thor none_zero is fixed in trt 14, reenable_back #3928
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There was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_export_serde.py 2025-11-23 04:44:15.040051+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_export_serde.py 2025-11-23 04:44:58.015912+00:00
@@ -15,10 +15,11 @@
assertions = unittest.TestCase()
if importlib.util.find_spec("torchvision"):
import torchvision.models as models
+
@pytest.mark.unit
@pytest.mark.critical
def test_base_full_compile(ir):
"""
This tests export serde functionality on a base model
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_export_kwargs_serde.py 2025-11-23 04:44:15.040051+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_export_kwargs_serde.py 2025-11-23 04:44:58.214570+00:00
@@ -299,11 +299,13 @@
assertions.assertTrue(
cos_sim > COSINE_THRESHOLD,
msg=f"CustomKwargs Module TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
)
# Save the module
- tmp_dir = tempfile.mkdtemp(prefix="test_custom_model_with_dynamo_trace_kwarg_dynamic")
+ tmp_dir = tempfile.mkdtemp(
+ prefix="test_custom_model_with_dynamo_trace_kwarg_dynamic"
+ )
trt_ep_path = os.path.join(tmp_dir, "compiled.ep")
torchtrt.save(trt_gm, trt_ep_path, retrace=False)
# Clean up model env
torch._dynamo.reset()
@@ -390,11 +392,13 @@
assertions.assertTrue(
cos_sim > COSINE_THRESHOLD,
msg=f"CustomKwargs Module TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
)
# Save the module
- tmp_dir = tempfile.mkdtemp(prefix="test_custom_model_with_dynamo_trace_kwarg_dynamic")
+ tmp_dir = tempfile.mkdtemp(
+ prefix="test_custom_model_with_dynamo_trace_kwarg_dynamic"
+ )
trt_ep_path = os.path.join(tmp_dir, "compiled.ep")
torchtrt.save(trt_gm, trt_ep_path, retrace=False)
# Clean up model env
torch._dynamo.reset()
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_model_refit.py 2025-11-23 04:44:15.040051+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_model_refit.py 2025-11-23 04:44:58.911484+00:00
@@ -530,11 +530,13 @@
not torch_trt.ENABLED_FEATURES.refit,
"Refit feature is not supported in Python 3.13 or higher",
)
@pytest.mark.unit
def test_refit_one_engine_inline_runtime_with_weightmap():
- tmp_dir = tempfile.mkdtemp(prefix="test_refit_one_engine_inline_runtime_with_weightmap")
+ tmp_dir = tempfile.mkdtemp(
+ prefix="test_refit_one_engine_inline_runtime_with_weightmap"
+ )
trt_ep_path = os.path.join(tmp_dir, "compiled.ep")
model = models.resnet18(pretrained=False).eval().to("cuda")
model2 = models.resnet18(pretrained=True).eval().to("cuda")
inputs = [torch.randn((1, 3, 224, 224)).to("cuda")]
enabled_precisions = {torch.float}
@@ -888,11 +890,13 @@
not torch_trt.ENABLED_FEATURES.refit,
"Refit feature is not supported in Python 3.13 or higher",
)
@pytest.mark.unit
def test_refit_one_engine_inline_runtime_without_weightmap():
- tmp_dir = tempfile.mkdtemp(prefix="test_refit_one_engine_inline_runtime_without_weightmap")
+ tmp_dir = tempfile.mkdtemp(
+ prefix="test_refit_one_engine_inline_runtime_without_weightmap"
+ )
trt_ep_path = os.path.join(tmp_dir, "compiled.ep")
model = models.resnet18(pretrained=True).eval().to("cuda")
model2 = models.resnet18(pretrained=False).eval().to("cuda")
inputs = [torch.randn((1, 3, 224, 224)).to("cuda")]
enabled_precisions = {torch.float}
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_reexport.py 2025-11-23 04:44:15.040051+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_reexport.py 2025-11-23 04:44:59.288504+00:00
@@ -158,10 +158,11 @@
def forward(self, x):
conv = self.conv(x)
conv = conv * 0.5
relu = self.relu(conv)
return conv, relu
+
tmp_dir = tempfile.mkdtemp(prefix="test_no_compile")
trt_ep_path = os.path.join(tmp_dir, "trt.ep")
model = MyModule().eval().cuda()
input = torch.randn((1, 3, 224, 224)).to("cuda")
There was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_export_kwargs_serde.py 2025-11-23 04:46:35.093132+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_export_kwargs_serde.py 2025-11-23 04:47:21.201660+00:00
@@ -299,11 +299,13 @@
assertions.assertTrue(
cos_sim > COSINE_THRESHOLD,
msg=f"CustomKwargs Module TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
)
# Save the module
- tmp_dir = tempfile.mkdtemp(prefix="test_custom_model_with_dynamo_trace_kwarg_dynamic")
+ tmp_dir = tempfile.mkdtemp(
+ prefix="test_custom_model_with_dynamo_trace_kwarg_dynamic"
+ )
trt_ep_path = os.path.join(tmp_dir, "compiled.ep")
torchtrt.save(trt_gm, trt_ep_path, retrace=False)
# Clean up model env
torch._dynamo.reset()
@@ -390,11 +392,13 @@
assertions.assertTrue(
cos_sim > COSINE_THRESHOLD,
msg=f"CustomKwargs Module TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
)
# Save the module
- tmp_dir = tempfile.mkdtemp(prefix="test_custom_model_with_dynamo_trace_kwarg_dynamic")
+ tmp_dir = tempfile.mkdtemp(
+ prefix="test_custom_model_with_dynamo_trace_kwarg_dynamic"
+ )
trt_ep_path = os.path.join(tmp_dir, "compiled.ep")
torchtrt.save(trt_gm, trt_ep_path, retrace=False)
# Clean up model env
torch._dynamo.reset()
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_export_serde.py 2025-11-23 04:46:35.093132+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_export_serde.py 2025-11-23 04:47:21.577144+00:00
@@ -15,10 +15,11 @@
assertions = unittest.TestCase()
if importlib.util.find_spec("torchvision"):
import torchvision.models as models
+
@pytest.mark.unit
@pytest.mark.critical
def test_base_full_compile(ir):
"""
This tests export serde functionality on a base model
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_model_refit.py 2025-11-23 04:46:35.093132+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_model_refit.py 2025-11-23 04:47:22.496365+00:00
@@ -530,11 +530,13 @@
not torch_trt.ENABLED_FEATURES.refit,
"Refit feature is not supported in Python 3.13 or higher",
)
@pytest.mark.unit
def test_refit_one_engine_inline_runtime_with_weightmap():
- tmp_dir = tempfile.mkdtemp(prefix="test_refit_one_engine_inline_runtime_with_weightmap")
+ tmp_dir = tempfile.mkdtemp(
+ prefix="test_refit_one_engine_inline_runtime_with_weightmap"
+ )
trt_ep_path = os.path.join(tmp_dir, "compiled.ep")
model = models.resnet18(pretrained=False).eval().to("cuda")
model2 = models.resnet18(pretrained=True).eval().to("cuda")
inputs = [torch.randn((1, 3, 224, 224)).to("cuda")]
enabled_precisions = {torch.float}
@@ -888,11 +890,13 @@
not torch_trt.ENABLED_FEATURES.refit,
"Refit feature is not supported in Python 3.13 or higher",
)
@pytest.mark.unit
def test_refit_one_engine_inline_runtime_without_weightmap():
- tmp_dir = tempfile.mkdtemp(prefix="test_refit_one_engine_inline_runtime_without_weightmap")
+ tmp_dir = tempfile.mkdtemp(
+ prefix="test_refit_one_engine_inline_runtime_without_weightmap"
+ )
trt_ep_path = os.path.join(tmp_dir, "compiled.ep")
model = models.resnet18(pretrained=True).eval().to("cuda")
model2 = models.resnet18(pretrained=False).eval().to("cuda")
inputs = [torch.randn((1, 3, 224, 224)).to("cuda")]
enabled_precisions = {torch.float}
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_reexport.py 2025-11-23 04:46:35.093132+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_reexport.py 2025-11-23 04:47:22.542164+00:00
@@ -158,10 +158,11 @@
def forward(self, x):
conv = self.conv(x)
conv = conv * 0.5
relu = self.relu(conv)
return conv, relu
+
tmp_dir = tempfile.mkdtemp(prefix="test_no_compile")
trt_ep_path = os.path.join(tmp_dir, "trt.ep")
model = MyModule().eval().cuda()
input = torch.randn((1, 3, 224, 224)).to("cuda")
There was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_export_serde.py 2025-11-23 04:48:33.156579+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_export_serde.py 2025-11-23 04:49:18.306172+00:00
@@ -15,10 +15,11 @@
assertions = unittest.TestCase()
if importlib.util.find_spec("torchvision"):
import torchvision.models as models
+
@pytest.mark.unit
@pytest.mark.critical
def test_base_full_compile(ir):
"""
This tests export serde functionality on a base model
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_export_kwargs_serde.py 2025-11-23 04:48:33.156579+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_export_kwargs_serde.py 2025-11-23 04:49:18.559689+00:00
@@ -299,11 +299,13 @@
assertions.assertTrue(
cos_sim > COSINE_THRESHOLD,
msg=f"CustomKwargs Module TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
)
# Save the module
- tmp_dir = tempfile.mkdtemp(prefix="test_custom_model_with_dynamo_trace_kwarg_dynamic")
+ tmp_dir = tempfile.mkdtemp(
+ prefix="test_custom_model_with_dynamo_trace_kwarg_dynamic"
+ )
trt_ep_path = os.path.join(tmp_dir, "compiled.ep")
torchtrt.save(trt_gm, trt_ep_path, retrace=False)
# Clean up model env
torch._dynamo.reset()
@@ -390,11 +392,13 @@
assertions.assertTrue(
cos_sim > COSINE_THRESHOLD,
msg=f"CustomKwargs Module TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
)
# Save the module
- tmp_dir = tempfile.mkdtemp(prefix="test_custom_model_with_dynamo_trace_kwarg_dynamic")
+ tmp_dir = tempfile.mkdtemp(
+ prefix="test_custom_model_with_dynamo_trace_kwarg_dynamic"
+ )
trt_ep_path = os.path.join(tmp_dir, "compiled.ep")
torchtrt.save(trt_gm, trt_ep_path, retrace=False)
# Clean up model env
torch._dynamo.reset()
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_reexport.py 2025-11-23 04:48:33.156579+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_reexport.py 2025-11-23 04:49:19.558116+00:00
@@ -158,10 +158,11 @@
def forward(self, x):
conv = self.conv(x)
conv = conv * 0.5
relu = self.relu(conv)
return conv, relu
+
tmp_dir = tempfile.mkdtemp(prefix="test_no_compile")
trt_ep_path = os.path.join(tmp_dir, "trt.ep")
model = MyModule().eval().cuda()
input = torch.randn((1, 3, 224, 224)).to("cuda")
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_model_refit.py 2025-11-23 04:48:33.156579+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_model_refit.py 2025-11-23 04:49:19.609943+00:00
@@ -530,11 +530,13 @@
not torch_trt.ENABLED_FEATURES.refit,
"Refit feature is not supported in Python 3.13 or higher",
)
@pytest.mark.unit
def test_refit_one_engine_inline_runtime_with_weightmap():
- tmp_dir = tempfile.mkdtemp(prefix="test_refit_one_engine_inline_runtime_with_weightmap")
+ tmp_dir = tempfile.mkdtemp(
+ prefix="test_refit_one_engine_inline_runtime_with_weightmap"
+ )
trt_ep_path = os.path.join(tmp_dir, "compiled.ep")
model = models.resnet18(pretrained=False).eval().to("cuda")
model2 = models.resnet18(pretrained=True).eval().to("cuda")
inputs = [torch.randn((1, 3, 224, 224)).to("cuda")]
enabled_precisions = {torch.float}
@@ -888,11 +890,13 @@
not torch_trt.ENABLED_FEATURES.refit,
"Refit feature is not supported in Python 3.13 or higher",
)
@pytest.mark.unit
def test_refit_one_engine_inline_runtime_without_weightmap():
- tmp_dir = tempfile.mkdtemp(prefix="test_refit_one_engine_inline_runtime_without_weightmap")
+ tmp_dir = tempfile.mkdtemp(
+ prefix="test_refit_one_engine_inline_runtime_without_weightmap"
+ )
trt_ep_path = os.path.join(tmp_dir, "compiled.ep")
model = models.resnet18(pretrained=True).eval().to("cuda")
model2 = models.resnet18(pretrained=False).eval().to("cuda")
inputs = [torch.randn((1, 3, 224, 224)).to("cuda")]
enabled_precisions = {torch.float}
There was a problem hiding this comment.
There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_export_kwargs_serde.py 2025-11-23 04:58:27.029037+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_export_kwargs_serde.py 2025-11-23 04:59:09.451767+00:00
@@ -299,11 +299,13 @@
assertions.assertTrue(
cos_sim > COSINE_THRESHOLD,
msg=f"CustomKwargs Module TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
)
# Save the module
- tmp_dir = tempfile.mkdtemp(prefix="test_custom_model_with_dynamo_trace_kwarg_dynamic")
+ tmp_dir = tempfile.mkdtemp(
+ prefix="test_custom_model_with_dynamo_trace_kwarg_dynamic"
+ )
trt_ep_path = os.path.join(tmp_dir, "compiled.ep")
torchtrt.save(trt_gm, trt_ep_path, retrace=False)
# Clean up model env
torch._dynamo.reset()
@@ -390,11 +392,13 @@
assertions.assertTrue(
cos_sim > COSINE_THRESHOLD,
msg=f"CustomKwargs Module TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
)
# Save the module
- tmp_dir = tempfile.mkdtemp(prefix="test_custom_model_with_dynamo_trace_kwarg_dynamic")
+ tmp_dir = tempfile.mkdtemp(
+ prefix="test_custom_model_with_dynamo_trace_kwarg_dynamic"
+ )
trt_ep_path = os.path.join(tmp_dir, "compiled.ep")
torchtrt.save(trt_gm, trt_ep_path, retrace=False)
# Clean up model env
torch._dynamo.reset()
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_export_serde.py 2025-11-23 04:58:27.029037+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_export_serde.py 2025-11-23 04:59:09.545289+00:00
@@ -15,10 +15,11 @@
assertions = unittest.TestCase()
if importlib.util.find_spec("torchvision"):
import torchvision.models as models
+
@pytest.mark.unit
@pytest.mark.critical
def test_base_full_compile(ir):
"""
This tests export serde functionality on a base model
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_model_refit.py 2025-11-23 04:58:27.029037+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_model_refit.py 2025-11-23 04:59:10.265129+00:00
@@ -530,11 +530,13 @@
not torch_trt.ENABLED_FEATURES.refit,
"Refit feature is not supported in Python 3.13 or higher",
)
@pytest.mark.unit
def test_refit_one_engine_inline_runtime_with_weightmap():
- tmp_dir = tempfile.mkdtemp(prefix="test_refit_one_engine_inline_runtime_with_weightmap")
+ tmp_dir = tempfile.mkdtemp(
+ prefix="test_refit_one_engine_inline_runtime_with_weightmap"
+ )
trt_ep_path = os.path.join(tmp_dir, "compiled.ep")
model = models.resnet18(pretrained=False).eval().to("cuda")
model2 = models.resnet18(pretrained=True).eval().to("cuda")
inputs = [torch.randn((1, 3, 224, 224)).to("cuda")]
enabled_precisions = {torch.float}
@@ -888,11 +890,13 @@
not torch_trt.ENABLED_FEATURES.refit,
"Refit feature is not supported in Python 3.13 or higher",
)
@pytest.mark.unit
def test_refit_one_engine_inline_runtime_without_weightmap():
- tmp_dir = tempfile.mkdtemp(prefix="test_refit_one_engine_inline_runtime_without_weightmap")
+ tmp_dir = tempfile.mkdtemp(
+ prefix="test_refit_one_engine_inline_runtime_without_weightmap"
+ )
trt_ep_path = os.path.join(tmp_dir, "compiled.ep")
model = models.resnet18(pretrained=True).eval().to("cuda")
model2 = models.resnet18(pretrained=False).eval().to("cuda")
inputs = [torch.randn((1, 3, 224, 224)).to("cuda")]
enabled_precisions = {torch.float}
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_reexport.py 2025-11-23 04:58:27.029037+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/models/test_reexport.py 2025-11-23 04:59:10.616549+00:00
@@ -158,10 +158,11 @@
def forward(self, x):
conv = self.conv(x)
conv = conv * 0.5
relu = self.relu(conv)
return conv, relu
+
tmp_dir = tempfile.mkdtemp(prefix="test_no_compile")
trt_ep_path = os.path.join(tmp_dir, "trt.ep")
model = MyModule().eval().cuda()
input = torch.randn((1, 3, 224, 224)).to("cuda")
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Description
two changes:
change to the unique tmp dir so that test run in parallel won't mixed up
Fixes # (issue)
Type of change
Please delete options that are not relevant and/or add your own.
Checklist: