class_docstr: ConvTranspose2D decoder generating an image distribution from a vector.
code: def forward(self, x):
      # x is [batch, hor_length, input_size]
      batch_dims = x.shape[:-1]
      model_out = self._model(x)
  
      # Equivalent to making a multivariate diag.
      reshape_size = batch_dims + self.output_shape
      mean = model_out.view(*reshape_size)
      return td.Independent(
          td.Normal(mean, 1.0), len(self.output_shape)
      )
  
file_path: ray/python/ray/rllib/models/torch/modules/convtranspose2d_stack.py
imports: from typing import Tuple
  from ray.rllib.models.torch.misc import Reshape
  from ray.rllib.models.utils import get_activation_fn, get_initializer
  from ray.rllib.utils.framework import try_import_torch
label_desc: Use image node_id 2 for calling the ConvTranspose2DStack obj's underlying member method code with example usage: obj.forward(x) and returns: td