class_docstr: Change tensor to PyTorch format for images (B x C x H x W).
  
  Parameters
  ----------
  channels_last : bool
      Use torch.channels_last.
  convert_back_int16 : bool
      Convert to float16.
code: def declare_state_and_memory(
      self, previous_state: State
  ) -> Tuple[State, Optional[AllocationQuery]]:
      alloc = None
      H, W, C = previous_state.shape
      new_type = previous_state.dtype
  
      if new_type is ch.int16 and self.convert_int16:
          new_type = ch.float16
          self.enable_int16conv = True
  
      if not self.channels_last:
          alloc = AllocationQuery((C, H, W), dtype=new_type)
      return (
          replace(previous_state, shape=(C, H, W), dtype=new_type),
          alloc,
      )
  
imports: import torch
  import numpy
  from typing import Callable, Optional, Tuple
  from ..pipeline.allocation_query import AllocationQuery
  from ..pipeline.operation import Operation
  from ..pipeline.state import State
  from dataclasses import replace
label_desc: Use image node_id 3 for calling the ToTorchImage obj's underlying member method code with example usage: obj.declare_state_and_memory(previous_state) and returns: replace,  alloc