def test_htk_lstm_truncated_distributed_gpu(device_id):
params = [ "-n", "3",
"-datadir", an4_dataset_directory(),
"-q", "1",
"-m", "640",
"-e", "1000",
"-device", str(device_id) ]
mpiexec_test(device_id, script_under_test, mpiexec_params, params, 0.76, True)
def test_htk_lstm_truncated_distributed_block_momentum(device_id):
params = [
"-n", "3", "-m", "640", "-e", "1000", "-datadir",
an4_dataset_directory(), "-b", "1600", "-device",
str(device_id)
]
mpiexec_test(device_id, script_under_test, mpiexec_params, params, 0.76,
False, 4)
def test_htk_lstm_truncated_distributed_block_momentum(device_id):
params = [ "-n", "3",
"-m", "640",
"-e", "1000",
"-datadir", an4_dataset_directory(),
"-b", "1600",
"-device", str(device_id) ]
mpiexec_test(device_id, script_under_test, mpiexec_params, params, 0.76, False, 4)
def test_htk_lstm_truncated_distributed_gpu_with_cv(device_id):
# Make sure that full sequence cross validation
# works in the middle of bptt training
params = [ "-n", "2",
"-datadir", an4_dataset_directory(),
"-q", "1",
"-m", "640",
"-e", "1500",
"-cvfreq", "1000",
"-device", str(device_id) ]
output = mpiexec_execute(device_id=device_id, script=script_under_test, mpiexec_params=mpiexec_params, params=params)
results = re.findall(r"Finished Evaluation \[.+?\]: Minibatch\[.+?\]: metric = (.+?)%", output)
assert len(results) == 6, output
def test_checkpointing_with_truncated_sequences(tmpdir):
model_path = os.path.join(tmpdir.strpath, 'Models')
data_path = an4_dataset_directory()
os.chdir(data_path)
features_file = os.path.join(data_path, 'glob_0000.scp')
labels_file = os.path.join(data_path, 'glob_0000.mlf')
label_mapping_file = os.path.join(data_path, 'state.list')
htk_lstm_truncated(features_file, labels_file, label_mapping_file,
minibatch_size=640, epoch_size=1000, max_epochs=2,
model_path=model_path)
htk_lstm_truncated(features_file, labels_file, label_mapping_file,
minibatch_size=640,epoch_size=1000, max_epochs=4,
restore=True, model_path=model_path)
def test_checkpointing_with_truncated_sequences(tmpdir):
model_path = os.path.join(tmpdir.strpath, 'Models')
data_path = an4_dataset_directory()
os.chdir(data_path)
features_file = os.path.join(data_path, 'glob_0000.scp')
labels_file = os.path.join(data_path, 'glob_0000.mlf')
label_mapping_file = os.path.join(data_path, 'state.list')
htk_lstm_truncated(features_file,
labels_file,
label_mapping_file,
minibatch_size=640,
epoch_size=1000,
max_epochs=2,
model_path=model_path)
htk_lstm_truncated(features_file,
labels_file,
label_mapping_file,
minibatch_size=640,
epoch_size=1000,
max_epochs=4,
restore=True,
model_path=model_path)