class_docstr: PyTorchVideo/accelerator provides a set of efficient blocks
  that have optimal efficiency for each target hardware device.
  
  Each efficient block has two forms:
  - original form: this form is for training. When efficient block is instantiated,
      it is in this original form.
  - deployable form: this form is for deployment. Once the network is ready for
      deploy, it can be converted into deployable form for efficient execution
      on target hardware. One block is transformed into deployable form by calling
      convert() method. By conversion to deployable form,
      various optimization (operator fuse, kernel optimization, etc.) are applied.
  
  EfficientBlockBase is the base class for efficient blocks.
  All efficient blocks should inherit this base class
  and implement following methods:
  - forward(): same as required by nn.Module
  - convert(): called to convert block into deployable form
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code: def forward(self):
      pass
  
imports: from abc import abstractmethod
  import torch.nn
label_desc: Use image node_id 2 for calling the EfficientBlockBase obj's underlying member method code with example usage: obj.forward() without return types