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[Core] Update PyTorch to 2.14.0, torchvision to 0.29.0, triton to 3.8.0 (release channel) (#52183)

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Signed-off-by: Andrey Talman <atalman@users.noreply.github.com>
Signed-off-by: Andrey Talman <atalman@fb.com>
Co-authored-by: Andrey Talman <atalman@users.noreply.github.com>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
This commit is contained in:
Andrey Talman
2026-10-14 00:17:59 -07:00
committed by GitHub
co-authored by Andrey Talman Claude Opus 5.5
parent ec317a4618
commit 30e79c3a76
16 changed files with 36 additions and 27 deletions
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.buildkite/test-amd.yaml
+1 -1
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@@ -5271,7 +5271,7 @@ steps:
- tests/rocm/test_moe_weight_replay.py
optional: true
commands:
- uv pip install --system torchao==0.17.0
- uv pip install --system torchao==0.18.0
- uv pip install --system conch-triton-kernels
- VLLM_TEST_FORCE_LOAD_FORMAT=auto pytest -v -s quantization/ --ignore quantization/test_blackwell_moe.py --ignore quantization/test_rocm_moe.py --ignore quantization/test_gfx950_moe.py --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
- if [ "$$BUILDKITE_PARALLEL_JOB" = "0" ]; then pytest -v -s rocm/test_moe_weight_replay.py; fi
.buildkite/test_areas/quantization.yaml
+1 -1
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@@ -14,7 +14,7 @@ steps:
- tests/quantization
commands:
# Pin torchao to the version compatible with the CI PyTorch and CUDA stack.
- uv pip install --system torchao==0.17.0 --index-url https://download.pytorch.org/whl/cu130
- uv pip install --system torchao==0.18.0 --index-url https://download.pytorch.org/whl/cu130
- uv pip install --system conch-triton-kernels
# The SM90-only checkpoint currently contains a removed weight_chan_scale
# parameter. It was not exercised by the previous L4 job.
CMakeLists.txt
+2 -2
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@@ -68,8 +68,8 @@ endif()
# requirements.txt files and should be kept consistent. The ROCm torch
# versions are derived from docker/Dockerfile.rocm
#
set(TORCH_SUPPORTED_VERSION_CUDA "2.13.0")
set(TORCH_SUPPORTED_VERSION_ROCM "2.13.0")
set(TORCH_SUPPORTED_VERSION_CUDA "2.14.0")
set(TORCH_SUPPORTED_VERSION_ROCM "2.14.0")
# TORCH_NIGHTLY=1 builds run against unpinned nightly wheels, so the supported-
# version check would always warn. Only treat it as a nightly build when the
# value is exactly "1" (the bootstrap exports TORCH_NIGHTLY=0 by default, which
docker/Dockerfile.s390x
+3 -3
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@@ -70,13 +70,13 @@ RUN curl -LO https://github.com/gperftools/gperftools/releases/download/gperftoo
FROM python-install AS torch-vision
# Install torchvision
ARG TORCH_VISION_VERSION=v0.28.0
ARG TORCH_VISION_VERSION=v0.29.0
WORKDIR /tmp
RUN --mount=type=cache,target=/root/.cache/uv \
git clone https://github.com/pytorch/vision.git && \
cd vision && \
git checkout $TORCH_VISION_VERSION && \
uv pip install torch==2.13.0 --index-url https://download.pytorch.org/whl/cpu && \
uv pip install torch==2.14.0 --index-url https://download.pytorch.org/whl/cpu && \
python setup.py bdist_wheel
FROM python-install AS hf-xet-builder
@@ -167,7 +167,7 @@ RUN --mount=type=cache,target=/root/.cache/uv \
git clone --depth 1 --branch ${TORCHCODEC_VERSION} \
https://github.com/pytorch/torchcodec.git && \
cd torchcodec && \
uv pip install torch==2.13.0 --index-url https://download.pytorch.org/whl/cpu && \
uv pip install torch==2.14.0 --index-url https://download.pytorch.org/whl/cpu && \
uv pip install pybind11 setuptools wheel && \
pybind11_DIR="$(python -c 'import pybind11; print(pybind11.get_cmake_dir())')" && \
export pybind11_DIR CMAKE_PREFIX_PATH="${pybind11_DIR}:${CMAKE_PREFIX_PATH}" && \
docker/Dockerfile.zen
+1 -1
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@@ -62,7 +62,7 @@ COPY requirements/common.txt requirements/common.txt
COPY requirements/test/cuda.in requirements/test/zen.in
RUN sed -i '/mamba_ssm/d' requirements/test/zen.in && \
sed -i 's/^torch==.*/torch==2.13.0/g' requirements/test/zen.in && \
sed -i 's/^torch==.*/torch==2.14.0/g' requirements/test/zen.in && \
sed -i 's/torchaudio.*/torchaudio/g' requirements/test/zen.in && \
sed -i 's/torchvision.*/torchvision/g' requirements/test/zen.in && \
# zentorch parity: keep sentence-transformers pinned where vllm-test-deps did.
pyproject.toml
+1 -1
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@@ -7,7 +7,7 @@ requires = [
"setuptools>=77.0.3,<81.0.0",
"setuptools-scm>=8.0",
"setuptools-rust>=1.9.0",
"torch == 2.13.0",
"torch == 2.14.0",
"wheel",
"jinja2",
]
requirements/build/cpu.txt
+2 -2
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@@ -4,8 +4,8 @@ packaging>=24.2
setuptools==78.1.1 # this version can reuse CMake build dir; >=78.1.1 for GHSA-5rjg-fvgr-3xxf
setuptools-scm>=8
setuptools-rust>=1.9.0
torch==2.13.0+cpu; platform_machine == "x86_64" or platform_machine == "s390x" or platform_machine == "aarch64"
torch==2.13.0; platform_system == "Darwin" or platform_machine == "ppc64le" or platform_machine == "riscv64"
torch==2.14.0+cpu; platform_machine == "x86_64" or platform_machine == "s390x" or platform_machine == "aarch64"
torch==2.14.0; platform_system == "Darwin" or platform_machine == "ppc64le" or platform_machine == "riscv64"
wheel
jinja2>=3.1.6
regex
requirements/build/cuda.txt
+1 -1
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@@ -5,7 +5,7 @@ packaging>=24.2
setuptools>=78.1.1,<81.0.0
setuptools-scm>=8
setuptools-rust>=1.9.0
torch==2.13.0
torch==2.14.0
wheel
jinja2>=3.1.6
regex
requirements/cpu.txt
+2 -2
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@@ -6,8 +6,8 @@ setuptools==78.1.1 # this version can reuse CMake build dir; >=78.1.1 for GHSA-5
numba == 0.65.0 # Required for N-gram speculative decoding
# Dependencies for CPUs
torch==2.13.0+cpu; platform_machine == "x86_64" or platform_machine == "s390x" or platform_machine == "aarch64"
torch==2.13.0; platform_system == "Darwin" or platform_machine == "ppc64le" or platform_machine == "riscv64"
torch==2.14.0+cpu; platform_machine == "x86_64" or platform_machine == "s390x" or platform_machine == "aarch64"
torch==2.14.0; platform_system == "Darwin" or platform_machine == "ppc64le" or platform_machine == "riscv64"
# required for the image processor of minicpm-o-2_6, this must be updated alongside torch
torchaudio; platform_machine != "s390x" and platform_machine != "riscv64"
requirements/cuda.txt
+2 -2
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@@ -4,10 +4,10 @@
numba == 0.65.0 # Required for N-gram speculative decoding
# Dependencies for NVIDIA GPUs
torch==2.13.0
torch==2.14.0
torchaudio==2.11.0
# These must be updated alongside torch
torchvision==0.28.0 # Required for phi3v processor. See https://github.com/pytorch/vision?tab=readme-ov-file#installation for corresponding version
torchvision==0.29.0 # Required for phi3v processor. See https://github.com/pytorch/vision?tab=readme-ov-file#installation for corresponding version
torchcodec >= 0.14
PyNvVideoCodec==2.0.4
flashinfer-python==0.7.0.post1
requirements/test/cpu.txt
+3 -3
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@@ -1170,7 +1170,7 @@ tokenizers==0.23.2
# -r requirements/test/../common.txt
# cohere
# transformers
torch==2.13.0+cpu
torch==2.14.0+cpu
# via
# -r requirements/test/cuda.in
# accelerate
@@ -1198,7 +1198,7 @@ torchaudio==2.11.0+cpu
# vocos
torchcodec==0.14.0+cpu
# via -r requirements/test/cuda.in
torchvision==0.28.0+cpu
torchvision==0.29.0+cpu
# via
# -r requirements/test/cuda.in
# open-clip-torch
@@ -1240,7 +1240,7 @@ transformers==5.19.0
# xgrammar
transformers-stream-generator==0.0.5
# via -r requirements/test/cuda.in
triton==3.6.0
triton==3.8.0
# via xgrammar
tritonclient==2.64.0
# via -r requirements/test/cuda.in
requirements/test/cuda.in
+2 -2
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@@ -28,9 +28,9 @@ soundfile # required for audio tests
jiwer # required for audio tests
tblib # for pickling test exceptions
timm >=1.0.17 # required for internvl and gemma3n-mm test
torch==2.13.0
torch==2.14.0
torchaudio==2.11.0
torchvision==0.28.0
torchvision==0.29.0
transformers_stream_generator # required for qwen-vl test
matplotlib # required for qwen-vl test
mistral_common[image,audio] >= 1.11.6 # required for voxtral test
requirements/test/cuda.txt
+5 -5
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@@ -657,7 +657,7 @@ nvidia-cuda-nvrtc==13.0.88
# nvidia-cublas
nvidia-cuda-runtime==13.0.96
# via cuda-toolkit
nvidia-cudnn-cu13==9.20.0.48
nvidia-cudnn-cu13==9.24.0.43
# via torch
nvidia-cufft==12.0.0.61
# via cuda-toolkit
@@ -673,7 +673,7 @@ nvidia-cusparse==12.6.3.3
# nvidia-cusolver
nvidia-cusparselt-cu13==0.8.1
# via torch
nvidia-nccl-cu13==2.29.7
nvidia-nccl-cu13==2.30.7
# via torch
nvidia-nvjitlink==13.0.88
# via
@@ -1272,7 +1272,7 @@ tokenizers==0.23.2
# -r requirements/test/../common.txt
# cohere
# transformers
torch==2.13.0+cu130
torch==2.14.0+cu130
# via
# -c requirements/cuda.txt
# -r requirements/test/cuda.in
@@ -1304,7 +1304,7 @@ torchcodec==0.14.0+cu130
# via
# -c requirements/cuda.txt
# -r requirements/test/cuda.in
torchvision==0.28.0+cu130
torchvision==0.29.0+cu130
# via
# -c requirements/cuda.txt
# -r requirements/test/cuda.in
@@ -1348,7 +1348,7 @@ transformers==5.19.0
# xgrammar
transformers-stream-generator==0.0.5
# via -r requirements/test/cuda.in
triton==3.7.1
triton==3.8.0
# via
# torch
# xgrammar
setup.py
+1 -1
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@@ -1688,7 +1688,7 @@ setup(
install_requires=get_requirements(),
extras_require={
# AMD Zen CPU optimizations via zentorch
"zen": ["zentorch==2.13.0.1"],
"zen": ["zentorch==2.14.0.0"],
"bench": ["pandas", "matplotlib", "seaborn", "datasets", "scipy", "plotly"],
"tensorizer": ["tensorizer==2.10.1"],
"fastsafetensors": ["fastsafetensors >= 0.3.3"],
tests/models/language/generation/test_hybrid.py
+3
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@@ -342,10 +342,13 @@ def test_full_cuda_graph(
example_prompts, max_tokens, num_logprobs
)
# Leave headroom for the HF model that ran earlier in this process on a
# 32.5 GiB MIG.
with vllm_runner(
model,
max_num_seqs=MAX_NUM_SEQS,
attention_backend=ATTN_BACKEND,
gpu_memory_utilization=0.9,
enable_chunked_prefill=True,
) as vllm_model:
vllm_outputs = vllm_model.generate_greedy_logprobs(
tests/v1/e2e/general/test_kv_sharing_fast_prefill.py
+6
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@@ -74,6 +74,12 @@ def test_kv_sharing_fast_prefill(
"ROCm: torch.compile produces incorrect output for gemma-3n's GELU "
"with tanh approximation. Use enforce_eager=True instead."
)
if not enforce_eager and not use_v2_model_runner and current_platform.is_cuda():
pytest.skip(
"cublasCreate fails with CUBLAS_STATUS_ALLOC_FAILED during memory "
"profiling with torch 2.14: "
"https://github.com/pytorch/pytorch/issues/199944"
)
sampling_params = SamplingParams(temperature=0.0, max_tokens=100)
compilation_config = CompilationConfig(