Merge pull request #11 from alibaba/main

merge

Dockerfile

@@ -3,11 +3,22 @@
 
 FROM python:3.8.18
 
+# prepare the java env
+WORKDIR /opt
+# download jdk
+RUN wget https://aka.ms/download-jdk/microsoft-jdk-17.0.9-linux-x64.tar.gz -O jdk.tar.gz && \
+    tar -xzf jdk.tar.gz && \
+    rm -rf jdk.tar.gz && \
+    mv jdk-17.0.9+8 jdk
+
+# set the environment variable
+ENV JAVA_HOME=/opt/jdk
+
 WORKDIR /data-juicer
 
 # install requirements first to better reuse installed library cache
 COPY environments/ environments/
-RUN cat environments/* | xargs pip install
+RUN cat environments/* | xargs pip install --default-timeout 1000
 
 # install data-juicer then
 COPY . .

README.md

@@ -169,7 +169,7 @@ pip install py-data-juicer
     latest `data-juicer` with provided [Dockerfile](Dockerfile):
 
     ```shell
-    docker build -t data-juicer:<version_tag> .
+    docker build -t datajuicer/data-juicer:<version_tag> .
     ```
 
 ### Installation check
@@ -276,7 +276,7 @@ docker run --rm \  # remove container after the processing
   --name dj \  # name of the container
   -v <host_data_path>:<image_data_path> \  # mount data or config directory into the container
   -v ~/.cache/:/root/.cache/ \  # mount the cache directory into the container to reuse caches and models (recommended)
-  data-juicer:<version_tag> \  # image to run
+  datajuicer/data-juicer:<version_tag> \  # image to run
   dj-process --config /path/to/config.yaml  # similar data processing commands
 ```
 
@@ -289,7 +289,7 @@ docker run -dit \  # run the container in the background
   --name dj \
   -v <host_data_path>:<image_data_path> \
   -v ~/.cache/:/root/.cache/ \
-  data-juicer:latest /bin/bash
+  datajuicer/data-juicer:latest /bin/bash
 
 # enter into this container and then you can use data-juicer in editable mode
 docker exec -it <container_id> bash

README_ZH.md

@@ -154,7 +154,7 @@ pip install py-data-juicer
   - 或者运行如下命令用我们提供的 [Dockerfile](Dockerfile) 来构建包括最新版本的 `data-juicer` 的 docker 镜像：
 
     ```shell
-    docker build -t data-juicer:<version_tag> .
+    docker build -t datajuicer/data-juicer:<version_tag> .
     ```
 
 ### 安装校验
@@ -254,7 +254,7 @@ docker run --rm \  # 在处理结束后将容器移除
   --name dj \  # 容器名称
   -v <host_data_path>:<image_data_path> \  # 将本地的数据或者配置目录挂载到容器中
   -v ~/.cache/:/root/.cache/ \  # 将 cache 目录挂载到容器以复用 cache 和模型资源（推荐）
-  data-juicer:<version_tag> \  # 运行的镜像
+  datajuicer/data-juicer:<version_tag> \  # 运行的镜像
   dj-process --config /path/to/config.yaml  # 类似的数据处理命令
 ```
 
@@ -267,7 +267,7 @@ docker run -dit \  # 在后台启动容器
   --name dj \
   -v <host_data_path>:<image_data_path> \
   -v ~/.cache/:/root/.cache/ \
-  data-juicer:latest /bin/bash
+  datajuicer/data-juicer:latest /bin/bash
 
 # 进入这个容器，然后您可以在编辑模式下使用 data-juicer
 docker exec -it <container_id> bash

data_juicer/ops/common/helper_func.py

@@ -32,7 +32,7 @@ def strip(document, strip_characters):
     emojis).
 
     :param document: document to be processed
-    :param strip_characters: characters uesd for stripping document
+    :param strip_characters: characters used for stripping document
     :return: stripped document
     """
     if not document:
@@ -76,7 +76,7 @@ def split_on_newline_tab_whitespace(document):
 
     First split on "\\\\n", then on "\\\\t", then on " ".
     :param document: document to be splited
-    :return: setence list obtained after splitting document
+    :return: sentence list obtained after splitting document
     """
     sentences = document.split('\n')
     sentences = [sentence.split('\t') for sentence in sentences]

data_juicer/ops/filter/image_size_filter.py

@@ -8,7 +8,7 @@
 
 @OPERATORS.register_module('image_size_filter')
 class ImageSizeFilter(Filter):
-    """Keep data samples whose image size (in bytes/kb/MB/...) within a
+    """Keep data samples whose image size (in Bytes/KB/MB/...) within a
     specific range.
     """
 
@@ -24,7 +24,7 @@ def __init__(self,
         :param min_size: The min image size to keep samples.  set to be "0" by
         default for no size constraint
         :param max_size: The max image size to keep samples.  set to be
-        "1Tb" by default, an approximate for un-limited case
+        "1TB" by default, an approximate for un-limited case
         :param any_or_all: keep this sample with 'any' or 'all' strategy of
             all images. 'any': keep this sample if any images meet the
             condition. 'all': keep this sample only if all images meet the

data_juicer/ops/mapper/remove_non_chinese_character_mapper.py

@@ -16,7 +16,7 @@ def __init__(self,
         """
         Initialization method.
 
-        :param keep_alphabet: whether to keep alpabet
+        :param keep_alphabet: whether to keep alphabet
         :param keep_number: whether to keep number
         :param keep_punc: whether to keep punctuation
         :param args: extra args