class_docstr: MobiletNet-V3
  
  Based on my EfficientNet implementation and building blocks, this model utilizes the MobileNet-v3 specific
  'efficient head', where global pooling is done before the head convolution without a final batch-norm
  layer before the classifier.
  
  Paper: `Searching for MobileNetV3` - https://arxiv.org/abs/1905.02244
  
  Other architectures utilizing MobileNet-V3 efficient head that are supported by this impl include:
    * HardCoRe-NAS - https://arxiv.org/abs/2102.11646 (defn in hardcorenas.py uses this class)
    * FBNet-V3 - https://arxiv.org/abs/2006.02049
    * LCNet - https://arxiv.org/abs/2109.15099
class_docstr_tok: ["MobiletNet-V3","Based","on","my","EfficientNet","implementation","and","building","blocks",",","this","model","utilizes","the","MobileNet-v3","specific","'efficient","head","'",",","where","global","pooling","is","done","before","the","head","convolution","without","a","final","batch-norm","layer","before","the","classifier",".","Paper",":","`","Searching","for","MobileNetV3","`","-","https",":","\/\/arxiv.org\/abs\/1905.02244","Other","architectures","utilizing","MobileNet-V3","efficient","head","that","are","supported","by","this","impl","include",":","*","HardCoRe-NAS","-","https",":","\/\/arxiv.org\/abs\/2102.11646","(","defn","in","hardcorenas.py","uses","this","class",")","*","FBNet-V3","-","https",":","\/\/arxiv.org\/abs\/2006.02049","*","LCNet","-","https",":","\/\/arxiv.org\/abs\/2109.15099"]
code: def forward_features(self, x: torch.Tensor) -> torch.Tensor:
      x = self.conv_stem(x)
      x = self.bn1(x)
      if self.grad_checkpointing and not torch.jit.is_scripting():
          x = checkpoint_seq(self.blocks, x, flatten=True)
      else:
          x = self.blocks(x)
      return x
  
imports: from functools import partial
  from typing import Callable, List, Optional, Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.utils.checkpoint import checkpoint
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, IMAGENET_INCEPTION_MEAN, IMAGENET_INCEPTION_STD
  from timm.layers import SelectAdaptivePool2d, Linear, LayerType, PadType, create_conv2d, get_norm_act_layer
  from ._builder import build_model_with_cfg, pretrained_cfg_for_features
  from ._efficientnet_blocks import SqueezeExcite
  from ._efficientnet_builder import BlockArgs, EfficientNetBuilder, decode_arch_def, efficientnet_init_weights, round_channels, resolve_bn_args, resolve_act_layer, BN_EPS_TF_DEFAULT
  from ._features import FeatureInfo, FeatureHooks
  from ._manipulate import checkpoint_seq
  from ._registry import generate_default_cfgs, register_model, register_model_deprecations
label_desc: Use image node_id 7 for calling the MobileNetV3 obj's underlying member method code with example usage: obj.forward_features(x) and returns: x