fix complex matmul shape

mlx/backend/cuda/device/binary_ops.cuh

@@ -196,7 +196,7 @@ struct Power {
     } else if constexpr (cuda::std::is_same_v<T, cuComplex>) {
       if (base.y == 0 && base.x == 0) {
         if (isnan(exp.x) || isnan(exp.y)) {
-          auto nan = cuda::std::numeric_limits<T>::quiet_NaN();
+          auto nan = cuda::std::numeric_limits<float>::quiet_NaN();
           return make_cuFloatComplex(nan, nan);
         }
         return make_cuFloatComplex(0.0, 0.0);

mlx/ops.cpp

@@ -2847,21 +2847,6 @@ array matmul(
         "[matmul] Got 0 dimension input. Inputs must "
         "have at least one dimension.");
   }
-  if (a.ndim() == 1) {
-    // Insert a singleton dim in the beginning
-    a = expand_dims(a, 0, s);
-  }
-  if (b.ndim() == 1) {
-    // Insert a singleton dim at the end
-    b = expand_dims(b, 1, s);
-  }
-  if (a.shape(-1) != b.shape(-2)) {
-    std::ostringstream msg;
-    msg << "[matmul] Last dimension of first input with shape " << a.shape()
-        << " must match second to last dimension of"
-        << " second input with shape " << b.shape() << ".";
-    throw std::invalid_argument(msg.str());
-  }
 
   // complex matmul using Karatsuba's Algorithm
   if (a.dtype() == complex64 || b.dtype() == complex64) {
@@ -2883,6 +2868,22 @@ array matmul(
         c_real, multiply(array(complex64_t{0, 1}, complex64), c_imag, s), s);
   }
 
+  if (a.ndim() == 1) {
+    // Insert a singleton dim in the beginning
+    a = expand_dims(a, 0, s);
+  }
+  if (b.ndim() == 1) {
+    // Insert a singleton dim at the end
+    b = expand_dims(b, 1, s);
+  }
+  if (a.shape(-1) != b.shape(-2)) {
+    std::ostringstream msg;
+    msg << "[matmul] Last dimension of first input with shape " << a.shape()
+        << " must match second to last dimension of"
+        << " second input with shape " << b.shape() << ".";
+    throw std::invalid_argument(msg.str());
+  }
+
   // Type promotion
   auto out_type = promote_types(a.dtype(), b.dtype());
 
@@ -4240,6 +4241,16 @@ array addmm(
         "have at least one dimension.");
   }
 
+  // Type promotion
+  auto out_type = result_type(a, b, c);
+
+  if (out_type == complex64) {
+    return add(
+        multiply(matmul(a, b, s), array(alpha), s),
+        multiply(array(beta), c, s),
+        s);
+  }
+
   if (a.ndim() == 1) {
     // Insert a singleton dim in the beginning
     a = expand_dims(a, 0, s);
@@ -4257,16 +4268,6 @@ array addmm(
     throw std::invalid_argument(msg.str());
   }
 
-  // Type promotion
-  auto out_type = result_type(a, b, c);
-
-  if (out_type == complex64) {
-    return add(
-        multiply(matmul(a, b, s), array(alpha), s),
-        multiply(array(beta), c, s),
-        s);
-  }
-
   if (!issubdtype(out_type, floating)) {
     std::ostringstream msg;
     msg << "[addmm] Only real floating point types are supported but "

python/tests/test_blas.py

@@ -1195,6 +1195,16 @@ class TestBlas(mlx_tests.MLXTestCase):
         c_np = np.matmul(np.array(a).T, b)
         self.assertTrue(np.allclose(c, c_np))
 
+        # Check shapes
+        a = mx.random.normal((2, 3)).astype(mx.complex64)
+        b = mx.random.normal((3,))
+        self.assertEqual((a @ b).shape, (2,))
+
+        a = mx.random.normal((2, 3)).astype(mx.complex64)
+        b = mx.random.normal((3,))
+        c = mx.random.normal((2,))
+        self.assertEqual(mx.addmm(c, a, b).shape, (2,))
+
     def test_complex_gemm(self):
         M = 16
         K = 50