fix metal kernel linking issue on cuda

mlx/backend/metal/no_metal.cpp

@@ -3,8 +3,11 @@
 #include <stdexcept>
 
 #include "mlx/backend/metal/metal.h"
+#include "mlx/fast.h"
 
-namespace mlx::core::metal {
+namespace mlx::core {
+
+namespace metal {
 
 bool is_available() {
   return false;
@@ -19,4 +22,21 @@ device_info() {
       "[metal::device_info] Cannot get device info without metal backend");
 };
 
-} // namespace mlx::core::metal
+} // namespace metal
+
+namespace fast {
+
+MetalKernelFunction metal_kernel(
+    const std::string&,
+    const std::vector<std::string>&,
+    const std::vector<std::string>&,
+    const std::string&,
+    const std::string&,
+    bool ensure_row_contiguous,
+    bool atomic_outputs) {
+  throw std::runtime_error("[metal_kernel] No GPU back-end.");
+}
+
+} // namespace fast
+
+} // namespace mlx::core

mlx/backend/no_gpu/primitives.cpp

@@ -2,7 +2,6 @@
 
 #include "mlx/primitives.h"
 #include "mlx/distributed/primitives.h"
-#include "mlx/fast.h"
 #include "mlx/fast_primitives.h"
 
 #define NO_GPU_MULTI(func)                                             \
@@ -156,18 +155,6 @@ NO_GPU_USE_FALLBACK(RoPE)
 NO_GPU(ScaledDotProductAttention)
 NO_GPU_MULTI(AffineQuantize)
 NO_GPU_MULTI(CustomKernel)
-
-MetalKernelFunction metal_kernel(
-    const std::string&,
-    const std::vector<std::string>&,
-    const std::vector<std::string>&,
-    const std::string&,
-    const std::string&,
-    bool ensure_row_contiguous,
-    bool atomic_outputs) {
-  throw std::runtime_error("[metal_kernel] No GPU back-end.");
-}
-
 } // namespace fast
 
 namespace distributed {

python/tests/test_array.py

@@ -198,7 +198,7 @@ class TestInequality(mlx_tests.MLXTestCase):
     def test_dlx_device_type(self):
         a = mx.array([1, 2, 3])
         device_type, device_id = a.__dlpack_device__()
-        self.assertIn(device_type, [1, 8])
+        self.assertIn(device_type, [1, 8, 13])
         self.assertEqual(device_id, 0)
 
         if device_type == 8:

python/tests/test_device.py

@@ -10,7 +10,7 @@ import mlx_tests
 class TestDefaultDevice(unittest.TestCase):
     def test_mlx_default_device(self):
         device = mx.default_device()
-        if mx.metal.is_available():
+        if mx.is_available(mx.gpu):
             self.assertEqual(device, mx.Device(mx.gpu))
             self.assertEqual(str(device), "Device(gpu, 0)")
             self.assertEqual(device, mx.gpu)
@@ -73,7 +73,7 @@ class TestStream(mlx_tests.MLXTestCase):
         self.assertEqual(s2.device, mx.default_device())
         self.assertNotEqual(s1, s2)
 
-        if mx.metal.is_available():
+        if mx.is_available(mx.gpu):
             s_gpu = mx.default_stream(mx.gpu)
             self.assertEqual(s_gpu.device, mx.gpu)
         else:
@@ -86,7 +86,7 @@ class TestStream(mlx_tests.MLXTestCase):
         s_cpu = mx.new_stream(mx.cpu)
         self.assertEqual(s_cpu.device, mx.cpu)
 
-        if mx.metal.is_available():
+        if mx.is_available(mx.gpu):
             s_gpu = mx.new_stream(mx.gpu)
             self.assertEqual(s_gpu.device, mx.gpu)
         else:
@@ -99,7 +99,7 @@ class TestStream(mlx_tests.MLXTestCase):
 
         a = mx.add(x, y, stream=mx.default_stream(mx.default_device()))
 
-        if mx.metal.is_available():
+        if mx.is_available(mx.gpu):
             b = mx.add(x, y, stream=mx.default_stream(mx.gpu))
             self.assertEqual(a.item(), b.item())
             s_gpu = mx.new_stream(mx.gpu)

python/tests/test_optimizers.py

@@ -353,7 +353,7 @@ class TestOptimizers(mlx_tests.MLXTestCase):
         self.assertTrue(mx.allclose(result["w"], mx.full((5, 5), 3.0)))
 
 
-class TestSchedulers(unittest.TestCase):
+class TestSchedulers(mlx_tests.MLXTestCase):
     def test_decay_lr(self):
         for optim_class in optimizers_dict.values():
             lr_schedule = opt.step_decay(1e-1, 0.9, 1)