<commit_before># Library dependencies for the python code.  You need to install these with
# `pip install -r requirements.txt` before you can run this.
# NOTE: all essential packages must be placed under a section named 'ESSENTIAL ...'
# so that the script `./scripts/check_requirements_and_setup.py` can find them.

#### ESSENTIAL LIBRARIES FOR MAIN FUNCTIONALITY ####

# This installs Pytorch for CUDA 8 only. If you are using a newer version,
# please visit https://pytorch.org/ and install the relevant version.
# allennlp>0.8.5 requires PyTorch 1.2 or greater. If you need to use
# an older version of PyTorch you'll also need to use an older version of allennlp.
# Note: We're not precisely avoiding 1.3.0 here. Pytorch released new binaries as
# 1.3.0.post2 for a bugfix. This requirement allows 1.3.0.post2.
torch>=1.2.0,!=1.3.0

# Parameter parsing (but not on Windows).
jsonnet>=0.10.0 ; sys.platform != 'win32'

# Adds an @overrides decorator for better documentation and error checking when using subclasses.
overrides

# Used by some old code.  We moved away from it because it's too slow, but some old code still
# imports this.
nltk

# Mainly used for the faster tokenizer.
spacy>=2.1.0,<2.2

# Used by span prediction models.
numpy

# Used for reading configuration info out of numpy-style docstrings.
numpydoc>=0.8.0

# Used in coreference resolution evaluation metrics.
scipy
scikit-learn

# Write logs for training visualisation with the Tensorboard application<commit_msg>adding version to overrides packages (#3402)<commit_after># Library dependencies for the python code.  You need to install these with
# `pip install -r requirements.txt` before you can run this.
# NOTE: all essential packages must be placed under a section named 'ESSENTIAL ...'
# so that the script `./scripts/check_requirements_and_setup.py` can find them.

#### ESSENTIAL LIBRARIES FOR MAIN FUNCTIONALITY ####

# This installs Pytorch for CUDA 8 only. If you are using a newer version,
# please visit https://pytorch.org/ and install the relevant version.
# allennlp>0.8.5 requires PyTorch 1.2 or greater. If you need to use
# an older version of PyTorch you'll also need to use an older version of allennlp.
# Note: We're not precisely avoiding 1.3.0 here. Pytorch released new binaries as
# 1.3.0.post2 for a bugfix. This requirement allows 1.3.0.post2.
torch>=1.2.0,!=1.3.0

# Parameter parsing (but not on Windows).
jsonnet>=0.10.0 ; sys.platform != 'win32'

# Adds an @overrides decorator for better documentation and error checking when using subclasses.
overrides==2.0

# Used by some old code.  We moved away from it because it's too slow, but some old code still
# imports this.
nltk

# Mainly used for the faster tokenizer.
spacy>=2.1.0,<2.2

# Used by span prediction models.
numpy

# Used for reading configuration info out of numpy-style docstrings.
numpydoc>=0.8.0

# Used in coreference resolution evaluation metrics.
scipy
scikit-learn

# Write logs for training visualisation with the Tensorboard application
{'fraction_non_alphanumeric': 0.08278145695364239, 'fraction_numerical': 0.026490066225165563, 'mean_word_length': 4.129032258064516, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 13, 'https://': 2, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '1599372', 'n_tokens_mistral': 943, 'n_tokens_neox': 916, 'n_words': 406}