
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language: str = "python",
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use_iterative_compression: bool = True,
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iterative_size: int = 200,
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dynamic_compression_ratio: float = 0.2,
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context_budget: str = "+100",
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rank_only: bool = False,
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@@ -698,8 +696,6 @@ class CodeCompressor:
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rate: Compression rate for coarse-grained (function level) compression (0.0-1.0)
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target_token: Target number of tokens (alternative to rate)
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language: Programming language of the code
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use_iterative_compression: Whether to use iterative compression
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iterative_size: Size of each iteration for iterative compression
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dynamic_compression_ratio: Ratio for dynamic compression
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context_budget: String expression to modify token budget
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rank_only: If True, just rank and select contexts without fine-grained compression
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@@ -1857,9 +1853,9 @@ if __name__ == "__main__":
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query=question, # Using current function context as query focus
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instruction="Complete the following code function given the context.",
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rate=target_ratio,
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rank_only=False, # Test fine-grained compression
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fine_grained_importance_method="contrastive_perplexity", # Explicitly test default
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min_lines_for_fine_grained=5, # New parameter
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rank_only=True, # Only use coarse-grained compression
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fine_grained_importance_method="conditional_ppl", # Explicitly test default
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min_lines_for_fine_grained=5, # Min number of lines for fine-grained compression
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importance_beta=0.5, # Sensitivity to importance score
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use_knapsack=True,
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)
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21
requirements.txt
Normal file
21
requirements.txt
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@@ -0,0 +1,21 @@
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anthropic
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appdirs
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datasets
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editdistance
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fire
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google-api-core
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google-generativeai
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llmlingua
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loguru
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matplotlib
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nltk
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numpy
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openai>=1.0.0
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rich
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torch
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transformers==4.37.1
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tqdm
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tree-sitter-languages
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tempdir
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vllm
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wget
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