#!/usr/bin/env python3
from diffusers import StableDiffusionPipeline, DPMSolverSinglestepScheduler, DPMSolverMultistepScheduler, DEISMultistepScheduler, HeunDiscreteScheduler
import time
import os
from huggingface_hub import HfApi
import torch
import sys
from pathlib import Path

path = sys.argv[1]

api = HfApi()
start_time = time.time()
#pipe = StableDiffusionPipeline.from_pretrained(path, torch_dtype=torch.float16, device_map="auto")
#pipe.scheduler = HeunDiscreteScheduler.from_config(pipe.scheduler.config)
pipe = StableDiffusionPipeline.from_pretrained(path, torch_dtype=torch.float16)
pipe.scheduler = HeunDiscreteScheduler.from_config(pipe.scheduler.config)
pipe = pipe.to("cuda")

prompt = "a highly realistic photo of green turtle"
generator = torch.Generator(device="cuda").manual_seed(0)
image = pipe(prompt, generator=generator, num_inference_steps=25).images[0]
print("Time", time.time() - start_time)

path = os.path.join(Path.home(), "images", "aa.png")
image.save(path)

api.upload_file(
    path_or_fileobj=path,
    path_in_repo=path.split("/")[-1],
    repo_id="patrickvonplaten/images",
    repo_type="dataset",
)
print("https://huggingface.co/datasets/patrickvonplaten/images/blob/main/aa.png")