class_docstr: Reference Quantized GRU Module
  We'll store weight_qparams for all the weights in _flat_weights, we need to pass in
  a `weight_qparams_dict` that maps from weight name, e.g. weight_ih_l0,
  to the weight_qparams for that weight
class_docstr_tok: ["Reference","Quantized","GRU","Module","We","'ll","store","weight_qparams","for","all","the","weights","in","_flat_weights",",","we","need","to","pass","in","a","`","weight_qparams_dict","`","that","maps","from","weight","name",",","e.g",".","weight_ih_l0",",","to","the","weight_qparams","for","that","weight"]
code: def __init__(self, *args, **kwargs):
      if "proj_size" in kwargs:
          raise ValueError(
              "proj_size argument is only supported for LSTM, not RNN or GRU"
          )
      super().__init__("GRU", *args, **kwargs)
  
imports: import torch
  import torch.nn
  from torch import Tensor
  from .utils import _quantize_and_dequantize_weight
  from .utils import _quantize_weight
  from typing import Optional, Dict, Any, Tuple
  from torch import _VF
  from torch.nn.utils.rnn import PackedSequence
label_desc: Use image node_id 1 to create a new GRU object from inherited base classes: RNNBase with example: obj = GRU()