bump version to v0.7.2 (#3252)

* bump version to v0.7.2

* bump version to v0.7.2

* remote print

Author: lvhan028

docs/en/get_started/installation.md

@@ -23,7 +23,7 @@ pip install lmdeploy
 The default prebuilt package is compiled on **CUDA 12**. If CUDA 11+ (>=11.3) is required, you can install lmdeploy by:
 
 ```shell
-export LMDEPLOY_VERSION=0.7.1
+export LMDEPLOY_VERSION=0.7.2
 export PYTHON_VERSION=38
 pip install https://github.com/InternLM/lmdeploy/releases/download/v${LMDEPLOY_VERSION}/lmdeploy-${LMDEPLOY_VERSION}+cu118-cp${PYTHON_VERSION}-cp${PYTHON_VERSION}-manylinux2014_x86_64.whl --extra-index-url https://download.pytorch.org/whl/cu118
 ```

docs/zh_cn/get_started/installation.md

@@ -23,7 +23,7 @@ pip install lmdeploy
 默认的预构建包是在 **CUDA 12** 上编译的。如果需要 CUDA 11+ (>=11.3)，你可以使用以下命令安装 lmdeploy：
 
 ```shell
-export LMDEPLOY_VERSION=0.7.1
+export LMDEPLOY_VERSION=0.7.2
 export PYTHON_VERSION=38
 pip install https://github.com/InternLM/lmdeploy/releases/download/v${LMDEPLOY_VERSION}/lmdeploy-${LMDEPLOY_VERSION}+cu118-cp${PYTHON_VERSION}-cp${PYTHON_VERSION}-manylinux2014_x86_64.whl --extra-index-url https://download.pytorch.org/whl/cu118
 ```

lmdeploy/turbomind/turbomind.py

@@ -334,7 +334,6 @@ def _get_logprobs_impl(logprob_vals: torch.Tensor,
         tok_res = {idx[i].item(): val[i].item() for i in range(topn)}
         token_id = output_ids[pos]
         if token_id not in tok_res:
-            print(token_id, tok_res)
             valid_n = n.item()
             tok_res[token_id] = \
                 val[:valid_n][idx[:valid_n] == token_id].item()

lmdeploy/version.py

@@ -1,7 +1,7 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 from typing import Tuple
 
-__version__ = '0.7.1'
+__version__ = '0.7.2'
 short_version = __version__