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jwkirchenbauer
commited on
Commit
•
fa85da4
1
Parent(s):
4f1c9f2
add highlights to detection tab
Browse files- demo_watermark.py +20 -17
demo_watermark.py
CHANGED
@@ -571,7 +571,10 @@ def run_gradio(args, model=None, device=None, tokenizer=None):
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with gr.Tab("Detector Only"):
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with gr.Row():
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with gr.Column(scale=2):
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-
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with gr.Column(scale=1):
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detection_result = gr.Dataframe(headers=["Metric", "Value"], interactive=False,row_count=7,col_count=2)
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with gr.Row():
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@@ -708,7 +711,7 @@ def run_gradio(args, model=None, device=None, tokenizer=None):
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# Show truncated version of prompt if truncation occurred
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redecoded_input.change(fn=truncate_prompt, inputs=[redecoded_input,truncation_warning,prompt,session_args], outputs=[prompt,session_args])
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# Register main detection tab click
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detect_btn.click(fn=detect_partial, inputs=[detection_input,session_args,session_tokenizer], outputs=[detection_result, session_args,session_tokenizer], api_name="detection")
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# State management logic
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# define update callbacks that change the state dict
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@@ -821,25 +824,25 @@ def run_gradio(args, model=None, device=None, tokenizer=None):
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# When the parameters change, display the update and also fire detection, since some detection params dont change the model output.
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delta.change(lambda value: str(value), inputs=[session_args], outputs=[current_parameters])
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gamma.change(lambda value: str(value), inputs=[session_args], outputs=[current_parameters])
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gamma.change(fn=detect_partial, inputs=[output_without_watermark,session_args,session_tokenizer], outputs=[without_watermark_detection_result,session_args,session_tokenizer])
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gamma.change(fn=detect_partial, inputs=[output_with_watermark,session_args,session_tokenizer], outputs=[with_watermark_detection_result,session_args,session_tokenizer])
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gamma.change(fn=detect_partial, inputs=[detection_input,session_args,session_tokenizer], outputs=[detection_result,session_args,session_tokenizer])
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detection_z_threshold.change(lambda value: str(value), inputs=[session_args], outputs=[current_parameters])
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detection_z_threshold.change(fn=detect_partial, inputs=[output_without_watermark,session_args,session_tokenizer], outputs=[without_watermark_detection_result,session_args,session_tokenizer])
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detection_z_threshold.change(fn=detect_partial, inputs=[output_with_watermark,session_args,session_tokenizer], outputs=[with_watermark_detection_result,session_args,session_tokenizer])
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detection_z_threshold.change(fn=detect_partial, inputs=[detection_input,session_args,session_tokenizer], outputs=[detection_result,session_args,session_tokenizer])
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ignore_repeated_bigrams.change(lambda value: str(value), inputs=[session_args], outputs=[current_parameters])
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ignore_repeated_bigrams.change(fn=detect_partial, inputs=[output_without_watermark,session_args,session_tokenizer], outputs=[without_watermark_detection_result,session_args,session_tokenizer])
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ignore_repeated_bigrams.change(fn=detect_partial, inputs=[output_with_watermark,session_args,session_tokenizer], outputs=[with_watermark_detection_result,session_args,session_tokenizer])
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ignore_repeated_bigrams.change(fn=detect_partial, inputs=[detection_input,session_args,session_tokenizer], outputs=[detection_result,session_args,session_tokenizer])
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normalizers.change(lambda value: str(value), inputs=[session_args], outputs=[current_parameters])
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normalizers.change(fn=detect_partial, inputs=[output_without_watermark,session_args,session_tokenizer], outputs=[without_watermark_detection_result,session_args,session_tokenizer])
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normalizers.change(fn=detect_partial, inputs=[output_with_watermark,session_args,session_tokenizer], outputs=[with_watermark_detection_result,session_args,session_tokenizer])
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normalizers.change(fn=detect_partial, inputs=[detection_input,session_args,session_tokenizer], outputs=[detection_result,session_args,session_tokenizer])
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select_green_tokens.change(lambda value: str(value), inputs=[session_args], outputs=[current_parameters])
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select_green_tokens.change(fn=detect_partial, inputs=[output_without_watermark,session_args,session_tokenizer], outputs=[without_watermark_detection_result,session_args,session_tokenizer])
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select_green_tokens.change(fn=detect_partial, inputs=[output_with_watermark,session_args,session_tokenizer], outputs=[with_watermark_detection_result,session_args,session_tokenizer])
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select_green_tokens.change(fn=detect_partial, inputs=[detection_input,session_args,session_tokenizer], outputs=[detection_result,session_args,session_tokenizer])
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demo.queue(concurrency_count=3)
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with gr.Tab("Detector Only"):
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with gr.Row():
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with gr.Column(scale=2):
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with gr.Tab("Text to Analyze"):
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detection_input = gr.Textbox(interactive=True,lines=14,max_lines=14)
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with gr.Tab("Highlighted"):
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html_detection_input = gr.HTML(elem_id="html-detection-input")
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with gr.Column(scale=1):
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detection_result = gr.Dataframe(headers=["Metric", "Value"], interactive=False,row_count=7,col_count=2)
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with gr.Row():
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# Show truncated version of prompt if truncation occurred
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redecoded_input.change(fn=truncate_prompt, inputs=[redecoded_input,truncation_warning,prompt,session_args], outputs=[prompt,session_args])
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# Register main detection tab click
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detect_btn.click(fn=detect_partial, inputs=[detection_input,session_args,session_tokenizer], outputs=[detection_result, session_args,session_tokenizer,html_detection_input], api_name="detection")
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# State management logic
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# define update callbacks that change the state dict
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# When the parameters change, display the update and also fire detection, since some detection params dont change the model output.
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delta.change(lambda value: str(value), inputs=[session_args], outputs=[current_parameters])
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gamma.change(lambda value: str(value), inputs=[session_args], outputs=[current_parameters])
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gamma.change(fn=detect_partial, inputs=[output_without_watermark,session_args,session_tokenizer], outputs=[without_watermark_detection_result,session_args,session_tokenizer,html_without_watermark])
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gamma.change(fn=detect_partial, inputs=[output_with_watermark,session_args,session_tokenizer], outputs=[with_watermark_detection_result,session_args,session_tokenizer,html_with_watermark])
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gamma.change(fn=detect_partial, inputs=[detection_input,session_args,session_tokenizer], outputs=[detection_result,session_args,session_tokenizer,html_detection_input])
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detection_z_threshold.change(lambda value: str(value), inputs=[session_args], outputs=[current_parameters])
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detection_z_threshold.change(fn=detect_partial, inputs=[output_without_watermark,session_args,session_tokenizer], outputs=[without_watermark_detection_result,session_args,session_tokenizer,html_without_watermark])
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detection_z_threshold.change(fn=detect_partial, inputs=[output_with_watermark,session_args,session_tokenizer], outputs=[with_watermark_detection_result,session_args,session_tokenizer,html_with_watermark])
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detection_z_threshold.change(fn=detect_partial, inputs=[detection_input,session_args,session_tokenizer], outputs=[detection_result,session_args,session_tokenizer,html_detection_input])
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ignore_repeated_bigrams.change(lambda value: str(value), inputs=[session_args], outputs=[current_parameters])
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ignore_repeated_bigrams.change(fn=detect_partial, inputs=[output_without_watermark,session_args,session_tokenizer], outputs=[without_watermark_detection_result,session_args,session_tokenizer,html_without_watermark])
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ignore_repeated_bigrams.change(fn=detect_partial, inputs=[output_with_watermark,session_args,session_tokenizer], outputs=[with_watermark_detection_result,session_args,session_tokenizer,html_with_watermark])
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ignore_repeated_bigrams.change(fn=detect_partial, inputs=[detection_input,session_args,session_tokenizer], outputs=[detection_result,session_args,session_tokenizer,html_detection_input])
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normalizers.change(lambda value: str(value), inputs=[session_args], outputs=[current_parameters])
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normalizers.change(fn=detect_partial, inputs=[output_without_watermark,session_args,session_tokenizer], outputs=[without_watermark_detection_result,session_args,session_tokenizer,html_without_watermark])
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normalizers.change(fn=detect_partial, inputs=[output_with_watermark,session_args,session_tokenizer], outputs=[with_watermark_detection_result,session_args,session_tokenizer,html_with_watermark])
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normalizers.change(fn=detect_partial, inputs=[detection_input,session_args,session_tokenizer], outputs=[detection_result,session_args,session_tokenizer,html_detection_input])
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select_green_tokens.change(lambda value: str(value), inputs=[session_args], outputs=[current_parameters])
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select_green_tokens.change(fn=detect_partial, inputs=[output_without_watermark,session_args,session_tokenizer], outputs=[without_watermark_detection_result,session_args,session_tokenizer,html_without_watermark])
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select_green_tokens.change(fn=detect_partial, inputs=[output_with_watermark,session_args,session_tokenizer], outputs=[with_watermark_detection_result,session_args,session_tokenizer,html_with_watermark])
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select_green_tokens.change(fn=detect_partial, inputs=[detection_input,session_args,session_tokenizer], outputs=[detection_result,session_args,session_tokenizer,html_detection_input])
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demo.queue(concurrency_count=3)
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