"""
EfficientNet for ImageNet-1K, implemented in PyTorch.
Original papers:
- 'EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks,' https://arxiv.org/abs/1905.11946,
- 'Adversarial Examples Improve Image Recognition,' https://arxiv.org/abs/1911.09665.
"""
__all__ = ['EfficientNet', 'calc_tf_padding', 'EffiInvResUnit', 'EffiInitBlock', 'efficientnet_b0', 'efficientnet_b1',
'efficientnet_b2', 'efficientnet_b3', 'efficientnet_b4', 'efficientnet_b5', 'efficientnet_b6',
'efficientnet_b7', 'efficientnet_b8', 'efficientnet_b0b', 'efficientnet_b1b', 'efficientnet_b2b',
'efficientnet_b3b', 'efficientnet_b4b', 'efficientnet_b5b', 'efficientnet_b6b', 'efficientnet_b7b',
'efficientnet_b0c', 'efficientnet_b1c', 'efficientnet_b2c', 'efficientnet_b3c', 'efficientnet_b4c',
'efficientnet_b5c', 'efficientnet_b6c', 'efficientnet_b7c', 'efficientnet_b8c']
import os
import math
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.init as init
from .common import round_channels, conv1x1_block, conv3x3_block, dwconv3x3_block, dwconv5x5_block, SEBlock
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