class_docstr: EfficientNet model.
     Most easily loaded with the .from_name or .from_pretrained methods.
  
  Args:
      blocks_args (list[namedtuple]): A list of BlockArgs to construct blocks.
      global_params (namedtuple): A set of GlobalParams shared between blocks.
  
  References:
      [1] https://arxiv.org/abs/1905.11946 (EfficientNet)
  
  Example:
      >>> import torch
      >>> from efficientnet.model import EfficientNet
      >>> inputs = torch.rand(1, 3, 224, 224)
      >>> model = EfficientNet.from_pretrained('efficientnet-b0')
      >>> model.eval()
      >>> outputs = model(inputs)
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docstr: Validates model name.
  
  Args:
      model_name (str): Name for efficientnet.
  
  Returns:
      bool: Is a valid name or not.
docstr_tok: ["Validates","model","name",".","Args",":","model_name","(","str",")",":","Name","for","efficientnet",".","Returns",":","bool",":","Is","a","valid","name","or","not","."]
code: def _check_model_name_is_valid(cls, model_name):
      """Validates model name.
  
      Args:
          model_name (str): Name for efficientnet.
  
      Returns:
          bool: Is a valid name or not.
      """
      if model_name not in VALID_MODELS:
          raise ValueError(
              "model_name should be one of: " + ", ".join(VALID_MODELS)
          )
  
imports: import torch
  from torch import nn
  from torch.nn import functional
  from .utils import round_filters, round_repeats, drop_connect, get_same_padding_conv2d, get_model_params, efficientnet_params, load_pretrained_weights, Swish, MemoryEfficientSwish, calculate_output_image_size
label_desc: Use image node_id 9 for calling the EfficientNet obj's underlying member method code with example usage: obj._check_model_name_is_valid(cls, model_name) without return types