{"id":3921,"date":"2019-04-22T07:00:48","date_gmt":"2019-04-21T22:00:48","guid":{"rendered":"https:\/\/www.ecomottblog.com\/?p=3921"},"modified":"2019-04-22T09:24:55","modified_gmt":"2019-04-22T00:24:55","slug":"%e3%82%bd%e3%83%8b%e3%83%bcneural-network-console1%e3%81%a7%e5%ad%a6%e7%bf%92%e3%81%95%e3%81%9b%e3%81%9f%e3%83%8d%e3%83%83%e3%83%88%e3%83%af%e3%83%bc%e3%82%af%e3%82%92nnabla-neural-network-librari","status":"publish","type":"post","link":"https:\/\/www.ecomottblog.com\/?p=3921","title":{"rendered":"\u30bd\u30cb\u30fcNeural Network Console\u3067\u5b66\u7fd2\u3055\u305b\u305f\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092nnabla (Neural Network Libraries)\u3067\u63a8\u8ad6\u3059\u308b\u30b7\u30f3\u30d7\u30eb\u306a\u65b9\u6cd5"},"content":{"rendered":"<p>1\u5e74\u307b\u3069\u524d\u3001\u30bd\u30cb\u30fc Neural Network Console \u3068 \u30a8\u30af\u30bb\u30eb\u3067\u59cb\u3081\u308b \u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u6295\u7a3f\u3057\u307e\u3057\u305f\u3002<\/p>\n<blockquote class=\"wp-embedded-content\" data-secret=\"GofCyXTemZ\"><p><a href=\"https:\/\/www.ecomottblog.com\/?p=2424\">\u30bd\u30cb\u30fc Neural Network Console \u3068 \u30a8\u30af\u30bb\u30eb\u3067\u59cb\u3081\u308b \u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af<\/a><\/p><\/blockquote>\n<p><iframe class=\"wp-embedded-content\" sandbox=\"allow-scripts\" security=\"restricted\" style=\"position: absolute; clip: rect(1px, 1px, 1px, 1px);\" title=\"&#8220;\u30bd\u30cb\u30fc Neural Network Console \u3068 \u30a8\u30af\u30bb\u30eb\u3067\u59cb\u3081\u308b \u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af&#8221; &#8212; ecomott blog\" src=\"https:\/\/www.ecomottblog.com\/?p=2424&#038;embed=true#?secret=ESWxCkeO38#?secret=GofCyXTemZ\" data-secret=\"GofCyXTemZ\" width=\"500\" height=\"282\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\"><\/iframe><\/p>\n<p>Neural Network Console\uff08\u4ee5\u4e0b\u3001NNC\uff09\u306f\u3001\u30d7\u30ed\u30b0\u30e9\u30e0\u3092\u7d44\u307e\u305a\u3068\u3082\u3001\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u8a2d\u8a08\u30fb\u5b66\u7fd2\u30fb\u691c\u8a3c\u30fb\u63a8\u8ad6\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u3063\u3066\u3044\u307e\u3059\u3002\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3082\u5c55\u958b\u3059\u308b\u3060\u3051\u306a\u306e\u3067\u3001Windows\u3067\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u59cb\u3081\u3088\u3046\u3068\u601d\u3063\u3066\u3044\u308b\u65b9\u306b\u306f\u3001\u304a\u3059\u3059\u3081\u306e\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u3067\u3059\u3002\u3044\u308d\u3044\u308d\u4f7f\u3063\u3066\u3044\u304f\u3068\u3001\u5b66\u7fd2\u7d50\u679c\u3092\u4f7f\u3066\u63a8\u8ad6\u3060\u3051\u306e\u30b7\u30b9\u30c6\u30e0\u3092\u4f5c\u308a\u305f\u304f\u306a\u308b\u3053\u3068\u3067\u3057\u3087\u3046\u3002\u6298\u89d2\u3001\u5b66\u7fd2\u3057\u305f\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u30af\u30e9\u30a6\u30c9\u3084\u30a8\u30c3\u30b8\u3067\u4f7f\u308f\u306a\u3044\u306e\u306f\u3082\u3063\u305f\u3044\u306a\u3044\u3068\u8003\u3048\u3066\u3044\u308b\u65b9\u3082\u591a\u3044\u3068\u601d\u3044\u307e\u3059\u3002<br \/>\n\u4eca\u56de\u306f\u3001NNC\u3067\u5b66\u7fd2\u3057\u305f\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u7528\u3044\u3066\u3001\u540c\u3058\u304f\u30bd\u30cb\u30fc\u304c\u516c\u958b\u3057\u3066\u3044\u308bNeural Network libraries\uff08\u901a\u79f0\u3001nnabla\u3002\u4ee5\u4e0b\u3001nnabla\uff09\u3092\u4f7f\u3046\u3053\u3068\u3067\u3001\u9a5a\u304f\u307b\u3069\u7c21\u5358\u306b\u63a8\u8ad6\u30b7\u30b9\u30c6\u30e0\u3092\u4f5c\u308b\u65b9\u6cd5\u3092\u3054\u7d39\u4ecb\u3057\u307e\u3059\u3002<br \/>\n<!--more--><\/p>\n<h2>\uff11\uff0e\u30b4\u30fc\u30eb\u8a2d\u5b9a<\/h2>\n<p>\u3053\u306e\u30d6\u30ed\u30b0\u3067\u306f\u3001<br \/>\n* AI\u30a8\u30f3\u30b8\u30cb\u30a2<sup id=\"fnref-3921-3\"><a href=\"#fn-3921-3\">1<\/a><\/sup>\u304c\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u4f5c\u308a\u3001NNC\u3067\u6559\u5e2b\u30c7\u30fc\u30bf\u3092\u5b66\u7fd2\u3055\u305b\u3066\u3001\u30d7\u30ed\u30b0\u30e9\u30de<sup id=\"fnref-3921-4\"><a href=\"#fn-3921-4\">2<\/a><\/sup>\u306b\u305d\u306e\u7d50\u679c\u3092\u6e21\u3059<br \/>\n* \u30d7\u30ed\u30b0\u30e9\u30de\u304c\u3001\u305d\u306e\u7d50\u679c\u3092\u4f7f\u3063\u3066\u3001\u63a8\u8ad6\u30b7\u30b9\u30c6\u30e0<sup id=\"fnref-3921-5\"><a href=\"#fn-3921-5\">3<\/a><\/sup>\u3092\u4f5c\u308b<\/p>\n<p>\u3068\u3044\u3046\u30d7\u30ed\u30bb\u30b9\u3092\u8003\u3048\u307e\u3059\u3002<\/p>\n<h2>\uff12\uff0e\u30d7\u30ed\u30b0\u30e9\u30de\u306b\u6e21\u3059\u3082\u306e\u306f\u3001results.nnp \u3060\u3051<\/h2>\n<p>NNC\u3067\u5b66\u7fd2\u3055\u305b\u305f\u7d50\u679c\u306f\u3001\u901a\u5e38\u3001results.nnp\u3068\u3044\u3046\u30d5\u30a1\u30a4\u30eb\u306b\u4fdd\u5b58\u3055\u308c\u3066\u3044\u307e\u3059\u3002AI\u30a8\u30f3\u30b8\u30cb\u30a2\u306f\u3001\u3053\u306eresults.nnp\u3060\u3051\u3092\u30d7\u30ed\u30b0\u30e9\u30de\u306b\u6e21\u3057\u3066\u304f\u3060\u3055\u3044\u3002<sup id=\"fnref-3921-6\"><a href=\"#fn-3921-6\">4<\/a><\/sup><br \/>\n\u6b21\u306b\u3001\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u56f3\u3068config\u30bf\u30d6\u306eExcutor\u6b04\u306eNetwork\u5909\u6570\u306e\u5024<sup id=\"fnref-3921-7\"><a href=\"#fn-3921-7\">5<\/a><\/sup>\u3092\u4f1d\u3048\u3066\u304f\u3060\u3055\u3044\u3002<br \/>\n\u6700\u5f8c\u306b\u3001\u5165\u529b\u306e\u30c7\u30fc\u30bf\u5f62\u5f0f(JPEG\u30d5\u30a1\u30a4\u30eb\u3068\u304bCSV\u30d5\u30a1\u30a4\u30eb\u3068\u304b)\u3084\u51fa\u529b\u5f62\u5f0f\uff08\u753b\u50cf\u30d5\u30a1\u30a4\u30eb\u3068\u304b\u6a19\u6e96\u51fa\u529b\u3067\u6570\u5024\u3068\u304b\uff09\u304c\u3069\u3046\u306a\u3063\u3066\u3044\u308b\u304b\u7b49\u306e\u60c5\u5831\u4ea4\u63db\u3092\u3057\u3066\u304f\u3060\u3055\u3044\u3002<sup id=\"fnref-3921-8\"><a href=\"#fn-3921-8\">6<\/a><\/sup><br \/>\nAI\u30a8\u30f3\u30b8\u30cb\u30a2\u306f\u3053\u308c\u3067\u3053\u306e\u696d\u52d9\u306f\u5b8c\u4e86\u3067\u3059\u3002<sup id=\"fnref-3921-9\"><a href=\"#fn-3921-9\">7<\/a><\/sup><\/p>\n<h2>\uff13\uff0eresults.nnp\u3092\u30c1\u30a7\u30c3\u30af\u3059\u308b<\/h2>\n<p>\u30d7\u30ed\u30b0\u30e9\u30de\u306f\u4f1d\u3048\u3089\u308c\u305f\u5404\u7a2e\u60c5\u5831\u3068results.nnp\u3092\u30c1\u30a7\u30c3\u30af\u3059\u308b\u4ee5\u4e0b\u306e\u30d7\u30ed\u30b0\u30e9\u30e0\u7d50\u679c\u3092\u7167\u3089\u3057\u3066\u3001\u63a8\u8ad6\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u540d\u3001\u5165\u51fa\u529b\u540d<sup id=\"fnref-3921-10\"><a href=\"#fn-3921-10\">8<\/a><\/sup>\u3092\u6c7a\u5b9a\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n<pre><code>from nnabla.utils.nnp_graph import NnpLoader\nimport os\n\n\nnnppath = \"results.nnp\"\nif os.path.isfile(nnppath):\n    # Read a .nnp file.\n    nnp = NnpLoader(nnppath)\n    for x in nnp.get_network_names():\n        print(\"----------\\nNetworks:\", x)\n        net = nnp.get_network(x, batch_size = 1)\n        for y in net.inputs:\n            print(\"Inputs: \", y)\n        for z in net.outputs:\n            print(\"Outputs: \",z)\n<\/code><\/pre>\n<h3>\u4f8b<\/h3>\n<p>\u4f8b\u3048\u3070\u3001\u3053\u306e\u3088\u3046\u306a\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u300cMain\u300d\uff08\u65e2\u5b9a\u5024\uff09\u3068\u3057\u3066\u4f5c\u3063\u305f\u5834\u5408\u3001<\/p>\n<div id=\"attachment_3922\" style=\"width: 965px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-3922\" src=\"https:\/\/www.ecomottblog.com\/wp-content\/uploads\/2019\/04\/network.jpg\" alt=\"\" width=\"955\" height=\"791\" class=\"size-full wp-image-3922\" srcset=\"https:\/\/www.ecomottblog.com\/wp-content\/uploads\/2019\/04\/network.jpg 955w, https:\/\/www.ecomottblog.com\/wp-content\/uploads\/2019\/04\/network-300x248.jpg 300w, https:\/\/www.ecomottblog.com\/wp-content\/uploads\/2019\/04\/network-768x636.jpg 768w, https:\/\/www.ecomottblog.com\/wp-content\/uploads\/2019\/04\/network-258x214.jpg 258w, https:\/\/www.ecomottblog.com\/wp-content\/uploads\/2019\/04\/network-282x234.jpg 282w\" sizes=\"(max-width: 955px) 100vw, 955px\" \/><p id=\"caption-attachment-3922\" class=\"wp-caption-text\">Main\u30cd\u30c3\u30c8\u30ef\u30fc\u30af<\/p><\/div>\n<p>\u81ea\u52d5\u7684\u306b\u3001\u300cMainValidation\u300d\u3068\u300cMainRuntime\u300d\u304c\u751f\u6210\u3055\u308c\u3001config\u306eExecutor\u6b04\u306eNetwork\u306b\u300cMainRuntime\u300d\u304c\u767b\u9332\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u3053\u308c\u304c\u63a8\u8ad6\u3067\u4f7f\u7528\u3059\u308b\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3067\u3059\u3002<\/p>\n<div id=\"attachment_3923\" style=\"width: 875px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-3923\" src=\"https:\/\/www.ecomottblog.com\/wp-content\/uploads\/2019\/04\/config.jpg\" alt=\"\" width=\"865\" height=\"681\" class=\"size-full wp-image-3923\" srcset=\"https:\/\/www.ecomottblog.com\/wp-content\/uploads\/2019\/04\/config.jpg 865w, https:\/\/www.ecomottblog.com\/wp-content\/uploads\/2019\/04\/config-300x236.jpg 300w, https:\/\/www.ecomottblog.com\/wp-content\/uploads\/2019\/04\/config-768x605.jpg 768w, https:\/\/www.ecomottblog.com\/wp-content\/uploads\/2019\/04\/config-272x214.jpg 272w, https:\/\/www.ecomottblog.com\/wp-content\/uploads\/2019\/04\/config-282x222.jpg 282w\" sizes=\"(max-width: 865px) 100vw, 865px\" \/><p id=\"caption-attachment-3923\" class=\"wp-caption-text\">\u30b3\u30f3\u30d5\u30a3\u30b0<\/p><\/div>\n<p>\u5148\u307b\u3069\u306e\u30c1\u30a7\u30c3\u30af\u30d7\u30ed\u30b0\u30e9\u30e0\u3092\u5b9f\u884c\u3059\u308b\u3068<\/p>\n<pre><code>----------\nNetworks: Main\nInputs:  BinaryCrossEntropy_T\nInputs:  Input\nOutputs:  BinaryCrossEntropy\n----------\nNetworks: MainValidation\nInputs:  BinaryCrossEntropy_T\nInputs:  Input\nOutputs:  BinaryCrossEntropy\n----------\nNetworks: MainRuntime\nInputs:  Input\nOutputs:  Sigmoid\n<\/code><\/pre>\n<p>\u7d50\u679c\u306f\u3053\u3093\u306a\u611f\u3058\u306b\u306a\u308a\u307e\u3059\u306e\u3067\u3001\u300cMainRuntime\u300d\u306eInputs\u3068Outputs\u306e\u540d\u524d\u3092\u30e1\u30e2\u30ea\u307e\u3059\u3002<\/p>\n<h2>\u63a8\u8ad6\u30d7\u30ed\u30b0\u30e9\u30e0\u306e\u4f5c\u6210<\/h2>\n<p>\u5148\u307b\u3069\u30e1\u30e2\u3057\u305f\u3001\u300c\u63a8\u8ad6\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u540d\u300d\u3001\u300c\u5165\u529b\u540d\u300d\u3001\u300c\u51fa\u529b\u540d\u300d\u3092\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u6307\u5b9a\u3059\u308c\u3070\u3001\u5927\u4f53\u7d42\u308f\u308a\u3067\u3059\u3002\u5927\u4f53\u3068\u3044\u3063\u305f\u306e\u306f\u3001\u5b9f\u969b\u306bx\u306b\u5165\u308c\u308b\u30c7\u30fc\u30bf\u306e\u8aad\u307f\u8fbc\u307f\u3084\u51fa\u529b\u306e\u4ed5\u65b9\u306a\u3069\u3092\u66f8\u304b\u306a\u3051\u308c\u3070\u306a\u308a\u307e\u305b\u3093\u306e\u3067\u3001\u81ea\u5206\u306e\u30c7\u30fc\u30bf\u306b\u5408\u308f\u305b\u3066\u8a18\u8ff0\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n<pre><code>import nnabla as nn\nfrom nnabla.utils.nnp_graph import NnpLoader\nimport nnabla.functions as F\nimport nnabla.parametric_functions as PF\n# \u5165\u529b\u30c7\u30fc\u30bf\u304c\u753b\u50cf\u306e\u6642\u306b\u4f7f\u3046\u30e6\u30fc\u30c6\u30a3\u30ea\u30c6\u30a3\u30e9\u30a4\u30d6\u30e9\u30ea\nfrom nnabla.utils.image_utils import imread\nimport os\n\n\nnnppath = \"results.nnp\"\nif os.path.isfile(nnppath):\n    # Read a .nnp file.\n    nnp = NnpLoader(nnppath)\n    #net = nnp.get_network(\"\u63a8\u8ad6\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u540d\",batch_size = 1)\n    net = nnp.get_network(\"MainRuntime\", batch_size = 1)\n    #x = net.inputs['\u5165\u529b\u540d']\n    x = net.inputs['Input']\n    #y = net.outputs['\u51fa\u529b\u540d']\n    y = net.outputs['Sigmoid']\n    # \u5165\u529b\u30c7\u30fc\u30bf\u304c\u753b\u50cf\u306e\u5834\u5408\u306f\u3053\u3093\u306a\u611f\u3058\n    img = imread(imagefilename, channel_first=True)\n    # \u6559\u5e2b\u7528\u30c7\u30fc\u30bf\u3092255\u3067\u6b63\u898f\u5316\u3057\u3066\u3044\u305f\u3089255\u3067\u5272\u308b\n    x.d = img\/255.0\n    y.forward(clear_buffer=True)\n    print(\"inference: \",y.d)\n<\/code><\/pre>\n<h2>\u307e\u3068\u3081<\/h2>\n<p>\u30c7\u30d5\u30a9\u30eb\u30c8\u306eMain\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3060\u3051\u3067\u69cb\u7bc9\u3057\u305fNNC\u306e\u5b66\u7fd2\u6e08\u307f\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306f\u3001nnp\u30d5\u30a1\u30a4\u30eb\u3060\u3051\u3067\u3001\u63a8\u8ad6\u30d7\u30ed\u30b0\u30e9\u30e0\u304c\u7c21\u5358<sup id=\"fnref-3921-11\"><a href=\"#fn-3921-11\">9<\/a><\/sup>\u306b\u66f8\u3051\u308b\u3053\u3068\u304c\u308f\u304b\u3063\u3066\u3044\u305f\u3060\u3051\u305f\u3068\u601d\u3044\u307e\u3059\u3002\u3053\u306e\u3088\u3046\u306bNNC\u3092\u4f7f\u3046\u3068\u3001AI\u30a8\u30f3\u30b8\u30cb\u30a2\u306f\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u8a2d\u8a08\u306e\u307f\u306b\u5c02\u5ff5\u3067\u304d\u3001\u30b7\u30b9\u30c6\u30e0\u30a8\u30f3\u30b8\u30cb\u30a2\u306fnnabla\u3092\u4f7f\u3063\u305f\u63a8\u8ad6\u30d7\u30ed\u30b0\u30e9\u30e0\u304c\u53ef\u80fd\u306b\u306a\u308a\u3001\u5206\u696d\u5316<sup id=\"fnref-3921-12\"><a href=\"#fn-3921-12\">10<\/a><\/sup>\u3067\u304d\u307e\u3059\u306d\u3002<\/p>\n<p>\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u306f\u3061\u3087\u3063\u3068\u4e0d\u5f97\u610f\u3060\u3051\u3069\u3001\u5206\u6790\u306f\u5f97\u610f\u3060\u304b\u3089\u3084\u308a\u305f\u3044\u3068\u304b\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u3082\u4f7f\u3063\u305f\u5206\u6790\u304c\u3057\u305f\u3044\u3068\u304b\u304a\u8003\u3048\u306e\u3042\u306a\u305f\uff01\u3044\u3044\u74b0\u5883\u3042\u308a\u307e\u3059\u3088\u3002\u307e\u305a\u306f\u304a\u554f\u3044\u5408\u308f\u305b\u304f\u3060\u3055\u3044\u3002<\/p>\n<div class=\"footnotes\">\n<hr \/>\n<ol>\n<li id=\"fn-3921-3\">\n\u3053\u306e\u5834\u5408\u3001AI\u30a8\u30f3\u30b8\u30cb\u30a2\u306f\u30d7\u30ed\u30b0\u30e9\u30e0\u304c\u7d44\u3081\u306a\u304f\u3066\u3082\u554f\u984c\u3042\u308a\u307e\u305b\u3093\u3002&#160;<a href=\"#fnref-3921-3\">&#8617;<\/a>\n<\/li>\n<li id=\"fn-3921-4\">\n\u3053\u3053\u3067\u306f\u3001python\u30d7\u30ed\u30b0\u30e9\u30de\u3092\u60f3\u5b9a\u3057\u3066\u3044\u307e\u3059\u3002\u3053\u3053\u3067\u306f\u7d39\u4ecb\u3057\u307e\u305b\u3093\u304c\u3001C++\u3067\u3082\u3067\u304d\u307e\u3059\u3002&#160;<a href=\"#fnref-3921-4\">&#8617;<\/a>\n<\/li>\n<li id=\"fn-3921-5\">\n\u5165\u529b\u30c7\u30fc\u30bf\u3092\u5165\u308c\u3066\u3001\u5bfe\u5fdc\u3059\u308b\u4f55\u304b\uff08\u5206\u985e\u306a\u3089\u5206\u985e\u7d50\u679c\u3001\u56de\u5e30\u306a\u3089\u4e88\u6e2c\u7d50\u679c\uff09\u3092\u51fa\u529b\u3059\u308b\u30b7\u30b9\u30c6\u30e0\u306e\u3053\u3068\u3067\u3059\u3002&#160;<a href=\"#fnref-3921-5\">&#8617;<\/a>\n<\/li>\n<li id=\"fn-3921-6\">\n\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u69cb\u9020\u30d5\u30a1\u30a4\u30eb\uff08net.nntxt\uff09\u3084NNC\u4e0a\u3067Export\u3067\u304d\u308bpython\u30b3\u30fc\u30c9\u306f\u3044\u308a\u307e\u305b\u3093\u3002&#160;<a href=\"#fnref-3921-6\">&#8617;<\/a>\n<\/li>\n<li id=\"fn-3921-7\">\n\u63a8\u8ad6\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u540d\u3067\u3059\u3002\u30c7\u30d5\u30a9\u30eb\u30c8\u306f&#8221;MainRuntime&#8221;\u3067\u3059\u3002&#160;<a href=\"#fnref-3921-7\">&#8617;<\/a>\n<\/li>\n<li id=\"fn-3921-8\">\n\u306a\u3093\u306a\u3089\u3001results.nnp\u304c\u542b\u307e\u308c\u3066\u3044\u308b\u30d5\u30a9\u30eb\u30c0\u30fc\u4e38\u3054\u3068\u6e21\u305b\u3070\u3044\u3044\u3093\u3067\u3059\u3051\u3069\u306d\u3002&#160;<a href=\"#fnref-3921-8\">&#8617;<\/a>\n<\/li>\n<li id=\"fn-3921-9\">\n\u6b21\u306e\u6848\u4ef6\u306b\u79fb\u308a\u307e\u3057\u3087\u3046\u3002&#160;<a href=\"#fnref-3921-9\">&#8617;<\/a>\n<\/li>\n<li id=\"fn-3921-10\">\n\u5165\u529b\u304c1\u3064\u3067\u3001\u51fa\u529b\u304c\uff11\u3064\u3068\u306f\u9650\u308a\u307e\u305b\u3093\u3002&#160;<a href=\"#fnref-3921-10\">&#8617;<\/a>\n<\/li>\n<li id=\"fn-3921-11\">\n\u307b\u3068\u3093\u3069\u306e\u5834\u5408\u3001\u63a8\u8ad6\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\uff1dMainRuntime\u3001\u5165\u529b\u540d\uff1dInput\u306a\u306e\u3067\u3001\u51fa\u529b\u540d\u3060\u3051\u5909\u3048\u308c\u3070\u3088\u3044\u3060\u3051\u3067\u3059\u3002&#160;<a href=\"#fnref-3921-11\">&#8617;<\/a>\n<\/li>\n<li id=\"fn-3921-12\">\n\u500b\u4eba\u3068\u3057\u3066\u5206\u696d\u5316\u304c\u3044\u3044\u304b\u3069\u3046\u304b\u308f\u304b\u308a\u307e\u305b\u3093\u304c\u3001\u4f1a\u793e\u7684\u306a\u52b9\u7387\u306f\u4e0a\u304c\u308b\u30cf\u30ba\u3067\u3059\u3002&#160;<a href=\"#fnref-3921-12\">&#8617;<\/a>\n<\/li>\n<\/ol>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>1\u5e74\u307b\u3069\u524d\u3001\u30bd\u30cb\u30fc Neural Network Console \u3068 \u30a8\u30af\u30bb\u30eb\u3067\u59cb\u3081\u308b \u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u6295\u7a3f\u3057\u307e\u3057\u305f\u3002 \u30bd\u30cb\u30fc Neural Network Console \u3068 \u30a8\u30af\u30bb\u30eb\u3067\u59cb\u3081\u308b \u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8 [&hellip;]<\/p>\n","protected":false},"author":15,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[27,29],"tags":[45,61,60,62],"_links":{"self":[{"href":"https:\/\/www.ecomottblog.com\/index.php?rest_route=\/wp\/v2\/posts\/3921"}],"collection":[{"href":"https:\/\/www.ecomottblog.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.ecomottblog.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.ecomottblog.com\/index.php?rest_route=\/wp\/v2\/users\/15"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ecomottblog.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3921"}],"version-history":[{"count":5,"href":"https:\/\/www.ecomottblog.com\/index.php?rest_route=\/wp\/v2\/posts\/3921\/revisions"}],"predecessor-version":[{"id":3925,"href":"https:\/\/www.ecomottblog.com\/index.php?rest_route=\/wp\/v2\/posts\/3921\/revisions\/3925"}],"wp:attachment":[{"href":"https:\/\/www.ecomottblog.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3921"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.ecomottblog.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3921"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.ecomottblog.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3921"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}