zhengjl/text-generation-webui
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Refactor the UI

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A single dictionary called 'interface_state' is now passed as input to all functions. The values are updated only when necessary.

The goal is to make it easier to add new elements to the UI.
This commit is contained in:
oobabooga
2023-04-11 11:46:30 -03:00
committed by GitHub
parent 64f5c90ee7
commit 0f212093a3
3 changed files with 136 additions and 100 deletions
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20
modules/text_generation.py
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@@ -69,6 +69,7 @@ def generate_softprompt_input_tensors(input_ids):
# filler_input_ids += shared.model.config.bos_token_id # setting dummy input_ids to bos tokens
return inputs_embeds, filler_input_ids
# Removes empty replies from gpt4chan outputs
def fix_gpt4chan(s):
for i in range(10):
@@ -77,6 +78,7 @@ def fix_gpt4chan(s):
s = re.sub("--- [0-9]*\n\n\n---", "---", s)
return s
# Fix the LaTeX equations in galactica
def fix_galactica(s):
s = s.replace(r'\[', r'$')
@@ -117,9 +119,9 @@ def stop_everything_event():
shared.stop_everything = True
def generate_reply(question, generate_state, eos_token=None, stopping_strings=[]):
def generate_reply(question, state, eos_token=None, stopping_strings=[]):
clear_torch_cache()
seed = set_manual_seed(generate_state['seed'])
seed = set_manual_seed(state['seed'])
shared.stop_everything = False
generate_params = {}
t0 = time.time()
@@ -134,8 +136,8 @@ def generate_reply(question, generate_state, eos_token=None, stopping_strings=[]
# separately and terminate the function call earlier
if any((shared.is_RWKV, shared.is_llamacpp)):
for k in ['temperature', 'top_p', 'top_k', 'repetition_penalty']:
generate_params[k] = generate_state[k]
generate_params['token_count'] = generate_state['max_new_tokens']
generate_params[k] = state[k]
generate_params['token_count'] = state['max_new_tokens']
try:
if shared.args.no_stream:
reply = shared.model.generate(context=question, **generate_params)
@@ -164,7 +166,7 @@ def generate_reply(question, generate_state, eos_token=None, stopping_strings=[]
print(f'Output generated in {(t1-t0):.2f} seconds ({new_tokens/(t1-t0):.2f} tokens/s, {new_tokens} tokens, context {original_tokens}, seed {seed})')
return
input_ids = encode(question, generate_state['max_new_tokens'], add_bos_token=generate_state['add_bos_token'])
input_ids = encode(question, state['max_new_tokens'], add_bos_token=state['add_bos_token'])
original_input_ids = input_ids
output = input_ids[0]
@@ -179,13 +181,13 @@ def generate_reply(question, generate_state, eos_token=None, stopping_strings=[]
if not shared.args.flexgen:
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] = generate_state[k]
generate_params[k] = state[k]
generate_params['eos_token_id'] = eos_token_ids
generate_params['stopping_criteria'] = stopping_criteria_list
else:
for k in ['max_new_tokens', 'do_sample', 'temperature']:
generate_params[k] = generate_state[k]
generate_params['stop'] = generate_state['eos_token_ids'][-1]
generate_params[k] = state[k]
generate_params['stop'] = state['eos_token_ids'][-1]
if not shared.args.no_stream:
generate_params['max_new_tokens'] = 8
@@ -248,7 +250,7 @@ def generate_reply(question, generate_state, eos_token=None, stopping_strings=[]
# Stream the output naively for FlexGen since it doesn't support 'stopping_criteria'
else:
for i in range(generate_state['max_new_tokens'] // 8 + 1):
for i in range(state['max_new_tokens'] // 8 + 1):
clear_torch_cache()
with torch.no_grad():
output = shared.model.generate(**generate_params)[0]