Apply isort and black reformatting

Signed-off-by: tomlifu <[email protected]>

nemo/collections/diffusion/models/flux/model.py

@@ -12,13 +12,12 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import math
+import os
 from dataclasses import dataclass
 from pathlib import Path
 from typing import Callable, Optional
 
-import os
-import math
-
 import lightning.pytorch as L
 import numpy as np
 import torch
@@ -45,7 +44,11 @@
 )
 from nemo.collections.diffusion.models.flux.layers import EmbedND, MLPEmbedder, TimeStepEmbedder
 from nemo.collections.diffusion.sampler.flow_matching.flow_match_euler_discrete import FlowMatchEulerDiscreteScheduler
-from nemo.collections.diffusion.utils.flux_ckpt_converter import _import_qkv, _import_qkv_bias, flux_transformer_converter
+from nemo.collections.diffusion.utils.flux_ckpt_converter import (
+    _import_qkv,
+    _import_qkv_bias,
+    flux_transformer_converter,
+)
 from nemo.collections.diffusion.vae.autoencoder import AutoEncoder, AutoEncoderConfig
 from nemo.collections.llm import fn
 from nemo.lightning import io, teardown

nemo/collections/diffusion/models/flux_controlnet/model.py

@@ -190,7 +190,8 @@ def __init__(self, config: FluxControlNetConfig):
 
         if config.conditioning_embedding_channels is not None:
             self.input_hint_block = ControlNetConditioningEmbedding(
-                conditioning_embedding_channels=config.conditioning_embedding_channels, block_out_channels=(16, 16, 16, 16)
+                conditioning_embedding_channels=config.conditioning_embedding_channels,
+                block_out_channels=(16, 16, 16, 16),
             )
             self.controlnet_x_embedder = torch.nn.Linear(config.in_channels, self.hidden_size)
         else: