https://github.com/huggingface/transformers/blob/546dc24e0883e5e9f5eb06ec8060e3e6ccc5f6d7/src/transformers/models/gpt2/modeling_gpt2.py#L698

Assertions can't be relied upon for control flow because they can be disabled, as per the following:

$ python --help
usage: python [option] ... [-c cmd | -m mod | file | -] [arg] ...
...
-O     : remove assert and __debug__-dependent statem

Change tensor.data to tensor.detach() due to
pytorch/pytorch#6990 (comment)
tensor.detach() is more robust than tensor.data.

Is your feature request related to a problem? Please describe.
I typically used compressed datasets (e.g. gzipped) to save disk space. This works fine with AllenNLP during training because I can write my dataset reader to load the compressed data. However, the predict command opens the file and reads lines for the Predictor. This fails when it tries to load data from my compressed files.

When using the SmoothingFunction's method4 with a a single word as a hypothesis I get the following error. Which is of course because math.log(1) is 0.
I ended up using just method2 or method1 which doesn't use the function that throws the error, but I guess it would be useful to report it, as some other poor soul may

Is your feature request related to a problem? Please describe.
A clear and concise description of what the problem is.

from datasets import load_dataset
dataset = load_dataset("c4", 'realnewslike', streaming =True, split='train')
dataset = dataset.remove_columns('url')

AttributeError: 'IterableDataset' object has no attribute 'remove_columns'

**Describe the

Hello spoooopyyy hackers 🎃

This is a Hacktoberfest only issue! 👻

This is also data-sciency!

The Problem

Our English dictionary contains words that aren't English, and does not contain common English words.

Examples of non-common words in the dictionary:

"hlithskjalf",
  "hlorrithi",
  "hlqn",
  "hm",
  "hny",
  "ho",
  "hoactzin",
  "hoactzine