format

Author: Awni Hannun

benchmarks/python/batch_matmul_bench.py

@@ -2,9 +2,8 @@
 
 import argparse
 
-from time_utils import time_fn
-
 import mlx.core as mx
+from time_utils import time_fn
 
 B = 8
 T = 1024

benchmarks/python/blas/bench_gemm.py

@@ -6,11 +6,10 @@
 import subprocess
 import time
 
+import mlx.core as mx
 import numpy as np
 import torch
 
-import mlx.core as mx
-
 device_name = subprocess.check_output(["sysctl", "-n", "machdep.cpu.brand_string"])
 device_name = device_name.decode("utf-8").strip("\n")
 

benchmarks/python/blas/bench_gemv.py

@@ -6,11 +6,10 @@
 import time
 
 import matplotlib.pyplot as plt
+import mlx.core as mx
 import numpy as np
 import torch
 
-import mlx.core as mx
-
 results_dir = "./results"
 
 if not os.path.isdir(results_dir):

benchmarks/python/compile_bench.py

@@ -4,9 +4,8 @@
 import math
 import random
 
-from time_utils import time_fn
-
 import mlx.core as mx
+from time_utils import time_fn
 
 
 def bench_gelu():

benchmarks/python/conv1d_bench.py

@@ -4,11 +4,10 @@
 import subprocess
 import time
 
+import mlx.core as mx
 import numpy as np
 import torch
 
-import mlx.core as mx
-
 device_name = subprocess.check_output(["sysctl", "-n", "machdep.cpu.brand_string"])
 device_name = device_name.decode("utf-8").strip("\n")
 

benchmarks/python/conv2d_bench_cpu.py

@@ -2,11 +2,10 @@
 import math
 import time
 
+import mlx.core as mx
 import numpy as np
 import torch
 
-import mlx.core as mx
-
 N_warmup = 1
 N_iter_bench = 10
 N_iter_func = 5

benchmarks/python/conv2d_train_bench_cpu.py

@@ -1,10 +1,9 @@
 import time
 
-import torch
-
 import mlx.core as mx
 import mlx.nn
 import mlx.optimizers as opt
+import torch
 
 
 def bench_mlx(steps: int = 20) -> float:

benchmarks/python/conv2d_transpose_bench_cpu.py

@@ -2,11 +2,10 @@
 import math
 import time
 
+import mlx.core as mx
 import numpy as np
 import torch
 
-import mlx.core as mx
-
 N_warmup = 1
 N_iter_bench = 10
 N_iter_func = 5

benchmarks/python/conv3d_bench_cpu.py

@@ -2,11 +2,10 @@
 import math
 import time
 
+import mlx.core as mx
 import numpy as np
 import torch
 
-import mlx.core as mx
-
 N_warmup = 1
 N_iter_bench = 10
 N_iter_func = 5

benchmarks/python/conv3d_train_bench_cpu.py

@@ -1,10 +1,9 @@
 import time
 
-import torch
-
 import mlx.core as mx
 import mlx.nn
 import mlx.optimizers as opt
+import torch
 
 
 def bench_mlx(steps: int = 20, shape=(10, 32, 32, 32, 3)) -> float: