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maskrcnn_resnet50_fpn cannot be exported #9321

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maskrcnn_resnet50_fpn cannot be exported#9321
@justinchuby

Description

@justinchuby
justinchuby
opened on Dec 31, 2025

🐛 Describe the bug

import torchvision as tv
import torch

model = tv.models.detection.maskrcnn_resnet50_fpn(pretrained=False).eval()
x = (torch.rand(3, 300, 400), torch.rand(3, 500, 400))
ep = torch.export.export(model, (x,))
Traceback (most recent call last):
  File "/home/justinchu/dev/onnxscript/test.py", line 6, in <module>
    ep = torch.export.export(model, (x,))
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/export/__init__.py", line 311, in export
    raise e
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/export/__init__.py", line 277, in export
    return _export(
        mod,
    ...<6 lines>...
        prefer_deferred_runtime_asserts_over_guards=prefer_deferred_runtime_asserts_over_guards,
    )
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/export/_trace.py", line 1229, in wrapper
    raise e
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/export/_trace.py", line 1195, in wrapper
    ep = fn(*args, **kwargs)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/export/exported_program.py", line 124, in wrapper
    return fn(*args, **kwargs)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/export/_trace.py", line 2336, in _export
    ep = _export_for_training(
        mod,
    ...<5 lines>...
        prefer_deferred_runtime_asserts_over_guards=prefer_deferred_runtime_asserts_over_guards,
    )
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/export/_trace.py", line 1229, in wrapper
    raise e
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/export/_trace.py", line 1195, in wrapper
    ep = fn(*args, **kwargs)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/export/exported_program.py", line 124, in wrapper
    return fn(*args, **kwargs)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/export/_trace.py", line 2144, in _export_for_training
    export_artifact = export_func(
        mod=mod,
    ...<6 lines>...
        _to_aten_func=_export_to_aten_ir_make_fx,
    )
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/export/_trace.py", line 2075, in _non_strict_export
    aten_export_artifact = _to_aten_func(
        patched_mod,
    ...<5 lines>...
        transform=_tuplify_outputs,
    )
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/export/_trace.py", line 1863, in _export_to_aten_ir_make_fx
    gm, graph_signature = transform(_make_fx_helper)(
                          ~~~~~~~~~~~~~~~~~~~~~~~~~~^
        stack,
        ^^^^^^
    ...<3 lines>...
        kwargs=fake_kwargs,
        ^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/export/_trace.py", line 1993, in _aot_export_non_strict
    gm, sig = aot_export(stack, wrapped_mod, args, kwargs=kwargs, **flags)
              ~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/export/_trace.py", line 1775, in _make_fx_helper
    gm = make_fx(
    ...<2 lines>...
        pre_dispatch=True,
    )(*flat_args)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/experimental/proxy_tensor.py", line 2581, in wrapped
    return make_fx_tracer.trace(f, *args)
           ~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/experimental/proxy_tensor.py", line 2508, in trace
    return self._trace_inner(f, *args)
           ~~~~~~~~~~~~~~~~~^^^^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/experimental/proxy_tensor.py", line 2470, in _trace_inner
    t = dispatch_trace(
        wrap_key(func, args, self.fx_tracer, self.pre_dispatch),
        tracer=self.fx_tracer,
        concrete_args=tuple(phs),
    )
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/_compile.py", line 54, in inner
    return disable_fn(*args, **kwargs)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/_dynamo/eval_frame.py", line 1129, in _fn
    return fn(*args, **kwargs)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/experimental/proxy_tensor.py", line 1443, in dispatch_trace
    graph = tracer.trace(root, concrete_args)  # type: ignore[arg-type]
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/experimental/proxy_tensor.py", line 2062, in trace
    res = super().trace(root, concrete_args)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/_symbolic_trace.py", line 869, in trace
    (self.create_arg(fn(*args)),),
                     ~~^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/experimental/proxy_tensor.py", line 1501, in wrapped
    out = f(*tensors)  # type:ignore[call-arg]
  File "<string>", line 1, in <lambda>
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/export/_trace.py", line 1662, in wrapped_fn
    return tuple(flat_fn(*args))
                 ~~~~~~~^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/_functorch/_aot_autograd/utils.py", line 192, in flat_fn
    tree_out = fn(*args, **kwargs)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/_functorch/_aot_autograd/graph_capture_wrappers.py", line 1369, in functional_call
    out = mod(*args[params_len:], **kwargs)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/_symbolic_trace.py", line 844, in module_call_wrapper
    return self.call_module(mod, forward, args, kwargs)
           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/experimental/proxy_tensor.py", line 2149, in call_module
    return Tracer.call_module(self, m, forward, args, kwargs)
           ~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/_symbolic_trace.py", line 560, in call_module
    ret_val = forward(*args, **kwargs)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/_symbolic_trace.py", line 837, in forward
    return _orig_module_call(mod, *args, **kwargs)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/export/_trace.py", line 1977, in forward
    tree_out = mod(*args, **kwargs)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/_symbolic_trace.py", line 844, in module_call_wrapper
    return self.call_module(mod, forward, args, kwargs)
           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/experimental/proxy_tensor.py", line 2149, in call_module
    return Tracer.call_module(self, m, forward, args, kwargs)
           ~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/_symbolic_trace.py", line 560, in call_module
    ret_val = forward(*args, **kwargs)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/_symbolic_trace.py", line 837, in forward
    return _orig_module_call(mod, *args, **kwargs)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torchvision/models/detection/generalized_rcnn.py", line 117, in forward
    proposals, proposal_losses = self.rpn(images, features, targets)
                                 ~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/_symbolic_trace.py", line 844, in module_call_wrapper
    return self.call_module(mod, forward, args, kwargs)
           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/experimental/proxy_tensor.py", line 2149, in call_module
    return Tracer.call_module(self, m, forward, args, kwargs)
           ~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/_symbolic_trace.py", line 560, in call_module
    ret_val = forward(*args, **kwargs)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/_symbolic_trace.py", line 837, in forward
    return _orig_module_call(mod, *args, **kwargs)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/nn/modules/module.py", line 1783, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/nn/modules/module.py", line 1794, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torchvision/models/detection/rpn.py", line 372, in forward
    boxes, scores = self.filter_proposals(proposals, objectness, images.image_sizes, num_anchors_per_level)
                    ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torchvision/models/detection/rpn.py", line 289, in filter_proposals
    keep = box_ops.batched_nms(boxes, scores, lvl, self.nms_thresh)
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torchvision/ops/boxes.py", line 80, in batched_nms
    if boxes.numel() > (4000 if boxes.device.type == "cpu" else 100_000) and not torchvision._is_tracing():
       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/__init__.py", line 763, in __bool__
    return self.node.bool_()
           ~~~~~~~~~~~~~~~^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/experimental/sym_node.py", line 602, in bool_
    return self.guard_bool("", 0)
           ~~~~~~~~~~~~~~~^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/experimental/sym_node.py", line 538, in guard_bool
    r = self.evaluate()
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/experimental/sym_node.py", line 512, in evaluate
    return self.shape_env.evaluate_sym_node(self, size_oblivious)
           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/experimental/symbolic_shapes.py", line 7308, in evaluate_sym_node
    return self.evaluate_expr(
           ~~~~~~~~~~~~~~~~~~^
        sym_node.expr,
        ^^^^^^^^^^^^^^
    ...<3 lines>...
        fallback_value=fallback_value,
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/experimental/symbolic_shapes.py", line 7408, in evaluate_expr
    return self._inner_evaluate_expr(
           ~~~~~~~~~~~~~~~~~~~~~~~~~^
        orig_expr,
        ^^^^^^^^^^
    ...<5 lines>...
        fallback_value,
        ^^^^^^^^^^^^^^^
    )
    ^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/experimental/recording.py", line 273, in wrapper
    return retlog(fn(*args, **kwargs))
                  ~~^^^^^^^^^^^^^^^^^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/experimental/symbolic_shapes.py", line 7431, in _inner_evaluate_expr
    return self._evaluate_expr(
           ~~~~~~~~~~~~~~~~~~~^
        orig_expr,
        ^^^^^^^^^^
    ...<4 lines>...
        forcing_spec=forcing_spec,
        ^^^^^^^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "/home/justinchu/anaconda3/envs/onnx/lib/python3.13/site-packages/torch/fx/experimental/symbolic_shapes.py", line 7650, in _evaluate_expr
    raise self._make_data_dependent_error(
    ...<3 lines>...
    )
torch.fx.experimental.symbolic_shapes.GuardOnDataDependentSymNode: Could not guard on data-dependent expression 4*u1 > 4000 (unhinted: 4*u1 > 4000).  (Size-like symbols: u1)

consider using data-dependent friendly APIs such as guard_or_false, guard_or_true and statically_known_trueCaused by: (torchvision/ops/boxes.py:80 in batched_nms)
For more information, run with TORCH_LOGS="dynamic"
For extended logs when we create symbols, also add TORCHDYNAMO_EXTENDED_DEBUG_CREATE_SYMBOL="u1"
If you suspect the guard was triggered from C++, add TORCHDYNAMO_EXTENDED_DEBUG_CPP=1
For more debugging help, see https://docs.google.com/document/d/1HSuTTVvYH1pTew89Rtpeu84Ht3nQEFTYhAX3Ypa_xJs/edit?usp=sharing

For C++ stack trace, run with TORCHDYNAMO_EXTENDED_DEBUG_CPP=1

The error above occurred when calling torch.export.export. If you would like to view some more information about this error, and get a list of all other errors that may occur in your export call, you can replace your `export()` call with `draft_export()`.

Versions

Collecting environment information...
PyTorch version: 2.10.0.dev20251028+cpu
Is debug build: False
CUDA used to build PyTorch: Could not collect
ROCM used to build PyTorch: N/A

OS: Ubuntu 24.04.1 LTS (x86_64)
GCC version: (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
Clang version: Could not collect
CMake version: version 3.31.2
Libc version: glibc-2.39

Python version: 3.13.0 | packaged by Anaconda, Inc. | (main, Oct  7 2024, 21:29:38) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-6.6.87.2-microsoft-standard-WSL2-x86_64-with-glibc2.39
Is CUDA available: False
CUDA runtime version: 12.0.140
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 4060 Laptop GPU
Nvidia driver version: 573.71
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.9.6.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv.so.9.6.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn.so.9.6.0
/usr/lib/x86_64-linux-gnu/libcudnn_engines_precompiled.so.9.6.0
/usr/lib/x86_64-linux-gnu/libcudnn_engines_runtime_compiled.so.9.6.0
/usr/lib/x86_64-linux-gnu/libcudnn_graph.so.9.6.0
/usr/lib/x86_64-linux-gnu/libcudnn_heuristic.so.9.6.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops.so.9.6.0
Is XPU available: False
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        46 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               20
On-line CPU(s) list:                  0-19
Vendor ID:                            GenuineIntel
Model name:                           13th Gen Intel(R) Core(TM) i7-13800H
CPU family:                           6
Model:                                186
Thread(s) per core:                   2
Core(s) per socket:                   10
Socket(s):                            1
Stepping:                             2
BogoMIPS:                             5836.82
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology tsc_reliable nonstop_tsc cpuid tsc_known_freq pni pclmulqdq vmx ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves avx_vnni vnmi umip waitpkg gfni vaes vpclmulqdq rdpid movdiri movdir64b fsrm md_clear serialize flush_l1d arch_capabilities
Virtualization:                       VT-x
Hypervisor vendor:                    Microsoft
Virtualization type:                  full
L1d cache:                            480 KiB (10 instances)
L1i cache:                            320 KiB (10 instances)
L2 cache:                             12.5 MiB (10 instances)
L3 cache:                             24 MiB (1 instance)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-19
Vulnerability Gather data sampling:   Not affected
Vulnerability Itlb multihit:          Not affected
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Not affected
Vulnerability Reg file data sampling: Mitigation; Clear Register File
Vulnerability Retbleed:               Mitigation; Enhanced IBRS
Vulnerability Spec rstack overflow:   Not affected
Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

Versions of relevant libraries:
[pip3] flake8==7.3.0
[pip3] flake8-bugbear==24.12.12
[pip3] flake8-comprehensions==3.16.0
[pip3] flake8-executable==2.1.3
[pip3] flake8-logging-format==2024.24.12
[pip3] flake8-pyi==25.5.0
[pip3] flake8_simplify==0.22.0
[pip3] model-explorer-onnx==0.3.8
[pip3] mypy==1.10.1
[pip3] mypy-extensions==1.0.0
[pip3] numpy==2.1.0
[pip3] nvidia-cublas-cu12==12.8.4.1
[pip3] nvidia-cuda-cupti-cu12==12.8.90
[pip3] nvidia-cuda-nvrtc-cu12==12.8.93
[pip3] nvidia-cuda-runtime-cu12==12.8.90
[pip3] nvidia-cudnn-cu12==9.10.2.21
[pip3] nvidia-cufft-cu12==11.3.3.83
[pip3] nvidia-curand-cu12==10.3.9.90
[pip3] nvidia-cusolver-cu12==11.7.3.90
[pip3] nvidia-cusparse-cu12==12.5.8.93
[pip3] nvidia-cusparselt-cu12==0.7.1
[pip3] nvidia-nccl-cu12==2.27.5
[pip3] nvidia-nvjitlink-cu12==12.8.93
[pip3] nvidia-nvtx-cu12==12.8.90
[pip3] onnx==1.20.0
[pip3] onnx-diagnostic==0.7.11
[pip3] onnx-flatbuffers==0.1.0
[pip3] onnx-ir==0.1.13
[pip3] onnx-safetensors==1.0.0
[pip3] onnxconverter-common==1.16.0
[pip3] onnxruntime==1.23.2
[pip3] onnxruntime-easy==0.0.1
[pip3] onnxruntime_extensions==0.14.0
[pip3] onnxruntime-genai-cuda==0.10.0
[pip3] onnxruntime-gpu==1.23.0
[pip3] onnxscript==0.5.7.dev20251211
[pip3] onnxslim==0.1.80
[pip3] optree==0.17.0
[pip3] pytorch-triton==3.5.0+git7416ffcb
[pip3] skl2onnx==1.19.0
[pip3] tflite2torch==0.1.0
[pip3] torch==2.10.0.dev20251028+cpu
[pip3] torch-code-tracing==0.1.0
[pip3] torch-geometric==2.6.1
[pip3] torch-onnx-models==0.1.0
[pip3] torchaudio==2.8.0
[pip3] torchax==0.0.5
[pip3] torchmetrics==1.7.1
[pip3] torchvision==0.25.0.dev20251028+cpu
[pip3] triton==3.4.0
[conda] numpy                     2.1.0                    pypi_0    pypi
[conda] nvidia-cublas-cu12        12.8.4.1                 pypi_0    pypi
[conda] nvidia-cuda-cupti-cu12    12.8.90                  pypi_0    pypi
[conda] nvidia-cuda-nvrtc-cu12    12.8.93                  pypi_0    pypi
[conda] nvidia-cuda-runtime-cu12  12.8.90                  pypi_0    pypi
[conda] nvidia-cudnn-cu12         9.10.2.21                pypi_0    pypi
[conda] nvidia-cufft-cu12         11.3.3.83                pypi_0    pypi
[conda] nvidia-curand-cu12        10.3.9.90                pypi_0    pypi
[conda] nvidia-cusolver-cu12      11.7.3.90                pypi_0    pypi
[conda] nvidia-cusparse-cu12      12.5.8.93                pypi_0    pypi
[conda] nvidia-cusparselt-cu12    0.7.1                    pypi_0    pypi
[conda] nvidia-nccl-cu12          2.27.5                   pypi_0    pypi
[conda] nvidia-nvjitlink-cu12     12.8.93                  pypi_0    pypi
[conda] nvidia-nvtx-cu12          12.8.90                  pypi_0    pypi
[conda] optree                    0.17.0                   pypi_0    pypi
[conda] pytorch-triton            3.5.0+git7416ffcb          pypi_0    pypi
[conda] tflite2torch              0.1.0                    pypi_0    pypi
[conda] torch                     2.10.0.dev20251028+cpu          pypi_0    pypi
[conda] torch-code-tracing        0.1.0                    pypi_0    pypi
[conda] torch-geometric           2.6.1                    pypi_0    pypi
[conda] torch-onnx-models         0.1.0                    pypi_0    pypi
[conda] torchaudio                2.8.0                    pypi_0    pypi
[conda] torchax                   0.0.5                    pypi_0    pypi
[conda] torchmetrics              1.7.1                    pypi_0    pypi
[conda] torchvision               0.25.0.dev20251028+cpu          pypi_0    pypi
[conda] triton                    3.4.0                    pypi_0    pypi

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