# Copyright 2024 Huawei Technologies Co., Ltd
# Copyright 2023 The HuggingFace Team. All rights reserved.


import random
import os
from diffusers import DiffusionPipeline
import torch
import torch_npu
from accelerate import PartialState
from torch_npu.contrib import transfer_to_npu
import numpy as np

output_path = "./sdxl_lora_NPU"
os.makedirs(output_path, exist_ok=True)

model_path = "/stabilityai/stable-diffusion-xl-base-1.0"  # Path for base model
lora_weights = "/pytorch_lora_weights.safetensors"  # Path for LoRA weights

pipe = DiffusionPipeline.from_pretrained(model_path, torch_dtype=torch.float32, local_files_only=True)

if os.path.exists(lora_weights):
    print(f"Loading LoRA weights from {lora_weights}")
    pipe.load_lora_weights(lora_weights)
else:
    print("LoRA weights not found. Using the base model")

distributed_state = PartialState()
pipe.to(distributed_state.device)

prompts = dict()
prompts["masterpiece, best quality, Cute dragon creature, pokemon style, night, moonlight, dim lighting"] = "deformed, disfigured, underexposed, overexposed, rugged, (low quality), (normal quality),"
prompts["masterpiece, best quality, Pikachu walking in beijing city, pokemon style, night, moonlight, dim lighting"] = "deformed, disfigured, underexposed, overexposed, (low quality), (normal quality),"
prompts["masterpiece, best quality, red panda , pokemon style, evening light, sunset, rim lighting"] = "deformed, disfigured, underexposed, overexposed, (low quality), (normal quality),"
prompts["masterpiece, best quality, Photo of (Lion:1.2) on a couch, flower in vase, dof, film grain, crystal clear, pokemon style, dark studio"] = "deformed, disfigured, underexposed, overexposed, "
prompts["masterpiece, best quality, siberian cat pokemon on river, pokemon style, evening light, sunset, rim lighting, depth of field"] = "deformed, disfigured, underexposed, overexposed, "
prompts["masterpiece, best quality, pig, Exquisite City, (sky:1.3), (Miniature tree:1.3), Miniature object, many flowers, glowing mushrooms, (creek:1.3), lots of fruits, cute colorful animal protagonist, Firefly, meteor, Colorful cloud, pokemon style, Complicated background, rainbow,"] = "Void background,black background,deformed, disfigured, underexposed, overexposed, "
prompts["masterpiece, best quality, (pokemon), a cute pikachu, girl with glasses, (masterpiece, top quality, best quality, official art, beautiful and aesthetic:1.2),"] = "(low quality), (normal quality), (monochrome), lowres, extra fingers, fewer fingers, (watermark), "
prompts["masterpiece, best quality, sugimori ken \(style\), (pokemon \(creature\)), pokemon electric type, grey and yellow skin, mechanical arms, cyberpunk city background, night, neon light"] = "(worst quality, low quality:1.4), watermark, signature, deformed, disfigured, underexposed, overexposed, "
#设置随机数种子
seed_list = [8, 23, 42, 1334]

# 输出图片
for i in seed_list:
    generator = torch.Generator(device="npu").manual_seed(i)

    # Convert dictionary to list
    prompt_list = list(prompts.keys())
    negative_prompt_list = list(prompts.values())

    with distributed_state.split_between_processes(
        list(zip(prompt_list, negative_prompt_list))
    ) as distributed_pairs:
        for prompt, negative_prompt in distributed_pairs:
            image = pipe(
                prompt=prompt,
                negative_prompt=negative_prompt,
                generator=generator,
                num_inference_steps=28,
                height=1024,
                width=1024,
                guidance_scale=1.0,
            ).images

            # Create name for the image
            prompt_words = prompt.replace("masterpiece, best quality, ", "").split()[:3]
            prompt_abbr = "_".join(prompt_words)

            filename = f"{prompt_abbr}_seed{i}_rank{distributed_state.process_index}.png"
            filename = "".join(c for c in filename if c.isalnum() or c in "._-") # remove special chars

            image[0].save(f"{output_path}/{filename}")