use xfail

Author: a-r-r-o-w

tests/models/test_modeling_common.py

@@ -1366,7 +1366,6 @@ def check_linear_dtype(module, storage_dtype, compute_dtype):
                 if any(re.search(pattern, name) for pattern in patterns_to_check):
                     dtype_to_check = compute_dtype
                 if getattr(submodule, "weight", None) is not None:
-                    print(name, submodule.weight.dtype, dtype_to_check, patterns_to_check)
                     self.assertEqual(submodule.weight.dtype, dtype_to_check)
                 if getattr(submodule, "bias", None) is not None:
                     self.assertEqual(submodule.bias.dtype, dtype_to_check)

tests/models/unets/test_models_unet_1d.py

@@ -15,6 +15,7 @@
 
 import unittest
 
+import pytest
 import torch
 
 from diffusers import UNet1DModel
@@ -152,20 +153,24 @@ def test_unet_1d_maestro(self):
         assert (output_sum - 224.0896).abs() < 0.5
         assert (output_max - 0.0607).abs() < 4e-4
 
-    @unittest.skip(
-        "RuntimeError: 'fill_out' not implemented for 'Float8_e4m3fn'. The error is caused due to certain torch.float8_e4m3fn and torch.float8_e5m2 operations "
-        "not being supported when using deterministic algorithms (which is what the tests run with). To fix:\n"
-        "1. Wait for next PyTorch release: https://github.com/pytorch/pytorch/issues/137160.\n"
-        "2. Unskip this test."
+    @pytest.mark.xfail(
+        reason=(
+            "RuntimeError: 'fill_out' not implemented for 'Float8_e4m3fn'. The error is caused due to certain torch.float8_e4m3fn and torch.float8_e5m2 operations "
+            "not being supported when using deterministic algorithms (which is what the tests run with). To fix:\n"
+            "1. Wait for next PyTorch release: https://github.com/pytorch/pytorch/issues/137160.\n"
+            "2. Unskip this test."
+        ),
     )
     def test_layerwise_casting_inference(self):
-        pass
-
-    @unittest.skip(
-        "RuntimeError: 'fill_out' not implemented for 'Float8_e4m3fn'. The error is caused due to certain torch.float8_e4m3fn and torch.float8_e5m2 operations "
-        "not being supported when using deterministic algorithms (which is what the tests run with). To fix:\n"
-        "1. Wait for next PyTorch release: https://github.com/pytorch/pytorch/issues/137160.\n"
-        "2. Unskip this test."
+        super().test_layerwise_casting_inference()
+
+    @pytest.mark.xfail(
+        reason=(
+            "RuntimeError: 'fill_out' not implemented for 'Float8_e4m3fn'. The error is caused due to certain torch.float8_e4m3fn and torch.float8_e5m2 operations "
+            "not being supported when using deterministic algorithms (which is what the tests run with). To fix:\n"
+            "1. Wait for next PyTorch release: https://github.com/pytorch/pytorch/issues/137160.\n"
+            "2. Unskip this test."
+        ),
     )
     def test_layerwise_casting_memory(self):
         pass
@@ -293,20 +298,24 @@ def test_forward_with_norm_groups(self):
         # Not implemented yet for this UNet
         pass
 
-    @unittest.skip(
-        "RuntimeError: 'fill_out' not implemented for 'Float8_e4m3fn'. The error is caused due to certain torch.float8_e4m3fn and torch.float8_e5m2 operations "
-        "not being supported when using deterministic algorithms (which is what the tests run with). To fix:\n"
-        "1. Wait for next PyTorch release: https://github.com/pytorch/pytorch/issues/137160.\n"
-        "2. Unskip this test."
+    @pytest.mark.xfail(
+        reason=(
+            "RuntimeError: 'fill_out' not implemented for 'Float8_e4m3fn'. The error is caused due to certain torch.float8_e4m3fn and torch.float8_e5m2 operations "
+            "not being supported when using deterministic algorithms (which is what the tests run with). To fix:\n"
+            "1. Wait for next PyTorch release: https://github.com/pytorch/pytorch/issues/137160.\n"
+            "2. Unskip this test."
+        ),
     )
     def test_layerwise_casting_inference(self):
         pass
 
-    @unittest.skip(
-        "RuntimeError: 'fill_out' not implemented for 'Float8_e4m3fn'. The error is caused due to certain torch.float8_e4m3fn and torch.float8_e5m2 operations "
-        "not being supported when using deterministic algorithms (which is what the tests run with). To fix:\n"
-        "1. Wait for next PyTorch release: https://github.com/pytorch/pytorch/issues/137160.\n"
-        "2. Unskip this test."
+    @pytest.mark.xfail(
+        reason=(
+            "RuntimeError: 'fill_out' not implemented for 'Float8_e4m3fn'. The error is caused due to certain torch.float8_e4m3fn and torch.float8_e5m2 operations "
+            "not being supported when using deterministic algorithms (which is what the tests run with). To fix:\n"
+            "1. Wait for next PyTorch release: https://github.com/pytorch/pytorch/issues/137160.\n"
+            "2. Unskip this test."
+        ),
     )
     def test_layerwise_casting_memory(self):
         pass