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new 03267616a6 [DOCS] Refine tvm pypi wheel optional install guidance
(#19892)
03267616a6 is described below
commit 03267616a676dbfee8b040d1dee6de1139eb350a
Author: Shushi Hong <[email protected]>
AuthorDate: Sun Jun 28 12:22:45 2026 -0400
[DOCS] Refine tvm pypi wheel optional install guidance (#19892)
This PR refines the PyPI and optional backend installation docs.
It adds lightweight CUDA environment guidance for PyPI installs, removes
duplicated TIRx source-build instructions, and avoids showing optional
TensorRT/CUDA skip messages in the BYOC tutorial output.
---
docs/how_to/tutorials/bring_your_own_codegen.py | 11 +++--------
docs/install/pypi.rst | 15 +++++++++++++++
docs/tirx/install.rst | 13 -------------
3 files changed, 18 insertions(+), 21 deletions(-)
diff --git a/docs/how_to/tutorials/bring_your_own_codegen.py
b/docs/how_to/tutorials/bring_your_own_codegen.py
index a0d4534cc4..0587a040b1 100644
--- a/docs/how_to/tutorials/bring_your_own_codegen.py
+++ b/docs/how_to/tutorials/bring_your_own_codegen.py
@@ -193,6 +193,9 @@ else:
# into the engine it builds, so bind the parameters before partitioning.
# - **Real values.** TensorRT actually computes, so we build for CUDA, run on
# the GPU, and cross-check against a plain CPU build -- not just the shape.
+#
+# The build-and-run cells below execute only when TensorRT and CUDA are
+# available. In CPU-only documentation builds, they produce no output.
trt_mod = relax.transform.BindParams("main", {"weight": weight_np})(ConvReLU)
trt_mod = partition_for_tensorrt(trt_mod)
@@ -218,8 +221,6 @@ if has_tensorrt and has_cuda:
np.testing.assert_allclose(trt_out, cpu_out, rtol=1e-2, atol=1e-2)
print("TensorRT output shape:", trt_out.shape, "- matches the CPU
reference.")
-else:
- print("TensorRT/CUDA unavailable; skipping the GPU build and run.")
######################################################################
# A real backend also exposes knobs the stub does not. Setting ``use_fp16``
@@ -244,8 +245,6 @@ if has_tensorrt and has_cuda:
np.testing.assert_allclose(fp16_out, cpu_out, rtol=5e-2, atol=5e-2)
print("TensorRT FP16 output shape:", fp16_out.shape, "- matches within
FP16 tolerance.")
-else:
- print("TensorRT/CUDA unavailable; skipping the FP16 build.")
######################################################################
# Example NPU vs TensorRT at a glance
@@ -322,8 +321,6 @@ if has_torch and has_tensorrt and has_cuda:
np.testing.assert_allclose(deployed, torch_ref, rtol=1e-2, atol=1e-2)
print("Deployed PyTorch model on TensorRT; output", deployed.shape,
"matches PyTorch.")
-else:
- print("PyTorch / TensorRT / CUDA unavailable; skipping the deployment
example.")
######################################################################
# Real deployment builds once and reuses the artifact. Export the compiled
@@ -340,8 +337,6 @@ if has_torch and has_tensorrt and has_cuda:
)[0].numpy()
np.testing.assert_allclose(reran, torch_ref, rtol=1e-2, atol=1e-2)
print("Reloaded the exported library and reran; output", reran.shape,
"still matches.")
-else:
- print("PyTorch / TensorRT / CUDA unavailable; skipping the export/reload
step.")
######################################################################
# Notes for real deployments
diff --git a/docs/install/pypi.rst b/docs/install/pypi.rst
index 095835312f..48c25bf5d2 100644
--- a/docs/install/pypi.rst
+++ b/docs/install/pypi.rst
@@ -30,6 +30,21 @@ TVM wheel from PyPI:
This installs the Python package, including modules such as ``tvm.tirx``, and
is suitable for trying tutorials that do not require a custom build.
+CUDA environments
+-----------------
+
+Some CUDA workflows use NVIDIA's Python CUDA bindings for runtime compilation.
+Install the CUDA extra in the same environment as TVM when you need this path:
+
+.. code-block:: bash
+
+ pip install "apache-tvm[cuda]"
+
+This extra installs Python-side CUDA bindings only. It does not make the PyPI
+wheel a CUDA-enabled TVM build, and it does not install NVIDIA drivers or a
CUDA
+toolkit. If you need CUDA support in TVM itself, build TVM from source with
+``USE_CUDA=ON``.
+
For more details on installing the TIRx compiler and optional kernel library,
visit the :doc:`TIRx installation </tirx/install>` page. If you need to
customize TVM's build configuration, visit the
diff --git a/docs/tirx/install.rst b/docs/tirx/install.rst
index ddc185cc7e..e74a1cc636 100644
--- a/docs/tirx/install.rst
+++ b/docs/tirx/install.rst
@@ -85,16 +85,3 @@ kernel):
* - ``flashinfer``
- ``nvfp4_gemm``
- optional — quantization and the baseline
-
-Build from source
------------------
-
-To develop TIRx or build the docs, build TVM from source and make it
importable.
-See :doc:`/install/from_source` for the full instructions; in short:
-
-.. code-block:: bash
-
- export TVM_HOME=/path/to/tvm
- export TVM_LIBRARY_PATH=$TVM_HOME/build
- export PYTHONPATH=$TVM_HOME/python:$PYTHONPATH
- python -c "import tvm, tvm.tirx; print(tvm.__file__)"
