Python torch.backends.cudnn 模块，RNNDescriptor() 实例源码

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
    )

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
    )

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
    )

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
    )

def init_rnn_descriptor(fn):
    rnn_desc = cudnn.RNNDescriptor()

    rnn_desc.set(
        fn.hidden_size,
        fn.num_layers,
        fn.dropout_desc,
        fn.input_mode,
        fn.bidirectional,
        fn.mode,
        fn.datatype
    )
    return rnn_desc