b2074ddf9d8bc2069d66976fea58a52f40238496,pretrainedmodels/nasnet.py,,,#,448

Before Change

    model = NasNetLarge()

    input = Variable(torch.randn(2,3,331,331))
    output = model(input)
    print(output.size())

After Change

import torch.nn.functional as F
from torch.autograd import Variable

pretrained_settings = {
    "nasnetalarge": {
        "imagenet": {
            "url": "http://webia.lip6.fr/~cadene/Downloads/nasnetalarge-431029df.pth",
            "input_space": "RGB",
            "input_size": [3, 331, 331],
            "input_range": [0, 1],
            "mean": [0.5, 0.5, 0.5],
            "std": [0.5, 0.5, 0.5],
            "num_classes": 1000
        },
        "imagenet+background": {
            "url": "http://webia.lip6.fr/~cadene/Downloads/nasnetalarge-431029df.pth",
            "input_space": "RGB",
            "input_size": [3, 331, 331],
            "input_range": [0, 1],
            "mean": [0.5, 0.5, 0.5],
            "std": [0.5, 0.5, 0.5],
            "num_classes": 1001
        }
    }
}

class MaxPoolPad(nn.Module):
    
    def __init__(self):

Instances