def forward(self, x, **kw):

B, C, H, W = x.shape

assert H % self.patch_size[0] == 0, f"Input image height ({H}) is not a multiple of patch size ({self.patch_size[0]})."

assert W % self.patch_size[1] == 0, f"Input image width ({W}) is not a multiple of patch size ({self.patch_size[1]})."

x = self.proj(x)

pos = self.position_getter(B, x.size(2), x.size(3), x.device)

if self.flatten:

x = x.flatten(2).transpose(1, 2) # BCHW -> BNC

x = self.norm(x)

""" Handle images with non-square aspect ratio.

All images in the same batch have the same aspect ratio.

true_shape = [(height, width) ...] indicates the actual shape of each image.

"""

def __init__(self, img_size=224, patch_size=16, in_chans=3, embed_dim=768, norm_layer=None, flatten=True):

self.embed_dim = embed_dim

super().__init__(img_size, patch_size, in_chans, embed_dim, norm_layer, flatten)

def forward(self, img, true_shape):

B, C, H, W = img.shape

assert W >= H, f'img should be in landscape mode, but got {W=} {H=}'

assert H % self.patch_size[0] == 0, f"Input image height ({H}) is not a multiple of patch size ({self.patch_size[0]})."

assert W % self.patch_size[1] == 0, f"Input image width ({W}) is not a multiple of patch size ({self.patch_size[1]})."

assert true_shape.shape == (B, 2), f"true_shape has the wrong shape={true_shape.shape}"

# size expressed in tokens

W //= self.patch_size[0]

H //= self.patch_size[1]

n_tokens = H * W

height, width = true_shape.T

is_landscape = (width >= height)

is_portrait = ~is_landscape

# allocate result

x = img.new_zeros((B, n_tokens, self.embed_dim))

pos = img.new_zeros((B, n_tokens, 2), dtype=torch.int64)

# linear projection, transposed if necessary

x[is_landscape] = self.proj(img[is_landscape]).permute(0, 2, 3, 1).flatten(1, 2).float()

x[is_portrait] = self.proj(img[is_portrait].swapaxes(-1, -2)).permute(0, 2, 3, 1).flatten(1, 2).float()

pos[is_landscape] = self.position_getter(1, H, W, pos.device)

pos[is_portrait] = self.position_getter(1, W, H, pos.device)

x = self.norm(x)