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# Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import torch
from torch.nn.parameter import Parameter
from ..policy import DSPolicy
from ...model_implementations.diffusers.unet import DSUNet
class UNetPolicy(DSPolicy):
def __init__(self):
super().__init__()
try:
import diffusers
self._orig_layer_class = diffusers.models.unet_2d_condition.UNet2DConditionModel
except AttributeError:
self._orig_layer_class = diffusers.models.unets.unet_2d_condition.UNet2DConditionModel
except ImportError:
self._orig_layer_class = None
def match(self, module):
return isinstance(module, self._orig_layer_class)
def match_replaced(self, module):
return isinstance(module, DSUNet)
def apply(self, module, enable_cuda_graph=True):
# TODO(cmikeh2): Enable cuda graph should be an inference configuration
return DSUNet(module, enable_cuda_graph=enable_cuda_graph)
def attention(self, client_module):
qw = client_module.to_q.weight
kw = client_module.to_k.weight
vw = client_module.to_v.weight
if qw.shape[1] == kw.shape[1]:
qkvw = Parameter(torch.cat((qw, kw, vw), dim=0), requires_grad=False)
return qkvw, \
client_module.to_out[0].weight, \
client_module.to_out[0].bias, \
qw.shape[-1], \
client_module.heads
else:
#return None
#kvw = Parameter(torch.cat((kw, vw), dim=0), requires_grad=False)
return qw, \
kw, vw, \
client_module.to_out[0].weight, \
client_module.to_out[0].bias, \
qw.shape[-1], \
client_module.heads
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