release cut for 2.10

docker/dist-build.sh

@@ -4,7 +4,7 @@ set -x
 
 TOP_DIR=$(cd $(dirname $0); pwd)/..
 
-BUILD_CMD="python -m pip wheel .  --extra-index-url https://download.pytorch.org/whl/nightly/cu130 -w dist"
+BUILD_CMD="python -m pip wheel .  --extra-index-url https://download.pytorch.org/whl/test/cu130 -w dist"
 
 # TensorRT restricts our pip version
 cd ${TOP_DIR} \

py/requirements.txt

@@ -1,8 +1,8 @@
 numpy
 packaging
 pybind11==2.6.2
---extra-index-url https://download.pytorch.org/whl/nightly/cu130
-torch>=2.10.0.dev,<2.11.0
+--extra-index-url https://download.pytorch.org/whl/test/cu130
+torch>=2.10.0,<2.11.0
 --extra-index-url https://pypi.ngc.nvidia.com
 pyyaml
 dllist

py/torch_tensorrt/_features.py

@@ -1,4 +1,4 @@
-import importlib
+# import importlib
 import os
 import sys
 from collections import namedtuple
@@ -52,10 +52,12 @@
 _WINDOWS_CROSS_COMPILE = check_cross_compile_trt_win_lib()
 _TRTLLM_AVAIL = load_tensorrt_llm_for_nccl()
 
-if importlib.util.find_spec("tensorrt.plugin"):
-    _QDP_PLUGIN_AVAIL = True
-else:
-    _QDP_PLUGIN_AVAIL = False
+# if importlib.util.find_spec("tensorrt.plugin"):
+#     _QDP_PLUGIN_AVAIL = True
+# else:
+#     _QDP_PLUGIN_AVAIL = False
+
+_QDP_PLUGIN_AVAIL = False
 
 ENABLED_FEATURES = FeatureSet(
     _TS_FE_AVAIL,

py/torch_tensorrt/dynamo/conversion/plugins/_custom_op.py

@@ -1,6 +1,7 @@
 from typing import Callable, Optional
 
 from torch.fx.node import Node
+from torch_tensorrt._features import needs_qdp_plugin
 from torch_tensorrt.dynamo._settings import CompilationSettings
 from torch_tensorrt.dynamo.conversion._ConverterRegistry import ConverterPriority
 from torch_tensorrt.dynamo.conversion.plugins._generate_plugin import generate_plugin
@@ -9,6 +10,7 @@
 )
 
 
+@needs_qdp_plugin
 def custom_op(
     op_name: str,
     capability_validator: Optional[Callable[[Node, CompilationSettings], bool]] = None,

pyproject.toml

@@ -6,7 +6,7 @@ requires = [
     "ninja>=1.11.0",
     "pyyaml>=6.0",
     "cffi>=1.15.1",
-    "torch>=2.10.0.dev,<2.11.0",
+    "torch>=2.10.0,<2.11.0",
     "pybind11==2.6.2",
 ]
 build-backend = "setuptools.build_meta"
@@ -32,7 +32,7 @@ classifiers = [
     "Topic :: Software Development :: Libraries",
 ]
 readme = { file = "README.md", content-type = "text/markdown" }
-requires-python = ">=3.10, <=3.13"
+requires-python = ">=3.10"
 keywords = [
     "pytorch",
     "torch",
@@ -103,10 +103,10 @@ index-strategy = "unsafe-best-match"
 
 [tool.uv.sources]
 torch = [
-    { index = "pytorch-nightly-cu130" },
+    { index = "pytorch-test-cu130" },
 ]
 torchvision = [
-    { index = "pytorch-nightly-cu130" },
+    { index = "pytorch-test-cu130" },
 ]
 
 [[tool.uv.index]]

setup.py

@@ -742,7 +742,7 @@ def get_sbsa_requirements(base_requirements):
         # TensorRT does not currently build wheels for Tegra, so we need to use the local tensorrt install from the tarball for thor
         # also due to we use sbsa torch_tensorrt wheel for thor, so when we build sbsa wheel, we need to only include tensorrt dependency.
         return requirements + [
-            "torch>=2.10.0.dev,<2.11.0",
+            "torch>=2.10.0,<2.11.0",
             "tensorrt>=10.14.1,<10.15.0",
         ]
 
@@ -753,7 +753,7 @@ def get_x86_64_requirements(base_requirements):
     if IS_DLFW_CI:
         return requirements
     else:
-        requirements = requirements + ["torch>=2.10.0.dev,<2.11.0"]
+        requirements = requirements + ["torch>=2.10.0,<2.11.0"]
         if USE_TRT_RTX:
             return requirements + [
                 "tensorrt_rtx>=1.2.0.54",

tests/py/dynamo/automatic_plugin/test_automatic_plugin.py

@@ -3,13 +3,12 @@
 
 import torch
 import torch.nn as nn
+import torch_tensorrt
 import triton
 import triton.language as tl
 from parameterized import parameterized
 from torch.testing._internal.common_utils import run_tests
 
-import torch_tensorrt
-
 from ..conversion.harness import DispatchTestCase
 
 
@@ -56,15 +55,15 @@ def elementwise_mul(x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
     return x
 
 
-if not torch_tensorrt.ENABLED_FEATURES.tensorrt_rtx:
+if torch_tensorrt.ENABLED_FEATURES.qdp_plugin:
     torch_tensorrt.dynamo.conversion.plugins.custom_op(
         "torchtrt_ex::elementwise_mul", supports_dynamic_shapes=True
     )
 
 
 @unittest.skipIf(
-    torch_tensorrt.ENABLED_FEATURES.tensorrt_rtx,
-    "TensorRT RTX does not support plugins",
+    not torch_tensorrt.ENABLED_FEATURES.qdp_plugin,
+    "QDP plugin is not enabled",
 )
 class TestAutomaticPlugin(DispatchTestCase):
 

tests/py/dynamo/automatic_plugin/test_automatic_plugin_with_attrs.py

@@ -3,13 +3,12 @@
 
 import torch
 import torch.nn as nn
+import torch_tensorrt
 import triton
 import triton.language as tl
 from parameterized import parameterized
 from torch.testing._internal.common_utils import run_tests
 
-import torch_tensorrt
-
 from ..conversion.harness import DispatchTestCase
 
 
@@ -57,15 +56,15 @@ def _(x: torch.Tensor, y: torch.Tensor, b: float = 0.2, a: int = 2) -> torch.Ten
     return x
 
 
-if not torch_tensorrt.ENABLED_FEATURES.tensorrt_rtx:
+if torch_tensorrt.ENABLED_FEATURES.qdp_plugin:
     torch_tensorrt.dynamo.conversion.plugins.custom_op(
         "torchtrt_ex::elementwise_scale_mul", supports_dynamic_shapes=True
     )
 
 
 @unittest.skipIf(
-    torch_tensorrt.ENABLED_FEATURES.tensorrt_rtx,
-    "TensorRT RTX does not support plugins",
+    not torch_tensorrt.ENABLED_FEATURES.qdp_plugin,
+    "TensorRT RTX does not support plugins or QDP plugin is not enabled",
 )
 class TestAutomaticPlugin(DispatchTestCase):
 

tests/py/dynamo/automatic_plugin/test_flashinfer_rmsnorm.py

@@ -4,10 +4,9 @@
 import pytest
 import torch
 import torch.nn as nn
+import torch_tensorrt
 from parameterized import parameterized
 from torch.testing._internal.common_utils import run_tests
-
-import torch_tensorrt
 from torch_tensorrt._enums import dtype
 
 from ..conversion.harness import DispatchTestCase
@@ -28,7 +27,7 @@ def _(input: torch.Tensor, weight: torch.Tensor, b: float = 1e-6) -> torch.Tenso
     return input
 
 
-if not torch_tensorrt.ENABLED_FEATURES.tensorrt_rtx:
+if torch_tensorrt.ENABLED_FEATURES.qdp_plugin:
     torch_tensorrt.dynamo.conversion.plugins.custom_op(
         "flashinfer::rmsnorm", supports_dynamic_shapes=True
     )
@@ -37,7 +36,7 @@ def _(input: torch.Tensor, weight: torch.Tensor, b: float = 1e-6) -> torch.Tenso
 @unittest.skip("Not Available")
 @unittest.skipIf(
     not importlib.util.find_spec("flashinfer")
-    or torch_tensorrt.ENABLED_FEATURES.tensorrt_rtx,
+    or not torch_tensorrt.ENABLED_FEATURES.qdp_plugin,
     "flashinfer not installed or TensorRT RTX is present",
 )
 class TestAutomaticPlugin(DispatchTestCase):

tests/py/requirements.txt

@@ -14,6 +14,6 @@ nvidia-modelopt[all]; python_version >'3.9' and python_version <'3.13'
 # flashinfer-python is not supported for python version 3.13 or higher
 # flashinfer-python is broken on python 3.9 at the moment, so skip it for now
 flashinfer-python; python_version >'3.9' and python_version <'3.13'
---extra-index-url https://download.pytorch.org/whl/nightly/cu130
-torchvision>=0.25.0.dev,<0.26.0
+--extra-index-url https://download.pytorch.org/whl/test/cu130
+torchvision>=0.25.0,<0.26.0
 timm>=1.0.3