INNER CODE UNIT · Python

bot_streaming_T2I

FoundationVision/Liquid · evaluation/app.py:190

def bot_streaming_T2I(message, history,guidance_scale, temperature, top_K, top_P):
 
    global stop_flag
    stop_flag = True
    time.sleep(0.2)
    stop_flag = False
    
    text_inputs = [message]*4  # generate 4 samples once
    uncondition_text_inputs = ['<unconditional><boi>']*len(text_inputs)
    for i in range(len(text_inputs)):
        text_inputs[i] = text_inputs[i]+' Generate an image based on this description.<boi>'

    ori_batchsize = len(text_inputs)

    if guidance_scale>1:
        model_inputs = tokenizer(text_inputs+uncondition_text_inputs, return_tensors="pt",padding=True).to("cuda:0")
    else:
        model_inputs = tokenizer(text_inputs, return_tensors="pt",padding=True).to("cuda:0")

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