| import os |
| from torch import multiprocessing as mp |
|
|
| from torchvision.utils import save_image |
|
|
| from argparse import ArgumentParser |
| import time |
| import multiprocessing |
|
|
| from dataset_tools.multi_gpu_infer_with_prompt import _run_on_multiple_gpus |
|
|
| from absl import logging |
| from utils import set_logger |
|
|
| if __name__ == "__main__": |
|
|
| |
| multiprocessing.set_start_method('spawn') |
|
|
| parser = ArgumentParser() |
| parser.add_argument("-v", "--verbose", action="store_true") |
|
|
| parser.add_argument("--multiprocess", action="store_true") |
| parser.add_argument("--gpu_ids", type=lambda x: [int(i) for i in x.split(",")], default=[0]) |
|
|
| parser.add_argument( |
| "--cache_dir", |
| type=str, |
| default=None, |
| help="The directory to store the cache files." |
| ) |
|
|
| parser.add_argument( |
| "--node_id", |
| type=int, |
| default=0, |
| help="Node ID for distributed inference." |
| ) |
|
|
| parser.add_argument( |
| "--node_ids", |
| type=lambda x: [int(i) for i in x.split(",")], |
| default=[0], |
| help="Node IDs for distributed inference, separated by commas." |
| ) |
|
|
| parser.add_argument( |
| "--dataset_name", |
| type=str, |
| default="coco", |
| ) |
| parser.add_argument( |
| "--dataset_anno_file", |
| type=str, |
| default="./data/prompts/captions_val2017.json", |
| ) |
|
|
| parser.add_argument( |
| "--model_name", |
| type=str, |
| default="leloy/Anole-7b-v0.1-hf", |
| ) |
|
|
| parser.add_argument( |
| "--max_num_new_tokens", |
| type=int, |
| default=16, |
| ) |
|
|
| parser.add_argument( |
| "--multi_token_init_scheme", |
| type=str, |
| default='random', |
| ) |
|
|
| parser.add_argument( |
| "--seed", |
| type=int, |
| default=42, |
| ) |
|
|
| parser.add_argument( |
| "--image_top_k", |
| type=int, |
| default=2000, |
| ) |
|
|
| parser.add_argument( |
| "--target_size", |
| type=int, |
| default=1024, |
| ) |
|
|
| parser.add_argument( |
| "--prefix_token_sampler_scheme", |
| type=str, |
| default='speculative_jacobi', |
| ) |
|
|
| parser.add_argument( |
| "--guidance_scale", |
| type=float, |
| default=3.0, |
| ) |
|
|
| parser.add_argument( |
| "--output_dir", |
| type=str, |
| default="/home/leihaodong/AAAI25/exp/SJD", |
| ) |
|
|
| parser.add_argument( |
| "--temperature", |
| type=float, |
| default=1.0, |
| ) |
|
|
| parser.add_argument( |
| "--num_images", |
| type=int, |
| default=1, |
| ) |
|
|
| parser.add_argument( |
| "--tokenizer_path", |
| default='/data/lei/localmodel/lumina_mgpt/chameleon/tokenizer', |
| type=str, help="location of the reference images for evaluation" |
| ) |
|
|
| parser.add_argument("--return_accl",default=True,type=bool) |
|
|
| args = parser.parse_args() |
|
|
| start_time = time.time() |
|
|
| max_num_new_tokens = args.max_num_new_tokens |
| multi_token_init_scheme = args.multi_token_init_scheme |
| seed = args.seed if args.seed >=0 else None |
| model_name = args.model_name |
| dataset_name = args.dataset_name |
| guidance_scale = args.guidance_scale |
| image_top_k = args.image_top_k |
| prefix_token_sampler_scheme = args.prefix_token_sampler_scheme |
|
|
| num_images = args.num_images |
|
|
| if args.target_size > 0: |
| target_size = args.target_size |
| else: |
| potential_target_size = model_name.split("-")[-1] |
| if potential_target_size.isdigit(): |
| target_size = int(potential_target_size) |
| else: |
| target_size = 512 |
|
|
| workdir = args.output_dir |
| if not os.path.exists(workdir): |
| os.makedirs(workdir) |
|
|
| set_logger(log_level='info', fname=os.path.join(workdir, 'gen_img_output.log')) |
| |
|
|
| logging.info(f"cache dir: {args.cache_dir}") |
| logging.info(f"gpu_ids: {args.gpu_ids}") |
| logging.info(f"node_ids: {args.node_ids}") |
| logging.info(f"target_size: {target_size}") |
|
|
| _run_on_multiple_gpus( |
| gpu_ids=args.gpu_ids, |
| node_ids=args.node_ids, |
| node_id=args.node_id, |
| \ |
| dataset_params = dict( |
| name = args.dataset_name, |
| annFile = args.dataset_anno_file, |
| data_len = num_images |
| ), |
| model_name = args.model_name, |
| \ |
| cache_dir = args.cache_dir, |
| target_size = target_size, |
| seed = seed, |
| max_num_new_tokens = max_num_new_tokens, |
| multi_token_init_scheme = multi_token_init_scheme, |
| guidance_scale = guidance_scale, |
| image_top_k=image_top_k, |
| max_gen_len=8192, |
| temperature=args.temperature, |
| output_dir = workdir, |
| prefix_token_sampler_scheme = prefix_token_sampler_scheme, |
| local_chameleon_tokenizer_path = args.tokenizer_path, |
| return_accl = args.return_accl |
| ) |
| end_time = time.time() |
| logging.info(f"Total Time taken: {end_time - start_time}") |
