def test_get_module_root(self):
"""
When a user runs `allennlp test-install`, we have no idea where
they're running it from, so we do an `os.chdir` to the _module_
root in order to get all the paths in the fixtures to resolve properly.
The logic within `allennlp test-install` is pretty hard to test in
its entirety, so this test is verifies that the `os.chdir` component
works properly by checking that we correctly find the path to
`os.chdir` to.
"""
project_root = _get_module_root()
assert os.path.exists(os.path.join(project_root, "__main__.py"))
params["trainer"]["cuda_device"] = 0
# train this one to a tempdir
tempdir = tempfile.gettempdir()
train_model(params, tempdir)
# now copy back the weights and and archived model
shutil.copy(os.path.join(tempdir, "best.th"),
os.path.join(serialization_dir, "best_gpu.th"))
shutil.copy(os.path.join(tempdir, "model.tar.gz"),
os.path.join(serialization_dir, "model_gpu.tar.gz"))
if __name__ == "__main__":
initial_working_dir = os.getcwd()
module_root = _get_module_root().parent
logger.info("Changing directory to %s", module_root)
os.chdir(module_root)
if len(sys.argv) >= 2 and sys.argv[1].lower() == "gpu":
train_fixture_gpu("allennlp/tests/fixtures/srl/")
else:
models = [
'biaffine_dependency_parser',
'bidaf',
'dialog_qa',
'constituency_parser',
'coref',
'decomposable_attention',
'encoder_decoder/composed_seq2seq',
'encoder_decoder/simple_seq2seq',
'encoder_decoder/copynet_seq2seq',
serialization_dir = config_prefix + 'serialization'
params = Params.from_file(config_file)
params["trainer"]["cuda_device"] = 0
# train this one to a tempdir
tempdir = tempfile.gettempdir()
train_model(params, tempdir)
# now copy back the weights and and archived model
shutil.copy(os.path.join(tempdir, "best.th"), os.path.join(serialization_dir, "best_gpu.th"))
shutil.copy(os.path.join(tempdir, "model.tar.gz"), os.path.join(serialization_dir, "model_gpu.tar.gz"))
if __name__ == "__main__":
initial_working_dir = os.getcwd()
module_root = _get_module_root()
logger.info("Changing directory to %s", module_root)
os.chdir(module_root)
if len(sys.argv) >= 2 and sys.argv[1].lower() == "gpu":
train_fixture_gpu("tests/fixtures/srl/")
else:
models = [
'bidaf',
'constituency_parser',
'coref',
'decomposable_attention',
'encoder_decoder/simple_seq2seq',
'semantic_parsing/nlvr_coverage_semantic_parser',
'semantic_parsing/nlvr_direct_semantic_parser',
'semantic_parsing/wikitables',
'srl',
serialization_dir = config_prefix + 'serialization'
params = Params.from_file(config_file)
params["trainer"]["cuda_device"] = 0
# train this one to a tempdir
tempdir = tempfile.gettempdir()
train_model(params, tempdir)
# now copy back the weights and and archived model
shutil.copy(os.path.join(tempdir, "best.th"), os.path.join(serialization_dir, "best_gpu.th"))
shutil.copy(os.path.join(tempdir, "model.tar.gz"), os.path.join(serialization_dir, "model_gpu.tar.gz"))
if __name__ == "__main__":
initial_working_dir = os.getcwd()
module_root = _get_module_root().parent
logger.info("Changing directory to %s", module_root)
os.chdir(module_root)
if len(sys.argv) >= 2 and sys.argv[1].lower() == "gpu":
train_fixture_gpu("allennlp/tests/fixtures/srl/")
else:
models = [
'biaffine_dependency_parser',
'bidaf',
'dialog_qa',
'constituency_parser',
'coref',
'decomposable_attention',
'encoder_decoder/simple_seq2seq',
'semantic_parsing/nlvr_coverage_semantic_parser',
'semantic_parsing/nlvr_direct_semantic_parser',