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chore: Bump TRTLLM to 1.2.0rc6.post2 (#5580) (#5621)
Signed-off-by: jthomson04 <jwillthomson19@gmail.com> Co-authored-by: Pavithra Vijayakrishnan <160681768+pvijayakrish@users.noreply.github.com>
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benchmarks/pyproject.toml

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@@ -46,7 +46,7 @@ dependencies = [
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"pydantic>=2",
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"tabulate",
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"types-tabulate",
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# Satisfies vLLM 0.11.0 (>=4.55.2), vLLM 0.11.2 (>=4.56.0,<5), TRT-LLM 1.2.0rc6.post1 (==4.57.1), SGLang 0.5.6.post2 (==4.57.1)
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# Satisfies vLLM 0.11.0 (>=4.55.2), vLLM 0.11.2 (>=4.56.0,<5), TRT-LLM 1.2.0rc6.post2 (==4.57.1), SGLang 0.5.6.post2 (==4.57.1)
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"transformers>=4.56.0",
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"pytest-mypy",
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]

container/Dockerfile.trtllm

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@@ -551,7 +551,7 @@ RUN if [ "$HAS_TRTLLM_CONTEXT" = "1" ]; then \
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sed -i 's/pip3 install/uv pip install/g' /tmp/install_tensorrt.sh && \
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bash /tmp/install_tensorrt.sh && \
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# Install TensorRT-LLM wheel from the provided index URL, allow dependencies from PyPI
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# TRTLLM 1.2.0rc6.post1 has issues installing from pypi with uv, installing from direct wheel link works best
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# TRTLLM 1.2.0rc6.post2 has issues installing from pypi with uv, installing from direct wheel link works best
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# explicitly installing triton 3.5.0 as trtllm only lists triton as dependency on x64_64 for some reason
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if echo "${TENSORRTLLM_PIP_WHEEL}" | grep -q '^tensorrt-llm=='; then \
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TRTLLM_VERSION=$(echo "${TENSORRTLLM_PIP_WHEEL}" | sed -E 's/tensorrt-llm==([0-9a-zA-Z.+-]+).*/\1/'); \

container/build.sh

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@@ -89,7 +89,7 @@ DEFAULT_TENSORRTLLM_PIP_WHEEL_DIR="/tmp/trtllm_wheel/"
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# TensorRT-LLM commit to use for building the trtllm wheel if not provided.
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# Important Note: This commit is not used in our CI pipeline. See the CI
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# variables to learn how to run a pipeline with a specific commit.
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DEFAULT_EXPERIMENTAL_TRTLLM_COMMIT="e4a6c9995dacf66bab4410475a6774152f95a0a6" # 1.2.0rc6.post1
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DEFAULT_EXPERIMENTAL_TRTLLM_COMMIT="50379d028c2689ffb5cefe7797c5afb199e9df93" # 1.2.0rc6.post2
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TRTLLM_COMMIT=""
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TRTLLM_USE_NIXL_KVCACHE_EXPERIMENTAL="0"
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TRTLLM_GIT_URL=""
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DEFAULT_TENSORRTLLM_INDEX_URL="https://pypi.nvidia.com/"
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# TODO: Remove the version specification from here and use the ai-dynamo[trtllm] package.
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# Need to update the Dockerfile.trtllm to use the ai-dynamo[trtllm] package.
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DEFAULT_TENSORRTLLM_PIP_WHEEL="tensorrt-llm==1.2.0rc6.post1"
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DEFAULT_TENSORRTLLM_PIP_WHEEL="tensorrt-llm==1.2.0rc6.post2"
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TENSORRTLLM_PIP_WHEEL=""
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VLLM_BASE_IMAGE="nvcr.io/nvidia/cuda-dl-base"

container/deps/requirements.txt

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@@ -52,7 +52,7 @@ tensorboard>=2.19.0,<2.21.0
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tensorboardX==2.6.2.2
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# Transformers version constraint for container builds
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# - vLLM 0.11.0: >=4.55.2, vLLM 0.11.2: >=4.56.0,<5
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# - TensorRT-LLM 1.2.0rc6.post1: ==4.57.1
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# - TensorRT-LLM 1.2.0rc6.post2: ==4.57.1
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# - SGLang 0.5.6.post2: ==4.57.1
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# Using >=4.56.0 to satisfy all frameworks
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transformers>=4.56.0

docs/reference/support-matrix.md

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@@ -65,7 +65,7 @@ The following table shows the dependency versions included with each Dynamo rele
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| **Dependency** | **main (ToT)** | **v0.8.0** | **v0.7.1** | **v0.7.0.post1** | **v0.7.0** |
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| :------------- | :------------- | :--------- | :--------- | :--------------- | :--------- |
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| SGLang | 0.5.7 | 0.5.6.post2 | 0.5.3.post4| 0.5.3.post4 | 0.5.3.post4|
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| TensorRT-LLM | 1.2.0rc6.post1 | 1.2.0rc6.post1 | 1.2.0rc3 | 1.2.0rc3 | 1.2.0rc2 |
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| TensorRT-LLM | 1.2.0rc6.post2 | 1.2.0rc6.post1 | 1.2.0rc3 | 1.2.0rc3 | 1.2.0rc2 |
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| vLLM | 0.13.0 | 0.12.0 | 0.11.0 | 0.11.0 | 0.11.0 |
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| NIXL | 0.8.0 | 0.8.0 | 0.8.0 | 0.8.0 | 0.8.0 |
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pyproject.toml

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@@ -50,7 +50,7 @@ Repository = "https://github.com/ai-dynamo/dynamo.git"
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[project.optional-dependencies]
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trtllm =[
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"uvloop",
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"tensorrt-llm==1.2.0rc6.post1",
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"tensorrt-llm==1.2.0rc6.post2",
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]
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vllm = [

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