From abcf62ee55ab959b6613437d4ca8b8b9ee50595a Mon Sep 17 00:00:00 2001
From: Awni Hannun <awni@apple.com>
Date: Mon, 16 Jun 2025 12:35:26 -0700
Subject: [PATCH] format

---
 mlx/backend/cuda/device/binary_ops.cuh |  8 +++++---
 mlx/backend/cuda/unary.cu              |  5 ++---
 python/tests/cuda_skip.py              | 10 ----------
 3 files changed, 7 insertions(+), 16 deletions(-)

diff --git a/mlx/backend/cuda/device/binary_ops.cuh b/mlx/backend/cuda/device/binary_ops.cuh
index d847200d4..ca5ac35e6 100644
--- a/mlx/backend/cuda/device/binary_ops.cuh
+++ b/mlx/backend/cuda/device/binary_ops.cuh
@@ -1,7 +1,7 @@
 // Copyright © 2025 Apple Inc.
 
-#include "mlx/backend/cuda/device/fp16_math.cuh"
 #include "mlx/backend/cuda/device/cucomplex_math.cuh"
+#include "mlx/backend/cuda/device/fp16_math.cuh"
 #include "mlx/backend/cuda/device/utils.cuh"
 
 #include <cuComplex.h>
@@ -124,11 +124,13 @@ struct LogAddExp {
         ? maxval
         : T(float(maxval) + log1p(expf(minval - maxval)));
   };
- 
+
   __device__ cuComplex operator()(cuComplex x, cuComplex y) {
     if (isnan(cuCrealf(x)) || isnan(cuCimagf(x)) || isnan(cuCrealf(y)) ||
         isnan(cuCimagf(y))) {
-      return {cuda::std::numeric_limits<float>::quiet_NaN(), cuda::std::numeric_limits<float>::quiet_NaN()};
+      return {
+          cuda::std::numeric_limits<float>::quiet_NaN(),
+          cuda::std::numeric_limits<float>::quiet_NaN()};
     }
     constexpr float inf = cuda::std::numeric_limits<float>::infinity();
     auto maxval = x > y ? x : y;
diff --git a/mlx/backend/cuda/unary.cu b/mlx/backend/cuda/unary.cu
index 83e206ff9..e45144eda 100644
--- a/mlx/backend/cuda/unary.cu
+++ b/mlx/backend/cuda/unary.cu
@@ -27,9 +27,8 @@ constexpr bool supports_unary_op() {
       std::is_same_v<Op, ArcSin> || std::is_same_v<Op, ArcSinh> ||
       std::is_same_v<Op, ArcTan> || std::is_same_v<Op, ArcTanh> ||
       std::is_same_v<Op, Erf> || std::is_same_v<Op, ErfInv> ||
-      std::is_same_v<Op, Expm1> || 
-      std::is_same_v<Op, Sigmoid> || std::is_same_v<Op, Sqrt> ||
-      std::is_same_v<Op, Rsqrt>) {
+      std::is_same_v<Op, Expm1> || std::is_same_v<Op, Sigmoid> ||
+      std::is_same_v<Op, Sqrt> || std::is_same_v<Op, Rsqrt>) {
     return std::is_same_v<In, Out> && is_floating_v<In>;
   }
   if (std::is_same_v<Op, Log> || std::is_same_v<Op, Log2> ||
diff --git a/python/tests/cuda_skip.py b/python/tests/cuda_skip.py
index cd09de0c4..23c5fb19c 100644
--- a/python/tests/cuda_skip.py
+++ b/python/tests/cuda_skip.py
@@ -25,32 +25,25 @@ cuda_skip = {
     "TestReduce.test_expand_sums",
     "TestReduce.test_many_reduction_axes",
     "TestUpsample.test_torch_upsample",
-
     # DivMod NYI
     "TestOps.test_divmod",
     "TestEval.test_multi_output_eval_during_transform",
-
     # Partition NYI
     "TestAutograd.test_topk_grad",
     "TestOps.test_argpartition",
     "TestOps.test_partition",
-
     # Block masked matmul NYI
     "TestBlas.test_block_masked_matmul",
-
     # Gather matmul NYI
     "TestBlas.test_gather_matmul",
     "TestBlas.test_gather_matmul_grad",
-
     # Scan NYI
     "TestAutograd.test_cumprod_grad",
     "TestOps.test_scans",
     "TestOps.test_logcumsumexp",
-
     # Hadamard NYI
     "TestOps.test_hadamard",
     "TestOps.test_hadamard_grad_vmap",
-
     # Convolutions NYI
     "TestConv.test_1d_conv_with_2d",
     "TestConv.test_asymmetric_padding",
@@ -82,7 +75,6 @@ cuda_skip = {
     "TestLayers.test_conv1d",
     "TestLayers.test_conv2d",
     "TestVmap.test_vmap_conv",
-
     # FFTs NYI
     "TestFFT.test_fft",
     "TestFFT.test_fft_big_powers_of_two",
@@ -93,7 +85,6 @@ cuda_skip = {
     "TestFFT.test_fft_large_numbers",
     "TestFFT.test_fft_shared_mem",
     "TestFFT.test_fftn",
-
     # Lapack ops NYI
     "TestLinalg.test_cholesky",
     "TestLinalg.test_cholesky_inv",
@@ -109,7 +100,6 @@ cuda_skip = {
     "TestLinalg.test_svd_decomposition",
     "TestVmap.test_vmap_svd",
     "TestLinalg.test_tri_inverse",
-
     # Quantization NYI
     "TestQuantized.test_gather_matmul_grad",
     "TestQuantized.test_gather_qmm",