master
SV08 3 years ago
5 changed file(s) with 154 addition(s) and 297 deletion(s). Raw diff Collapse all Expand all
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_README.ipynb less more
55 "source": [
66 "## 1. 项目介绍\n",
77 "\n",
8 " - 项目是由模块组成、有特定功能的程序。它能够满足用户的直接使用需求，例如[古诗词生成器](https://momodel.cn/explore/5bfb634e1afd943c623dd9cf?type=app&tab=1)、[风格迁移](https://momodel.cn/explore/5bfb634e1afd943c623dd9cf?type=app&tab=1)等。\n",
9 " - 开发项目过程中你可以导入数据集，也可以通过每个 cell 上方工具栏的`<+>`直接插入[模块](https://momodel.cn/modules)和代码块。\n",
10 " - 你可以将开发好的项目进行[部署](https://momodel.cn/docs/#/zh-cn/%E5%BC%80%E5%8F%91%E5%92%8C%E9%83%A8%E7%BD%B2%E4%B8%80%E4%B8%AA%E9%A1%B9%E7%9B%AE)，项目部署成功并选择正式版本发布后会展示在“项目”页面，用户可以在线使用，也可以通过 API 调用。\n",
8 " - 古诗生成器基于RNN开发，训练数据为几万首唐诗，可以输入想要的开始字、想要的意境和想要的长度，提交后生成想要的古诗。\n",
119 "\n",
1210 " - 项目目录结构:\n",
1311 "\n",
1614 " - ```_README.md```*-----说明文档*\n",
1715 " - ```app_spec.yml```*-----定义项目的输入输出，为部署服务*\n",
1816 " - ```coding_here.ipynb```*-----输入并运行代码*"
19 ]
20 },
21 {
22 "cell_type": "code",
23 "execution_count": null,
24 "metadata": {},
25 "outputs": [],
26 "source": [
27 "def handle(conf):\n",
28 " \"\"\"\n",
29 " 该方法是部署之后，其他人调用你的服务时候的处理方法。\n",
30 " 请按规范填写参数结构，这样我们就能替你自动生成配置文件，方便其他人的调用。\n",
31 " 范例：\n",
32 " params['key'] = value # value_type: str # description: some description\n",
33 " value_type 可以选择：img, video, audio, str, int, float, [int], [str], [float]\n",
34 " 参数请放到params字典中，我们会自动解析该变量。\n",
35 " \"\"\"\n",
36 "\n",
37 " param1 = conf['param1'] # value_type: str # description: some description\n",
38 " # add your code\n",
39 " return {'ret1': 'cat'}\n",
40 " "
41 ]
42 },
43 {
44 "cell_type": "code",
45 "execution_count": null,
46 "metadata": {},
47 "outputs": [],
48 "source": [
49 "def handle(conf):\n",
50 " \"\"\"\n",
51 " 该方法是部署之后，其他人调用你的服务时候的处理方法。\n",
52 " 请按规范填写参数结构，这样我们就能替你自动生成配置文件，方便其他人的调用。\n",
53 " 范例：\n",
54 " params['key'] = value # value_type: str # description: some description\n",
55 " value_type 可以选择：img, video, audio, str, int, float, [int], [str], [float]\n",
56 " 参数请放到params字典中，我们会自动解析该变量。\n",
57 " \"\"\"\n",
58 "\n",
59 " param1 = conf['param1'] # value_type: str # description: some description\n",
60 " # add your code\n",
61 " return {'ret1': 'cat'}\n",
62 " "
63 ]
64 },
65 {
66 "cell_type": "markdown",
67 "metadata": {},
68 "source": [
69 "\n",
70 "## 2. 开发环境简介\n",
71 "\n",
72 "你当前所在的页面 Notebook 是一个内嵌 JupyterLab 的在线类 IDE 编程环境，开发过程中可以使用页面右侧的 API 文档进行快速查询。Notebook 有以下主要功能：\n",
73 "\n",
74 "- [调用数据集、模块和代码块资源](https://momodel.cn/docs/#/zh-cn/%E5%A6%82%E4%BD%95%E5%AF%BC%E5%85%A5%E5%B9%B6%E4%BD%BF%E7%94%A8%E6%A8%A1%E5%9D%97%E5%92%8C%E6%95%B0%E6%8D%AE%E9%9B%86)\n",
75 "- [多人代码协作](https://momodel.cn/docs/#/zh-cn/%E5%9C%A8Mo%E8%BF%90%E8%A1%8C%E4%BD%A0%E7%9A%84%E7%AC%AC%E4%B8%80%E6%AE%B5%E4%BB%A3%E7%A0%81?id=_7-%e4%bd%a0%e5%8f%af%e4%bb%a5%e9%82%80%e8%af%b7%e5%a5%bd%e5%8f%8b%e8%bf%9b%e8%a1%8c%e5%8d%8f%e4%bd%9c)\n",
76 "- [在 GPU 资源上训练机器学习模型](https://momodel.cn/docs/#/zh-cn/%E5%9C%A8GPU%E6%88%96CPU%E8%B5%84%E6%BA%90%E4%B8%8A%E8%AE%AD%E7%BB%83%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E6%A8%A1%E5%9E%8B)\n",
77 "- [简单部署](https://momodel.cn/docs/#/zh-cn/%E5%BC%80%E5%8F%91%E5%92%8C%E9%83%A8%E7%BD%B2%E4%B8%80%E4%B8%AA%E9%A1%B9%E7%9B%AE)\n",
78 "\n",
79 "快来动手试试吧！点击左侧工具栏的新建文件图标即可选择你需要的文件类型。\n",
80 "\n",
81 "<img src='https://imgbed.momodel.cn/006tNc79gy1g61agfcv23j31c30u0789.jpg' width=100% height=100%>\n",
82 "\n",
83 "\n",
84 "\n",
85 "左侧和右侧工具栏都可根据使用需要进行收合。\n",
86 "<img src='https://imgbed.momodel.cn/collapse_tab.2019-09-06 11_07_44.gif' width=100% height=100%>"
87 ]
88 },
89 {
90 "cell_type": "markdown",
91 "metadata": {},
92 "source": [
93 "## 3. 快捷键与代码补全\n",
94 "Mo Notebook 已完全采用 Jupyter Notebook 的原生快捷键，并且支持 `tab` 代码补全。\n",
95 "\n",
96 "运行代码：`shift` + `enter` 或者 `shift` + `return`"
97 ]
98 },
99 {
100 "cell_type": "markdown",
101 "metadata": {},
102 "source": [
103 "## 4. 常用指令介绍\n",
104 "\n",
105 "- 解压上传后的文件\n",
106 "\n",
107 "在 cell 中输入并运行以下命令：\n",
108 "```!7zx file_name.zip```\n",
109 "\n",
110 "- 查看所有包（package）\n",
111 "\n",
112 "`!pip list --format=columns`\n",
113 "\n",
114 "- 检查是否已有某个包\n",
115 "\n",
116 "`!pip show package_name`\n",
117 "\n",
118 "- 安装缺失的包\n",
119 "\n",
120 "`!pip install package_name`\n",
121 "\n",
122 "- 更新已有的包\n",
123 "\n",
124 "`!pip install package_name --upgrade`\n",
125 "\n",
126 "\n",
127 "- 使用包\n",
128 "\n",
129 "`import package_name`\n",
130 "\n",
131 "- 显示当前目录下的档案及目录\n",
132 "\n",
133 "`ls`\n",
134 "\n",
135 "- 使用引入的数据集\n",
136 "\n",
137 "数据集被引入后存放在 datasets 文件夹下，注意，这个文件夹是只读的，不可修改。如果需要修改，可在 Notebook 中使用\n",
138 "\n",
139 "`!cp -R ./datasets/<imported_dataset_dir> ./<your_folder>`\n",
140 "\n",
141 "指令将其复制到其他文件夹后再编辑，对于引入的数据集中的 zip 文件，可使用\n",
142 "\n",
143 "`!7zx ./datasets/<imported_dataset_dir>/<XXX.zip> ./<your_folder>`\n",
144 "\n",
145 "指令解压缩到其他文件夹后使用"
146 ]
147 },
148 {
149 "cell_type": "markdown",
150 "metadata": {},
151 "source": [
152 "## 5. 其他可参考资源\n",
153 "\n",
154 "- [帮助文档](https://momodel.cn/docs/#/)：基本页面介绍和常见问题都可以在里面找到\n",
155 "- [平台功能教程](https://momodel.cn/classroom/class/5c5696cd1afd9458d456bf54)：通过图文结合的 Notebook 详细介绍开发环境基本功能和操作\n",
156 "- [从 Python 到人工智能](https://momodel.cn/classroom/course/detail?&id=60f02c635076ff487bce4c6f)：超易入门的 Python 课程\n",
157 "- [吴恩达机器学习](https://momodel.cn/classroom/class/5c5696191afd94720cc94533)：机器学习经典课程\n",
158 "- [李宏毅机器学习](https://momodel.cn/classroom/class/5d63dde21afd9461419f5ebf)：中文世界最好的机器学习课程\n",
159 "- [机器学习实战](https://momodel.cn/classroom/class/60af61b6f955c61c2cddfcb5)：通过实操指引完成独立的模型，掌握相应的机器学习知识\n",
160 "- [深度学习实战](https://momodel.cn/classroom/class/5c680b311afd943a9f70901b)：通过实操指引完成独立的模型，掌握相应的深度学习知识\n",
161 "- [模块开发](https://momodel.cn/modules)：关于模型训练、开发与部署的高阶教程"
16217 ]
16318 }
16419 ],
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job_logs/job-cpu-6243b431b38562dfcd9e9e0e.log less more
44 2022-03-30T01:37:00.202308379Z from data import get_data
55 2022-03-30T01:37:00.202332663Z ModuleNotFoundError: No module named 'data'
66 2022-03-30T01:37:00.318630589Z SYSTEM: Finishing...
7 2022-03-30T01:37:00.619572806Z SYSTEM: Error Exists!
+1
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job_logs/job-gpu-6243b389c415503e59e51369.log less more
44 2022-03-30T01:34:09.514459087Z from data import get_data
55 2022-03-30T01:34:09.514480993Z ModuleNotFoundError: No module named 'data'
66 2022-03-30T01:34:09.612018351Z SYSTEM: Finishing...
7 2022-03-30T01:34:09.920619034Z SYSTEM: Error Exists!
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main.py less more
226226 return result
227227
228228
229 if __name__ == '__main__':
230 conf={'start_words':"雨",'prefix_words':"天晴", 'max_gen_len':100}
231 start_words = conf['start_words'] #诗歌开始
232 prefix_words = conf['prefix_words'] #诗歌语境
233 max_gen_len = conf['max_gen_len'] #诗歌最大长度
234 cof={
235 "max_gen_len": max_gen_len, # 生成诗歌最长长度
236 "prefix_words":prefix_words, # 不是诗歌的组成部分，用来控制生成诗歌的意境
237 "start_words" : start_words # 诗歌开始
238 }
239 result = gen(**cof)
240 # return {'ret1':result}
241 print(result)
229 # if __name__ == '__main__':
230 # conf={'start_words':"雨",'prefix_words':"天晴", 'max_gen_len':100}
231 # start_words = conf['start_words'] #诗歌开始
232 # prefix_words = conf['prefix_words'] #诗歌语境
233 # max_gen_len = conf['max_gen_len'] #诗歌最大长度
234 # cof={
235 # "max_gen_len": max_gen_len, # 生成诗歌最长长度
236 # "prefix_words":prefix_words, # 不是诗歌的组成部分，用来控制生成诗歌的意境
237 # "start_words" : start_words # 诗歌开始
238 # }
239 # result = gen(**cof)
240 # # return {'ret1':result}
241 # print(result)
+138
-138
project_requirements.txt less more
0 cffi==1.14.6
1 packaging==21.0
2 pyrsistent==0.18.0
3 baytune==0.3.12
4 google-pasta==0.2.0
5 imageio==2.8.0
6 jupyterlab-pygments==0.1.1
7 asttokens==2.0.5
8 jdcal==1.4.1
9 mpmath==1.2.1
10 plac==1.1.3
11 click==8.0.1
12 cymem==2.0.5
13 tensorflow-privacy==0.5.2
14 requests-oauthlib==1.3.0
15 jmespath==0.10.0
16 pyasn1==0.4.8
17 joblib==1.0.1
18 zipp==3.4.1
19 regex==2021.8.3
20 func-timeout==4.3.5
21 pyasn1-modules==0.2.8
22 et-xmlfile==1.1.0
23 nest-asyncio==1.5.1
24 attrs==19.3.0
25 jieba==0.42.1
26 dlib==19.22.0
27 torchtext==0.6.0
28 opt-einsum==3.3.0
29 tinycss2==1.1.0
30 rsa==4.7.2
31 distlib==0.3.2
32 cachetools==3.1.1
33 importlib-metadata==3.7.2
34 tokenizers==0.9.4
35 wrapt==1.12.1
36 smart-open==5.1.0
37 tensorflow-model-optimization==0.4.1
38 xlrd==1.2.0
39 s3transfer==0.3.3
40 portpicker==1.3.9
41 pydot==1.4.1
42 easydict==1.9
43 nltk==3.5
44 PyWavelets==1.1.1
45 google-auth==1.27.1
46 calysto==1.0.6
47 kanren==0.2.3
48 cairocffi==1.2.0
49 typing-extensions==3.7.4.3
50 retrying==1.3.3
51 openpyxl==2.6.4
52 tensorflow-addons==0.11.2
53 boto3==1.16.25
54 Cython==0.29.20
55 argon2-cffi==20.1.0
56 typeguard==2.12.1
57 astunparse==1.6.3
58 configparser==5.0.2
59 copulas==0.3.3
60 sympy==1.6.2
61 jsonpointer==2.2
62 pyglet==1.5.0
63 tensorflow-estimator==2.3.0
64 preshed==3.0.5
65 greenlet==1.1.1
66 google-auth-oauthlib==0.4.3
67 toolz==0.11.1
68 Shapely==1.7.0
69 catalogue==1.0.0
70 mindspore==https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.0.0/MindSpore/cpu/ubuntu_x86/mindspore-1.0.0-cp37-cp37m-linux_x86_64.whl
71 matplotlib-inline==0.1.2
72 minepy==1.2.4
73 word2vec==0.11.1
74 graphviz==0.14
75 blis==0.4.1
76 debugpy==1.4.1
77 cmake==3.21.1
78 unification==0.2.2
79 semantic-version==2.8.5
80 filelock==3.0.12
81 yellowbrick==1.1
82 PyAudio==0.2.11
83 pygame==2.0.1
84 CairoSVG==2.5.2
85 numpyencoder==0.3.0
86 torchvision==0.5.0+cpu
87 botocore==1.19.25
88 dm-tree==0.1.6
89 pyOpenSSL==20.0.1
90 srsly==1.0.5
91 jsonpatch==1.32
92 nbclient==0.5.0
93 networkx==2.6.2
94 minio==5.0.10
95 plotly==4.8.1
96 gensim==3.8.3
97 defusedxml==0.7.1
98 fire==0.4.0
99 async-generator==1.10
100 cssselect2==0.4.1
101 rouge==1.0.0
102 torchfile==0.1.0
103 tensorboard-plugin-wit==1.8.0
104 murmurhash==1.0.5
105 Augmentor==0.2.8
106 pytorch-transformers==1.2.0
107 oauthlib==3.1.0
108 transformers==4.1.1
109 certipy==0.1.3
110 cloudpickle==1.3.0
111 multipledispatch==0.6.0
112 websocket-client==1.3.1
113 tensorboardX==2.0
114 tqdm==4.46.1
115 visdom==0.1.8.9
116 sacremoses==0.0.45
0117 sentencepiece==0.1.91
1 toolz==0.11.1
118 paddlepaddle==2.0.1
119 XlsxWriter==1.4.3
120 cryptography==3.4.7
121 platformdirs==2.1.0
122 scikit-image==0.15.0
123 torchnet==0.0.4
124 thinc==7.4.1
2125 en-core-web-sm==https://files.momodel.cn/en_core_web_sm-2.3.0.tar.gz
3 botocore==1.19.25
4 openpyxl==2.6.4
5 google-auth-oauthlib==0.4.3
6 jsonpatch==1.32
7 paddlepaddle==2.0.1
8 tensorboard-plugin-wit==1.8.0
126 svgwrite==1.4.1
127 imbalanced-learn==0.6.2
128 pytorch-pretrained-bert==0.6.2
129 torch==1.4.0+cpu
130 wasabi==0.8.2
131 tf-slim==1.1.0
132 jupyterlab-server==0.2.0
133 imgaug==0.4.0
134 install==1.3.4
135 ipdb==0.13.2
9136 gym==0.17.2
10 gensim==3.8.3
11 dm-tree==0.1.6
12 tqdm==4.46.1
13 pyOpenSSL==20.0.1
14 google-auth==1.27.1
15 pytorch-transformers==1.2.0
16 Cython==0.29.20
17 boto3==1.16.25
18 plac==1.1.3
137 metakernel==0.27.5
138 pycparser==2.20
139 tdqm==0.0.1
140 tensorflow-federated==0.17.0
19141 backports.entry-points-selectable==1.1.0
20 sympy==1.6.2
21 Augmentor==0.2.8
22 copulas==0.3.3
23 multipledispatch==0.6.0
24 visdom==0.1.8.9
25 pyasn1==0.4.8
26 sacremoses==0.0.45
27 cmake==3.21.1
28 torchfile==0.1.0
29 argon2-cffi==20.1.0
30 certipy==0.1.3
31 configparser==5.0.2
32 jmespath==0.10.0
33 unification==0.2.2
34 plotly==4.8.1
35 opt-einsum==3.3.0
36 word2vec==0.11.1
37 pycparser==2.20
38 metakernel==0.27.5
39 defusedxml==0.7.1
40 xlrd==1.2.0
41 func-timeout==4.3.5
42 ipdb==0.13.2
43 smart-open==5.1.0
44 transformers==4.1.1
45 kanren==0.2.3
46 graphviz==0.14
47 nest-asyncio==1.5.1
48 PyAudio==0.2.11
49 jieba==0.42.1
50 astunparse==1.6.3
51 CairoSVG==2.5.2
52 XlsxWriter==1.4.3
53 tensorflow-model-optimization==0.4.1
54 pyasn1-modules==0.2.8
55 tinycss2==1.1.0
56 mindspore==https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.0.0/MindSpore/cpu/ubuntu_x86/mindspore-1.0.0-cp37-cp37m-linux_x86_64.whl
57 tokenizers==0.9.4
58 yellowbrick==1.1
59 matplotlib-inline==0.1.2
60 joblib==1.0.1
61 pyglet==1.5.0
62 tensorflow-addons==0.11.2
63 Shapely==1.7.0
64 minepy==1.2.4
65 PyWavelets==1.1.1
66 networkx==2.6.2
67 mpmath==1.2.1
68 pydot==1.4.1
69 semantic-version==2.8.5
70 cloudpickle==1.3.0
71 cffi==1.14.6
72 imgaug==0.4.0
73 google-pasta==0.2.0
74 jupyterlab-server==0.2.0
75 asttokens==2.0.5
76 srsly==1.0.5
77 svgwrite==1.4.1
78 pyrsistent==0.18.0
79 attrs==19.3.0
80 debugpy==1.4.1
81 websocket-client==1.3.1
82 dlib==19.22.0
83 baytune==0.3.12
84 cryptography==3.4.7
85 tdqm==0.0.1
86 torchnet==0.0.4
87 oauthlib==3.1.0
88 et-xmlfile==1.1.0
89 jsonpointer==2.2
90 jupyterlab-pygments==0.1.1
91 zipp==3.4.1
92 portpicker==1.3.9
93 typing-extensions==3.7.4.3
94 fire==0.4.0
95 scikit-image==0.15.0
96 click==8.0.1
97142 spacy==2.3.2
98 pytorch-pretrained-bert==0.6.2
99 cssselect2==0.4.1
100 imageio==2.8.0
101 platformdirs==2.1.0
102 retrying==1.3.3
103 torchvision==0.5.0+cpu
104 preshed==3.0.5
105 torch==1.4.0+cpu
106 requests-oauthlib==1.3.0
107 easydict==1.9
108 install==1.3.4
109 blis==0.4.1
110 torchtext==0.6.0
111 tensorflow-privacy==0.5.2
112 wasabi==0.8.2
113 cachetools==3.1.1
114 tensorboardX==2.0
115 minio==5.0.10
116 filelock==3.0.12
117 nltk==3.5
118 imbalanced-learn==0.6.2
119 cymem==2.0.5
120 async-generator==1.10
121 distlib==0.3.2
122 murmurhash==1.0.5
123 jdcal==1.4.1
124 typeguard==2.12.1
125 thinc==7.4.1
126 regex==2021.8.3
127 tensorflow-federated==0.17.0
128 nbclient==0.5.0
129 catalogue==1.0.0
130 packaging==21.0
131 tf-slim==1.1.0
132 tensorflow-estimator==2.3.0
133 importlib-metadata==3.7.2
134 pygame==2.0.1
135 s3transfer==0.3.3
136 cairocffi==1.2.0
137 rouge==1.0.0
138 numpyencoder==0.3.0
139 greenlet==1.1.1
140 calysto==1.0.6
141 rsa==4.7.2
142 wrapt==1.12.1