Mark Neumann DeNeutoy
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| import streamlit as st | |
| import spacy | |
| from spacy import displacy | |
| import pandas as pd | |
| from scispacy.umls_linking import UmlsEntityLinker | |
| from scispacy.abbreviation import AbbreviationDetector | |
| SPACY_MODEL_NAMES = ["en_core_sci_sm", "en_core_sci_md", "en_core_sci_lg"] |
DeNeutoy
/ snli_20.jsonl
Created
October 18, 2019 19:20
Idea for new Allennlp Dataset and Iterator API
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| {"annotator_labels": ["neutral", "entailment", "neutral", "neutral", "neutral"], "captionID": "4705552913.jpg#2", "gold_label": "neutral", "pairID": "4705552913.jpg#2r1n", "sentence1": "Two women are embracing while holding to go packages.", "sentence1_binary_parse": "( ( Two women ) ( ( are ( embracing ( while ( holding ( to ( go packages ) ) ) ) ) ) . ) )", "sentence1_parse": "(ROOT (S (NP (CD Two) (NNS women)) (VP (VBP are) (VP (VBG embracing) (SBAR (IN while) (S (NP (VBG holding)) (VP (TO to) (VP (VB go) (NP (NNS packages)))))))) (. .)))", "sentence2": "The sisters are hugging goodbye while holding to go packages after just eating lunch.", "sentence2_binary_parse": "( ( The sisters ) ( ( are ( ( hugging goodbye ) ( while ( holding ( to ( ( go packages ) ( after ( just ( eating lunch ) ) ) ) ) ) ) ) ) . ) )", "sentence2_parse": "(ROOT (S (NP (DT The) (NNS sisters)) (VP (VBP are) (VP (VBG hugging) (NP (UH goodbye)) (PP (IN while) (S (VP (VBG holding) (S (VP (TO to) (VP (VB go) (NP (NNS packages)) (PP (IN af |
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| name: CI | |
| on: | |
| pull_request: | |
| branches: | |
| - master | |
| push: | |
| branches: | |
| - master |
DeNeutoy
/ logsumexp_experiments.py
Last active
April 30, 2019 20:01
— forked from sjmielke/logsumexp_experiments.py
https://twitter.com/sjmielke/status/1123035927612411905
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| from mpmath import mp | |
| mp.dps = 100 | |
| import torch | |
| # Take some list of values that shrink to be really small in log space: | |
| torch_lps = torch.log_softmax(-torch.arange(20.0, dtype=torch.float64), dim=0) | |
| mpmath_lps = -torch.arange(20.0, dtype=torch.float64) | |
| Z = sum([mp.exp(mp.mpf(mpmath_lps[i].item())) for i in range(len(mpmath_lps))]) |
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| import tensorflow as tf | |
| def mix_models_scalar(linear_outputs, rnn_outputs, lstm_outputs): | |
| # Generate scalar valued weights to combine outputs of a | |
| # Linear RNN, vanilla RNN and LSTM. Each of the inputs to | |
| # this function is a list of outputs from the respective model. | |
| context_window_size = 20 | |
| all_model_outputs = [linear_outputs, rnn_outputs, lstm_outputs] |