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Add epsilon_cutoff/eta_cutoff parameters (#2258)

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oobabooga 2023-05-21 15:11:57 -03:00 committed by GitHub
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9 changed files with 36 additions and 9 deletions
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2
api-example-chat-stream.py
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@ -36,6 +36,8 @@ async def run(user_input, history):
'temperature': 0.7,
'top_p': 0.1,
'typical_p': 1,
'epsilon_cutoff': 0, # In units of 1e-4
'eta_cutoff': 0, # In units of 1e-4
'repetition_penalty': 1.18,
'top_k': 40,
'min_length': 0,

2
api-example-chat.py
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@ -30,6 +30,8 @@ def run(user_input, history):
'temperature': 0.7,
'top_p': 0.1,
'typical_p': 1,
'epsilon_cutoff': 0, # In units of 1e-4
'eta_cutoff': 0, # In units of 1e-4
'repetition_penalty': 1.18,
'top_k': 40,
'min_length': 0,

2
api-example-stream.py
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@ -24,6 +24,8 @@ async def run(context):
'temperature': 1.3,
'top_p': 0.1,
'typical_p': 1,
'epsilon_cutoff': 0, # In units of 1e-4
'eta_cutoff': 0, # In units of 1e-4
'repetition_penalty': 1.18,
'top_k': 40,
'min_length': 0,

2
api-example.py
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@ -16,6 +16,8 @@ def run(prompt):
'temperature': 1.3,
'top_p': 0.1,
'typical_p': 1,
'epsilon_cutoff': 0, # In units of 1e-4
'eta_cutoff': 0, # In units of 1e-4
'repetition_penalty': 1.18,
'top_k': 40,
'min_length': 0,

2
extensions/api/util.py
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@ -15,6 +15,8 @@ def build_parameters(body, chat=False):
'temperature': float(body.get('temperature', 0.5)),
'top_p': float(body.get('top_p', 1)),
'typical_p': float(body.get('typical_p', body.get('typical', 1))),
'epsilon_cutoff': float(body.get('epsilon_cutoff', 0)),
'eta_cutoff': float(body.get('eta_cutoff', 0)),
'repetition_penalty': float(body.get('repetition_penalty', body.get('rep_pen', 1.1))),
'encoder_repetition_penalty': float(body.get('encoder_repetition_penalty', 1.0)),
'top_k': int(body.get('top_k', 0)),

4
extensions/openai/script.py
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@ -208,6 +208,8 @@ class Handler(BaseHTTPRequestHandler):
'add_bos_token': shared.settings.get('add_bos_token', True),
'do_sample': True,
'typical_p': 1.0,
'epsilon_cutoff': 0, # In units of 1e-4
'eta_cutoff': 0, # In units of 1e-4
'min_length': 0,
'no_repeat_ngram_size': 0,
'num_beams': 1,
@ -516,6 +518,8 @@ class Handler(BaseHTTPRequestHandler):
'add_bos_token': shared.settings.get('add_bos_token', True),
'do_sample': True,
'typical_p': 1.0,
'epsilon_cutoff': 0, # In units of 1e-4
'eta_cutoff': 0, # In units of 1e-4
'min_length': 0,
'no_repeat_ngram_size': 0,
'num_beams': 1,

4
modules/text_generation.py
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@ -190,6 +190,10 @@ def generate_reply_HF(question, original_question, seed, state, eos_token=None,
for k in ['max_new_tokens', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping']:
generate_params[k] = state[k]
for k in ['epsilon_cutoff', 'eta_cutoff']:
if state[k] > 0:
generate_params[k] = state[k] * 1e-4
if state['ban_eos_token']:
generate_params['suppress_tokens'] = [shared.tokenizer.eos_token_id]

2
modules/ui.py
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@ -37,7 +37,7 @@ def list_model_elements():
def list_interface_input_elements(chat=False):
elements = ['max_new_tokens', 'seed', 'temperature', 'top_p', 'top_k', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'no_repeat_ngram_size', 'min_length', 'do_sample', 'penalty_alpha', 'num_beams', 'length_penalty', 'early_stopping', 'add_bos_token', 'ban_eos_token', 'truncation_length', 'custom_stopping_strings', 'skip_special_tokens', 'preset_menu', 'stream']
elements = ['max_new_tokens', 'seed', 'temperature', 'top_p', 'top_k', 'typical_p', 'epsilon_cutoff', 'eta_cutoff', 'repetition_penalty', 'encoder_repetition_penalty', 'no_repeat_ngram_size', 'min_length', 'do_sample', 'penalty_alpha', 'num_beams', 'length_penalty', 'early_stopping', 'add_bos_token', 'ban_eos_token', 'truncation_length', 'custom_stopping_strings', 'skip_special_tokens', 'preset_menu', 'stream']
if chat:
elements += ['name1', 'name2', 'greeting', 'context', 'chat_prompt_size', 'chat_generation_attempts', 'stop_at_newline', 'mode', 'instruction_template', 'character_menu', 'name1_instruct', 'name2_instruct', 'context_instruct', 'turn_template', 'chat_style', 'chat-instruct_command']

25
server.py
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@ -84,6 +84,8 @@ def load_preset_values(preset_menu, state, return_dict=False):
'temperature': 1,
'top_p': 1,
'typical_p': 1,
'epsilon_cutoff': 0,
'eta_cutoff': 0,
'repetition_penalty': 1,
'encoder_repetition_penalty': 1,
'top_k': 50,
@ -100,13 +102,13 @@ def load_preset_values(preset_menu, state, return_dict=False):
i = i.rstrip(',').strip().split('=')
if len(i) == 2 and i[0].strip() != 'tokens':
generate_params[i[0].strip()] = eval(i[1].strip())
generate_params['temperature'] = min(1.99, generate_params['temperature'])
generate_params['temperature'] = min(1.99, generate_params['temperature'])
if return_dict:
return generate_params
else:
state.update(generate_params)
return state, *[generate_params[k] for k in ['do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping']]
return state, *[generate_params[k] for k in ['do_sample', 'temperature', 'top_p', 'typical_p', 'epsilon_cutoff', 'eta_cutoff', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping']]
def upload_soft_prompt(file):
@ -453,17 +455,24 @@ def create_settings_menus(default_preset):
shared.gradio['do_sample'] = gr.Checkbox(value=generate_params['do_sample'], label='do_sample')
with gr.Column():
with gr.Box():
gr.Markdown('Contrastive search')
shared.gradio['penalty_alpha'] = gr.Slider(0, 5, value=generate_params['penalty_alpha'], label='penalty_alpha')
gr.Markdown('Beam search (uses a lot of VRAM)')
with gr.Row():
with gr.Column():
gr.Markdown('Contrastive search')
shared.gradio['penalty_alpha'] = gr.Slider(0, 5, value=generate_params['penalty_alpha'], label='penalty_alpha')
gr.Markdown('Beam search (uses a lot of VRAM)')
shared.gradio['num_beams'] = gr.Slider(1, 20, step=1, value=generate_params['num_beams'], label='num_beams')
shared.gradio['length_penalty'] = gr.Slider(-5, 5, value=generate_params['length_penalty'], label='length_penalty')
with gr.Column():
shared.gradio['early_stopping'] = gr.Checkbox(value=generate_params['early_stopping'], label='early_stopping')
with gr.Column():
gr.Markdown('Other')
with gr.Row():
with gr.Column():
shared.gradio['epsilon_cutoff'] = gr.Slider(0, 9, value=generate_params['epsilon_cutoff'], step=0.01, label='epsilon_cutoff', info='In units of 1e-4')
with gr.Column():
shared.gradio['eta_cutoff'] = gr.Slider(0, 20, value=generate_params['eta_cutoff'], step=0.01, label='eta_cutoff', info='In units of 1e-4')
with gr.Box():
with gr.Row():
with gr.Column():
@ -485,7 +494,7 @@ def create_settings_menus(default_preset):
with gr.Row():
shared.gradio['upload_softprompt'] = gr.File(type='binary', file_types=['.zip'])
shared.gradio['preset_menu'].change(load_preset_values, [shared.gradio[k] for k in ['preset_menu', 'interface_state']], [shared.gradio[k] for k in ['interface_state', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping']])
shared.gradio['preset_menu'].change(load_preset_values, [shared.gradio[k] for k in ['preset_menu', 'interface_state']], [shared.gradio[k] for k in ['interface_state', 'do_sample', 'temperature', 'top_p', 'typical_p', 'epsilon_cutoff', 'eta_cutoff', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping']])
shared.gradio['softprompts_menu'].change(load_soft_prompt, shared.gradio['softprompts_menu'], shared.gradio['softprompts_menu'], show_progress=True)
shared.gradio['upload_softprompt'].upload(upload_soft_prompt, shared.gradio['upload_softprompt'], shared.gradio['softprompts_menu'])