rollback to the stable of Version 2.0 app

app.py

@@ -66,53 +66,6 @@ def single_generation(text,min_length,max_length,temperature,top_k,top_p,num_bea
     else:
         return error_unknown
 
-# create the decoder parameter to generate the text
-def multiple_generation(text,min_length,max_length,temperature,top_k,top_p,num_beams,repetition_penalty,do_sample):
-    # create local variable for error parameter    
-    error_rep=ValueError(f"ERROR: repetition penalty cannot be lower than one! Given rep penalty = {repetition_penalty}")
-    error_temp=ValueError(f"ERROR: temperature cannot be zero or lower! Given temperature = {temperature}")
-    error_minmax=ValueError(f"ERROR: min length must be lower than or equal to max length! Given min length = {min_length}")
-    error_numbeams_type=TypeError(f"ERROR: number of beams must be an integer not {type(num_beams)}")
-    error_topk_type=TypeError(f"ERROR: top k must be an integer not {type(top_k)}")
-    error_minmax_type=TypeError(f"ERROR: min length and max length must be an integer not {type(min_length)} and {type(max_length)}")   
-    error_empty=ValueError("ERROR: Input Text cannot be empty!")
-    error_unknown=TypeError("Unknown Error.")
-
-    if text != '':
-        if type(min_length) == int and type(max_length) == int:
-            if type(top_k) == int:
-                if type(num_beams) == int:
-                    if min_length <= max_length:
-                        if temperature > 0:
-                            if repetition_penalty >= 1:
-                                result = generator(text,
-                                                   min_length=min_length,
-                                                   max_length=max_length,
-                                                   temperature=temperature,
-                                                   top_k=top_k,
-                                                   top_p=top_p,
-                                                   num_beams=num_beams,
-                                                   repetition_penalty=repetition_penalty,
-                                                   do_sample=do_sample,
-                                                   no_repeat_ngram_size=2,
-                                                   num_return_sequences=3)
-                                return result[0]["generated_text"], result[1]["generated_text"], result[2]["generated_text"],
-                            elif repetition_penalty < 1:
-                                return error_rep,error_rep,error_rep
-                        elif temperature <= 0:
-                            return error_temp,error_temp,error_temp
-                    elif min_length > max_length:
-                        return error_minmax,error_minmax,error_minmax
-                elif type(num_beams) != int:
-                    return error_numbeams_type,error_numbeams_type,error_numbeams_type
-            elif type(top_k) != int:
-                return error_topk_type,error_topk_type,error_topk_type
-        elif type(min_length) != int or type(max_length) != int:
-            return  error_minmax_type,error_minmax_type,error_minmax_type
-    elif text == '':
-        return error_empty,error_empty,error_empty
-    else:
-        return error_unknown,error_unknown,error_unknown
 
 # create the variable needed for the gradio app
 forinput=[gr.Textbox(lines=5, label="Input Text"),
@@ -125,10 +78,7 @@ forinput=[gr.Textbox(lines=5, label="Input Text"),
         gr.Number(label="Repetition Penalty", value=2.0),
         gr.Dropdown(label="Do Sample?", choices=[True,False], value=True, multiselect=False)]
 
-output1=gr.Textbox(lines=5, max_lines=50, label="Generated Text with Greedy/Beam Search Decoding")
-output2=[gr.Textbox(lines=5, max_lines=50, label="#1 Generated Text with Greedy/Beam Search Decoding"),
-         gr.Textbox(lines=5, max_lines=50, label="#2 Generated Text with Greedy/Beam Search Decoding"),
-         gr.Textbox(lines=5, max_lines=50, label="#3 Generated Text with Greedy/Beam Search Decoding")]
+foroutput=gr.Textbox(lines=5, max_lines=50, label="Generated Text with Greedy/Beam Search Decoding")
 
 examples = [
     ["Indonesia adalah negara kepulauan", 10, 30, 1.0, 25, 0.92, 5, 2.0, True],
@@ -173,22 +123,10 @@ article = """<p style='text-align: center'>
     """
 
 # using gradio interfaces
-app1 = gr.Interface(
+app = gr.Interface(
     fn=single_generation,
     inputs=forinput,
-    outputs=output1,
-    examples=examples,
-    title=title,
-    description=description,
-    article=article,
-    allow_flagging='manual',
-    flagging_options=['Well Performed', 'Inappropriate Word Selection', 'Wordy', 'Strange Word', 'Others'],
-    flagging_callback=hf_writer)
-
-app2 = gr.Interface(
-    fn=multiple_generation,
-    inputs=forinput,
-    outputs=output2,
+    outputs=foroutput,
     examples=examples,
     title=title,
     description=description,
@@ -197,7 +135,6 @@ app2 = gr.Interface(
     flagging_options=['Well Performed', 'Inappropriate Word Selection', 'Wordy', 'Strange Word', 'Others'],
     flagging_callback=hf_writer)
 
-final_app = gr.TabbedInterface([app1,app2],["Single Generation", "Multiple Generation (high computation)"])
 
 if __name__=='__main__':
-    final_app.launch()
+    app.launch()