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from flax.jax_utils import replicate | |
from jax import pmap | |
from flax.training.common_utils import shard | |
import jax | |
import jax.numpy as jnp | |
from pathlib import Path | |
from PIL import Image | |
import numpy as np | |
from diffusers import FlaxStableDiffusionPipeline | |
import os | |
if 'TPU_NAME' in os.environ: | |
import requests | |
if 'TPU_DRIVER_MODE' not in globals(): | |
url = 'http:' + os.environ['TPU_NAME'].split(':')[1] + ':8475/requestversion/tpu_driver_nightly' | |
resp = requests.post(url) | |
TPU_DRIVER_MODE = 1 | |
from jax.config import config | |
config.FLAGS.jax_xla_backend = "tpu_driver" | |
config.FLAGS.jax_backend_target = os.environ['TPU_NAME'] | |
print('Registered TPU:', config.FLAGS.jax_backend_target) | |
else: | |
print('No TPU detected. Can be changed under "Runtime/Change runtime type".') | |
import jax | |
jax.local_devices() | |
num_devices = jax.device_count() | |
device_type = jax.devices()[0].device_kind | |
print(f"Found {num_devices} JAX devices of type {device_type}.") | |
def sd2_inference(pipeline, prompts, params, seed = 42, num_inference_steps = 50 ): | |
prng_seed = jax.random.PRNGKey(seed) | |
prompt_ids = pipeline.prepare_inputs(prompts) | |
params = replicate(params) | |
prng_seed = jax.random.split(prng_seed, jax.device_count()) | |
prompt_ids = shard(prompt_ids) | |
images = pipeline(prompt_ids, params, prng_seed, num_inference_steps, jit=True).images | |
images = images.reshape((images.shape[0] * images.shape[1], ) + images.shape[-3:]) | |
images = pipeline.numpy_to_pil(images) | |
return images | |
def image_grid(imgs, rows, cols, down_sample = 1 ): | |
w,h = imgs[0].size | |
grid = Image.new('RGB', size=(cols*w, rows*h)) | |
for i, img in enumerate(imgs): grid.paste(img, box=(i%cols*w, i//cols*h)) | |
grid = grid.resize( (grid.size[0]//down_sample, grid.size[1]//down_sample) ) | |
return grid | |
HF_ACCESS_TOKEN = os.environ["HFAUTH"] | |
# Load Model | |
# - Reference: https://github.com/huggingface/diffusers/blob/main/README.md | |
pipeline, params = FlaxStableDiffusionPipeline.from_pretrained( | |
"CompVis/stable-diffusion-v1-4", | |
use_auth_token = HF_ACCESS_TOKEN, | |
revision="bf16", | |
dtype=jnp.bfloat16, | |
) |