# NNOIR
## Install
```
pip install nnoir
```
## Example
### Create & Save
```python
inputs = [nnoir.Value(b'v0', dtype='<f4', shape=(10,10)),
nnoir.Value(b'v1', dtype='<f4', shape=(10,10))]
outputs = [nnoir.Value(b'v2', dtype='<f4', shape=(10,10))]
nodes = inputs + outputs
input_names = [ x.name for x in inputs ]
output_names = [ x.name for x in outputs ]
functions = [nnoir.functions.Add(input_names, output_names)]
result = nnoir.NNOIR(b'Add', b'add_test', '0.1', input_names, output_names, nodes, functions)
result.dump('add.nnoir')
```
### Load
```python
add_nnoir = nnoir.load('add.nnoir')
```
### Read/Write metadata from command line
```bash
$ nnoir-metadata resnet_50.nnoir
name = CaffeFunction
description =
generator.name = chainer
generator.version = 7.7.0
$ nnoir-metadata resnet_50.nnoir --write-description "This is resnet_50 (written by nnoir-metada)"
$ nnoir-metadata resnet_50.nnoir
name = CaffeFunction
description = This is resnet_50 (written by nnoir-metada)
generator.name = chainer
generator.version = 7.7.0
$ nnoir-metadata resnet_50.nnoir --write-name "CaffeFunction_V2"
$ nnoir-metadata resnet_50.nnoir
name = CaffeFunction_V2
description = This is resnet_50 (written by nnoir-metada)
generator.name = chainer
generator.version = 7.7.0
```
Raw data
{
"_id": null,
"home_page": "https://github.com/Idein/nnoir/tree/master/nnoir",
"name": "nnoir",
"maintainer": null,
"docs_url": null,
"requires_python": "<4.0,>=3.9",
"maintainer_email": null,
"keywords": "nnoir, machine learning",
"author": "Idein Inc.",
"author_email": null,
"download_url": "https://files.pythonhosted.org/packages/4c/10/1dcc05d224b725d598fe205ae363e31e4f2d25056042171b4688f88219bb/nnoir-1.3.0.tar.gz",
"platform": null,
"description": "# NNOIR\n\n## Install\n\n```\npip install nnoir\n```\n\n## Example\n\n### Create & Save\n\n```python\ninputs = [nnoir.Value(b'v0', dtype='<f4', shape=(10,10)),\n nnoir.Value(b'v1', dtype='<f4', shape=(10,10))]\noutputs = [nnoir.Value(b'v2', dtype='<f4', shape=(10,10))]\nnodes = inputs + outputs\ninput_names = [ x.name for x in inputs ]\noutput_names = [ x.name for x in outputs ]\nfunctions = [nnoir.functions.Add(input_names, output_names)]\nresult = nnoir.NNOIR(b'Add', b'add_test', '0.1', input_names, output_names, nodes, functions)\nresult.dump('add.nnoir')\n```\n\n### Load\n\n```python\nadd_nnoir = nnoir.load('add.nnoir')\n```\n\n### Read/Write metadata from command line\n\n```bash\n$ nnoir-metadata resnet_50.nnoir\nname = CaffeFunction\ndescription =\ngenerator.name = chainer\ngenerator.version = 7.7.0\n$ nnoir-metadata resnet_50.nnoir --write-description \"This is resnet_50 (written by nnoir-metada)\"\n$ nnoir-metadata resnet_50.nnoir \nname = CaffeFunction\ndescription = This is resnet_50 (written by nnoir-metada)\ngenerator.name = chainer\ngenerator.version = 7.7.0\n$ nnoir-metadata resnet_50.nnoir --write-name \"CaffeFunction_V2\"\n$ nnoir-metadata resnet_50.nnoir\nname = CaffeFunction_V2\ndescription = This is resnet_50 (written by nnoir-metada)\ngenerator.name = chainer\ngenerator.version = 7.7.0\n```",
"bugtrack_url": null,
"license": "MIT",
"summary": "API for NNOIR",
"version": "1.3.0",
"project_urls": {
"Homepage": "https://github.com/Idein/nnoir/tree/master/nnoir",
"Repository": "https://github.com/Idein/nnoir/tree/master/nnoir"
},
"split_keywords": [
"nnoir",
" machine learning"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "074eafe381783e5935b2b6621f6b915b0e1cee07b3d1de618e1187b932ce0724",
"md5": "58049633e967013facf72e62669b003b",
"sha256": "890f718ed01a56b450837fde712a0ef41e54f5610712b105404f1cf676de53b2"
},
"downloads": -1,
"filename": "nnoir-1.3.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "58049633e967013facf72e62669b003b",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": "<4.0,>=3.9",
"size": 32958,
"upload_time": "2024-12-04T01:50:32",
"upload_time_iso_8601": "2024-12-04T01:50:32.469603Z",
"url": "https://files.pythonhosted.org/packages/07/4e/afe381783e5935b2b6621f6b915b0e1cee07b3d1de618e1187b932ce0724/nnoir-1.3.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "4c101dcc05d224b725d598fe205ae363e31e4f2d25056042171b4688f88219bb",
"md5": "fc49e7701dc464cd818308caa68e1256",
"sha256": "4d6f1644958cb37401dd5c230fc2e8558f48c7db261c0eb477dd25b8e759b944"
},
"downloads": -1,
"filename": "nnoir-1.3.0.tar.gz",
"has_sig": false,
"md5_digest": "fc49e7701dc464cd818308caa68e1256",
"packagetype": "sdist",
"python_version": "source",
"requires_python": "<4.0,>=3.9",
"size": 14570,
"upload_time": "2024-12-04T01:50:33",
"upload_time_iso_8601": "2024-12-04T01:50:33.999607Z",
"url": "https://files.pythonhosted.org/packages/4c/10/1dcc05d224b725d598fe205ae363e31e4f2d25056042171b4688f88219bb/nnoir-1.3.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-12-04 01:50:33",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "Idein",
"github_project": "nnoir",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"circle": true,
"lcname": "nnoir"
}
JSON
