code: def run_feature_validation(
      state_float_features_dim: int,
      action_float_features_dim: int,
      state_float_features_batch_size: int,
      action_float_features_batch_size: int,
  ) -> None:
      assert (
          state_float_features_dim == 2
      ), f"Expected dimension of state is 2. Got {state_float_features_dim}"
  
      assert (
          action_float_features_dim == state_float_features_dim
      ), "Dimensions of state and action mismatch"
  
      assert (
          state_float_features_batch_size
          == action_float_features_batch_size
      ), "Batch sizes of state and action mismatch"
  
file_path: ReAgent/reagent/models/critic.py
imports: from typing import List
  import torch
  import torch.fx
  from reagent.core import types
  from reagent.models.base import ModelBase
  from reagent.models.fully_connected_network import FullyConnectedNetwork
label_desc: Use image node_id 1 for calling a global function with example usage: run_feature_validation(state_float_features_dim, action_float_features_dim, state_float_features_batch_size, action_float_features_batch_size) without return types