From 0d6791be86b02ac494156ced5ab37cadea37251f Mon Sep 17 00:00:00 2001
From: comfyanonymous <comfyanonymous@protonmail.com>
Date: Tue, 25 Nov 2025 00:57:49 -0500
Subject: [PATCH] Fix tests.

---
 tests-unit/comfy_quant/test_mixed_precision.py | 17 +++++------------
 1 file changed, 5 insertions(+), 12 deletions(-)

diff --git a/tests-unit/comfy_quant/test_mixed_precision.py b/tests-unit/comfy_quant/test_mixed_precision.py
index f8d1fd04e..63361309f 100644
--- a/tests-unit/comfy_quant/test_mixed_precision.py
+++ b/tests-unit/comfy_quant/test_mixed_precision.py
@@ -37,11 +37,8 @@ class TestMixedPrecisionOps(unittest.TestCase):
 
     def test_all_layers_standard(self):
         """Test that model with no quantization works normally"""
-        # Configure no quantization
-        ops.MixedPrecisionOps._layer_quant_config = {}
-
         # Create model
-        model = SimpleModel(operations=ops.MixedPrecisionOps)
+        model = SimpleModel(operations=ops.mixed_precision_ops({}))
 
         # Initialize weights manually
         model.layer1.weight = torch.nn.Parameter(torch.randn(20, 10, dtype=torch.bfloat16))
@@ -76,7 +73,6 @@ class TestMixedPrecisionOps(unittest.TestCase):
                 "params": {}
             }
         }
-        ops.MixedPrecisionOps._layer_quant_config = layer_quant_config
 
         # Create state dict with mixed precision
         fp8_weight1 = torch.randn(20, 10, dtype=torch.float32).to(torch.float8_e4m3fn)
@@ -99,7 +95,7 @@ class TestMixedPrecisionOps(unittest.TestCase):
         }
 
         # Create model and load state dict (strict=False because custom loading pops keys)
-        model = SimpleModel(operations=ops.MixedPrecisionOps)
+        model = SimpleModel(operations=ops.mixed_precision_ops(layer_quant_config))
         model.load_state_dict(state_dict, strict=False)
 
         # Verify weights are wrapped in QuantizedTensor
@@ -132,7 +128,6 @@ class TestMixedPrecisionOps(unittest.TestCase):
                 "params": {}
             }
         }
-        ops.MixedPrecisionOps._layer_quant_config = layer_quant_config
 
         # Create and load model
         fp8_weight = torch.randn(20, 10, dtype=torch.float32).to(torch.float8_e4m3fn)
@@ -146,7 +141,7 @@ class TestMixedPrecisionOps(unittest.TestCase):
             "layer3.bias": torch.randn(40, dtype=torch.bfloat16),
         }
 
-        model = SimpleModel(operations=ops.MixedPrecisionOps)
+        model = SimpleModel(operations=ops.mixed_precision_ops(layer_quant_config))
         model.load_state_dict(state_dict1, strict=False)
 
         # Save state dict
@@ -170,7 +165,6 @@ class TestMixedPrecisionOps(unittest.TestCase):
                 "params": {}
             }
         }
-        ops.MixedPrecisionOps._layer_quant_config = layer_quant_config
 
         # Create and load model
         fp8_weight = torch.randn(20, 10, dtype=torch.float32).to(torch.float8_e4m3fn)
@@ -184,7 +178,7 @@ class TestMixedPrecisionOps(unittest.TestCase):
             "layer3.bias": torch.randn(40, dtype=torch.bfloat16),
         }
 
-        model = SimpleModel(operations=ops.MixedPrecisionOps)
+        model = SimpleModel(operations=ops.mixed_precision_ops(layer_quant_config))
         model.load_state_dict(state_dict, strict=False)
 
         # Add a weight function (simulating LoRA)
@@ -210,7 +204,6 @@ class TestMixedPrecisionOps(unittest.TestCase):
                 "params": {}
             }
         }
-        ops.MixedPrecisionOps._layer_quant_config = layer_quant_config
 
         # Create state dict
         state_dict = {
@@ -223,7 +216,7 @@ class TestMixedPrecisionOps(unittest.TestCase):
         }
 
         # Load should raise KeyError for unknown format in QUANT_FORMAT_MIXINS
-        model = SimpleModel(operations=ops.MixedPrecisionOps)
+        model = SimpleModel(operations=ops.mixed_precision_ops(layer_quant_config))
         with self.assertRaises(KeyError):
             model.load_state_dict(state_dict, strict=False)