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Readability improvements

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oobabooga 2023-03-08 03:00:06 -03:00
parent 72d539dbff
commit ad2970374a
1 changed files with 3 additions and 3 deletions
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6
modules/text_generation.py
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@ -195,8 +195,8 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
for output in eval(f"generate_with_streaming({', '.join(generate_params)})"): for output in eval(f"generate_with_streaming({', '.join(generate_params)})"):
if shared.soft_prompt: if shared.soft_prompt:
output = torch.cat((input_ids[0], output[filler_input_ids.shape[1]:])) output = torch.cat((input_ids[0], output[filler_input_ids.shape[1]:]))
reply = decode(output) reply = decode(output)
if not (shared.args.chat or shared.args.cai_chat): if not (shared.args.chat or shared.args.cai_chat):
reply = original_question + apply_extensions(reply[len(question):], "output") reply = original_question + apply_extensions(reply[len(question):], "output")
yield formatted_outputs(reply, shared.model_name) yield formatted_outputs(reply, shared.model_name)
@ -213,16 +213,16 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
output = eval(f"shared.model.generate({', '.join(generate_params)})")[0] output = eval(f"shared.model.generate({', '.join(generate_params)})")[0]
if shared.soft_prompt: if shared.soft_prompt:
output = torch.cat((input_ids[0], output[filler_input_ids.shape[1]:])) output = torch.cat((input_ids[0], output[filler_input_ids.shape[1]:]))
reply = decode(output) reply = decode(output)
if not (shared.args.chat or shared.args.cai_chat): if not (shared.args.chat or shared.args.cai_chat):
reply = original_question + apply_extensions(reply[len(question):], "output") reply = original_question + apply_extensions(reply[len(question):], "output")
yield formatted_outputs(reply, shared.model_name) yield formatted_outputs(reply, shared.model_name)
if np.count_nonzero(input_ids[0] == n) < np.count_nonzero(output == n): if np.count_nonzero(input_ids[0] == n) < np.count_nonzero(output == n):
break break
input_ids = np.reshape(output, (1, output.shape[0]))
input_ids = np.reshape(output, (1, output.shape[0]))
if shared.soft_prompt: if shared.soft_prompt:
inputs_embeds, filler_input_ids = generate_softprompt_input_tensors(input_ids) inputs_embeds, filler_input_ids = generate_softprompt_input_tensors(input_ids)