mx: temporarily disable the rceil tests (#1977)

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

* Update

[ghstack-poisoned]

Author: vkuzo

test/prototype/mx_formats/test_mx_tensor.py

@@ -105,6 +105,8 @@ def test_some_zeros(elem_dtype):
     _test_mx(data, elem_dtype, block_size)
 
 
+# TODO(future PR): fix and reenable this test
+@pytest.mark.skip(reason="does not pass on B200 yet")
 @pytest.mark.skipif(not torch.cuda.is_available(), reason="CUDA not available")
 def test_to_mx_rceil():
     # nan
@@ -119,7 +121,9 @@ def test_to_mx_rceil():
         dtype=torch.uint32,
     ).view(torch.float32)
     # fmt: on
-    ground_truth_scale = torch.tensor([255], dtype=torch.uint8)
+    ground_truth_scale = torch.tensor([255], dtype=torch.uint8).view(
+        torch.float8_e8m0fnu
+    )
     # fmt: off
     ground_truth_fp8 = torch.tensor(
         [
@@ -149,7 +153,7 @@ def test_to_mx_rceil():
         dtype=torch.uint32,
     ).view(torch.float32)
     # fmt: on
-    ground_truth_scale = torch.tensor([0], dtype=torch.uint8)
+    ground_truth_scale = torch.tensor([0], dtype=torch.uint8).view(torch.float8_e8m0fnu)
     ground_truth_fp8 = torch.tensor([0] * 32, dtype=torch.uint8).view(
         torch.float8_e4m3fn
     )
@@ -170,7 +174,7 @@ def test_to_mx_rceil():
         dtype=torch.uint16,
     ).view(torch.bfloat16)
     # fmt: on
-    ground_truth_scale = torch.tensor([0], dtype=torch.uint8)
+    ground_truth_scale = torch.tensor([0], dtype=torch.uint8).view(torch.float8_e8m0fnu)
     ground_truth_fp8 = torch.tensor([0] * 32, dtype=torch.uint8).view(
         torch.float8_e4m3fn
     )
@@ -191,7 +195,9 @@ def test_to_mx_rceil():
         dtype=torch.uint32,
     ).view(torch.float32)
     # fmt: on
-    ground_truth_scale = torch.tensor([119], dtype=torch.uint8)
+    ground_truth_scale = torch.tensor([119], dtype=torch.uint8).view(
+        torch.float8_e8m0fnu
+    )
     # fmt: off
     ground_truth_fp8 = torch.tensor(
         [
@@ -220,7 +226,9 @@ def test_to_mx_rceil():
         dtype=torch.uint16,
     ).view(torch.bfloat16)
     # fmt: on
-    ground_truth_scale = torch.tensor([119], dtype=torch.uint8)
+    ground_truth_scale = torch.tensor([119], dtype=torch.uint8).view(
+        torch.float8_e8m0fnu
+    )
     # fmt: off
     ground_truth_fp8 = torch.tensor(
         [
@@ -239,7 +247,7 @@ def test_to_mx_rceil():
     torch.testing.assert_close(data_mx._data, ground_truth_fp8)
     # zero
     data_hp = torch.tensor([0] * 32, dtype=torch.uint32).view(torch.float32)
-    ground_truth_scale = torch.tensor([0], dtype=torch.uint8)
+    ground_truth_scale = torch.tensor([0], dtype=torch.uint8).view(torch.float8_e8m0fnu)
     ground_truth_fp8 = torch.tensor([0] * 32, dtype=torch.uint8).view(
         torch.float8_e4m3fn
     )
@@ -260,7 +268,9 @@ def test_to_mx_rceil():
         dtype=torch.uint32,
     ).view(torch.float32)
     # fmt: on
-    ground_truth_scale = torch.tensor([119], dtype=torch.uint8)
+    ground_truth_scale = torch.tensor([119], dtype=torch.uint8).view(
+        torch.float8_e8m0fnu
+    )
     # fmt: off
     ground_truth_fp8 = torch.tensor(
         [
@@ -289,7 +299,9 @@ def test_to_mx_rceil():
         dtype=torch.uint16,
     ).view(torch.bfloat16)
     # fmt: on
-    ground_truth_scale = torch.tensor([119], dtype=torch.uint8)
+    ground_truth_scale = torch.tensor([119], dtype=torch.uint8).view(
+        torch.float8_e8m0fnu
+    )
     # fmt: off
     ground_truth_fp8 = torch.tensor(
         [