(Create a symlink pytest for py.test)
pytest [options] [file_or_dir] [file_or_dir] ...
Help:
| # 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 |