Nu Appleblossom commited on
Commit
a7918a7
·
1 Parent(s): 6510302

back to last promising version with treebuild crashlog, revising whole tree gen thing with Claude 7

Browse files
Files changed (1) hide show
  1. app.py +4 -4
app.py CHANGED
@@ -535,10 +535,10 @@ def gradio_interface():
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  tree_generator = generate_definition_tree(base_prompt, feature_vector, model, tokenizer, config)
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  log_output = []
 
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  for item in tree_generator:
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  if isinstance(item, str):
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  log_output.append(item)
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- yield item, None
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  else:
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  tree_data = item
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@@ -547,10 +547,10 @@ def gradio_interface():
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  max_weight, min_weight = find_max_min_cumulative_weight(tree_data)
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  tree_image = create_tree_diagram(tree_data, config, max_weight, min_weight)
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  logger.info("Tree image generated successfully")
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- yield "\n".join(log_output), tree_image
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  else:
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  logger.error("Failed to generate tree data")
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- yield "Error: Failed to generate tree data.", None
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  return "Mode not recognized or not implemented in this step.", None
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@@ -627,7 +627,7 @@ def gradio_interface():
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  inputs=[selected_sae, feature_number, weight_type, use_token_centroid, scaling_factor, use_pca, pca_weight, num_exp, denom_exp, mode],
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  outputs=[output_stream, output_image],
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  show_progress="full"
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- ).then(lambda: gr.update(visible=False, value=""), None, [output_500_text])
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  generate_top_500_btn.click(
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  generate_top_500,
 
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  tree_generator = generate_definition_tree(base_prompt, feature_vector, model, tokenizer, config)
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  log_output = []
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+ tree_data = None
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  for item in tree_generator:
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  if isinstance(item, str):
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  log_output.append(item)
 
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  else:
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  tree_data = item
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  max_weight, min_weight = find_max_min_cumulative_weight(tree_data)
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  tree_image = create_tree_diagram(tree_data, config, max_weight, min_weight)
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  logger.info("Tree image generated successfully")
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+ return "\n".join(log_output), tree_image
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  else:
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  logger.error("Failed to generate tree data")
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+ return "Error: Failed to generate tree data.", None
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  return "Mode not recognized or not implemented in this step.", None
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  inputs=[selected_sae, feature_number, weight_type, use_token_centroid, scaling_factor, use_pca, pca_weight, num_exp, denom_exp, mode],
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  outputs=[output_stream, output_image],
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  show_progress="full"
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+ )
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  generate_top_500_btn.click(
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  generate_top_500,