Add mx.finfo and use it when making causal mask (#1726)

* finfo

* fixes

* docs

python/mlx/nn/layers/transformer.py

@@ -102,9 +102,7 @@ class MultiHeadAttention(Module):
     def create_additive_causal_mask(N: int, dtype: mx.Dtype = mx.float32):
         indices = mx.arange(N)
         mask = indices[:, None] < indices[None]
-        # usually inf but 1e9 is as good and softmax(full(1e9)) != nan
-        # TODO: Should replace this with finfo(dtype).min
-        mask = mask.astype(dtype) * -1e9
+        mask = mask.astype(dtype) * mx.finfo(dtype).min
         return mask
 
 

python/src/array.cpp

@@ -179,6 +179,31 @@ void init_array(nb::module_& m) {
       .value("number", mx::number)
       .value("generic", mx::generic)
       .export_values();
+
+  nb::class_<mx::finfo>(
+      m,
+      "finfo",
+      R"pbdoc(
+      Get information on floating-point types.
+      )pbdoc")
+      .def(nb::init<mx::Dtype>())
+      .def_ro(
+          "min",
+          &mx::finfo::min,
+          R"pbdoc(The smallest representable number.)pbdoc")
+      .def_ro(
+          "max",
+          &mx::finfo::max,
+          R"pbdoc(The largest representable number.)pbdoc")
+      .def_ro("dtype", &mx::finfo::dtype, R"pbdoc(The :obj:`Dtype`.)pbdoc")
+      .def("__repr__", [](const mx::finfo& f) {
+        std::ostringstream os;
+        os << "finfo("
+           << "min=" << f.min << ", max=" << f.max << ", dtype=" << f.dtype
+           << ")";
+        return os.str();
+      });
+
   nb::class_<ArrayAt>(
       m,
       "ArrayAt",

python/tests/test_array.py

@@ -97,6 +97,18 @@ class TestDtypes(mlx_tests.MLXTestCase):
                 self.assertListEqual(list(z.shape), list(x.shape))
                 self.assertListEqual(list(z.shape), list(y.shape))
 
+    def test_finfo(self):
+        with self.assertRaises(ValueError):
+            mx.finfo(mx.int32)
+
+        self.assertEqual(mx.finfo(mx.float32).min, np.finfo(np.float32).min)
+        self.assertEqual(mx.finfo(mx.float32).max, np.finfo(np.float32).max)
+        self.assertEqual(mx.finfo(mx.float32).dtype, mx.float32)
+
+        self.assertEqual(mx.finfo(mx.float16).min, np.finfo(np.float16).min)
+        self.assertEqual(mx.finfo(mx.float16).max, np.finfo(np.float16).max)
+        self.assertEqual(mx.finfo(mx.float16).dtype, mx.float16)
+
 
 class TestEquality(mlx_tests.MLXTestCase):
     def test_array_eq_array(self):

python/tests/test_nn.py

@@ -1826,6 +1826,15 @@ class TestLayers(mlx_tests.MLXTestCase):
 
         self.assertGreater(cosine(y, yq).min(), 0.99)
 
+    def test_causal_mask(self):
+        mask = nn.MultiHeadAttention.create_additive_causal_mask(4, mx.float16)
+        self.assertFalse(mx.any(mx.isnan(mask)))
+        self.assertTrue(mask[0, -1].item() < 0)
+
+        mask = nn.MultiHeadAttention.create_additive_causal_mask(4, mx.bfloat16)
+        self.assertFalse(mx.any(mx.isnan(mask)))
+        self.assertTrue(mask[0, -1].item() < 0)
+
 
 if __name__ == "__main__":
     unittest.main()