tf.raw_ops.CudnnRNNParamsSize

Computes size of weights that can be used by a Cudnn RNN model.

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.raw_ops.CudnnRNNParamsSize

tf.raw_ops.CudnnRNNParamsSize(
    num_layers, num_units, input_size, T, S, rnn_mode='lstm',
    input_mode='linear_input', direction='unidirectional', dropout=0, seed=0,
    seed2=0, num_proj=0, name=None
)

Return the params size that can be used by the Cudnn RNN model. Subsequent weight allocation and initialization should use this size.

num_layers: Specifies the number of layers in the RNN model. num_units: Specifies the size of the hidden state. input_size: Specifies the size of the input state. rnn_mode: Indicates the type of the RNN model. input_mode: Indicate whether there is a linear projection between the input and The actual computation before the first layer. 'skip_input' is only allowed when input_size == num_units; 'auto_select' implies 'skip_input' when input_size == num_units; otherwise, it implies 'linear_input'. direction: Indicates whether a bidirectional model will be used. dir = (direction == bidirectional) ? 2 : 1 dropout: dropout probability. When set to 0., dropout is disabled. seed: the 1st part of a seed to initialize dropout. seed2: the 2nd part of a seed to initialize dropout. params_size: The size of the params buffer that should be allocated and initialized for this RNN model. Note that this params buffer may not be compatible across GPUs. Please use CudnnRNNParamsWeights and CudnnRNNParamsBiases to save and restore them in a way that is compatible across different runs.

Args
num_layers	A Tensor of type int32.
num_units	A Tensor of type int32.
input_size	A Tensor of type int32.
T	A tf.DType from: tf.half, tf.float32, tf.float64.
S	A tf.DType from: tf.int32, tf.int64.
rnn_mode	An optional string from: "rnn_relu", "rnn_tanh", "lstm", "gru". Defaults to "lstm".
input_mode	An optional string from: "linear_input", "skip_input", "auto_select". Defaults to "linear_input".
direction	An optional string from: "unidirectional", "bidirectional". Defaults to "unidirectional".
dropout	An optional float. Defaults to 0.
seed	An optional int. Defaults to 0.
seed2	An optional int. Defaults to 0.
num_proj	An optional int. Defaults to 0.
name	A name for the operation (optional).

Returns
A Tensor of type S.