jcm/metrics.py [56:72]:
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    def __init__(self, files, mode, size=(299, 299), fdir=None):
        self.files = files
        self.fdir = fdir
        self.transforms = torchvision.transforms.ToTensor()
        self.size = size
        self.fn_resize = fid.build_resizer(mode)
        self.custom_image_tranform = lambda x: x

    def __len__(self):
        return len(self.files)

    def __getitem__(self, i):
        img_np = self.files[i]
        # apply a custom image transform before resizing the image to 299x299
        img_np = self.custom_image_tranform(img_np)
        # fn_resize expects a np array and returns a np array
        img_resized = self.fn_resize(img_np)
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jcm/metrics.py [92:108]:
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    def __init__(self, files, mode, size=(299, 299), fdir=None):
        self.files = files
        self.fdir = fdir
        self.transforms = torchvision.transforms.ToTensor()
        self.size = size
        self.fn_resize = fid.build_resizer(mode)
        self.custom_image_tranform = lambda x: x

    def __len__(self):
        return len(self.files)

    def __getitem__(self, i):
        img_np = self.files[i]
        # apply a custom image transform before resizing the image to 299x299
        img_np = self.custom_image_tranform(img_np)
        # fn_resize expects a np array and returns a np array
        img_resized = self.fn_resize(img_np)
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