我们从Python开源项目中，提取了以下5个代码示例，用于说明如何使用torch.backends.cudnn.DropoutDescriptor()。
def init_dropout_descriptor(fn, handle): dropout_desc = cudnn.DropoutDescriptor() dropout_states_size = ctypes.c_long() check_error(cudnn.lib.cudnnDropoutGetStatesSize( handle, ctypes.byref(dropout_states_size))) dropout_states = torch.cuda.ByteTensor(dropout_states_size.value) dropout_desc.set( handle, fn.dropout, dropout_states, fn.seed ) return dropout_desc
def init_rnn_descriptor(fn, handle): dropout_desc_name = 'desc_' + str(torch.cuda.current_device()) dropout_p = fn.dropout if fn.train else 0 if (dropout_desc_name not in fn.dropout_state) or (fn.dropout_state[dropout_desc_name].get() is None): fn.dropout_state[dropout_desc_name] = Unserializable( cudnn.DropoutDescriptor(handle, dropout_p, fn.dropout_seed) ) dropout_desc = fn.dropout_state[dropout_desc_name].get() dropout_desc.set_dropout(dropout_p, fn.dropout_seed) return cudnn.RNNDescriptor( handle, fn.hidden_size, fn.num_layers, dropout_desc, fn.input_mode, fn.bidirectional, fn.mode, fn.datatype )
