class_docstr: An MLPHead that implements floating log stds for Gaussian distributions.
code: def __init__(self, config: FreeLogStdMLPHeadConfig) -> None:
      super().__init__(config)
  
      assert (
          config.output_dims[0] % 2 == 0
      ), "output_dims must be even for free std!"
      self._half_output_dim = config.output_dims[0] // 2
  
      self.net = TorchMLP(
          input_dim=config.input_dims[0],
          hidden_layer_dims=config.hidden_layer_dims,
          hidden_layer_activation=config.hidden_layer_activation,
          hidden_layer_use_layernorm=config.hidden_layer_use_layernorm,
          hidden_layer_use_bias=config.hidden_layer_use_bias,
          hidden_layer_weights_initializer=config.hidden_layer_weights_initializer,
          hidden_layer_weights_initializer_config=(
              config.hidden_layer_weights_initializer_config
          ),
          hidden_layer_bias_initializer=config.hidden_layer_bias_initializer,
          hidden_layer_bias_initializer_config=(
              config.hidden_layer_bias_initializer_config
          ),
          output_dim=self._half_output_dim,
          output_activation=config.output_layer_activation,
          output_use_bias=config.output_layer_use_bias,
          output_weights_initializer=config.output_layer_weights_initializer,
          output_weights_initializer_config=(
              config.output_layer_weights_initializer_config
          ),
          output_bias_initializer=config.output_layer_bias_initializer,
          output_bias_initializer_config=config.output_layer_bias_initializer_config,
      )
  
      self.log_std = torch.nn.Parameter(
          torch.as_tensor([0.0] * self._half_output_dim)
      )
  
imports: import functools
  from typing import Optional
  import numpy
  from ray.rllib.core.models.base import Model
  from ray.rllib.core.models.configs import CNNTransposeHeadConfig, FreeLogStdMLPHeadConfig, MLPHeadConfig
  from ray.rllib.core.models.specs.checker import SpecCheckingError
  from ray.rllib.core.models.specs.specs_base import Spec
  from ray.rllib.core.models.specs.specs_base import TensorSpec
  from ray.rllib.core.models.torch.base import TorchModel
  from ray.rllib.core.models.torch.primitives import TorchCNNTranspose, TorchMLP
  from ray.rllib.models.utils import get_initializer_fn
  from ray.rllib.utils.annotations import override
  from ray.rllib.utils.framework import try_import_torch
label_desc: Use image node_id 1 to create a new TorchFreeLogStdMLPHead object from inherited base classes: TorchModel with example: obj = TorchFreeLogStdMLPHead(config)