search

gradio-app / gradio

Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
http://www.gradio.app
Apache License 2.0
29.49k stars 2.19k forks source link

`TimeoutError: The read operation timed out` in `gradio_client` #8190

Closed MohamedAliRashad closed 1 week ago

MohamedAliRashad commented 2 weeks ago

Describe the bug

in the title

Have you searched existing issues? 🔎

Reproduction

from gradio_client import Client

client = Client("xxxx")
result = client.predict(....) # long api request

Screenshot

No response

Logs

None

System Info

ERROR:    Error loading ASGI app. Could not import module "environment".

Severity

Blocking usage of gradio

freddyaboulton commented 2 weeks ago

Can you share the app you're connecting to? Will be hard to debug this if others can't repro exactly.

MohamedAliRashad commented 2 weeks ago

@freddyaboulton 

from transformers import AutoTokenizer, AutoModel, TextIteratorStreamer
import torch
import torchvision.transforms as T
from PIL import Image

from torchvision.transforms.functional import InterpolationMode
import gradio as gr
import os
from threading import Thread

IMAGENET_MEAN = (0.485, 0.456, 0.406)
IMAGENET_STD = (0.229, 0.224, 0.225)

def build_transform(input_size):
    MEAN, STD = IMAGENET_MEAN, IMAGENET_STD
    transform = T.Compose(
        [
            T.Lambda(lambda img: img.convert("RGB") if img.mode != "RGB" else img),
            T.Resize((input_size, input_size), interpolation=InterpolationMode.BICUBIC),
            T.ToTensor(),
            T.Normalize(mean=MEAN, std=STD),
        ]
    )
    return transform

def find_closest_aspect_ratio(aspect_ratio, target_ratios, width, height, image_size):
    best_ratio_diff = float("inf")
    best_ratio = (1, 1)
    area = width * height
    for ratio in target_ratios:
        target_aspect_ratio = ratio[0] / ratio[1]
        ratio_diff = abs(aspect_ratio - target_aspect_ratio)
        if ratio_diff < best_ratio_diff:
            best_ratio_diff = ratio_diff
            best_ratio = ratio
        elif ratio_diff == best_ratio_diff:
            if area > 0.5 * image_size * image_size * ratio[0] * ratio[1]:
                best_ratio = ratio
    return best_ratio

def dynamic_preprocess(
    image, min_num=1, max_num=6, image_size=448, use_thumbnail=False
):
    orig_width, orig_height = image.size
    aspect_ratio = orig_width / orig_height

    # calculate the existing image aspect ratio
    target_ratios = set(
        (i, j)
        for n in range(min_num, max_num + 1)
        for i in range(1, n + 1)
        for j in range(1, n + 1)
        if i * j <= max_num and i * j >= min_num
    )
    target_ratios = sorted(target_ratios, key=lambda x: x[0] * x[1])

    # find the closest aspect ratio to the target
    target_aspect_ratio = find_closest_aspect_ratio(
        aspect_ratio, target_ratios, orig_width, orig_height, image_size
    )

    # calculate the target width and height
    target_width = image_size * target_aspect_ratio[0]
    target_height = image_size * target_aspect_ratio[1]
    blocks = target_aspect_ratio[0] * target_aspect_ratio[1]

    # resize the image
    resized_img = image.resize((target_width, target_height))
    processed_images = []
    for i in range(blocks):
        box = (
            (i % (target_width // image_size)) * image_size,
            (i // (target_width // image_size)) * image_size,
            ((i % (target_width // image_size)) + 1) * image_size,
            ((i // (target_width // image_size)) + 1) * image_size,
        )
        # split the image
        split_img = resized_img.crop(box)
        processed_images.append(split_img)
    assert len(processed_images) == blocks
    if use_thumbnail and len(processed_images) != 1:
        thumbnail_img = image.resize((image_size, image_size))
        processed_images.append(thumbnail_img)
    return processed_images

def load_image(image_file, input_size=448, max_num=6):
    image = Image.open(image_file).convert("RGB")
    transform = build_transform(input_size=input_size)
    images = dynamic_preprocess(
        image, image_size=input_size, use_thumbnail=True, max_num=max_num
    )
    pixel_values = [transform(image) for image in images]
    pixel_values = torch.stack(pixel_values)
    return pixel_values

path = "OpenGVLab/InternVL-Chat-V1-5-Int8"

# Otherwise, you need to set device_map='auto' to use multiple GPUs for inference.
os.environ["CUDA_LAUNCH_BLOCKING"] = "1"
model = AutoModel.from_pretrained(
    path,
    torch_dtype=torch.bfloat16,
    low_cpu_mem_usage=True,
    trust_remote_code=True,
    device_map="auto",
).eval()

tokenizer = AutoTokenizer.from_pretrained(path, trust_remote_code=True)
streamer = TextIteratorStreamer(tokenizer, skip_prompt=True)

generation_config = dict(
    num_beams=1,
    max_new_tokens=1024,
    do_sample=False,
    # streamer=streamer,
)

with gr.Blocks(title="InternVL-Chat-1.5") as demo:
    with gr.Row():
        with gr.Column():
            image = gr.Image(type="filepath")
            question = gr.Textbox(
                lines=2, value="Please describe the picture in detail"
            )
            submit_button = gr.Button(value="Submit", variant="primary")
        with gr.Column():
            output = gr.Textbox(label="Response")

    def internvl_chat(image, question):
        pixel_values = load_image(image, max_num=6).to(torch.bfloat16).to(model.device)
        output_text = model.chat(tokenizer, pixel_values, question, generation_config)

        # thread = Thread(target=model.chat, args=(tokenizer, pixel_values, question, generation_config))
        # thread.start()

        # output_text = ""
        # for response in streamer:
        #     if response == "<|im_end|>":
        #         break
        #     output_text += response
        #     yield output_text

        return output_text

    submit_button.click(internvl_chat, inputs=[image, question], outputs=output)

demo.queue().launch(share=True)
MohamedAliRashad commented 2 weeks ago

@freddyaboulton Now i get this error:

httpx.ConnectTimeout: _ssl.c:990: The handshake operation timed out
abidlabs commented 2 weeks ago

@MohamedAliRashad do you notice this with other Gradio apps too? E.g. if you make a simple Gradio app that just takes a little while to return the results of a function, do you still notice this timeout?

Can you provide us the full stack trace of the error?

MohamedAliRashad commented 2 weeks ago

@abidlabs I tried it with time.sleep(20) and it gave me the following error:

Traceback (most recent call last):
  File "/home/morashad/.local/lib/python3.10/site-packages/httpx/_transports/default.py", line 69, in map_httpcore_exceptions
    yield
  File "/home/morashad/.local/lib/python3.10/site-packages/httpx/_transports/default.py", line 233, in handle_request
    resp = self._pool.handle_request(req)
  File "/home/morashad/.local/lib/python3.10/site-packages/httpcore/_sync/connection_pool.py", line 216, in handle_request
    raise exc from None
  File "/home/morashad/.local/lib/python3.10/site-packages/httpcore/_sync/connection_pool.py", line 196, in handle_request
    response = connection.handle_request(
  File "/home/morashad/.local/lib/python3.10/site-packages/httpcore/_sync/connection.py", line 101, in handle_request
    return self._connection.handle_request(request)
  File "/home/morashad/.local/lib/python3.10/site-packages/httpcore/_sync/http11.py", line 143, in handle_request
    raise exc
  File "/home/morashad/.local/lib/python3.10/site-packages/httpcore/_sync/http11.py", line 113, in handle_request
    ) = self._receive_response_headers(**kwargs)
  File "/home/morashad/.local/lib/python3.10/site-packages/httpcore/_sync/http11.py", line 186, in _receive_response_headers
    event = self._receive_event(timeout=timeout)
  File "/home/morashad/.local/lib/python3.10/site-packages/httpcore/_sync/http11.py", line 224, in _receive_event
    data = self._network_stream.read(
  File "/home/morashad/.local/lib/python3.10/site-packages/httpcore/_backends/sync.py", line 124, in read
    with map_exceptions(exc_map):
  File "/usr/lib/python3.10/contextlib.py", line 153, in __exit__
    self.gen.throw(typ, value, traceback)
  File "/home/morashad/.local/lib/python3.10/site-packages/httpcore/_exceptions.py", line 14, in map_exceptions
    raise to_exc(exc) from exc
httpcore.ReadTimeout: The read operation timed out

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/home/morashad/projects/text-to-image/civitai-image.py", line 149, in <module>
    image_description = caption_img(image_path, prompt)
  File "/home/morashad/projects/text-to-image/civitai-image.py", line 41, in caption_img
    client = Client("https://ed23c6739dbb810faf.gradio.live", ssl_verify=False)
  File "/home/morashad/.local/lib/python3.10/site-packages/gradio_client/client.py", line 157, in __init__
    self.config = self._get_config()
  File "/home/morashad/.local/lib/python3.10/site-packages/gradio_client/client.py", line 831, in _get_config
    r = httpx.get(
  File "/home/morashad/.local/lib/python3.10/site-packages/httpx/_api.py", line 198, in get
    return request(
  File "/home/morashad/.local/lib/python3.10/site-packages/httpx/_api.py", line 106, in request
    return client.request(
  File "/home/morashad/.local/lib/python3.10/site-packages/httpx/_client.py", line 827, in request
    return self.send(request, auth=auth, follow_redirects=follow_redirects)
  File "/home/morashad/.local/lib/python3.10/site-packages/httpx/_client.py", line 914, in send
    response = self._send_handling_auth(
  File "/home/morashad/.local/lib/python3.10/site-packages/httpx/_client.py", line 942, in _send_handling_auth
    response = self._send_handling_redirects(
  File "/home/morashad/.local/lib/python3.10/site-packages/httpx/_client.py", line 979, in _send_handling_redirects
    response = self._send_single_request(request)
  File "/home/morashad/.local/lib/python3.10/site-packages/httpx/_client.py", line 1015, in _send_single_request
    response = transport.handle_request(request)
  File "/home/morashad/.local/lib/python3.10/site-packages/httpx/_transports/default.py", line 232, in handle_request
    with map_httpcore_exceptions():
  File "/usr/lib/python3.10/contextlib.py", line 153, in __exit__
    self.gen.throw(typ, value, traceback)
  File "/home/morashad/.local/lib/python3.10/site-packages/httpx/_transports/default.py", line 86, in map_httpcore_exceptions
    raise mapped_exc(message) from exc
httpx.ReadTimeout: The read operation timed out
abidlabs commented 1 week ago

Hi @MohamedAliRashad I tried reproducing this issue but I'm not able to. Here's the Colab notebook I put together: https://colab.research.google.com/drive/1RwAWknYO8pIK18RqhzziKeVfJx0r5fYy#scrollTo=mGYn8aS9-v_E

Can you provide a Colab notebook or something similar so that we can see what the issue?

abidlabs commented 1 week ago

Going to close for now, but we can reopen once we have a repro.