multimodalart HF staff commited on
Commit
3164600
1 Parent(s): c57b1f6

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +11 -6
app.py CHANGED
@@ -120,9 +120,9 @@ def train(*inputs):
120
  os.makedirs('output_model',exist_ok=True)
121
  uses_custom = inputs[-1]
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  type_of_thing = inputs[-4]
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- model_name = inputs[-7]
124
  remove_attribution_after = inputs[-6]
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- hf_token = inputs[-5]
126
  if(uses_custom):
127
  Training_Steps = int(inputs[-3])
128
  Train_text_encoder_for = int(inputs[-2])
@@ -176,7 +176,10 @@ def train(*inputs):
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  trained_file = open("hastrained.success", "w")
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  trained_file.close()
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  if(remove_attribution_after):
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- push(model_name, "My personal profile", hf_token, True)
 
 
 
180
  hardware_url = f"https://huggingface.co/spaces/{os.environ['SPACE_ID']}/hardware"
181
  headers = { "authorization" : f"Bearer {hf_token}"}
182
  body = {'flavor': 'cpu-basic'}
@@ -321,7 +324,7 @@ def check_status(top_description):
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  ]
322
 
323
  def checkbox_swap(checkbox):
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- return [gr.update(visible=checkbox), gr.update(visible=checkbox), gr.update(visible=checkbox)]
325
 
326
  with gr.Blocks(css=css) as demo:
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  with gr.Box():
@@ -406,6 +409,7 @@ with gr.Blocks(css=css) as demo:
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  training_summary_text = gr.HTML("", visible=False, label="Training Summary")
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  training_summary_checkbox = gr.Checkbox(label="Automatically remove paid GPU attribution and upload model to the Hugging Face Hub after training", value=False)
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  training_summary_model_name = gr.Textbox(label="Name of your model", visible=False)
 
409
  training_summary_token_message = gr.Markdown("[A Hugging Face write access token](https://huggingface.co/settings/tokens), go to \"New token\" -> Role : Write. A regular read token won't work here.", visible=False)
410
  training_summary_token = gr.Textbox(label="Hugging Face Write Token", type="password", visible=False)
411
 
@@ -430,6 +434,7 @@ with gr.Blocks(css=css) as demo:
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  where_to_upload = gr.Dropdown(["My personal profile", "Public Library"], label="Upload to")
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  gr.Markdown("[A Hugging Face write access token](https://huggingface.co/settings/tokens), go to \"New token\" -> Role : Write. A regular read token won't work here.")
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  hf_token = gr.Textbox(label="Hugging Face Write Token", type="password")
 
433
  push_button = gr.Button("Push to the Hub")
434
 
435
  result = gr.File(label="Download the uploaded models in the diffusers format", visible=True)
@@ -446,12 +451,12 @@ with gr.Blocks(css=css) as demo:
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  perc_txt_encoder.change(fn=count_files, inputs=file_collection+[type_of_thing]+[steps]+[perc_txt_encoder]+[swap_auto_calculated], outputs=[training_summary, training_summary_text], queue=False)
447
 
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  #Give more options if the user wants to finish everything after training
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- training_summary_checkbox.change(fn=checkbox_swap, inputs=training_summary_checkbox, outputs=[training_summary_token_message, training_summary_token, training_summary_model_name],queue=False, show_progress=False)
450
  #Add a message for while it is in training
451
  train_btn.click(lambda:gr.update(visible=True), inputs=None, outputs=training_ongoing)
452
 
453
  #The main train function
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- train_btn.click(fn=train, inputs=is_visible+concept_collection+file_collection+[training_summary_model_name]+[training_summary_checkbox]+[training_summary_token]+[type_of_thing]+[steps]+[perc_txt_encoder]+[swap_auto_calculated], outputs=[result, try_your_model, push_to_hub, convert_button, training_ongoing, completed_training], queue=False)
455
 
456
  #Button to generate an image from your trained model after training
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  generate_button.click(fn=generate, inputs=prompt, outputs=result_image, queue=False)
 
120
  os.makedirs('output_model',exist_ok=True)
121
  uses_custom = inputs[-1]
122
  type_of_thing = inputs[-4]
123
+
124
  remove_attribution_after = inputs[-6]
125
+
126
  if(uses_custom):
127
  Training_Steps = int(inputs[-3])
128
  Train_text_encoder_for = int(inputs[-2])
 
176
  trained_file = open("hastrained.success", "w")
177
  trained_file.close()
178
  if(remove_attribution_after):
179
+ hf_token = inputs[-5]
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+ model_name = inputs[-7]
181
+ where_to_upload = inputs[-8]
182
+ push(model_name, where_to_upload, hf_token, True)
183
  hardware_url = f"https://huggingface.co/spaces/{os.environ['SPACE_ID']}/hardware"
184
  headers = { "authorization" : f"Bearer {hf_token}"}
185
  body = {'flavor': 'cpu-basic'}
 
324
  ]
325
 
326
  def checkbox_swap(checkbox):
327
+ return [gr.update(visible=checkbox), gr.update(visible=checkbox), gr.update(visible=checkbox), gr.update(visible=checkbox)]
328
 
329
  with gr.Blocks(css=css) as demo:
330
  with gr.Box():
 
409
  training_summary_text = gr.HTML("", visible=False, label="Training Summary")
410
  training_summary_checkbox = gr.Checkbox(label="Automatically remove paid GPU attribution and upload model to the Hugging Face Hub after training", value=False)
411
  training_summary_model_name = gr.Textbox(label="Name of your model", visible=False)
412
+ training_summary_where_to_upload = gr.Dropdown(["My personal profile", "Public Library"], label="Upload to", visible=False)
413
  training_summary_token_message = gr.Markdown("[A Hugging Face write access token](https://huggingface.co/settings/tokens), go to \"New token\" -> Role : Write. A regular read token won't work here.", visible=False)
414
  training_summary_token = gr.Textbox(label="Hugging Face Write Token", type="password", visible=False)
415
 
 
434
  where_to_upload = gr.Dropdown(["My personal profile", "Public Library"], label="Upload to")
435
  gr.Markdown("[A Hugging Face write access token](https://huggingface.co/settings/tokens), go to \"New token\" -> Role : Write. A regular read token won't work here.")
436
  hf_token = gr.Textbox(label="Hugging Face Write Token", type="password")
437
+
438
  push_button = gr.Button("Push to the Hub")
439
 
440
  result = gr.File(label="Download the uploaded models in the diffusers format", visible=True)
 
451
  perc_txt_encoder.change(fn=count_files, inputs=file_collection+[type_of_thing]+[steps]+[perc_txt_encoder]+[swap_auto_calculated], outputs=[training_summary, training_summary_text], queue=False)
452
 
453
  #Give more options if the user wants to finish everything after training
454
+ training_summary_checkbox.change(fn=checkbox_swap, inputs=training_summary_checkbox, outputs=[training_summary_token_message, training_summary_token, training_summary_model_name, training_summary_where_to_upload],queue=False, show_progress=False)
455
  #Add a message for while it is in training
456
  train_btn.click(lambda:gr.update(visible=True), inputs=None, outputs=training_ongoing)
457
 
458
  #The main train function
459
+ train_btn.click(fn=train, inputs=is_visible+concept_collection+file_collection+[training_summary_where_to_upload]+[training_summary_model_name]+[training_summary_checkbox]+[training_summary_token]+[type_of_thing]+[steps]+[perc_txt_encoder]+[swap_auto_calculated], outputs=[result, try_your_model, push_to_hub, convert_button, training_ongoing, completed_training], queue=False)
460
 
461
  #Button to generate an image from your trained model after training
462
  generate_button.click(fn=generate, inputs=prompt, outputs=result_image, queue=False)