class_docstr: This module produces sinusoidal positional embeddings of any length.
  
  Padding symbols are ignored.
class_docstr_tok: ["This","module","produces","sinusoidal","positional","embeddings","of","any","length",".","Padding","symbols","are","ignored","."]
code: def _load_from_state_dict(self, state_dict, prefix, *args, **kwargs):
      # Ignore some deprecated keys that were used in older versions
      deprecated_keys = ["weights", "_float_tensor"]
      for key in deprecated_keys:
          if prefix + key in state_dict:
              del state_dict[prefix + key]
      super()._load_from_state_dict(state_dict, prefix, *args, **kwargs)
  
file_path: fairseq/fairseq/modules/sinusoidal_positional_embedding.py
imports: import math
  from typing import Any, Optional
  import torch
  import torch.onnx.operators
  from fairseq import utils
  from torch import nn, Tensor
label_desc: Use image node_id 3 for calling the SinusoidalPositionalEmbedding obj's underlying member method code with example usage: obj._load_from_state_dict(state_dict, prefix) without return types