Upload 264 files

51d52fc verified 3 months ago

4.8 kB

"""
generate.py
Simple CLI script to interactively test generating from a pretrained VLM; provides a minimal REPL for specify image
URLs, prompts, and language generation parameters.
Run with: python scripts/generate.py --model_path <PATH TO LOCAL MODEL OR HF HUB>
"""

import os
from dataclasses import dataclass
from pathlib import Path
from typing import Union

import draccus
import requests
import torch
from PIL import Image

from prismatic import load
from prismatic.overwatch import initialize_overwatch

# Initialize Overwatch =>> Wraps `logging.Logger`
overwatch = initialize_overwatch(__name__)


# Default Image URL (Beignets)
DEFAULT_IMAGE_URL = (
    "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png"
)


@dataclass
class GenerateConfig:
    # fmt: off
    model_path: Union[str, Path] = (                                    # Path to Pretrained VLM (on disk or HF Hub)
        "prism-dinosiglip+7b"
    )

    # HF Hub Credentials (required for Gated Models like LLaMa-2)
    hf_token: Union[str, Path] = Path(".hf_token")                      # Environment variable or Path to HF Token

    # Default Generation Parameters =>> subscribes to HuggingFace's GenerateMixIn API
    do_sample: bool = False
    temperature: float = 1.0
    max_new_tokens: int = 512
    min_length: int = 1

    # fmt: on


@draccus.wrap()
def generate(cfg: GenerateConfig) -> None:
    overwatch.info(f"Initializing Generation Playground with Prismatic Model `{cfg.model_path}`")
    hf_token = cfg.hf_token.read_text().strip() if isinstance(cfg.hf_token, Path) else os.environ[cfg.hf_token]
    device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")

    # Load the pretrained VLM --> uses default `load()` function
    vlm = load(cfg.model_path, hf_token=hf_token)
    vlm.to(device, dtype=torch.bfloat16)

    # Initial Setup
    image = Image.open(requests.get(DEFAULT_IMAGE_URL, stream=True).raw).convert("RGB")
    prompt_builder = vlm.get_prompt_builder()
    system_prompt = prompt_builder.system_prompt

    # REPL Welcome Message
    print(
        "[*] Dropping into Prismatic VLM REPL with Default Generation Setup => Initial Conditions:\n"
        f"       => Prompt Template:\n\n{prompt_builder.get_potential_prompt('<INSERT PROMPT HERE>')}\n\n"
        f"       => Default Image URL: `{DEFAULT_IMAGE_URL}`\n===\n"
    )

    # REPL
    repl_prompt = (
        "|=>> Enter (i)mage to fetch image from URL, (p)rompt to update prompt template, (q)uit to exit, or any other"
        " key to enter input questions: "
    )
    while True:
        user_input = input(repl_prompt)

        if user_input.lower().startswith("q"):
            print("\n|=>> Received (q)uit signal => Exiting...")
            return

        elif user_input.lower().startswith("i"):
            # Note => a new image starts a _new_ conversation (for now)
            url = input("\n|=>> Enter Image URL: ")
            image = Image.open(requests.get(url, stream=True).raw).convert("RGB")
            prompt_builder = vlm.get_prompt_builder(system_prompt=system_prompt)

        elif user_input.lower().startswith("p"):
            if system_prompt is None:
                print("\n|=>> Model does not support `system_prompt`!")
                continue

            # Note => a new system prompt starts a _new_ conversation
            system_prompt = input("\n|=>> Enter New System Prompt: ")
            prompt_builder = vlm.get_prompt_builder(system_prompt=system_prompt)
            print(
                "\n[*] Set New System Prompt:\n"
                f"    => Prompt Template:\n{prompt_builder.get_potential_prompt('<INSERT PROMPT HERE>')}\n\n"
            )

        else:
            print("\n[*] Entering Chat Session - CTRL-C to start afresh!\n===\n")
            try:
                while True:
                    message = input("|=>> Enter Prompt: ")

                    # Build Prompt
                    prompt_builder.add_turn(role="human", message=message)
                    prompt_text = prompt_builder.get_prompt()

                    # Generate from the VLM
                    generated_text = vlm.generate(
                        image,
                        prompt_text,
                        do_sample=cfg.do_sample,
                        temperature=cfg.temperature,
                        max_new_tokens=cfg.max_new_tokens,
                        min_length=cfg.min_length,
                    )
                    prompt_builder.add_turn(role="gpt", message=generated_text)
                    print(f"\t|=>> VLM Response >>> {generated_text}\n")

            except KeyboardInterrupt:
                print("\n===\n")
                continue


if __name__ == "__main__":
    generate()

	"""
	generate.py

	Simple CLI script to interactively test generating from a pretrained VLM; provides a minimal REPL for specify image
	URLs, prompts, and language generation parameters.

	Run with: python scripts/generate.py --model_path <PATH TO LOCAL MODEL OR HF HUB>
	"""

	import os
	from dataclasses import dataclass
	from pathlib import Path
	from typing import Union

	import draccus
	import requests
	import torch
	from PIL import Image

	from prismatic import load
	from prismatic.overwatch import initialize_overwatch

	# Initialize Overwatch =>> Wraps `logging.Logger`
	overwatch = initialize_overwatch(__name__)


	# Default Image URL (Beignets)
	DEFAULT_IMAGE_URL = (
	"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png"
	)


	@dataclass
	class GenerateConfig:
	# fmt: off
	model_path: Union[str, Path] = ( # Path to Pretrained VLM (on disk or HF Hub)
	"prism-dinosiglip+7b"
	)

	# HF Hub Credentials (required for Gated Models like LLaMa-2)
	hf_token: Union[str, Path] = Path(".hf_token") # Environment variable or Path to HF Token

	# Default Generation Parameters =>> subscribes to HuggingFace's GenerateMixIn API
	do_sample: bool = False
	temperature: float = 1.0
	max_new_tokens: int = 512
	min_length: int = 1

	# fmt: on


	@draccus.wrap()
	def generate(cfg: GenerateConfig) -> None:
	overwatch.info(f"Initializing Generation Playground with Prismatic Model `{cfg.model_path}`")
	hf_token = cfg.hf_token.read_text().strip() if isinstance(cfg.hf_token, Path) else os.environ[cfg.hf_token]
	device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")

	# Load the pretrained VLM --> uses default `load()` function
	vlm = load(cfg.model_path, hf_token=hf_token)
	vlm.to(device, dtype=torch.bfloat16)

	# Initial Setup
	image = Image.open(requests.get(DEFAULT_IMAGE_URL, stream=True).raw).convert("RGB")
	prompt_builder = vlm.get_prompt_builder()
	system_prompt = prompt_builder.system_prompt

	# REPL Welcome Message
	print(
	"[*] Dropping into Prismatic VLM REPL with Default Generation Setup => Initial Conditions:\n"
	f" => Prompt Template:\n\n{prompt_builder.get_potential_prompt('<INSERT PROMPT HERE>')}\n\n"
	f" => Default Image URL: `{DEFAULT_IMAGE_URL}`\n===\n"
	)

	# REPL
	repl_prompt = (
	"\|=>> Enter (i)mage to fetch image from URL, (p)rompt to update prompt template, (q)uit to exit, or any other"
	" key to enter input questions: "
	)
	while True:
	user_input = input(repl_prompt)

	if user_input.lower().startswith("q"):
	print("\n\|=>> Received (q)uit signal => Exiting...")
	return

	elif user_input.lower().startswith("i"):
	# Note => a new image starts a _new_ conversation (for now)
	url = input("\n\|=>> Enter Image URL: ")
	image = Image.open(requests.get(url, stream=True).raw).convert("RGB")
	prompt_builder = vlm.get_prompt_builder(system_prompt=system_prompt)

	elif user_input.lower().startswith("p"):
	if system_prompt is None:
	print("\n\|=>> Model does not support `system_prompt`!")
	continue

	# Note => a new system prompt starts a _new_ conversation
	system_prompt = input("\n\|=>> Enter New System Prompt: ")
	prompt_builder = vlm.get_prompt_builder(system_prompt=system_prompt)
	print(
	"\n[*] Set New System Prompt:\n"
	f" => Prompt Template:\n{prompt_builder.get_potential_prompt('<INSERT PROMPT HERE>')}\n\n"
	)

	else:
	print("\n[*] Entering Chat Session - CTRL-C to start afresh!\n===\n")
	try:
	while True:
	message = input("\|=>> Enter Prompt: ")

	# Build Prompt
	prompt_builder.add_turn(role="human", message=message)
	prompt_text = prompt_builder.get_prompt()

	# Generate from the VLM
	generated_text = vlm.generate(
	image,
	prompt_text,
	do_sample=cfg.do_sample,
	temperature=cfg.temperature,
	max_new_tokens=cfg.max_new_tokens,
	min_length=cfg.min_length,
	)
	prompt_builder.add_turn(role="gpt", message=generated_text)
	print(f"\t\|=>> VLM Response >>> {generated_text}\n")

	except KeyboardInterrupt:
	print("\n===\n")
	continue


	if __name__ == "__main__":
	generate()