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)