class_docstr: Temporal Entropy Model
class_docstr_tok: ["Temporal","Entropy","Model"]
docstr: TODO implement JIT version of the transformer forward pass
      (mean, scale, dec_output = self._get_transformer_output(...))
  
  Args:
      encoded_patched: what we condition on, tensor of shape
          [b', context_len*seq_len_enc, d_model]
      latent_q_patched: tensor of shape [b', seq_len_dec, C]
  
  Returns:
      runs the transformer and returns mean, scale and decoder_output
docstr_tok: ["TODO","implement","JIT","version","of","the","transformer","forward","pass","(","mean",",","scale",",","dec_output","=","self._get_transformer_output","(","...",")",")","Args",":","encoded_patched",":","what","we","condition","on",",","tensor","of","shape","[","b","'",",","context_len","*","seq_len_enc",",","d_model","]","latent_q_patched",":","tensor","of","shape","[","b","'",",","seq_len_dec",",","C","]","Returns",":","runs","the","transformer","and","returns","mean",",","scale","and","decoder_output"]
code: def _get_mean_scale_jitted(
      self, *, encoded_patched: Tensor, latent_q_patched: Tensor
  ):
      """
      TODO implement JIT version of the transformer forward pass
          (mean, scale, dec_output = self._get_transformer_output(...))
  
      Args:
          encoded_patched: what we condition on, tensor of shape
              [b', context_len*seq_len_enc, d_model]
          latent_q_patched: tensor of shape [b', seq_len_dec, C]
  
      Returns:
          runs the transformer and returns mean, scale and decoder_output
      """
      raise NotImplementedError("JIT not supported yet.")
  
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 8 for calling the VCTEntropyModel obj's underlying member method code with example usage: obj._get_mean_scale_jitted() without return types