style

Author: Sara Adkins

src/deepsparse/benchmark/data_creation.py

@@ -110,7 +110,10 @@ def generate_random_image_data(
             f"Using default image shape {image_shape}"
         )
 
-    input_data = [numpy.random.randint(0, high=255, size=image_shape).astype(numpy.uint8) for _ in range(batch_size)]
+    input_data = [
+        numpy.random.randint(0, high=255, size=image_shape).astype(numpy.uint8)
+        for _ in range(batch_size)
+    ]
     return input_data
 
 

src/deepsparse/benchmark/helpers.py

@@ -36,6 +36,7 @@
 DEFAULT_STRING_LENGTH = 50
 DEFAULT_IMAGE_SHAPE = (240, 240, 3)
 
+
 class ThreadPinningMode:
     CORE: str = "core"
     NUMA: str = "numa"

tests/test_pipeline_benchmark.py

@@ -129,7 +129,9 @@ def test_generate_random_question_data():
     avg_word_len = 10
     config_args = {"gen_sequence_length": 50}
     config = PipelineBenchmarkConfig(**config_args)
-    question, context = generate_random_question_data(config, 1, avg_word_len=avg_word_len)
+    question, context = generate_random_question_data(
+        config, 1, avg_word_len=avg_word_len
+    )
     assert len(question) == config.gen_sequence_length
     assert len(context) == config.gen_sequence_length
     num_q_spaces = question.count(" ")