Imrayya/stable-diffusion-webui-Prompt_Generator
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Code Issues Releases Wiki Activity

Casting parameters to avoid errors

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This commit is contained in:
Kareem
2023-02-03 16:57:31 +01:00
parent 57d621a781
commit b4833e90ce
1 changed files with 10 additions and 15 deletions
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scripts/prompt_generator.py
+10 -15
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@@ -15,7 +15,7 @@ import modules
from modules import script_callbacks
from transformers import GPT2Tokenizer, GPT2LMHeadModel
import re
import math
result_prompt = ""
@@ -43,14 +43,13 @@ def get_list_blacklist():
def on_ui_tabs():
# Method to create the extended prompt
def generate_longer_prompt_gustavosta(prompt, temperature, top_k,
max_length, repetition_penalty, num_return_sequences, use_blacklist=False, use_early_stop=True):
try:
tokenizer = GPT2Tokenizer.from_pretrained('gpt2')
tokenizer.add_special_tokens({'pad_token': '[PAD]'})
#Full credits for the model to Gustavosta (https://huggingface.co/Gustavosta). Under the MIT license
# Full credits for the model to Gustavosta (https://huggingface.co/Gustavosta). Under the MIT license
model = GPT2LMHeadModel.from_pretrained(
'Gustavosta/MagicPrompt-Dalle')
except Exception as e:
@@ -61,9 +60,9 @@ def on_ui_tabs():
print(f"Generate new prompt from: \"{prompt}\"")
input_ids = tokenizer(prompt, return_tensors='pt').input_ids
output = model.generate(input_ids, do_sample=True, temperature=temperature,
top_k=top_k, max_length=max_length,
top_k=round(top_k), max_length=max_length,
num_return_sequences=num_return_sequences*4,
repetition_penalty=repetition_penalty,
repetition_penalty=float(repetition_penalty),
penalty_alpha=0.6, no_repeat_ngram_size=1,
early_stopping=use_early_stop)
print("Generation complete!")
@@ -74,8 +73,6 @@ def on_ui_tabs():
for i in range(len(output)):
tempt_of_temp_String = tokenizer.decode(
output[i], skip_special_tokens=True)
# print(tempt_of_temp_String[:-1], j,
# len(tempt_of_temp_String) > min + 4) # Debugger
if (len(tempt_of_temp_String) > min + 4):
tempString += str(j+1) + ": " + tempt_of_temp_String
j += 1
@@ -90,7 +87,6 @@ def on_ui_tabs():
global result_prompt
result_prompt = tempString
# print(result_prompt)
return {results: tempString,
send_to_img2img: gr.update(visible=True),
@@ -110,7 +106,7 @@ def on_ui_tabs():
try:
tokenizer = GPT2Tokenizer.from_pretrained('distilgpt2')
tokenizer.add_special_tokens({'pad_token': '[PAD]'})
#Full credits for the model to FredZhang7 (https://huggingface.co/FredZhang7). Under creativeml-openrail-m license.
# Full credits for the model to FredZhang7 (https://huggingface.co/FredZhang7). Under creativeml-openrail-m license.
model = GPT2LMHeadModel.from_pretrained(
'FredZhang7/distilgpt2-stable-diffusion-v2')
except Exception as e:
@@ -120,9 +116,9 @@ def on_ui_tabs():
print(f"Generate new prompt from: \"{prompt}\"")
input_ids = tokenizer(prompt, return_tensors='pt').input_ids
output = model.generate(input_ids, do_sample=True, temperature=temperature,
top_k=top_k, max_length=max_length,
top_k=round(top_k), max_length=max_length,
num_return_sequences=num_return_sequences,
repetition_penalty=repetition_penalty,
repetition_penalty=float(repetition_penalty),
penalty_alpha=0.6, no_repeat_ngram_size=1,
early_stopping=True)
print("Generation complete!")
@@ -168,17 +164,16 @@ def on_ui_tabs():
lines=2, elem_id="promptTxt", label="Start of the prompt")
with gr.Column():
with gr.Row():
#tooltip_slider = gr.tooltip("This is the tooltip text.")
temp_slider = gr.Slider(
elem_id="temp_slider", label="Temperature", interactive=True, minimum=0, maximum=1, value=0.9)
max_length_slider = gr.Slider(
elem_id="max_length_slider", label="Max Length", interactive=True, minimum=1, maximum=200, step=1, value=90)
top_k_slider = gr.Slider(
elem_id="top_k_slider", label="Top K", value=8, minimum=1, maximum=20, interactive=True)
elem_id="top_k_slider", label="Top K", value=8, minimum=1, maximum=20, step=1, interactive=True)
with gr.Column():
with gr.Row():
repetition_penalty_slider = gr.Slider(
elem_id="repetition_penalty_slider", label="Repetition Penalty", value=1.2, minimum=0, maximum=10, interactive=True)
elem_id="repetition_penalty_slider", label="Repetition Penalty", value=1.2, minimum=0.1, maximum=10, interactive=True)
num_return_sequences_slider = gr.Slider(
elem_id="num_return_sequences_slider", label="How Many To Generate", value=5, minimum=1, maximum=20, interactive=True, step=1)
with gr.Column():