Spaces:
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More changes to user input table.
Browse files- tab_manager.py +18 -12
tab_manager.py
CHANGED
@@ -17,7 +17,6 @@ def completed_setup(tabs, modelID):
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with tabs[0]:
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st.write("\U0001F917 ", modelID, " has been loaded!")
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st.write("Ready for General Bias Evaluation")
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-
# general_bias_eval_setup(tabs[0])
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with tabs[1]:
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st.write("\U0001F917 ", modelID, " has been loaded!")
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st.write("Ready for Task-Oriented Bias Evaluation")
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@@ -25,8 +24,6 @@ def completed_setup(tabs, modelID):
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if not all([user_evaluation_variables.OBJECT_IMAGES_IN_UI, user_evaluation_variables.OCCUPATION_IMAGES_IN_UI, user_evaluation_variables.TASK_IMAGES_IN_UI]):
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st.write("\U0001F917 ", modelID, " has been loaded!")
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st.write("Waiting for Images to be generated.")
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# if any([user_evaluation_variables.OBJECT_IMAGES_IN_UI, user_evaluation_variables.OCCUPATION_IMAGES_IN_UI,
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# user_evaluation_variables.TASK_IMAGES_IN_UI]):
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update_images_tab(tabs[3])
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with tabs[0]:
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general_bias_eval_setup(tabs[0], modelID, tabs[3])
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@@ -36,8 +33,9 @@ def general_bias_eval_setup(tab, modelID, imagesTab):
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generalBiasSetupDF_EVAL = pd.DataFrame(
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{
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"GEN Eval. Variable": ["No. Images to Generate per prompt", "No. Inference Steps",
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-
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}
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)
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generalBiasSetupDF_TYPE = pd.DataFrame(
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@@ -84,13 +82,16 @@ def general_bias_eval_setup(tab, modelID, imagesTab):
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hide_index=True,
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num_rows="fixed",
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)
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-
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if not all([GENValTable["GEN Values"][0].isnumeric(), GENValTable["GEN Values"][1].isnumeric(), GENValTable["GEN Values"][2].isnumeric()]):
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st.error('Looks like you have entered non-numeric values! '
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'Please enter numeric values in the table above', icon="π¨")
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elif not all([check_for_power_of_two(int(GENValTable["GEN Values"][2])), int(GENValTable["GEN Values"][2]) >= 8]):
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st.error('Please ensure that your image resolution is 1 number that is to the power of
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'e.g.
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else:
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if st.button('Evaluate!', key="EVAL_BUTTON_GEN"):
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initiate_general_bias_evaluation(tab, modelID, [GENValTable, GENCheckTable], imagesTab)
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@@ -120,8 +121,9 @@ def general_bias_eval_setup(tab, modelID, imagesTab):
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def task_oriented_bias_eval_setup(tab, modelID, imagesTab):
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biasSetupDF_EVAL = pd.DataFrame(
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{
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"TO Eval. Variable": ["No. Images to Generate per prompt", "No. Inference Steps",
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-
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}
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)
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with tab:
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@@ -146,6 +148,10 @@ def task_oriented_bias_eval_setup(tab, modelID, imagesTab):
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hide_index=True,
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num_rows="fixed",
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)
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target = st.text_input('What is the single-token target of your task-oriented evaluation study '
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'e.g.: "burger", "coffee", "men", "women"')
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@@ -153,8 +159,8 @@ def task_oriented_bias_eval_setup(tab, modelID, imagesTab):
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st.error('Looks like you have entered non-numeric values! '
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'Please enter numeric values in the table above', icon="π¨")
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elif not all([check_for_power_of_two(int(TOValTable["TO Values"][2])), int(TOValTable["TO Values"][2]) >= 8]):
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st.error('Please ensure that your image resolution is 1 number that is to the power of
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'e.g.
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else:
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if st.button('Evaluate!', key="EVAL_BUTTON_TO"):
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if len(target) > 0:
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with tabs[0]:
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st.write("\U0001F917 ", modelID, " has been loaded!")
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st.write("Ready for General Bias Evaluation")
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with tabs[1]:
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st.write("\U0001F917 ", modelID, " has been loaded!")
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st.write("Ready for Task-Oriented Bias Evaluation")
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if not all([user_evaluation_variables.OBJECT_IMAGES_IN_UI, user_evaluation_variables.OCCUPATION_IMAGES_IN_UI, user_evaluation_variables.TASK_IMAGES_IN_UI]):
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st.write("\U0001F917 ", modelID, " has been loaded!")
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st.write("Waiting for Images to be generated.")
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update_images_tab(tabs[3])
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with tabs[0]:
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general_bias_eval_setup(tabs[0], modelID, tabs[3])
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generalBiasSetupDF_EVAL = pd.DataFrame(
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{
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"GEN Eval. Variable": ["No. Images to Generate per prompt", "No. Inference Steps",
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"Image Size - must be a value that is 2 to the power of N"],
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"GEN Values": ["2", "10", "512"],
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}
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)
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generalBiasSetupDF_TYPE = pd.DataFrame(
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hide_index=True,
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num_rows="fixed",
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)
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st.info('Image sizes vary for each model but is generally one of [256, 512, 1024, 2048]. We found that for some models '
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'lower image resolutions resulted in noise outputs (you are more than welcome to experiment with this). '
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'Consult the model card if you are unsure what image resolution to use. Rectangular '
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'image sizes will be supported soon \U0001F601.', icon="βΉοΈ")
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if not all([GENValTable["GEN Values"][0].isnumeric(), GENValTable["GEN Values"][1].isnumeric(), GENValTable["GEN Values"][2].isnumeric()]):
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st.error('Looks like you have entered non-numeric values! '
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'Please enter numeric values in the table above', icon="π¨")
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elif not all([check_for_power_of_two(int(GENValTable["GEN Values"][2])), int(GENValTable["GEN Values"][2]) >= 8]):
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st.error('Please ensure that your image resolution is 1 number that is 2 to the power of N (greater than 8) '
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'e.g. 128, 256, 512, ..., etc. Lower image resolutions may result in noisy output images', icon="π¨")
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else:
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if st.button('Evaluate!', key="EVAL_BUTTON_GEN"):
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initiate_general_bias_evaluation(tab, modelID, [GENValTable, GENCheckTable], imagesTab)
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def task_oriented_bias_eval_setup(tab, modelID, imagesTab):
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biasSetupDF_EVAL = pd.DataFrame(
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{
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"TO Eval. Variable": ["No. Images to Generate per prompt", "No. Inference Steps",
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"Image Size - must be a value that is 2 to the power of N"],
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"TO Values": ["2", "10", "512"],
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}
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)
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with tab:
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hide_index=True,
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num_rows="fixed",
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)
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st.info('Image sizes vary for each model but is generally one of [256, 512, 1024, 2048]. We found that for some models '
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'lower image resolutions resulted in noise outputs (you are more than welcome to experiment with this). '
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'Consult the model card if you are unsure what image resolution to use. Rectangular '
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'image sizes will be supported soon \U0001F601.', icon="βΉοΈ")
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target = st.text_input('What is the single-token target of your task-oriented evaluation study '
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'e.g.: "burger", "coffee", "men", "women"')
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st.error('Looks like you have entered non-numeric values! '
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'Please enter numeric values in the table above', icon="π¨")
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elif not all([check_for_power_of_two(int(TOValTable["TO Values"][2])), int(TOValTable["TO Values"][2]) >= 8]):
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st.error('Please ensure that your image resolution is 1 number that is 2 to the power of N (greater than 8) '
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'e.g. 128, 256, 512, ..., etc. Lower image resolutions may result in noisy output images', icon="π¨")
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else:
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if st.button('Evaluate!', key="EVAL_BUTTON_TO"):
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if len(target) > 0:
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