Replace multiple variables with one variable. (#5715)

* I added a new doc string to the class. This is more flexible to understanding other developers what are doing and where it's using.

* Update src/diffusers/models/unet_2d_blocks.py

This changes suggest by maintener.
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update src/diffusers/models/unet_2d_blocks.py

Add suggested text
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update unet_2d_blocks.py

I changed the Parameter to Args text.

* Update unet_2d_blocks.py

proper indentation set in this file.

* Update unet_2d_blocks.py

a little bit of change in the act_fun argument line.

* I run the black command to reformat style in the code

* Update unet_2d_blocks.py

similar doc-string add to have in the original diffusion repository.

* I enhanced the code by replacing multiple redundant variables with a single variable, as they all served the same purpose. Additionally, I utilized the get_activation function for improved flexibility in choosing activation functions.

* Using as black package to reformated my file

* reverte some changes

* Remove conv_out_padding variables and using as conv_in_padding

* conv_out_padding create and add them into the code.

* run black command to solving styling problem

* add little bit space between comment and import statement

* I am utilizing the ruff library to address the style issues in my Makefile.

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

src/diffusers/models/unet_3d_condition.py

@@ -12,6 +12,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+
 from dataclasses import dataclass
 from typing import Any, Dict, List, Optional, Tuple, Union
 
@@ -22,6 +23,7 @@ import torch.utils.checkpoint
 from ..configuration_utils import ConfigMixin, register_to_config
 from ..loaders import UNet2DConditionLoadersMixin
 from ..utils import BaseOutput, logging
+from .activations import get_activation
 from .attention_processor import (
     ADDED_KV_ATTENTION_PROCESSORS,
     CROSS_ATTENTION_PROCESSORS,
@@ -271,7 +273,7 @@ class UNet3DConditionModel(ModelMixin, ConfigMixin, UNet2DConditionLoadersMixin)
             self.conv_norm_out = nn.GroupNorm(
                 num_channels=block_out_channels[0], num_groups=norm_num_groups, eps=norm_eps
             )
-            self.conv_act = nn.SiLU()
+            self.conv_act = get_activation("silu")
         else:
             self.conv_norm_out = None
             self.conv_act = None