Shuffler inside a Zipper only shuffle some elements

🐛 Describe the bug

d1 and d2 have different length, d3 is a zipper contains them.

import torchdata.datapipes as dp
d1 = dp.map.SequenceWrapper(['0', '1', '2', '3'])
d1 = dp.map.Shuffler(d1)

d2 = dp.map.SequenceWrapper(['a', 'b', 'c', 'd', 'e', 'f'])
d2 = dp.map.Shuffler(d2)

d3 = dp.map.Zipper(d2, d1)
from torch.utils.data import DataLoader
dl = DataLoader(d3, batch_size=None, num_workers=1, shuffle=True)

for i in range(10):
    o = []
    for x in dl:
        o.append(x)
    print(o)

The results:

[['f', '2'], ['a', '3'], ['e', '0'], ['c', '1']]
[['e', '0'], ['c', '1'], ['f', '2'], ['a', '3']]
[['c', '1'], ['a', '3'], ['f', '2'], ['e', '0']]
[['e', '0'], ['a', '3'], ['c', '1'], ['f', '2']]
[['e', '0'], ['c', '1'], ['f', '2'], ['a', '3']]
[['c', '1'], ['e', '0'], ['f', '2'], ['a', '3']]
[['a', '3'], ['e', '0'], ['f', '2'], ['c', '1']]
[['a', '3'], ['c', '1'], ['e', '0'], ['f', '2']]
[['c', '1'], ['e', '0'], ['f', '2'], ['a', '3']]
[['e', '0'], ['c', '1'], ['a', '3'], ['f', '2']]

As we can see, the results of 10 runs only contain partial elements of d2.

Versions

Collecting environment information...
PyTorch version: 1.12.1
Is debug build: False
CUDA used to build PyTorch: 11.6
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.4 LTS (x86_64)
GCC version: (Ubuntu 7.5.0-6ubuntu2) 7.5.0
Clang version: Could not collect
CMake version: version 3.16.3
Libc version: glibc-2.31

Python version: 3.9.12 (main, Apr 5 2022, 06:56:58) [GCC 7.5.0] (64-bit runtime)
Python platform: Linux-5.4.0-124-generic-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: 10.1.243
GPU models and configuration:
GPU 0: NVIDIA A100-SXM4-80GB
GPU 1: NVIDIA A100-SXM4-80GB
GPU 2: NVIDIA A100-SXM4-80GB
GPU 3: NVIDIA A100-SXM4-80GB
GPU 4: NVIDIA A100-SXM4-80GB
GPU 5: NVIDIA A100-SXM4-80GB
GPU 6: NVIDIA A100-SXM4-80GB
GPU 7: NVIDIA A100-SXM4-80GB

Nvidia driver version: 510.85.02
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] mypy==0.971
[pip3] mypy-extensions==0.4.3
[pip3] numpy==1.22.4
[pip3] pytorch-lightning==1.7.3
[pip3] pytorch-ranger==0.1.1
[pip3] torch==1.12.1
[pip3] torch-complex==0.4.3
[pip3] torch-optimizer==0.3.0
[pip3] torch-stoi==0.1.2
[pip3] torchaudio==0.12.1
[pip3] torchdata==0.4.1
[pip3] torchmetrics==0.9.3
[pip3] torchvision==0.13.1
[conda] blas 1.0 mkl
[conda] cudatoolkit 11.6.0 hecad31d_10 conda-forge
[conda] ffmpeg 4.3 hf484d3e_0 pytorch
[conda] mkl 2021.4.0 h06a4308_640
[conda] mkl-service 2.4.0 py39h7e14d7c_0 conda-forge
[conda] mkl_fft 1.3.1 py39h0c7bc48_1 conda-forge
[conda] mkl_random 1.2.2 py39hde0f152_0 conda-forge
[conda] numpy 1.22.4 pypi_0 pypi
[conda] pytorch 1.12.1 py3.9_cuda11.6_cudnn8.3.2_0 pytorch
[conda] pytorch-lightning 1.7.3 pypi_0 pypi
[conda] pytorch-mutex 1.0 cuda pytorch
[conda] pytorch-ranger 0.1.1 pypi_0 pypi
[conda] torch-complex 0.4.3 pypi_0 pypi
[conda] torch-optimizer 0.3.0 pypi_0 pypi
[conda] torch-stoi 0.1.2 pypi_0 pypi
[conda] torchaudio 0.12.1 py39_cu116 pytorch
[conda] torchdata 0.4.1 pypi_0 pypi
[conda] torchmetrics 0.9.3 pypi_0 pypi
[conda] torchvision 0.13.1 py39_cu116 pytorch

Start with the provided Python reproducer and inspect the interaction between torchdata's Shuffler and Zipper when their inputs have different lengths, then check how DataLoader iteration affects it. Done means the behavior is covered by a regression test and the shuffled output matches the intended handling of all input elements.