def linear_fst(labels: Union[List[int], List[List[int]]],
aux_labels: Union[List[int], List[List[int]]]) -> Fsa:
'''Construct a linear FST from labels and its corresponding
auxiliary labels.
Note:
The scores of arcs in the returned FST are all 0.
Args:
labels:
A list of integers or a list of list of integers.
aux_labels:
A list of integers or a list of list of integers.
Returns:
An FST if the labels is a list of integers.
A vector of FSTs (FsaVec) if the input is a list of list of integers.
'''
ragged_arc = _k2.linear_fsa(labels)
if isinstance(labels[0], List):
assert isinstance(aux_labels[0],
list), 'aux_labels and labels do not match.'
buf = []
for aux in aux_labels:
buf.extend(aux + [-1])
aux_labels_tmp = torch.tensor(buf, dtype=torch.int32)
else:
aux_labels_tmp = torch.tensor(aux_labels + [-1], dtype=torch.int32)
fsa = Fsa(ragged_arc, aux_labels=aux_labels_tmp)
return fsa
def linear_fsa(labels: Union[List[int], List[List[int]], k2.RaggedTensor],
device: Optional[Union[torch.device, str]] = None) -> Fsa:
'''Construct an linear FSA from labels.
Note:
The scores of arcs in the returned FSA are all 0.
Args:
labels:
It can be one of the following types:
- A list of integers, e.g., `[1, 2, 3]`
- A list of list-of-integers, e..g, `[ [1, 2], [1, 2, 3] ]`
- An instance of :class:`k2.RaggedTensor`.
Must have `num_axes == 2`.
device:
Optional. It can be either a string (e.g., 'cpu', 'cuda:0') or a
torch.device.
If it is ``None``, then the returned FSA is on CPU. It has to be None
if ``labels`` is an instance of :class:`k2.RaggedTensor`.
Returns:
- If ``labels`` is a list of integers, return an FSA
- If ``labels`` is a list of list-of-integers, return an FsaVec
- If ``labels`` is an instance of :class:`k2.RaggedTensor`, return
an FsaVec
'''
if isinstance(labels, k2.RaggedTensor):
assert device is None
ragged_arc = _k2.linear_fsa(labels, device)
fsa = Fsa(ragged_arc)
return fsa
def linear_fsa(labels: Union[List[int], List[List[int]]],
device: Optional[Union[torch.device, str]] = None) -> Fsa:
'''Construct an linear FSA from labels.
Note:
The scores of arcs in the returned FSA are all 0.
Args:
labels:
A list of integers or a list of list of integers.
device:
Optional. It can be either a string (e.g., 'cpu',
'cuda:0') or a torch.device.
If it is None, then the returned FSA is on CPU.
Returns:
An FSA if the labels is a list of integers.
A vector of FSAs (i.e., FsaVec) if the input is a list of list
of integers.
'''
if device is not None:
device = torch.device(device)
if device.type == 'cpu':
gpu_id = -1
else:
assert device.type == 'cuda'
gpu_id = getattr(device, 'index', 0)
else:
gpu_id = -1
ragged_arc = _k2.linear_fsa(labels, gpu_id)
fsa = Fsa(ragged_arc)
return fsa
def linear_fsa(symbols: Union[List[int], List[List[int]]]) -> Fsa:
'''Construct an linear FSA from symbols.
Note:
The scores of arcs in the returned FSA are all 0.
Args:
symbols:
A list of integers or a list of list of integers.
Returns:
An FSA if the input is a list of integers.
A vector of FSAs if the input is a list of list of integers.
'''
ragged_arc = _k2.linear_fsa(symbols)
fsa = Fsa(ragged_arc)
return fsa
def linear_fsa(labels: Union[List[int], List[List[int]], k2.RaggedInt],
device: Optional[Union[torch.device, str]] = None) -> Fsa:
'''Construct an linear FSA from labels.
Note:
The scores of arcs in the returned FSA are all 0.
Args:
labels:
It can be one of the following types:
- A list of integers, e.g., `[1, 2, 3]`
- A list of list-of-integers, e..g, `[ [1, 2], [1, 2, 3] ]`
- An instance of :class:`k2.RaggedInt`. Must have `num_axes() == 2`.
device:
Optional. It can be either a string (e.g., 'cpu',
'cuda:0') or a torch.device.
If it is None, then the returned FSA is on CPU. It has to be None
if `labels` is an instance of :class:`k2.RaggedInt`.
Returns:
- If `labels` is a list of integers, return an FSA
- If `labels` is a list of list-of-integers, return an FsaVec
- If `labels` is an instance of :class:`k2.RaggedInt`, return an FsaVec
'''
if isinstance(labels, k2.RaggedInt):
assert device is None
assert labels.num_axes() == 2
if device is not None:
device = torch.device(device)
if device.type == 'cpu':
gpu_id = -1
else:
assert device.type == 'cuda'
gpu_id = getattr(device, 'index', 0)
else:
gpu_id = -1
ragged_arc = _k2.linear_fsa(labels, gpu_id)
fsa = Fsa(ragged_arc)
return fsa
