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chore: bump version to 0.5.3
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ovowei
parent
9e6484a538
commit
b21c848922
9 changed files with 44 additions and 32 deletions
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@ -30,8 +30,8 @@ ARG GITHUB_ARTIFACTORY=github.com
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ARG FLASHINFER_VERSION=0.5.3
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# ktransformers wheel version (cu128torch28 for CUDA 12.8 + PyTorch 2.8)
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ARG KTRANSFORMERS_VERSION=0.4.2
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ARG KTRANSFORMERS_WHEEL=ktransformers-0.4.2+cu128torch28fancy-cp312-cp312-linux_x86_64.whl
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ARG KTRANSFORMERS_VERSION=0.5.3
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ARG KTRANSFORMERS_WHEEL=ktransformers-0.5.3+cu128torch28fancy-cp312-cp312-linux_x86_64.whl
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# flash_attn wheel for fine-tune env
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ARG FLASH_ATTN_WHEEL=flash_attn-2.8.3+cu12torch2.8cxx11abiTRUE-cp312-cp312-linux_x86_64.whl
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@ -25,16 +25,16 @@ sglang-v{sglang版本}_ktransformers-v{ktransformers版本}_{cpu信息}_{gpu信
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**Tar file:**
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```
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sglang-v0.5.6_ktransformers-v0.4.3_x86-intel-multi_cu128_sft_llamafactory-v0.9.3_20241212143022.tar
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sglang-v0.5.6_ktransformers-v0.5.3_x86-intel-multi_cu128_sft_llamafactory-v0.9.3_20241212143022.tar
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```
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**DockerHub tags:**
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```
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Full tag:
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kvcache/ktransformers:sglang-v0.5.6_ktransformers-v0.4.3_x86-intel-multi_cu128_sft_llamafactory-v0.9.3_20241212143022
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kvcache/ktransformers:sglang-v0.5.6_ktransformers-v0.5.3_x86-intel-multi_cu128_sft_llamafactory-v0.9.3_20241212143022
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Simplified tag:
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kvcache/ktransformers:v0.4.3-cu128
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kvcache/ktransformers:v0.5.3-cu128
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```
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### Name Components
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@ -42,7 +42,7 @@ kvcache/ktransformers:v0.4.3-cu128
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| Component | Description | Example |
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|-----------|-------------|---------|
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| sglang version | SGLang package version | `v0.5.6` |
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| ktransformers version | KTransformers version | `v0.4.3` |
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| ktransformers version | KTransformers version | `v0.5.3` |
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| cpu info | CPU instruction set support | `x86-intel-multi` (includes AMX/AVX512/AVX2) |
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| gpu info | CUDA version | `cu128` (CUDA 12.8) |
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| functionality | Feature mode | `sft_llamafactory-v0.9.3` or `infer` |
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@ -197,8 +197,8 @@ docker login
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```
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This creates two tags:
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- Full: `kvcache/ktransformers:sglang-v0.5.6_ktransformers-v0.4.3_x86-intel-multi_cu128_sft_llamafactory-v0.9.3_20241212143022`
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- Simplified: `kvcache/ktransformers:v0.4.3-cu128`
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- Full: `kvcache/ktransformers:sglang-v0.5.6_ktransformers-v0.5.3_x86-intel-multi_cu128_sft_llamafactory-v0.9.3_20241212143022`
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- Simplified: `kvcache/ktransformers:v0.5.3-cu128`
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### Example 4: Dry Run
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@ -225,12 +225,12 @@ Pass additional Docker build arguments:
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```bash
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# Load the image
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docker load -i sglang-v0.5.6_ktransformers-v0.4.3_x86-intel-multi_cu128_sft_llamafactory-v0.9.3_20241212143022.tar
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docker load -i sglang-v0.5.6_ktransformers-v0.5.3_x86-intel-multi_cu128_sft_llamafactory-v0.9.3_20241212143022.tar
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# Run the container
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docker run -it --rm \
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--gpus all \
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sglang-v0.5.6_ktransformers-v0.4.3_x86-intel-multi_cu128_sft_llamafactory-v0.9.3_20241212143022 \
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sglang-v0.5.6_ktransformers-v0.5.3_x86-intel-multi_cu128_sft_llamafactory-v0.9.3_20241212143022 \
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/bin/bash
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```
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@ -238,15 +238,15 @@ docker run -it --rm \
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```bash
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# Pull with full tag
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docker pull kvcache/ktransformers:sglang-v0.5.6_ktransformers-v0.4.3_x86-intel-multi_cu128_sft_llamafactory-v0.9.3_20241212143022
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docker pull kvcache/ktransformers:sglang-v0.5.6_ktransformers-v0.5.3_x86-intel-multi_cu128_sft_llamafactory-v0.9.3_20241212143022
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# Or pull with simplified tag
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docker pull kvcache/ktransformers:v0.4.3-cu128
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docker pull kvcache/ktransformers:v0.5.3-cu128
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# Run the container
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docker run -it --rm \
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--gpus all \
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kvcache/ktransformers:v0.4.3-cu128 \
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kvcache/ktransformers:v0.5.3-cu128 \
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/bin/bash
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```
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@ -301,7 +301,7 @@ cat /workspace/versions.env
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# Output:
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SGLANG_VERSION=0.5.6
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KTRANSFORMERS_VERSION=0.4.3
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KTRANSFORMERS_VERSION=0.5.3
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LLAMAFACTORY_VERSION=0.9.3
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```
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@ -210,9 +210,9 @@ generate_image_name() {
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# Generate simplified tag for DockerHub
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# Input:
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# $1: ktransformers_version (e.g., 0.4.3)
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# $1: ktransformers_version (e.g., 0.5.3)
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# $2: cuda_version (e.g., 12.8.1)
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# Output: Simplified tag (e.g., v0.4.3-cu128)
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# Output: Simplified tag (e.g., v0.5.3-cu128)
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generate_simplified_tag() {
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local ktrans_ver="$1"
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local cuda_version="$2"
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@ -137,13 +137,13 @@ OUTPUT:
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{registry}/{repository}:sglang-v{ver}_ktransformers-v{ver}_{cpu}_{gpu}_{func}_{timestamp}
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Example:
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docker.io/kvcache/ktransformers:sglang-v0.5.6_ktransformers-v0.4.3_x86-intel-multi_cu128_sft_llamafactory-v0.9.3_20241212143022
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docker.io/kvcache/ktransformers:sglang-v0.5.6_ktransformers-v0.5.3_x86-intel-multi_cu128_sft_llamafactory-v0.9.3_20241212143022
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Simplified tag (if --also-push-simplified):
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{registry}/{repository}:v{ktransformers-ver}-{cuda}
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Example:
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docker.io/kvcache/ktransformers:v0.4.3-cu128
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docker.io/kvcache/ktransformers:v0.5.3-cu128
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EOF
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exit 0
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@ -372,7 +372,7 @@ generate_tags() {
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log_warning "DRY RUN: Using placeholder versions"
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# Use placeholder versions for dry run
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local versions="SGLANG_VERSION=0.5.6
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KTRANSFORMERS_VERSION=0.4.3
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KTRANSFORMERS_VERSION=0.5.3
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LLAMAFACTORY_VERSION=0.9.3"
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else
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# Extract versions from image
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@ -709,13 +709,13 @@ OUTPUT:
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{registry}/{repository}:sglang-v{ver}_ktransformers-v{ver}_{cpu}_{gpu}_{func}_{timestamp}
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Example:
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docker.io/kvcache/ktransformers:sglang-v0.5.6_ktransformers-v0.4.3_x86-intel-multi_cu128_sft_llamafactory-v0.9.3_20241212143022
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docker.io/kvcache/ktransformers:sglang-v0.5.6_ktransformers-v0.5.3_x86-intel-multi_cu128_sft_llamafactory-v0.9.3_20241212143022
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Simplified tag (if --also-push-simplified):
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{registry}/{repository}:v{ktransformers-ver}-{cuda}
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Example:
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docker.io/kvcache/ktransformers:v0.4.3-cu128
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docker.io/kvcache/ktransformers:v0.5.3-cu128
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EOF
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exit 0
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@ -944,7 +944,7 @@ generate_tags() {
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log_warning "DRY RUN: Using placeholder versions"
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# Use placeholder versions for dry run
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local versions="SGLANG_VERSION=0.5.6
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KTRANSFORMERS_VERSION=0.4.3
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KTRANSFORMERS_VERSION=0.5.3
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LLAMAFACTORY_VERSION=0.9.3"
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else
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# Extract versions from image
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@ -27,7 +27,7 @@ option(KTRANSFORMERS_CPU_MOE_AMD "ktransformers: CPU use moe kernel for amd" OFF
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# LTO control
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option(CPUINFER_ENABLE_LTO "Enable link time optimization (IPO)" OFF)
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project(kt_kernel_ext VERSION 0.5.0)
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project(kt_kernel_ext VERSION 0.5.3)
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# Auto-detect CPU features early (unless building with LLAMA_NATIVE)
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if(NOT LLAMA_NATIVE AND NOT MSVC)
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@ -692,4 +692,3 @@ if(NUMA_LIBRARY)
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else()
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message(FATAL_ERROR "NUMA library not found, please install NUMA, sudo apt install libnuma-dev")
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endif()
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@ -68,9 +68,9 @@ try:
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_version_ns = {}
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with open(_root_version_file, "r", encoding="utf-8") as f:
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exec(f.read(), _version_ns)
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__version__ = _version_ns.get("__version__", "0.4.3")
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__version__ = _version_ns.get("__version__", "0.5.3")
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else:
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__version__ = "0.4.3"
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__version__ = "0.5.3"
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except ImportError:
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# Python < 3.8, fallback to pkg_resources or hardcoded version
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try:
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@ -79,8 +79,8 @@ except ImportError:
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try:
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__version__ = get_distribution("kt-kernel").version
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except DistributionNotFound:
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__version__ = "0.4.3"
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__version__ = "0.5.3"
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except ImportError:
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__version__ = "0.4.3"
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__version__ = "0.5.3"
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__all__ = ["KTMoEWrapper", "generate_gpu_experts_masks", "kt_kernel_ext", "__cpu_variant__", "__version__"]
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@ -5,4 +5,17 @@ This CLI provides a user-friendly interface to all KTransformers functionality,
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including model inference, fine-tuning, benchmarking, and more.
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"""
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__version__ = "0.1.0"
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from importlib.metadata import PackageNotFoundError, version
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from pathlib import Path
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try:
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__version__ = version("kt-kernel")
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except PackageNotFoundError:
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_version_ns = {}
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_root_version_file = Path(__file__).resolve().parents[3] / "version.py"
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if _root_version_file.exists():
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exec(_root_version_file.read_text(encoding="utf-8"), _version_ns)
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__version__ = _version_ns.get("__version__", "0.5.3")
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else:
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__version__ = "0.5.3"
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@ -695,9 +695,9 @@ if _version_file.exists():
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_version_ns = {}
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with open(_version_file, "r", encoding="utf-8") as f:
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exec(f.read(), _version_ns)
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_base_version = _version_ns.get("__version__", "0.5.0")
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_base_version = _version_ns.get("__version__", "0.5.3")
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else:
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_base_version = "0.5.0"
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_base_version = "0.5.3"
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# Determine version
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if "CPUINFER_VERSION" in os.environ:
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@ -3,4 +3,4 @@ KTransformers version information.
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Shared across kt-kernel and kt-sft modules.
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"""
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__version__ = "0.5.2.post1"
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__version__ = "0.5.3"
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