def create_and_check_for_masked_lm(self, config, pixel_values, labels,
pixel_labels):
model = BeitForMaskedImageModeling(config=config)
model.to(torch_device)
model.eval()
result = model(pixel_values)
self.parent.assertEqual(
result.logits.shape,
(self.batch_size, self.seq_length - 1, self.vocab_size))
def create_and_check_for_masked_lm(self, config, pixel_values, labels):
model = BeitForMaskedImageModeling(config=config)
model.to(torch_device)
model.eval()
result = model(pixel_values)
# expected sequence length = num_patches
image_size = to_2tuple(self.image_size)
patch_size = to_2tuple(self.patch_size)
num_patches = (image_size[1] // patch_size[1]) * (image_size[0] // patch_size[0])
self.parent.assertEqual(result.logits.shape, (self.batch_size, num_patches, self.vocab_size))