Align mlx::core::max op nan propagation with NumPy (#2339)

* Make max op NaN propagation rules align with numpy

* Adding benchmarks and testing for max op nanpropagation

* Pre-commit formatting

* Fix max complex64 nan propagation and add test

* Improve the cpp unittest

* Only check nans on non-integral types in simd_reduce_impl.

* Cleanup using namespace alias

* Add cpu Max nanpropagation. Fix a small fib in cpu max dispatch data types for int8/int16.

* Make the max nanpropagation test more meaningful for integer types

* Remove tuple unpacking syntax to comply with earlier python versions. Add cuda skip to nanpropagation tests, fix cuda implementation in a separate PR.

python/tests/cuda_skip.py

@@ -3,6 +3,8 @@ cuda_skip = {
     "TestLayers.test_quantized_embedding",
     "TestOps.test_dynamic_slicing",
     "TestReduce.test_dtypes",
+    "TestReduce.test_nanpropagation",
+    "TestReduce.test_nanpropagation_complex64",
     # Block masked matmul NYI
     "TestBlas.test_block_masked_matmul",
     # Gather matmul NYI