From 793713ca760a1c626cb4529a63b7d5253f43f526 Mon Sep 17 00:00:00 2001
From: dilip patlolla <dilipreddi@gmail.com>
Date: Thu, 19 Dec 2024 12:41:03 -0800
Subject: [PATCH] fix lint

---
 .../micro_benchmarks/_export_torch_to_onnx.py | 54 ++++++++++---------
 1 file changed, 30 insertions(+), 24 deletions(-)

diff --git a/superbench/benchmarks/micro_benchmarks/_export_torch_to_onnx.py b/superbench/benchmarks/micro_benchmarks/_export_torch_to_onnx.py
index 00bd58fe9..9cc2dd65f 100644
--- a/superbench/benchmarks/micro_benchmarks/_export_torch_to_onnx.py
+++ b/superbench/benchmarks/micro_benchmarks/_export_torch_to_onnx.py
@@ -24,8 +24,10 @@
     from transformers import MixtralConfig
     from superbench.benchmarks.model_benchmarks.pytorch_mixtral import MixtralBenchmarkModel
 
+
 class torch2onnxExporter():
     """PyTorch model to ONNX exporter."""
+
     def __init__(self):
         """Constructor."""
         self.num_classes = 100
@@ -132,32 +134,36 @@ def __init__(self):
 
         # Only include Mixtral models if MixtralBenchmarkModel is available
         if MixtralBenchmarkModel is not None:
-            self.benchmark_models.update({
-                'mixtral-8x7b': lambda: MixtralBenchmarkModel(
-                    MixtralConfig(
-                        hidden_size=4096,
-                        num_hidden_layers=32,
-                        num_attention_heads=32,
-                        num_key_value_heads=8,
-                        intermediate_size=14336,
-                        max_position_embeddings=32768,
-                        router_aux_loss_coef=0.02,
+            self.benchmark_models.update(
+                {
+                    'mixtral-8x7b':
+                    lambda: MixtralBenchmarkModel(
+                        MixtralConfig(
+                            hidden_size=4096,
+                            num_hidden_layers=32,
+                            num_attention_heads=32,
+                            num_key_value_heads=8,
+                            intermediate_size=14336,
+                            max_position_embeddings=32768,
+                            router_aux_loss_coef=0.02,
+                        ),
+                        self.num_classes,
                     ),
-                    self.num_classes,
-                ),
-                'mixtral-8x22b': lambda: MixtralBenchmarkModel(
-                    MixtralConfig(
-                        hidden_size=6144,
-                        num_hidden_layers=56,
-                        num_attention_heads=48,
-                        num_key_value_heads=8,
-                        intermediate_size=16384,
-                        max_position_embeddings=65536,
-                        router_aux_loss_coef=0.001,
+                    'mixtral-8x22b':
+                    lambda: MixtralBenchmarkModel(
+                        MixtralConfig(
+                            hidden_size=6144,
+                            num_hidden_layers=56,
+                            num_attention_heads=48,
+                            num_key_value_heads=8,
+                            intermediate_size=16384,
+                            max_position_embeddings=65536,
+                            router_aux_loss_coef=0.001,
+                        ),
+                        self.num_classes,
                     ),
-                    self.num_classes,
-                ),
-            })
+                }
+            )
 
         self._onnx_model_path = Path(torch.hub.get_dir()) / 'onnx'
         self._onnx_model_path.mkdir(parents=True, exist_ok=True)