data: S3FileLister: ValueError: curlCode: 77, Problem with the SSL CA cert (path? access rights?)

🐛 Describe the bug

The code that I am running is -

import torchdata.datapipes as dp

s3_urls = dp.iter.IterableWrapper(["s3://bucket/key"]).list_files_by_s3(request_timeout_ms=100)

print(next(iter(s3_urls)))

The full readout that I am seeing is here -

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
/tmp/ipykernel_11947/2457993211.py in <cell line: 5>()
      3 s3_urls = dp.iter.IterableWrapper(["s3://bucket/key"]).list_files_by_s3(request_timeout_ms=100)
      4 
----> 5 print(next(iter(s3_urls)))

~/anaconda3/envs/pytorch_p39/lib/python3.9/site-packages/torch/utils/data/datapipes/_typing.py in wrap_generator(*args, **kwargs)
    512                         response = gen.send(None)
    513                 else:
--> 514                     response = gen.send(None)
    515 
    516                 while True:

~/anaconda3/envs/pytorch_p39/lib/python3.9/site-packages/torchdata/datapipes/iter/load/s3io.py in __iter__(self)
     56         for prefix in self.source_datapipe:
     57             while True:
---> 58                 urls = self.handler.list_files(prefix)
     59                 yield from urls
     60                 if not urls:

ValueError: curlCode: 77, Problem with the SSL CA cert (path? access rights?)
This exception is thrown by __iter__ of S3FileListerIterDataPipe(length=-1, source_datapipe=IterableWrapperIterDataPipe)

I can successfully run the following code -

import boto3

s3 = boto3.resource('s3')
object = s3.Object('bucket', 'key')

# Download the file from S3
object.download_file('./test.tfrecords')

Versions

Unsure if relevant but I am on an EC2 instance Deep Learning AMI.

PyTorch version: 1.12.0+cu102
Is debug build: False
CUDA used to build PyTorch: 10.2
ROCM used to build PyTorch: N/A

OS: Ubuntu 18.04.6 LTS (x86_64)
GCC version: (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
Clang version: Could not collect
CMake version: version 3.22.3
Libc version: glibc-2.27

Python version: 3.9.13 | packaged by conda-forge | (main, May 27 2022, 16:56:21)  [GCC 10.3.0] (64-bit runtime)
Python platform: Linux-5.4.0-1080-aws-x86_64-with-glibc2.27
Is CUDA available: True
CUDA runtime version: 11.5.119
GPU models and configuration: GPU 0: Tesla T4
Nvidia driver version: 510.47.03
cuDNN version: Probably one of the following:
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.0.5
/usr/local/cuda-11.1/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.0.5
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn.so.8.1.1
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.1.1
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.1.1
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.1.1
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.1.1
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.1.1
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.1.1
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] mypy-boto3-s3==1.21.0
[pip3] mypy-boto3-sagemaker==1.21.0
[pip3] mypy-extensions==0.4.3
[pip3] numpy==1.22.4
[pip3] numpydoc==1.2.1
[pip3] torch==1.12.0
[pip3] torch-model-archiver==0.5.3b20220226
[pip3] torch-workflow-archiver==0.2.4b20220513
[pip3] torchaudio==0.11.0
[pip3] torchdata==0.4.0
[pip3] torchserve==0.5.3b20220226
[pip3] torchtext==0.12.0
[pip3] torchvision==0.12.0
[conda] blas                      2.115                       mkl    conda-forge
[conda] blas-devel                3.9.0            15_linux64_mkl    conda-forge
[conda] captum                    0.5.0                         0    pytorch
[conda] cudatoolkit               11.5.1              hcf5317a_10    conda-forge
[conda] libblas                   3.9.0            15_linux64_mkl    conda-forge
[conda] libcblas                  3.9.0            15_linux64_mkl    conda-forge
[conda] liblapack                 3.9.0            15_linux64_mkl    conda-forge
[conda] liblapacke                3.9.0            15_linux64_mkl    conda-forge
[conda] magma-cuda115             2.6.1                         0    pytorch
[conda] mkl                       2022.1.0           h84fe81f_915    conda-forge
[conda] mkl-devel                 2022.1.0           ha770c72_916    conda-forge
[conda] mkl-include               2022.1.0           h84fe81f_915    conda-forge
[conda] mkl-service               2.4.0            py39hb699420_0    conda-forge
[conda] mkl_fft                   1.3.1            py39h1fd5c3a_3    conda-forge
[conda] mkl_random                1.2.2            py39h8b66066_1    conda-forge
[conda] numpy                     1.22.4           py39hc58783e_0    conda-forge
[conda] numpydoc                  1.2.1              pyhd8ed1ab_0    conda-forge
[conda] pytorch-mutex             1.0                        cuda    pytorch
[conda] torch                     1.12.0                   pypi_0    pypi
[conda] torch-model-archiver      0.5.3                    py39_0    pytorch
[conda] torch-workflow-archiver   0.2.4                    py39_0    pytorch
[conda] torchaudio                0.11.0               py39_cu115    pytorch
[conda] torchdata                 0.4.0                    pypi_0    pypi
[conda] torchserve                0.5.3                    py39_0    pytorch
[conda] torchtext                 0.12.0                     py39    pytorch
[conda] torchvision               0.12.0               py39_cu115    pytorch