| | import argparse |
| | import torch |
| |
|
| | from llava.constants import IMAGE_TOKEN_INDEX, DEFAULT_IMAGE_TOKEN, DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN |
| | from llava.conversation import conv_templates, SeparatorStyle |
| | from llava.model.builder import load_pretrained_model |
| | from llava.utils import disable_torch_init |
| | from llava.mm_utils import tokenizer_image_token, get_model_name_from_path, KeywordsStoppingCriteria |
| |
|
| | from PIL import Image |
| |
|
| | import requests |
| | from PIL import Image |
| | from io import BytesIO |
| | from transformers import TextStreamer |
| |
|
| |
|
| | def load_image(image_file): |
| | if image_file.startswith("http") or image_file.startswith("https"): |
| | response = requests.get(image_file) |
| | image = Image.open(BytesIO(response.content)).convert("RGB") |
| | else: |
| | image = Image.open(image_file).convert("RGB") |
| | return image |
| |
|
| |
|
| | def main(args): |
| | |
| | disable_torch_init() |
| |
|
| | model_name = get_model_name_from_path(args.model_path) |
| | tokenizer, model, image_processor, context_len = load_pretrained_model(args.model_path, args.model_base, model_name, args.load_8bit, args.load_4bit) |
| |
|
| | if "llama-2" in model_name.lower(): |
| | conv_mode = "llava_llama_2" |
| | elif "v1" in model_name.lower(): |
| | conv_mode = "llava_v1" |
| | elif "mpt" in model_name.lower(): |
| | conv_mode = "mpt" |
| | else: |
| | conv_mode = "llava_v0" |
| |
|
| | if args.conv_mode is not None and conv_mode != args.conv_mode: |
| | print("[WARNING] the auto inferred conversation mode is {}, while `--conv-mode` is {}, using {}".format(conv_mode, args.conv_mode, args.conv_mode)) |
| | else: |
| | args.conv_mode = conv_mode |
| |
|
| | conv = conv_templates[args.conv_mode].copy() |
| | if "mpt" in model_name.lower(): |
| | roles = ("user", "assistant") |
| | else: |
| | roles = conv.roles |
| |
|
| | image = load_image(args.image_file) |
| | image_tensor = image_processor.preprocess(image, return_tensors="pt")["pixel_values"].half().cuda() |
| |
|
| | while True: |
| | try: |
| | inp = input(f"{roles[0]}: ") |
| | except EOFError: |
| | inp = "" |
| | if not inp: |
| | print("exit...") |
| | break |
| |
|
| | print(f"{roles[1]}: ", end="") |
| |
|
| | if image is not None: |
| | |
| | if model.config.mm_use_im_start_end: |
| | inp = DEFAULT_IM_START_TOKEN + DEFAULT_IMAGE_TOKEN + DEFAULT_IM_END_TOKEN + "\n" + inp |
| | else: |
| | inp = DEFAULT_IMAGE_TOKEN + "\n" + inp |
| | conv.append_message(conv.roles[0], inp) |
| | image = None |
| | else: |
| | |
| | conv.append_message(conv.roles[0], inp) |
| | conv.append_message(conv.roles[1], None) |
| | prompt = conv.get_prompt() |
| |
|
| | input_ids = tokenizer_image_token(prompt, tokenizer, IMAGE_TOKEN_INDEX, return_tensors="pt").unsqueeze(0).cuda() |
| | stop_str = conv.sep if conv.sep_style != SeparatorStyle.TWO else conv.sep2 |
| | keywords = [stop_str] |
| | stopping_criteria = KeywordsStoppingCriteria(keywords, tokenizer, input_ids) |
| | streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True) |
| |
|
| | with torch.inference_mode(): |
| | output_ids = model.generate(input_ids, images=image_tensor, do_sample=True, temperature=0.2, max_new_tokens=1024, streamer=streamer, use_cache=True, stopping_criteria=[stopping_criteria]) |
| |
|
| | outputs = tokenizer.decode(output_ids[0, input_ids.shape[1] :]).strip() |
| | conv.messages[-1][-1] = outputs |
| |
|
| | if args.debug: |
| | print("\n", {"prompt": prompt, "outputs": outputs}, "\n") |
| |
|
| |
|
| | if __name__ == "__main__": |
| | parser = argparse.ArgumentParser() |
| | parser.add_argument("--model-path", type=str, default="facebook/opt-350m") |
| | parser.add_argument("--model-base", type=str, default=None) |
| | parser.add_argument("--image-file", type=str, required=True) |
| | parser.add_argument("--num-gpus", type=int, default=1) |
| | parser.add_argument("--conv-mode", type=str, default=None) |
| | parser.add_argument("--temperature", type=float, default=0.2) |
| | parser.add_argument("--max-new-tokens", type=int, default=512) |
| | parser.add_argument("--load-8bit", action="store_true") |
| | parser.add_argument("--load-4bit", action="store_true") |
| | parser.add_argument("--debug", action="store_true") |
| | args = parser.parse_args() |
| | main(args) |
| |
|
