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add backend inference and inferface output
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# Copyright (c) 2023 Amphion.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch.nn as nn
from abc import abstractmethod
class UNetBlock(nn.Module):
r"""Any module where forward() takes timestep embeddings as a second argument."""
@abstractmethod
def forward(self, x, emb):
r"""Apply the module to `x` given `emb` timestep embeddings."""