(Create a symlink pytest for py.test)
pytest [options] [file_or_dir] [file_or_dir] ...
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# This small script shows how to use AllenNLP Semantic Role Labeling (http://allennlp.org/) with SpaCy 2.0 (http://spacy.io) components and extensions | |
# Script installs allennlp default model | |
# Important: Install allennlp form source and replace the spacy requirement with spacy-nightly in the requirements.txt | |
# Developed for SpaCy 2.0.0a18 | |
from allennlp.commands import DEFAULT_MODELS | |
from allennlp.common.file_utils import cached_path | |
from allennlp.service.predictors import SemanticRoleLabelerPredictor | |
from allennlp.models.archival import load_archive |
from graphviz import Digraph | |
import torch | |
from torch.autograd import Variable, Function | |
def iter_graph(root, callback): | |
queue = [root] | |
seen = set() | |
while queue: | |
fn = queue.pop() | |
if fn in seen: |
import torch | |
from torch import nn | |
from torch.autograd import Variable | |
import torch.nn.functional as F | |
class RNN(nn.Module): | |
def __init__(self, input_size, hidden_size, output_size, n_layers=1): | |
super(RNN, self).__init__() | |
self.input_size = input_size | |
self.hidden_size = hidden_size |
#!/bin/bash | |
# install CUDA Toolkit v8.0 | |
# instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb (network)) | |
CUDA_REPO_PKG="cuda-repo-ubuntu1604_8.0.61-1_amd64.deb" | |
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/${CUDA_REPO_PKG} | |
sudo dpkg -i ${CUDA_REPO_PKG} | |
sudo apt-get update | |
sudo apt-get -y install cuda |