def assign_dev_data_single_seq(device, dataset, seq, load_seqs=True):
"""
:type device: Device.Device
:type dataset: Dataset.Dataset
:param int seq: sorted seq idx
:return: whether we succeeded
:rtype: bool
"""
batch = Batch()
batch.init_with_one_full_sequence(seq_idx=seq, dataset=dataset)
success, _ = assign_dev_data(device, dataset, [batch], load_seqs=load_seqs)
return success
def assign_dev_data_single_seq(device, dataset, seq, load_seqs=True): """ :type device: Device.Device :type dataset: Dataset.Dataset :param int seq: sorted seq idx :param bool load_seqs: :return: whether we succeeded :rtype: bool """ batch = Batch() batch.init_with_one_full_sequence(seq_idx=seq, dataset=dataset) success, _ = assign_dev_data(device, dataset, [batch], load_seqs=load_seqs) return success
def forward_single(self, dataset, seq_idx, output_layer_name=None):
"""
Forwards a single sequence.
If you want to perform search, and get a number of hyps out, use :func:`search_single`.
:param Dataset.Dataset dataset:
:param int seq_idx:
:param str|None output_layer_name: e.g. "output". if not set, will read from config "forward_output_layer"
:return: numpy array, output in time major format (time,dim)
:rtype: numpy.ndarray
"""
batch = Batch()
batch.init_with_one_full_sequence(seq_idx=seq_idx, dataset=dataset)
batch_generator = iter([batch])
batches = BatchSetGenerator(dataset, generator=batch_generator)
forwarder = ClassificationTaskThread(self.network, self.devices, dataset, batches)
forwarder.join()
assert forwarder.output.shape[1] == 1
return forwarder.output[:, 0]
def forward_single(self, dataset, seq_idx, output_layer_name=None):
"""
Forwards a single sequence.
If you want to perform search, and get a number of hyps out, use :func:`search_single`.
:param Dataset.Dataset dataset:
:param int seq_idx:
:param str|None output_layer_name: e.g. "output". if not set, will read from config "forward_output_layer"
:return: numpy array, output in time major format (time,dim)
:rtype: numpy.ndarray
"""
from EngineBatch import Batch, BatchSetGenerator
batch = Batch()
batch.init_with_one_full_sequence(seq_idx=seq_idx, dataset=dataset)
batch_generator = iter([batch])
batches = BatchSetGenerator(dataset, generator=batch_generator)
forwarder = ClassificationTaskThread(self.network, self.devices, dataset, batches)
forwarder.join()
assert forwarder.output.shape[1] == 1
return forwarder.output[:, 0]
