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Add optimization --cuda-stream

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See also the readme for more details
This commit is contained in:
lllyasviel
2024-02-24 14:00:48 -08:00
committed by GitHub
parent 0f09d98814
commit 434ca2169f
9 changed files with 63 additions and 73 deletions
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6
ldm_patched/modules/controlnet.py
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@@ -14,7 +14,7 @@ import ldm_patched.modules.ops
import ldm_patched.controlnet.cldm
import ldm_patched.t2ia.adapter
from ldm_patched.modules.ops import main_thread_worker
from ldm_patched.modules.ops import main_stream_worker
def broadcast_image_to(tensor, target_batch_size, batched_number):
@@ -306,7 +306,7 @@ class ControlLoraOps:
def forward(self, input):
weight, bias, signal = ldm_patched.modules.ops.cast_bias_weight(self, input)
with main_thread_worker(weight, bias, signal):
with main_stream_worker(weight, bias, signal):
if self.up is not None:
return torch.nn.functional.linear(input, weight + (torch.mm(self.up.flatten(start_dim=1), self.down.flatten(start_dim=1))).reshape(self.weight.shape).type(input.dtype), bias)
else:
@@ -347,7 +347,7 @@ class ControlLoraOps:
def forward(self, input):
weight, bias, signal = ldm_patched.modules.ops.cast_bias_weight(self, input)
with main_thread_worker(weight, bias, signal):
with main_stream_worker(weight, bias, signal):
if self.up is not None:
return torch.nn.functional.conv2d(input, weight + (torch.mm(self.up.flatten(start_dim=1), self.down.flatten(start_dim=1))).reshape(self.weight.shape).type(input.dtype), bias, self.stride, self.padding, self.dilation, self.groups)
else: