class_docstr: Decoder with Attention model.
  
  Args:
      n_mels (int): number of mel bins
      n_frames_per_step (int): number of frames processed per step, only 1 is supported
      encoder_embedding_dim (int): the number of embedding dimensions in the encoder.
      decoder_rnn_dim (int): number of units in decoder LSTM
      decoder_max_step (int): maximum number of output mel spectrograms
      decoder_dropout (float): dropout probability for decoder LSTM
      decoder_early_stopping (bool): stop decoding when all samples are finished
      attention_rnn_dim (int): number of units in attention LSTM
      attention_hidden_dim (int): dimension of attention hidden representation
      attention_location_n_filter (int): number of filters for attention model
      attention_location_kernel_size (int): kernel size for attention model
      attention_dropout (float): dropout probability for attention LSTM
      prenet_dim (int): number of ReLU units in prenet layers
      gate_threshold (float): probability threshold for stop token
class_docstr_tok: ["Decoder","with","Attention","model",".","Args",":","n_mels","(","int",")",":","number","of","mel","bins","n_frames_per_step","(","int",")",":","number","of","frames","processed","per","step",",","only","1","is","supported","encoder_embedding_dim","(","int",")",":","the","number","of","embedding","dimensions","in","the","encoder",".","decoder_rnn_dim","(","int",")",":","number","of","units","in","decoder","LSTM","decoder_max_step","(","int",")",":","maximum","number","of","output","mel","spectrograms","decoder_dropout","(","float",")",":","dropout","probability","for","decoder","LSTM","decoder_early_stopping","(","bool",")",":","stop","decoding","when","all","samples","are","finished","attention_rnn_dim","(","int",")",":","number","of","units","in","attention","LSTM","attention_hidden_dim","(","int",")",":","dimension","of","attention","hidden","representation","attention_location_n_filter","(","int",")",":","number","of","filters","for","attention","model","attention_location_kernel_size","(","int",")",":","kernel","size","for","attention","model","attention_dropout","(","float",")",":","dropout","probability","for","attention","LSTM","prenet_dim","(","int",")",":","number","of","ReLU","units","in","prenet","layers","gate_threshold","(","float",")",":","probability","threshold","for","stop","token"]
docstr: Gets all zeros frames to use as the first decoder input
  
  args:
      memory (Tensor): Encoder outputs
          with shape (n_batch, max of ``text_lengths``, ``encoder_embedding_dim``).
  
  returns:
      decoder_input (Tensor): All zeros frames with shape(n_batch, ``n_mels`` * ``n_frame_per_step``).
docstr_tok: ["Gets","all","zeros","frames","to","use","as","the","first","decoder","input","args",":","memory","(","Tensor",")",":","Encoder","outputs","with","shape","(","n_batch",",","max","of","``","text_lengths","``",",","``","encoder_embedding_dim","``",")",".","returns",":","decoder_input","(","Tensor",")",":","All","zeros","frames","with","shape","(","n_batch",",","``","n_mels","``","*","``","n_frame_per_step","``",")","."]
code: def _get_go_frame(self, memory: Tensor) -> Tensor:
      """Gets all zeros frames to use as the first decoder input
  
      args:
          memory (Tensor): Encoder outputs
              with shape (n_batch, max of ``text_lengths``, ``encoder_embedding_dim``).
  
      returns:
          decoder_input (Tensor): All zeros frames with shape(n_batch, ``n_mels`` * ``n_frame_per_step``).
      """
  
      n_batch = memory.size(0)
      dtype = memory.dtype
      device = memory.device
      decoder_input = torch.zeros(
          n_batch,
          self.n_mels * self.n_frames_per_step,
          dtype=dtype,
          device=device,
      )
      return decoder_input
  
imports: import warnings
  from typing import List, Optional, Tuple, Union
  import torch
  from torch import nn, Tensor
  from torch.nn import functional
label_desc: Use image node_id 8 for calling the _Decoder obj's underlying member method code with example usage: obj._get_go_frame(memory) and returns: decoder_input