testing for tabbed interface features

app.py

@@ -66,6 +66,53 @@ 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"),
@@ -78,7 +125,10 @@ 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)]
 
-foroutput=gr.Textbox(lines=5, max_lines=50, label="Generated Text with Greedy/Beam Search Decoding")
+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")]
 
 examples = [
     ["Indonesia adalah negara kepulauan", 10, 30, 1.0, 25, 0.92, 5, 2.0, True],
@@ -118,15 +168,27 @@ article = """<p style='text-align: center'>
     <a href='https://huggingface.co/spaces/anugrahap/gpt2-indo-text-gen/tree/main' target='_blank'>Link to the Project Repository<b>&nbsp;|</b></a>
     <a href='https://huggingface.co/datasets/anugrahap/output-gpt2-indo-textgen/' target='_blank'>Link to the Autosaved Generated Output<b>&nbsp;|</b></a>
     <a href='https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf' target='_blank'>Original Paper</a><br></p>
-    <p style='text-align: center'>Copyright Anugrah Akbar Praramadhan 2023 <br></p>
-    <p style='text-align: center'> Trained on Indo4B Benchmark Dataset of Indonesian language Wikipedia with a Causal Language Modeling (CLM) objective</p>
+    <p style='text-align: center'> Trained on Indo4B Benchmark Dataset of Indonesian language Wikipedia with a Causal Language Modeling (CLM) objective<br></p>
+    <p style='text-align: center'>Copyright Anugrah Akbar Praramadhan 2023</p>
     """
 
 # using gradio interfaces
-app = gr.Interface(
+app1 = gr.Interface(
     fn=single_generation,
     inputs=forinput,
-    outputs=foroutput,
+    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,
     examples=examples,
     title=title,
     description=description,
@@ -135,6 +197,7 @@ app = 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__':
-    app.launch()
+    final_app.launch()