Natural language processing
Natural language processing (NLP) is a field of computer science that studies how computers and humans interact. In the 1950s, Alan Turing published an article that proposed a measure of intelligence, now called the Turing test. More modern techniques, such as deep learning, have produced results in the fields of language modeling, parsing, and natural-language tasks.
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In gensim/models/fasttext.py:
model = FastText(
vector_size=m.dim,
vector_size=m.dim,
window=m.ws,
window=m.ws,
epochs=m.epoch,
epochs=m.epoch,
negative=m.neg,
negative=m.neg,
# FIXME: these next 2 lines read in unsupported FB FT modes (loss=3 softmax or loss=4 onevsall,
# or model=3 supervi
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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.
The new GrpcDataRuntime (https://github.com/jina-ai/jina/blob/master/jina/peapods/runtimes/grpc/__init__.py) does not support sharding at the moment. Thus a Flow should not specify this runtime and a sharded pod at the same time.
Right now this will not raise any error, but silently produce unexpected behavior. This is undesirable and the Flow should rather check this condition and raise an app
Running pytest with the new Python 3.9.4 shows a number of deprecation warnings about future failures to anticipate:
============================= test session starts ==============================
platform linux -- Python 3.9.4, pytest-6.2.0, py-1.10.0, pluggy-0.13.1
[....]
=============================== warnings summary ===============================
chunk.doctest::chunk.doctest
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Created by Alan Turing
- Wikipedia
- Wikipedia
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: