class_docstr: Temporal Entropy Model
class_docstr_tok: ["Temporal","Entropy","Model"]
docstr: Embed current patched latent for decoder
  
  The input latent is normalized, embedded in d_model dimension, and
  positional encoding is added.
  Args:
      latent_q_patched: tensor of shape [b', seq_len_dec, C]
  
  Returns:
      tensor of shape [b', seq_len_dec, d_model]
docstr_tok: ["Embed","current","patched","latent","for","decoder","The","input","latent","is","normalized",",","embedded","in","d_model","dimension",",","and","positional","encoding","is","added",".","Args",":","latent_q_patched",":","tensor","of","shape","[","b","'",",","seq_len_dec",",","C","]","Returns",":","tensor","of","shape","[","b","'",",","seq_len_dec",",","d_model","]"]
code: def _embed_latent_q_patched(self, latent_q_patched: Tensor) -> Tensor:
      """Embed current patched latent for decoder
  
      The input latent is normalized, embedded in d_model dimension, and
      positional encoding is added.
      Args:
          latent_q_patched: tensor of shape [b', seq_len_dec, C]
  
      Returns:
          tensor of shape [b', seq_len_dec, d_model]
      """
      latent_q_patched = (
          latent_q_patched / _LATENT_NORM_FAC
      )  # [b', seq_len_dec, C]
      latent_q_patched = self.decoder_embedding(
          latent_q_patched
      )  # [b', seq_len_dec, d_model]
      latent_q_patched = self.post_embedding_layernorm(
          latent_q_patched
      )  # [b', seq_len_dec, d_model]
      return self.dec_position(latent_q_patched)
  
imports: import itertools
  import sys
  from typing import Dict, List, NamedTuple, Optional, Sequence, Tuple
  import torch
  import torch.nn
  from torch import Tensor
  from .bottlenecks import GsnConditionalLocScaleShift
  from .entropy_model_layers import EncoderSection, LearnedPosition, StartSym, Transformer
  from .layers_utils import make_embedding
  from .patcher import Patcher
label_desc: Use image node_id 4 for calling the VCTEntropyModel obj's underlying member method code with example usage: obj._embed_latent_q_patched(latent_q_patched) and returns: self