Update dockefile to keep up with latest version (#779)

* Update dockefile to keep up with latest version * Update CMake version * Update submodule version

Author: mc-nv

dockerfile/Dockerfile.triton.trt_llm_backend

@@ -1,18 +1,18 @@
-ARG BASE_IMAGE=nvcr.io/nvidia/tritonserver:25.04-py3-min
-ARG PYTORCH_IMAGE=nvcr.io/nvidia/pytorch:25.04-py3
+ARG BASE_IMAGE=nvcr.io/nvidia/tritonserver:25.05-py3-min
+ARG PYTORCH_IMAGE=nvcr.io/nvidia/pytorch:25.05-py3
 ARG NVRTC_VER=12.9.41-1
 ARG TRT_VER=10.10.0.31
 ARG RELEASE_URL_TRT_x86=https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.10.0/tars/TensorRT-${TRT_VER}.Linux.x86_64-gnu.cuda-12.9.tar.gz
 ARG RELEASE_URL_TRT_ARM=https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.10.0/tars/TensorRT-${TRT_VER}.Linux.aarch64-gnu.cuda-12.9.tar.gz
 
 # Versions of packages to copy from pytorch image
-ARG TORCH_VER=2.7.0a0+79aa17489c.nv25.4
+ARG TORCH_VER=2.8.0a0+5228986c39.nv25.5
 ARG TORCHVISION_VER=0.22.0a0
-ARG SETUPTOOLS_VER=78.1.0
-ARG PYTORCH_TRITON_VER=3.2.0+git4b3bb1f8b.nvinternal
+ARG SETUPTOOLS_VER=78.1.1
+ARG PYTORCH_TRITON_VER=3.3.0+git96316ce52.nvinternal
 ARG JINJA2_VER=3.1.6
 ARG NETWORKX_VER=3.4.2
-ARG SYMPY_VER=1.13.3
+ARG SYMPY_VER=1.14.0
 ARG PACKAGING_VER=23.2
 ARG FLASH_ATTN_VER=2.7.3
 
@@ -137,7 +137,8 @@ ARG TENSORRTLLM_REPO_TAG
 RUN git-lfs install \
  && git clone --single-branch --recurse-submodules --depth=1 -b ${TENSORRTLLM_REPO_TAG} ${TENSORRTLLM_REPO} tensorrt_llm
 
-RUN pip3 install --no-cache-dir polygraphy==0.49.9 mpi4py==3.1.5 cmake==3.30.2 ninja
+RUN pip3 install --no-cache-dir polygraphy==0.49.9 mpi4py==3.1.5 cmake==4.0.3 ninja
+ENV CMAKE_POLICY_VERSION_MINIMUM=3.5
 
 RUN cd tensorrt_llm && \
  if [ -n "${CCACHE_REMOTE_STORAGE}" ] ; then \