Video reader segfaults on certain videos. Here's a partial-reproduction script

Follow up on the following observation by @vedantroy :

This segfaults on certain videos. Here's a partial-reproduction script (the videos are stored in a pandas dataframe):

import pandas as pd

# df2 = pd.read_pickle("df2.pkl")
df = pd.read_pickle("df.pkl")
# print the # of rows in the df
print(len(df))
# print the keys in the df
print(df.keys())
# print the first row in the df
print(df.iloc[0])


# print the type of the 1st value in the 1st row
first_vid = df.iloc[0][0]
print(f"Length: {len(first_vid)}")
print(f"Type: {type(first_vid)}")

# write first_vid to a file
with open("test.mp4", "wb") as f:
    f.write(first_vid)

import itertools
import copy

import torch
from torchvision.io import VideoReader
import torchvision

def clip_from_start(buf: bytes, expected_frames: int):
    # import av
    # import io
    # buffer = io.BytesIO(buf)
    # container = av.open(buffer)
    # i = 0 
    # for frame in container.decode(video=0):
    #     print(type(frame))
    #     i += 1
    #     print(i)
    #     pass

    tensor = torch.frombuffer(buf, dtype=torch.uint8)
    tensor = copy.deepcopy(tensor)
    # torchvision.io.read_video()
    rdr = VideoReader(tensor)
    sampled_frames = list(itertools.islice(iter(rdr), expected_frames))
    if len(sampled_frames) != expected_frames:
        return None
    data = []
    for frame in sampled_frames:
        data.append(frame["data"])
    return torch.stack(data, dim=0)

clip = clip_from_start(first_vid, 2)
print(clip.shape)

I'm working to get approval of the public copy of the data.

In the meantime, the error is:

test.py:41: UserWarning: The given buffer is not writable, and PyTorch does not support non-writable tensors. This means you can write to the underlying (supposedly non-writable) buffer using the tensor. You may want to copy the buffer to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at ../torch/csrc/utils/tensor_new.cpp:1563.)
  tensor = torch.frombuffer(buf, dtype=torch.uint8)
malloc(): corrupted top size
Aborted (core dumped)

Originally posted by @vedantroy in https://github.com/pytorch/vision/issues/6771#issuecomment-1283644752

Start with the partial reproduction in test.py, focusing on the torch.frombuffer call and torchvision.io.VideoReader entry point. Reproduce the malloc corruption once the referenced pandas data and video are available, then narrow the failure to the reader path. Done means the affected video no longer segfaults and the regression is covered by an available reproduction or test.