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There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/tests/py/ts/api/test_classes.py 2026-01-09 01:09:55.737085+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/ts/api/test_classes.py 2026-01-09 01:10:42.996612+00:00
@@ -8,24 +8,26 @@
def is_blackwell():
"""
Check if running on NVIDIA Blackwell architecture (sm_90+).
-
+
Blackwell architecture adds input/output reformat layers in TensorRT engines.
-
+
Returns:
bool: True if running on Blackwell (sm_90+), False otherwise
"""
if not torch.cuda.is_available():
return False
-
+
device_properties = torch.cuda.get_device_properties(0)
compute_capability = device_properties.major * 10 + device_properties.minor
-
+
# Blackwell is sm_90 and above
return compute_capability >= 90
+
+
@unittest.skipIf(
not torchtrt.ENABLED_FEATURES.torchscript_frontend,
"TorchScript Frontend is not available",
)
class TestInput(unittest.TestCase):
@@ -346,16 +348,17 @@
]
}
"""
import json
+
if is_blackwell():
- # blackwell has additional layers-
- #Layer 0: __mye88_myl0_0 ← Input reformat layer
- #Layer 1: aten__matmul(...) fc1 ← First matmul (fc1)
- #Layer 2: aten__matmul(...) fc2 ← Second matmul (fc2)
- #Layer 3: __mye90_myl0_3 ← Output reformat layer
+ # blackwell has additional layers-
+ # Layer 0: __mye88_myl0_0 ← Input reformat layer
+ # Layer 1: aten__matmul(...) fc1 ← First matmul (fc1)
+ # Layer 2: aten__matmul(...) fc2 ← Second matmul (fc2)
+ # Layer 3: __mye90_myl0_3 ← Output reformat layer
num_layers = 4
else:
num_layers = 2
for trt_mod in (
TestTorchTensorRTModule._get_trt_mod(),…refit flag not there
83fe8a2 to
f713c0d
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wenbingl
pushed a commit
to wenbingl/Torch-TRT
that referenced
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Jan 20, 2026
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Addresses two tests
INCLUDE_REFITflag due to old TRT 10.11. SoINCLUDE_REFITflag is not set after refitting and serializing engine. So the below test is disabled