def __init__(self, name=None):
NeuralModule.__init__(self, name) # For NeuralModule API
# Set module type.
self._type = ModuleType.loss
self._device = get_cuda_device(self.placement)
def __init__(self, pretrained_model_name=None, name=None):
NeuralModule.__init__(self, name) # For NeuralModule API
nn.Module.__init__(self) # For PyTorch API
self._device = get_cuda_device(self.placement)
# Store pretrained model name (to be removed/changed)
self._pretrained_model_name = pretrained_model_name
def __init__(self, pretrained_model_name=None, name=None):
# Initialize nn.Module first - important for the inspect during the init_params collection.
nn.Module.__init__(self) # For PyTorch API
NeuralModule.__init__(self, name) # For NeuralModule API
# Set module type.
self._type = ModuleType.trainable
self._device = get_cuda_device(self.placement)
# Store pretrained model name (to be removed/changed)
self._pretrained_model_name = pretrained_model_name
def __init__(self):
NeuralModule.__init__(self) # For NeuralModule API
self._device = get_cuda_device(self.placement)
# if 'batch_size' not in kwargs:
# logging.warning("No batch_size specified in the data layer. "
# "Setting batch_size to 1.")
# kwargs['batch_size'] = 1
# Set default values of variables used by trained/passed to DataLoader.
# NOTE: That also means that those are parameters of DataLoader/trainer, not DataLayer.
# Thus those fields will be removed from DataLayer and moved to trainer configuration
# (when the time for that will come;))
self._batch_size = 1
self._num_workers = os.cpu_count() # Use all CPUs by default.
self._shuffle = False # Don't shuffle by default.
def __init__(self):
# Neural Module API specific
NeuralModule.__init__(self)
# End of Neural Module API specific
self._criterion = nn.CrossEntropyLoss()
def __init__(self):
NeuralModule.__init__(self)
def __init__(self):
NeuralModule.__init__(self) # For NeuralModule API
self._device = get_cuda_device(self.placement)
def __init__(self, detokenizer=None):
NeuralModule.__init__(self)
self._detokenizer = detokenizer
def __init__(self, ids2classes=None):
NeuralModule.__init__(self)
if ids2classes is None:
ids2classes = {}
self._ids2classes = ids2classes
def __init__(self, detokenizer=None, **kwargs):
NeuralModule.__init__(self, **kwargs)
# self._sp_decoder = self.local_parameters.get("sp_decoder", {})
self._detokenizer = detokenizer
def __init__(self, ids2classes=None, **kwargs):
NeuralModule.__init__(self, **kwargs)
if ids2classes is None:
ids2classes = {}
self._ids2classes = ids2classes
def __init__(self, **kwargs):
# Neural Module API specific
NeuralModule.__init__(self, **kwargs)
def __init__(self):
# Neural Module API specific
NeuralModule.__init__(self)
