{"id":259,"date":"2018-11-26T07:34:37","date_gmt":"2018-11-26T07:34:37","guid":{"rendered":""},"modified":"2020-09-29T15:21:04","modified_gmt":"2020-09-29T07:21:04","slug":"%e8%bd%ac-%e5%a6%82%e4%bd%95%e5%9c%a8python%e4%b8%ad%e5%b0%86timedistributed%e5%b1%82%e7%94%a8%e4%ba%8elong-short-term-memory-networks","status":"publish","type":"post","link":"http:\/\/weizn.net\/?p=259","title":{"rendered":"[\u8f6c] \u5982\u4f55\u5728Python\u4e2d\u5c06TimeDistributed\u5c42\u7528\u4e8eLong Short-Term Memory Networks"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_17 counter-hierarchy\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\">\u76ee\u5f55<\/p>\n<span class=\"ez-toc-title-toggle\"><a class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" style=\"display: none;\"><i class=\"ez-toc-glyphicon ez-toc-icon-toggle\"><\/i><\/a><\/span><\/div>\n<nav><ul class=\"ez-toc-list ez-toc-list-level-1\"><li class=\"ez-toc-page-1 ez-toc-heading-level-2\"><a class=\"ez-toc-link ez-toc-heading-1\" href=\"http:\/\/weizn.net\/?p=259\/#How_to_Use_the_TimeDistributed_Layer_for_Long_Short-Term_Memory_Networks_in_Python\" title=\"How to Use the TimeDistributed Layer for Long Short-Term Memory Networks in Python\">How to Use the TimeDistributed Layer for Long Short-Term Memory Networks in Python<\/a><\/li><li class=\"ez-toc-page-1 ez-toc-heading-level-2\"><a class=\"ez-toc-link ez-toc-heading-2\" href=\"http:\/\/weizn.net\/?p=259\/#%E5%A6%82%E4%BD%95%E5%9C%A8Python%E4%B8%AD%E5%B0%86TimeDistributed%E5%B1%82%E7%94%A8%E4%BA%8ELong_Short-Term_Memory_Networks\" title=\"\u5982\u4f55\u5728Python\u4e2d\u5c06TimeDistributed\u5c42\u7528\u4e8eLong Short-Term Memory Networks\">\u5982\u4f55\u5728Python\u4e2d\u5c06TimeDistributed\u5c42\u7528\u4e8eLong Short-Term Memory Networks<\/a><\/li><li class=\"ez-toc-page-1 ez-toc-heading-level-2\"><a class=\"ez-toc-link ez-toc-heading-3\" href=\"http:\/\/weizn.net\/?p=259\/#%E6%95%99%E7%A8%8B%E6%A6%82%E8%BF%B0\" title=\"\u6559\u7a0b\u6982\u8ff0\">\u6559\u7a0b\u6982\u8ff0<\/a><ul class=\"ez-toc-list-level-3\"><li class=\"ez-toc-heading-level-3\"><a class=\"ez-toc-link ez-toc-heading-4\" href=\"http:\/\/weizn.net\/?p=259\/#%E7%8E%AF%E5%A2%83\" title=\"\u73af\u5883\">\u73af\u5883<\/a><\/li><\/ul><\/li><li class=\"ez-toc-page-1 ez-toc-heading-level-2\"><a class=\"ez-toc-link ez-toc-heading-5\" href=\"http:\/\/weizn.net\/?p=259\/#TimeDistributed%E5%B1%82\" title=\"TimeDistributed\u5c42\">TimeDistributed\u5c42<\/a><\/li><li class=\"ez-toc-page-1 ez-toc-heading-level-2\"><a class=\"ez-toc-link ez-toc-heading-6\" href=\"http:\/\/weizn.net\/?p=259\/#%E5%BA%8F%E5%88%97%E5%AD%A6%E4%B9%A0%E9%97%AE%E9%A2%98Sequence_Learning_Problem\" title=\"\u5e8f\u5217\u5b66\u4e60\u95ee\u9898(Sequence Learning Problem)\">\u5e8f\u5217\u5b66\u4e60\u95ee\u9898(Sequence Learning Problem)<\/a><\/li><li class=\"ez-toc-page-1 ez-toc-heading-level-2\"><a class=\"ez-toc-link ez-toc-heading-7\" href=\"http:\/\/weizn.net\/?p=259\/#%E7%94%A8%E4%BA%8E%E5%BA%8F%E5%88%97%E9%A2%84%E6%B5%8B%E7%9A%84%E4%B8%80%E5%AF%B9%E4%B8%80LSTM\" title=\"\u7528\u4e8e\u5e8f\u5217\u9884\u6d4b\u7684\u4e00\u5bf9\u4e00LSTM\">\u7528\u4e8e\u5e8f\u5217\u9884\u6d4b\u7684\u4e00\u5bf9\u4e00LSTM<\/a><\/li><li class=\"ez-toc-page-1 ez-toc-heading-level-2\"><a class=\"ez-toc-link ez-toc-heading-8\" href=\"http:\/\/weizn.net\/?p=259\/#%E7%94%A8%E4%BA%8E%E5%A4%9A%E5%AF%B9%E4%B8%80%E7%9A%84%E5%BA%8F%E5%88%97%E9%A2%84%E6%B5%8B%E7%9A%84LSTM%E4%B8%8D%E5%90%ABTimeDistributed\" title=\"\u7528\u4e8e\u591a\u5bf9\u4e00\u7684\u5e8f\u5217\u9884\u6d4b\u7684LSTM(\u4e0d\u542bTimeDistributed)\">\u7528\u4e8e\u591a\u5bf9\u4e00\u7684\u5e8f\u5217\u9884\u6d4b\u7684LSTM(\u4e0d\u542bTimeDistributed)<\/a><\/li><li class=\"ez-toc-page-1 ez-toc-heading-level-2\"><a class=\"ez-toc-link ez-toc-heading-9\" href=\"http:\/\/weizn.net\/?p=259\/#%E7%94%A8%E4%BA%8E%E5%BA%8F%E5%88%97%E9%A2%84%E6%B5%8B%E7%9A%84%E5%A4%9A%E5%AF%B9%E5%A4%9ALSTM%E5%B8%A6TimeDistributed\" title=\"\u7528\u4e8e\u5e8f\u5217\u9884\u6d4b\u7684\u591a\u5bf9\u591aLSTM(\u5e26TimeDistributed)\">\u7528\u4e8e\u5e8f\u5217\u9884\u6d4b\u7684\u591a\u5bf9\u591aLSTM(\u5e26TimeDistributed)<\/a><\/li><li class=\"ez-toc-page-1 ez-toc-heading-level-2\"><a class=\"ez-toc-link ez-toc-heading-10\" href=\"http:\/\/weizn.net\/?p=259\/#%E8%BF%9B%E4%B8%80%E6%AD%A5%E9%98%85%E8%AF%BB\" title=\"\u8fdb\u4e00\u6b65\u9605\u8bfb\">\u8fdb\u4e00\u6b65\u9605\u8bfb<\/a><\/li><li class=\"ez-toc-page-1 ez-toc-heading-level-2\"><a class=\"ez-toc-link ez-toc-heading-11\" href=\"http:\/\/weizn.net\/?p=259\/#%E6%A6%82%E8%A6%81\" title=\"\u6982\u8981\">\u6982\u8981<\/a><\/li><\/ul><\/nav><\/div>\n<h2 id=\"How-to-Use-the-TimeDistributed-Layer-for-Long-Short-Term-Memory-Networks-in-Python\"><span class=\"ez-toc-section\" id=\"How_to_Use_the_TimeDistributed_Layer_for_Long_Short-Term_Memory_Networks_in_Python\"><\/span>How to Use the TimeDistributed Layer for Long Short-Term Memory Networks in Python<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u539f\u6587\u4f5c\u8005\uff1aJason Brownlee<\/p>\n<p>\u539f\u6587\u5730\u5740\uff1a<a href=\"https:\/\/machinelearningmastery.com\/timedistributed-layer-for-long-short-term-memory-networks-in-python\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" data-from=\"10680\">https:\/\/machinelearningmastery.com\/timedistributed-layer-for-long-short-term-memory-networks-in-python\/<\/a><\/p>\n<p>\u8bd1\u8005\u5fae\u535a\uff1a@\u4ece\u6d41\u57df\u5230\u6d77\u57df<\/p>\n<p>\u8bd1\u8005\u535a\u5ba2\uff1ablog.csdn.net\/solo95<\/p>\n<h2 id=\"%E5%A6%82%E4%BD%95%E5%9C%A8Python%E4%B8%AD%E5%B0%86TimeDistributed%E5%B1%82%E7%94%A8%E4%BA%8ELong-Short-Term-Memory-Networks\"><span class=\"ez-toc-section\" id=\"%E5%A6%82%E4%BD%95%E5%9C%A8Python%E4%B8%AD%E5%B0%86TimeDistributed%E5%B1%82%E7%94%A8%E4%BA%8ELong_Short-Term_Memory_Networks\"><\/span>\u5982\u4f55\u5728Python\u4e2d\u5c06TimeDistributed\u5c42\u7528\u4e8eLong Short-Term Memory Networks<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Long Short-Term Memory Networks\u6216LSTM\u662f\u4e00\u79cd\u6d41\u884c\u7684\u5f3a\u5927\u7684\u5faa\u73af\u795e\u7ecf\u7f51\u7edc(\u5373RNN)\u3002<\/p>\n<p>\u5bf9\u4e8e\u4efb\u610f\u7684\u5e8f\u5217\u9884\u6d4b(sequence prediction )\u95ee\u9898\uff0c\u914d\u7f6e\u548c\u5e94\u7528\u8d77\u6765\u53ef\u80fd\u4f1a\u76f8\u5f53\u56f0\u96be\uff0c\u5373\u4f7f\u5728Python\u4e2d\u7684Keras\u6df1\u5ea6\u5b66\u4e60\u5e93\u4e2d\u63d0\u4f9b\u7684\u5b9a\u4e49\u826f\u597d\u4e14\u201c\u6613\u4e8e\u4f7f\u7528\u201d\u7684\u63a5\u53e3\u4e0a\u4e5f\u662f\u5982\u6b64\u3002<\/p>\n<p>\u5728Keras\u4e2d\u9047\u5230\u8fd9\u79cd\u56f0\u96be\u7684\u5176\u4e2d\u4e00\u4e2a\u539f\u56e0\u662f\u4f7f\u7528\u4e86TimeDistributed\u88c5\u9970\u5668\u5c42\uff0c\u5e76\u4e14\u9700\u8981\u4e00\u4e9bLSTM\u5c42\u6765\u8fd4\u56de\u5e8f\u5217\u800c\u4e0d\u662f\u5355\u4e2a\u503c\u3002<\/p>\n<p>\u5728\u672c\u6559\u7a0b\u4e2d\uff0c\u60a8\u5c06\u4e86\u89e3\u914d\u7f6eLSTM\u7f51\u7edc\u8fdb\u884c\u5e8f\u5217\u9884\u6d4b\u7684\u4e0d\u540c\u65b9\u6cd5\u3001TimeDistributed\u5c42\u6240\u626e\u6f14\u7684\u89d2\u8272\u4ee5\u53ca\u5982\u4f55\u4f7f\u7528\u5b83\u3002<\/p>\n<p>\u5b8c\u6210\u672c\u6559\u7a0b\u540e\uff0c\u60a8\u5c06\u77e5\u9053\uff1a<\/p>\n<ul class=\"ul-level-0\">\n<li>\u5982\u4f55\u8bbe\u8ba1\u4e00\u4e2a\u4e00\u5bf9\u4e00\u7684LSTM\u8fdb\u884c\u5e8f\u5217\u9884\u6d4b\u3002<\/li>\n<li>\u5982\u4f55\u5728\u6ca1\u6709TimeDistributed\u5c42\u7684\u60c5\u51b5\u4e0b\u8bbe\u8ba1\u4e00\u4e2a\u591a\u5bf9\u4e00\u7684LSTM\u8fdb\u884c\u5e8f\u5217\u9884\u6d4b\u3002<\/li>\n<li>\u5982\u4f55\u5229\u7528TimeDistributed\u5c42\u8bbe\u8ba1\u4e00\u4e2a\u591a\u5bf9\u591a\u7684LSTM\u8fdb\u884c\u5e8f\u5217\u9884\u6d4b\u3002<\/li>\n<\/ul>\n<p>\u8ba9\u6211\u4eec\u5f00\u59cb\u5427\u3002<\/p>\n<figure>\n<div class=\"image-block\"><img decoding=\"async\" class=\"\" src=\"https:\/\/ask.qcloudimg.com\/http-save\/1207328\/71yywffzb0.jpeg?imageView2\/2\/w\/1620\" \/><\/div>\n<\/figure>\n<p>\u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528TimeDistributed\u5c42\u5b9e\u73b0Long Short-Term Memory Networks<\/p>\n<p>\u56fe\u7247\u7531<a href=\"https:\/\/www.flickr.com\/photos\/43158397@N02\/5774000092\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" data-from=\"10680\">jans canon<\/a>\u63d0\u4f9b\uff0c\u4fdd\u7559\u90e8\u5206\u6743\u5229\u3002<\/p>\n<h2 id=\"%E6%95%99%E7%A8%8B%E6%A6%82%E8%BF%B0\"><span class=\"ez-toc-section\" id=\"%E6%95%99%E7%A8%8B%E6%A6%82%E8%BF%B0\"><\/span>\u6559\u7a0b\u6982\u8ff0<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u672c\u6559\u7a0b\u5206\u4e3a5\u4e2a\u90e8\u5206; \u4ed6\u4eec\u662f\uff1a<\/p>\n<ol class=\"ol-level-0\">\n<li>TimeDistributed\u5c42<\/li>\n<li>\u5e8f\u5217\u5b66\u4e60\u95ee\u9898<\/li>\n<li>\u7528\u4e8e\u5e8f\u5217\u9884\u6d4b\u7684\u4e00\u5bf9\u4e00LSTM<\/li>\n<li>\u7528\u4e8e\u5e8f\u5217\u9884\u6d4b\u7684\u591a\u5bf9\u4e00LSTM(\u4e0d\u542bTimeDistributed)<\/li>\n<li>\u7528\u4e8e\u5e8f\u5217\u9884\u6d4b\u7684\u591a\u5bf9\u591aLSTM(\u5e26TimeDistributed)<\/li>\n<\/ol>\n<h3 id=\"%E7%8E%AF%E5%A2%83\"><span class=\"ez-toc-section\" id=\"%E7%8E%AF%E5%A2%83\"><\/span>\u73af\u5883<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u672c\u6559\u7a0b\u5047\u8bbe\u4f60\u5df2\u7ecf\u5b89\u88c5\u4e86\u5e26SciPy\u7684Python 2\u6216Python 3\u5f00\u53d1\u73af\u5883\uff0c\u4ee5\u53caNumPy\u548cPandas\u3002<\/p>\n<p>\u8be5\u6559\u7a0b\u8fd8\u5047\u8bbe\u5df2\u7ecf\u5b89\u88c5\u4e86scikit-learn\u548ckeras v2.0 +\uff0c\u5e76\u4e14\u540e\u7aef\u6709Theano\u6216TensorFlow\u5176\u4e2d\u4e4b\u4e00\u3002<\/p>\n<p>\u6709\u5173\u5982\u4f55\u914d\u7f6e\u53ca\u60a8\u7684Python\u73af\u5883\u7684\u5e2e\u52a9\uff0c\u8bf7\u53c2\u9605\u4ee5\u4e0b\u6587\u7ae0\uff1a<\/p>\n<ul class=\"ul-level-0\">\n<li><a href=\"http:\/\/machinelearningmastery.com\/setup-python-environment-machine-learning-deep-learning-anaconda\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" data-from=\"10680\">\u5982\u4f55\u4f7f\u7528Anaconda\u914d\u7f6ePython\u73af\u5883\u8fdb\u884c\u673a\u5668\u5b66\u4e60\u548c\u6df1\u5ea6\u5b66\u4e60<\/a><\/li>\n<\/ul>\n<h2 id=\"TimeDistributed%E5%B1%82\"><span class=\"ez-toc-section\" id=\"TimeDistributed%E5%B1%82\"><\/span>TimeDistributed\u5c42<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>LSTM\u529f\u80fd\u5f3a\u5927\uff0c\u4f46\u96be\u4ee5\u4f7f\u7528\uff0c\u96be\u4e8e\u914d\u7f6e\uff0c\u5c24\u5176\u662f\u5bf9\u4e8e\u521d\u5b66\u8005\u6765\u8bf4\u3002<\/p>\n<p><a href=\"https:\/\/keras.io\/layers\/wrappers\/#timedistributed\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" data-from=\"10680\">TimeDistributed<\/a> Layer(\u4ee5\u524d\u7684_TimeDistributedDense_layer)\u88ab\u9690\u79d8\u5730\u5730\u63cf\u8ff0\u4e3a\u4e00\u4e2alayer\u88c5\u9970\u5668\uff0c\u8fd9\u662f\u4e00\u4e2a\u989d\u5916\u7684\u590d\u6742\u56e0\u7d20\uff1a<\/p>\n<blockquote><p>\u8fd9\u4e2a\u88c5\u9970\u5668\u5141\u8bb8\u6211\u4eec\u5728\u8f93\u5165\u7684\u6bcf\u4e2a\u65f6\u95f4\u7247\u4e0a\u5e94\u7528\u4e00\u4e2alayer\u3002<\/p><\/blockquote>\n<p>\u5982\u4f55\u5728LSTM\u4e0a\u4f7f\u7528\u8be5\u88c5\u9970\u5668\uff0c\u5e94\u8be5\u5728\u4f55\u65f6\u4f7f\u7528\uff1f<\/p>\n<p>\u5f53\u60a8\u5728Keras GitHub issues\u548cStackOverflow\u4e0a\u641c\u7d22\u8be5\u5305\u88c5\u9970\u5668\u5c42\u7684\u8ba8\u8bba\u65f6\uff0c\u60a8\u7684\u56f0\u60d1\u5c06\u4f1a\u662f\u591a\u4e2a\u5c42\u9762\u7684\u3002<\/p>\n<p>\u4f8b\u5982\uff0c\u5728\u95ee\u9898\u201c <a href=\"https:\/\/github.com\/fchollet\/keras\/issues\/1029\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" data-from=\"10680\">\u4f55\u65f6\u4ee5\u53ca\u5982\u4f55\u4f7f\u7528TimeDistributedDense<\/a> \u201d\u4e2d\uff0cfchollet(Keras\u7684\u4f5c\u8005)\u89e3\u91ca\u9053\uff1a<\/p>\n<blockquote><p>TimeDistributedDense\u5bf93D\u5f20\u91cf\u7684\u6bcf\u4e2a\u65f6\u95f4\u6b65\u5e94\u7528\u76f8\u540c\u7684Dense(\u5b8c\u5168\u8fde\u63a5)\u64cd\u4f5c\u3002<\/p><\/blockquote>\n<p>\u5982\u679c\u60a8\u5df2\u7ecf\u7406\u89e3\u4e86TimeDistributed\u56fe\u5c42\u7684\u7528\u9014\u4ee5\u53ca\u4f55\u65f6\u4f7f\u7528\u5b83\uff0c\u8fd9\u662f\u975e\u5e38\u6709\u610f\u4e49\u7684\uff0c\u4f46\u8fd9\u5bf9\u521d\u5b66\u8005\u6beb\u65e0\u5e2e\u52a9\uff0c\u3002<\/p>\n<p>\u672c\u6559\u7a0b\u65e8\u5728\u6d88\u9664\u60a8\u5728LSTM\u4e0a\u4f7f\u7528\u7684TimeDistributed\u88c5\u9970\u5668\u7684\u7591\u60d1\uff0c\u5176\u4e2d\u5305\u542b\u4e86\u60a8\u53ef\u4ee5\u68c0\u67e5\uff0c\u8fd0\u884c\u548c\u628a\u73a9\u7684\u5de5\u4f5c\u793a\u4f8b\uff0c\u4ee5\u5e2e\u52a9\u60a8\u8fdb\u884c\u5177\u4f53\u7684\u7406\u89e3\u3002<\/p>\n<h2 id=\"%E5%BA%8F%E5%88%97%E5%AD%A6%E4%B9%A0%E9%97%AE%E9%A2%98(Sequence-Learning-Problem)\"><span class=\"ez-toc-section\" id=\"%E5%BA%8F%E5%88%97%E5%AD%A6%E4%B9%A0%E9%97%AE%E9%A2%98Sequence_Learning_Problem\"><\/span>\u5e8f\u5217\u5b66\u4e60\u95ee\u9898(Sequence Learning Problem)<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u6211\u4eec\u5c06\u4f7f\u7528\u4e00\u4e2a\u7b80\u5355\u7684\u5e8f\u5217\u5b66\u4e60\u95ee\u9898\u6765\u6f14\u793aTimeDistributed\u5c42\u3002<\/p>\n<p>\u5728\u8fd9\u4e2a\u95ee\u9898\u4e2d\uff0c\u5e8f\u52170.0, 0.2, 0.4, 0.6, 0.8\u5c06\u4f5c\u4e3a\u8f93\u5165\u4e00\u6b21\u7ed9\u51fa\u4e00\u9879\uff0c\u5e76\u4e14\u5fc5\u987b\u4f9d\u6b21\u4f5c\u4e3a\u8f93\u51fa\u8fd4\u56de\uff0c\u4e00\u6b21\u4e00\u9879\u3002<\/p>\n<p>\u628a\u5b83\u60f3\u8c61\u6210\u5b66\u4e60\u4e00\u4e2a\u7b80\u5355\u56de\u58f0\u7684\u7a0b\u5e8f\u3002\u6211\u4eec\u7ed9\u51fa0.0\u4f5c\u4e3a\u8f93\u5165\uff0c\u6211\u4eec\u671f\u671b\u770b\u52300.0\u4f5c\u4e3a\u8f93\u51fa\uff0c\u5bf9\u5e8f\u5217\u4e2d\u7684\u6bcf\u4e2a\u9879\u76ee\u6765\u8bf4\u90fd\u662f\u5982\u6b64\u3002<\/p>\n<p>\u6211\u4eec\u53ef\u4ee5\u50cf\u4e0b\u9762\u8fd9\u6837\u76f4\u63a5\u751f\u6210\u8fd9\u4e2a\u5e8f\u5217\uff1a<\/p>\n<pre class=\"prism-token token language-js\"><span class=\"token keyword\">from<\/span> numpy <span class=\"token keyword\">import<\/span> array\r\nlength <span class=\"token operator\">=<\/span> <span class=\"token number\">5<\/span>\r\nseq <span class=\"token operator\">=<\/span> <span class=\"token function\">array<\/span><span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">[<\/span>i<span class=\"token operator\">\/<\/span><span class=\"token function\">float<\/span><span class=\"token punctuation\">(<\/span>length<span class=\"token punctuation\">)<\/span> <span class=\"token keyword\">for<\/span> i <span class=\"token keyword\">in<\/span> <span class=\"token function\">range<\/span><span class=\"token punctuation\">(<\/span>length<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">)<\/span>\r\n<span class=\"token function\">print<\/span><span class=\"token punctuation\">(<\/span>seq<span class=\"token punctuation\">)<\/span><\/pre>\n<p>\u8fd0\u884c\u8fd9\u4e2a\u4f8b\u5b50\u6253\u5370\u751f\u6210\u7684\u5e8f\u5217\uff1a<\/p>\n<pre class=\"prism-token token language-js\"><span class=\"token punctuation\">[<\/span> <span class=\"token number\">0<\/span><span class=\"token punctuation\">.<\/span>   <span class=\"token number\">0.2<\/span>  <span class=\"token number\">0.4<\/span>  <span class=\"token number\">0.6<\/span>  <span class=\"token number\">0.8<\/span><span class=\"token punctuation\">]<\/span> \r\n<\/pre>\n<p>\u8fd9\u4e2a\u4f8b\u5b50\u662f\u53ef\u914d\u7f6e\u7684\uff0c\u5982\u679c\u4f60\u559c\u6b22\uff0c\u4f60\u53ef\u4ee5\u7a0d\u540e\u81ea\u5df1\u7528\u66f4\u957f\/\u66f4\u77ed\u7684\u5e8f\u5217\u6765\u5c1d\u8bd5\u4e00\u4e0b\u3002\u8bf7\u5728\u8bc4\u8bba\u4e2d\u544a\u8bc9\u6211\u4eec\u4f60\u7684\u7ed3\u679c\u3002<\/p>\n<h2 id=\"%E7%94%A8%E4%BA%8E%E5%BA%8F%E5%88%97%E9%A2%84%E6%B5%8B%E7%9A%84%E4%B8%80%E5%AF%B9%E4%B8%80LSTM\"><span class=\"ez-toc-section\" id=\"%E7%94%A8%E4%BA%8E%E5%BA%8F%E5%88%97%E9%A2%84%E6%B5%8B%E7%9A%84%E4%B8%80%E5%AF%B9%E4%B8%80LSTM\"><\/span>\u7528\u4e8e\u5e8f\u5217\u9884\u6d4b\u7684\u4e00\u5bf9\u4e00LSTM<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u5728\u6211\u4eec\u6df1\u5165\u4e4b\u524d\uff0c\u6700\u91cd\u8981\u7684\u662f\u8981\u8bc1\u660e\u8fd9\u4e2a\u5e8f\u5217\u5b66\u4e60\u95ee\u9898\u53ef\u4ee5\u5206\u6bb5\u5730\u8fdb\u884c\u5b66\u4e60\u3002<\/p>\n<p>\u4e5f\u5c31\u662f\u8bf4\uff0c\u6211\u4eec\u53ef\u4ee5\u5c06\u95ee\u9898\u91cd\u6784\u4e3a\u4e00\u4e2a(\u7531\u5e8f\u5217\u4e2d\u6bcf\u4e2a\u9879\u76ee\u7684\u8f93\u5165-\u8f93\u51fa\u5bf9\u7ec4\u6210\u7684)\u6570\u636e\u96c6\u3002\u7ed9\u5b9a0\uff0c\u7f51\u7edc\u5e94\u8f93\u51fa0\uff0c\u7ed9\u5b9a0.2\uff0c\u7f51\u7edc\u5fc5\u987b\u8f93\u51fa0.2\uff0c\u4f9d\u6b64\u7c7b\u63a8\u3002<\/p>\n<p>\u8fd9\u662f\u95ee\u9898\u7684\u6700\u7b80\u5355\u7684\u8868\u8ff0\u5f62\u5f0f\uff0c\u5e76\u4e14\u8981\u6c42\u5c06\u5e8f\u5217\u5206\u6210\u8f93-\u8f93\u51fa\u5bf9\uff0c\u5e76\u4e14\u9700\u8981\u4e00\u6b21\u4e00\u6b65\u5730\u9884\u6d4b\u5e8f\u5217\u7136\u540e\u5728\u7f51\u7edc\u4e4b\u5916\u805a\u96c6\u5728\u4e00\u8d77\u3002<\/p>\n<p>\u8f93\u5165\u8f93\u51fa\u5bf9\u5982\u4e0b\u6240\u793a\uff1a<\/p>\n<pre class=\"prism-token token language-js\">X<span class=\"token punctuation\">,<\/span>     y\r\n<span class=\"token number\">0.0<\/span><span class=\"token punctuation\">,<\/span>    <span class=\"token number\">0.0<\/span>\r\n<span class=\"token number\">0.2<\/span><span class=\"token punctuation\">,<\/span>    <span class=\"token number\">0.2<\/span>\r\n<span class=\"token number\">0.4<\/span><span class=\"token punctuation\">,<\/span>    <span class=\"token number\">0.4<\/span>\r\n<span class=\"token number\">0.6<\/span><span class=\"token punctuation\">,<\/span>    <span class=\"token number\">0.6<\/span>\r\n<span class=\"token number\">0.8<\/span><span class=\"token punctuation\">,<\/span>    <span class=\"token number\">0.8<\/span><\/pre>\n<p>LSTM\u7684\u8f93\u5165\u5fc5\u987b\u662f\u4e09\u7ef4\u7684\u3002\u6211\u4eec\u53ef\u4ee5\u628a2D\u5e8f\u5217\u91cd\u5851\u4e00\u4e2a\u5177\u67095\u4e2a\u6837\u672c\u30011\u4e2a\u65f6\u95f4\u6b65\u548c1\u4e2a\u7279\u5f81\u76843D\u5e8f\u5217\u3002\u6211\u4eec\u5c06\u8f93\u51fa\u5b9a\u4e49\u4e3a\u5177\u67091\u4e2a\u7279\u5f81\u76845\u4e2a\u6837\u672c\u3002<\/p>\n<pre class=\"prism-token token language-js\">X <span class=\"token operator\">=<\/span> seq<span class=\"token punctuation\">.<\/span><span class=\"token function\">reshape<\/span><span class=\"token punctuation\">(<\/span><span class=\"token number\">5<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span>\r\ny <span class=\"token operator\">=<\/span> seq<span class=\"token punctuation\">.<\/span><span class=\"token function\">reshape<\/span><span class=\"token punctuation\">(<\/span><span class=\"token number\">5<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span><\/pre>\n<p>\u6211\u4eec\u5c06\u7f51\u7edc\u6a21\u578b\u5b9a\u4e49\u4e3a1\u4e2a\u65f6\u95f4\u6b65\u67091\u4e2a\u8f93\u51fa\u3002\u7b2c\u4e00\u4e2a\u9690\u85cf\u5c42\u5c06\u662f\u4e00\u4e2a5\u4e2a\u5355\u5143\u7684LSTM\u3002\u8f93\u51fa\u5c42\u5177\u67091\u4e2a\u8f93\u51fa\u7684\u5b8c\u5168\u8fde\u63a5\u5c42\u3002<\/p>\n<p>\u8be5\u6a21\u578b\u5c06\u9002\u914d\u9ad8\u6548ADAM\u4f18\u5316\u7b97\u6cd5\u548c\u5747\u65b9\u8bef\u5dee\u635f\u5931\u51fd\u6570\u3002<\/p>\n<p>\u6279\u5927\u5c0f(\u6216\u6279\u5c3a\u5bf8\uff0cbatch size)\u88ab\u8bbe\u7f6e\u4e3a\u8fed\u4ee3\u6b21\u6570(epoch)\u4e2d\u7684\u6837\u672c\u6570\u91cf\uff0c\u4ee5\u907f\u514d\u5fc5\u987b\u624b\u52a8\u914d\u7f6eLSTM\u5904\u4e8e\u6709\u72b6\u6001(\u6a21\u5f0f)\u548c\u7ba1\u7406\u72b6\u6001\u7684\u91cd\u7f6e\uff0c\u5c3d\u7ba1(\u8fd9\u4e9b\u64cd\u4f5c)\u5728\u6bcf\u4e2a\u6837\u672c\u88ab\u663e\u793a\u7ed9\u7f51\u7edc\u4e4b\u540e\uff0c\u4e3a\u4e86\u66f4\u65b0\u6743\u91cd\u53ef\u4ee5\u5f88\u5bb9\u6613\u5730\u5b8c\u6210\u3002<\/p>\n<p>(1\u4e2aepoch\u7b49\u4e8e\u4f7f\u7528\u8bad\u7ec3\u96c6\u4e2d\u7684\u5168\u90e8\u6837\u672c\u8fdb\u884c\u4e00\u6b21\u8bad\u7ec3\uff0c\u8bd1\u8005\u6ce8)<\/p>\n<p>\u4e0b\u9762\u63d0\u4f9b\u4e86\u5b8c\u6574\u7684\u4ee3\u7801\u6e05\u5355\uff1a<\/p>\n<pre class=\"prism-token token language-js\"><span class=\"token keyword\">from<\/span> numpy <span class=\"token keyword\">import<\/span> array\r\n<span class=\"token keyword\">from<\/span> keras<span class=\"token punctuation\">.<\/span>models <span class=\"token keyword\">import<\/span> Sequential\r\n<span class=\"token keyword\">from<\/span> keras<span class=\"token punctuation\">.<\/span>layers <span class=\"token keyword\">import<\/span> Dense\r\n<span class=\"token keyword\">from<\/span> keras<span class=\"token punctuation\">.<\/span>layers <span class=\"token keyword\">import<\/span> LSTM\r\n# prepare sequence\r\nlength <span class=\"token operator\">=<\/span> <span class=\"token number\">5<\/span>\r\nseq <span class=\"token operator\">=<\/span> <span class=\"token function\">array<\/span><span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">[<\/span>i<span class=\"token operator\">\/<\/span><span class=\"token function\">float<\/span><span class=\"token punctuation\">(<\/span>length<span class=\"token punctuation\">)<\/span> <span class=\"token keyword\">for<\/span> i <span class=\"token keyword\">in<\/span> <span class=\"token function\">range<\/span><span class=\"token punctuation\">(<\/span>length<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">)<\/span>\r\nX <span class=\"token operator\">=<\/span> seq<span class=\"token punctuation\">.<\/span><span class=\"token function\">reshape<\/span><span class=\"token punctuation\">(<\/span><span class=\"token function\">len<\/span><span class=\"token punctuation\">(<\/span>seq<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span>\r\ny <span class=\"token operator\">=<\/span> seq<span class=\"token punctuation\">.<\/span><span class=\"token function\">reshape<\/span><span class=\"token punctuation\">(<\/span><span class=\"token function\">len<\/span><span class=\"token punctuation\">(<\/span>seq<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span>\r\n# define LSTM configuration\r\nn_neurons <span class=\"token operator\">=<\/span> length\r\nn_batch <span class=\"token operator\">=<\/span> length\r\nn_epoch <span class=\"token operator\">=<\/span> <span class=\"token number\">1000<\/span>\r\n# create LSTM\r\nmodel <span class=\"token operator\">=<\/span> <span class=\"token function\">Sequential<\/span><span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span>\r\nmodel<span class=\"token punctuation\">.<\/span><span class=\"token function\">add<\/span><span class=\"token punctuation\">(<\/span><span class=\"token function\">LSTM<\/span><span class=\"token punctuation\">(<\/span>n_neurons<span class=\"token punctuation\">,<\/span> input_shape<span class=\"token operator\">=<\/span><span class=\"token punctuation\">(<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\r\nmodel<span class=\"token punctuation\">.<\/span><span class=\"token function\">add<\/span><span class=\"token punctuation\">(<\/span><span class=\"token function\">Dense<\/span><span class=\"token punctuation\">(<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\r\nmodel<span class=\"token punctuation\">.<\/span><span class=\"token function\">compile<\/span><span class=\"token punctuation\">(<\/span>loss<span class=\"token operator\">=<\/span><span class=\"token string\">'mean_squared_error'<\/span><span class=\"token punctuation\">,<\/span> optimizer<span class=\"token operator\">=<\/span><span class=\"token string\">'adam'<\/span><span class=\"token punctuation\">)<\/span>\r\n<span class=\"token function\">print<\/span><span class=\"token punctuation\">(<\/span>model<span class=\"token punctuation\">.<\/span><span class=\"token function\">summary<\/span><span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\r\n# train LSTM\r\nmodel<span class=\"token punctuation\">.<\/span><span class=\"token function\">fit<\/span><span class=\"token punctuation\">(<\/span>X<span class=\"token punctuation\">,<\/span> y<span class=\"token punctuation\">,<\/span> epochs<span class=\"token operator\">=<\/span>n_epoch<span class=\"token punctuation\">,<\/span> batch_size<span class=\"token operator\">=<\/span>n_batch<span class=\"token punctuation\">,<\/span> verbose<span class=\"token operator\">=<\/span><span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span>\r\n# evaluate\r\nresult <span class=\"token operator\">=<\/span> model<span class=\"token punctuation\">.<\/span><span class=\"token function\">predict<\/span><span class=\"token punctuation\">(<\/span>X<span class=\"token punctuation\">,<\/span> batch_size<span class=\"token operator\">=<\/span>n_batch<span class=\"token punctuation\">,<\/span> verbose<span class=\"token operator\">=<\/span><span class=\"token number\">0<\/span><span class=\"token punctuation\">)<\/span>\r\n<span class=\"token keyword\">for<\/span> value <span class=\"token keyword\">in<\/span> result<span class=\"token punctuation\">:<\/span>\r\n    <span class=\"token function\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">'%.1f'<\/span> <span class=\"token operator\">%<\/span> value<span class=\"token punctuation\">)<\/span><\/pre>\n<p>\u8fd0\u884c\u8be5\u793a\u4f8b\u9996\u5148\u4f1a\u6253\u5370\u51fa\u914d\u7f6e\u7f51\u7edc\u7684\u7ed3\u6784\u3002<\/p>\n<p>\u6211\u4eec\u53ef\u4ee5\u770b\u5230LSTM\u5c42\u6709140\u4e2a\u53c2\u6570\u3002\u8fd9\u662f\u6839\u636e\u8f93\u5165\u6570\u91cf(1)\u548c\u8f93\u51fa\u6570\u91cf(5\u662f\u9690\u85cf\u5c42\u4e2d\u67095\u4e2a\u5355\u5143)\u8ba1\u7b97\u7684\uff0c\u5982\u4e0b\u6240\u793a\uff1a<\/p>\n<pre class=\"prism-token token language-js\">n <span class=\"token operator\">=<\/span> <span class=\"token number\">4<\/span> <span class=\"token operator\">*<\/span> <span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">(<\/span>inputs <span class=\"token operator\">+<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span> <span class=\"token operator\">*<\/span> outputs <span class=\"token operator\">+<\/span> outputs<span class=\"token operator\">^<\/span><span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span>\r\nn <span class=\"token operator\">=<\/span> <span class=\"token number\">4<\/span> <span class=\"token operator\">*<\/span> <span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">(<\/span><span class=\"token number\">1<\/span> <span class=\"token operator\">+<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span> <span class=\"token operator\">*<\/span> <span class=\"token number\">5<\/span> <span class=\"token operator\">+<\/span> <span class=\"token number\">5<\/span><span class=\"token operator\">^<\/span><span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span>\r\nn <span class=\"token operator\">=<\/span> <span class=\"token number\">4<\/span> <span class=\"token operator\">*<\/span> <span class=\"token number\">35<\/span>\r\nn <span class=\"token operator\">=<\/span> <span class=\"token number\">140<\/span><\/pre>\n<p>\u6211\u4eec\u8fd8\u53ef\u4ee5\u770b\u5230\uff0c\u5b8c\u5168\u8fde\u63a5\u5c42\u53ea\u67096\u4e2a\u8f93\u5165\u53c2\u6570(5\u4ee3\u8868\u6765\u81ea\u524d\u4e00\u5c42\u76845\u4e2a\u8f93\u5165)\uff0c\u8f93\u51fa\u6570\u91cf(1\u4ee3\u8868\u8be5\u5c42\u67091\u4e2a\u795e\u7ecf\u5143)\u4ee5\u53ca\u4e56\u79bb\u7387(bias)\u3002<\/p>\n<pre class=\"prism-token token language-js\">n <span class=\"token operator\">=<\/span> inputs <span class=\"token operator\">*<\/span> outputs <span class=\"token operator\">+<\/span> outputs\r\nn <span class=\"token operator\">=<\/span> <span class=\"token number\">5<\/span> <span class=\"token operator\">*<\/span> <span class=\"token number\">1<\/span> <span class=\"token operator\">+<\/span> <span class=\"token number\">1<\/span>\r\nn <span class=\"token operator\">=<\/span> <span class=\"token number\">6<\/span><\/pre>\n<pre class=\"prism-token token language-js\">_________________________________________________________________\r\n<span class=\"token function\">Layer<\/span> <span class=\"token punctuation\">(<\/span>type<span class=\"token punctuation\">)<\/span>                 Output Shape              Param #\r\n<span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">==<\/span>\r\n<span class=\"token function\">lstm_1<\/span> <span class=\"token punctuation\">(<\/span>LSTM<span class=\"token punctuation\">)<\/span>                <span class=\"token punctuation\">(<\/span>None<span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">5<\/span><span class=\"token punctuation\">)<\/span>              <span class=\"token number\">140<\/span>\r\n_________________________________________________________________\r\n<span class=\"token function\">dense_1<\/span> <span class=\"token punctuation\">(<\/span>Dense<span class=\"token punctuation\">)<\/span>              <span class=\"token punctuation\">(<\/span>None<span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span>              <span class=\"token number\">6<\/span>\r\n<span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">==<\/span>\r\nTotal params<span class=\"token punctuation\">:<\/span> <span class=\"token number\">146.0<\/span>\r\nTrainable params<span class=\"token punctuation\">:<\/span> <span class=\"token number\">146<\/span>\r\nNon<span class=\"token operator\">-<\/span>trainable params<span class=\"token punctuation\">:<\/span> <span class=\"token number\">0.0<\/span>\r\n_________________________________________________________________<\/pre>\n<p>\u7f51\u7edc(\u5c06\u4f1a)\u6b63\u786e\u5730\u5b66\u4e60\u9884\u6d4b\u95ee\u9898\u3002<\/p>\n<pre class=\"prism-token token language-js\"><span class=\"token number\">0.0<\/span>\r\n<span class=\"token number\">0.2<\/span>\r\n<span class=\"token number\">0.4<\/span>\r\n<span class=\"token number\">0.6<\/span>\r\n<span class=\"token number\">0.8<\/span><\/pre>\n<h2 id=\"%E7%94%A8%E4%BA%8E%E5%A4%9A%E5%AF%B9%E4%B8%80%E7%9A%84%E5%BA%8F%E5%88%97%E9%A2%84%E6%B5%8B%E7%9A%84LSTM(%E4%B8%8D%E5%90%ABTimeDistributed)\"><span class=\"ez-toc-section\" id=\"%E7%94%A8%E4%BA%8E%E5%A4%9A%E5%AF%B9%E4%B8%80%E7%9A%84%E5%BA%8F%E5%88%97%E9%A2%84%E6%B5%8B%E7%9A%84LSTM%E4%B8%8D%E5%90%ABTimeDistributed\"><\/span>\u7528\u4e8e\u591a\u5bf9\u4e00\u7684\u5e8f\u5217\u9884\u6d4b\u7684LSTM(\u4e0d\u542bTimeDistributed)<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u5728\u672c\u5c0f\u8282\u4e2d\uff0c\u6211\u4eec\u5f00\u53d1\u4e86\u4e00\u4e2aLSTM\u6765\u4e00\u6b21\u6027\u8f93\u51fa\u5e8f\u5217\uff0c\u5c3d\u7ba1\u6ca1\u6709TimeDistributed\u88c5\u9970\u5668\u5c42\u3002<\/p>\n<p>LSTM\u7684\u8f93\u5165\u5fc5\u987b\u662f\u4e09\u7ef4\u7684\u3002\u6211\u4eec\u53ef\u4ee5\u5c062D\u5e8f\u5217\u91cd\u5851\u4e3a\u5177\u67091\u4e2a\u6837\u672c\u30015\u4e2a\u65f6\u95f4\u6b65\u957f\u548c1\u4e2a\u7279\u5f81\u76843D\u5e8f\u5217\u3002\u6211\u4eec\u5c06\u8f93\u51fa\u5b9a\u4e49\u4e3a\u5177\u67095\u4e2a\u7279\u5f81\u76841\u4e2a\u6837\u672c\u3002<\/p>\n<pre class=\"prism-token token language-js\">X <span class=\"token operator\">=<\/span> seq<span class=\"token punctuation\">.<\/span><span class=\"token function\">reshape<\/span><span class=\"token punctuation\">(<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">5<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span>\r\ny <span class=\"token operator\">=<\/span> seq<span class=\"token punctuation\">.<\/span><span class=\"token function\">reshape<\/span><span class=\"token punctuation\">(<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">5<\/span><span class=\"token punctuation\">)<\/span>\r\n<\/pre>\n<p>\u9a6c\u4e0a\uff0c\u60a8\u5c31\u53ef\u4ee5\u770b\u5230\u95ee\u9898\u5b9a\u4e49\u5fc5\u987b\u7a0d\u5fae\u8c03\u6574\uff0c\u4ee5\u652f\u6301\u6ca1\u6709TimeDistributed\u88c5\u9970\u5668\u7684\u7528\u4e8e\u5e8f\u5217\u9884\u6d4b\u7684\u7f51\u7edc\u3002\u5177\u4f53\u6765\u8bf4\uff0c\u8f93\u51fa\u4e00\u4e2a\u77e2\u91cf\uff0c\u800c\u4e0d\u662f\u4e00\u6b21\u4e00\u6b65\u5730\u6784\u5efa\u8f93\u51fa\u5e8f\u5217\u3002\u8fd9\u79cd\u5dee\u5f02\u542c\u8d77\u6765\u5f88\u5fae\u5999\uff0c\u4f46\u4e86\u89e3TimeDistributed\u88c5\u9970\u5668\u7684\u4f5c\u7528\u8fd8\u662f\u5f88\u91cd\u8981\u7684\u3002<\/p>\n<p>\u6211\u4eec\u5c06\u8be5\u6a21\u578b\u5b9a\u4e49\u4e3a\u4e00\u4e2a\u8f93\u5165\u5177\u67095\u4e2a\u65f6\u95f4\u6b65\u3002\u7b2c\u4e00\u4e2a\u9690\u85cf\u5c42\u5c06\u662f\u4e00\u4e2a5\u4e2a\u5355\u4f4d\u7684LSTM\u3002\u8f93\u51fa\u5c42\u662f\u4e00\u4e2a\u5177\u67095\u4e2a\u795e\u7ecf\u5143\u7684\u5b8c\u5168\u8fde\u63a5\u5c42\u3002<\/p>\n<pre class=\"prism-token token language-js\"># create LSTM\r\nmodel <span class=\"token operator\">=<\/span> <span class=\"token function\">Sequential<\/span><span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span>\r\nmodel<span class=\"token punctuation\">.<\/span><span class=\"token function\">add<\/span><span class=\"token punctuation\">(<\/span><span class=\"token function\">LSTM<\/span><span class=\"token punctuation\">(<\/span><span class=\"token number\">5<\/span><span class=\"token punctuation\">,<\/span> input_shape<span class=\"token operator\">=<\/span><span class=\"token punctuation\">(<\/span><span class=\"token number\">5<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\r\nmodel<span class=\"token punctuation\">.<\/span><span class=\"token function\">add<\/span><span class=\"token punctuation\">(<\/span><span class=\"token function\">Dense<\/span><span class=\"token punctuation\">(<\/span>length<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\r\nmodel<span class=\"token punctuation\">.<\/span><span class=\"token function\">compile<\/span><span class=\"token punctuation\">(<\/span>loss<span class=\"token operator\">=<\/span><span class=\"token string\">'mean_squared_error'<\/span><span class=\"token punctuation\">,<\/span> optimizer<span class=\"token operator\">=<\/span><span class=\"token string\">'adam'<\/span><span class=\"token punctuation\">)<\/span>\r\n<span class=\"token function\">print<\/span><span class=\"token punctuation\">(<\/span>model<span class=\"token punctuation\">.<\/span><span class=\"token function\">summary<\/span><span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span><\/pre>\n<p>\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u6a21\u578b\u9002\u914d\u5230500 epoches\u5e76\u4e14\u8bad\u7ec3\u6570\u636e\u96c6\u4e2d\u7684\u5355\u4e2a\u6837\u672c\u7684\u6279\u5927\u5c0f(bach size)\u4e3a1\u3002<\/p>\n<pre class=\"prism-token token language-js\"># train LSTM\r\nmodel<span class=\"token punctuation\">.<\/span><span class=\"token function\">fit<\/span><span class=\"token punctuation\">(<\/span>X<span class=\"token punctuation\">,<\/span> y<span class=\"token punctuation\">,<\/span> epochs<span class=\"token operator\">=<\/span><span class=\"token number\">500<\/span><span class=\"token punctuation\">,<\/span> batch_size<span class=\"token operator\">=<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> verbose<span class=\"token operator\">=<\/span><span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span><\/pre>\n<p>\u7efc\u4e0a\u6240\u8ff0\uff0c\u4e0b\u9762\u63d0\u4f9b\u4e86\u5b8c\u6574\u7684\u4ee3\u7801\u6e05\u5355\u3002<\/p>\n<pre class=\"prism-token token language-js\"><span class=\"token keyword\">from<\/span> numpy <span class=\"token keyword\">import<\/span> array\r\n<span class=\"token keyword\">from<\/span> keras<span class=\"token punctuation\">.<\/span>models <span class=\"token keyword\">import<\/span> Sequential\r\n<span class=\"token keyword\">from<\/span> keras<span class=\"token punctuation\">.<\/span>layers <span class=\"token keyword\">import<\/span> Dense\r\n<span class=\"token keyword\">from<\/span> keras<span class=\"token punctuation\">.<\/span>layers <span class=\"token keyword\">import<\/span> LSTM\r\n# prepare sequence\r\nlength <span class=\"token operator\">=<\/span> <span class=\"token number\">5<\/span>\r\nseq <span class=\"token operator\">=<\/span> <span class=\"token function\">array<\/span><span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">[<\/span>i<span class=\"token operator\">\/<\/span><span class=\"token function\">float<\/span><span class=\"token punctuation\">(<\/span>length<span class=\"token punctuation\">)<\/span> <span class=\"token keyword\">for<\/span> i <span class=\"token keyword\">in<\/span> <span class=\"token function\">range<\/span><span class=\"token punctuation\">(<\/span>length<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">)<\/span>\r\nX <span class=\"token operator\">=<\/span> seq<span class=\"token punctuation\">.<\/span><span class=\"token function\">reshape<\/span><span class=\"token punctuation\">(<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> length<span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span>\r\ny <span class=\"token operator\">=<\/span> seq<span class=\"token punctuation\">.<\/span><span class=\"token function\">reshape<\/span><span class=\"token punctuation\">(<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> length<span class=\"token punctuation\">)<\/span>\r\n# define LSTM configuration\r\nn_neurons <span class=\"token operator\">=<\/span> length\r\nn_batch <span class=\"token operator\">=<\/span> <span class=\"token number\">1<\/span>\r\nn_epoch <span class=\"token operator\">=<\/span> <span class=\"token number\">500<\/span>\r\n# create LSTM\r\nmodel <span class=\"token operator\">=<\/span> <span class=\"token function\">Sequential<\/span><span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span>\r\nmodel<span class=\"token punctuation\">.<\/span><span class=\"token function\">add<\/span><span class=\"token punctuation\">(<\/span><span class=\"token function\">LSTM<\/span><span class=\"token punctuation\">(<\/span>n_neurons<span class=\"token punctuation\">,<\/span> input_shape<span class=\"token operator\">=<\/span><span class=\"token punctuation\">(<\/span>length<span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\r\nmodel<span class=\"token punctuation\">.<\/span><span class=\"token function\">add<\/span><span class=\"token punctuation\">(<\/span><span class=\"token function\">Dense<\/span><span class=\"token punctuation\">(<\/span>length<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\r\nmodel<span class=\"token punctuation\">.<\/span><span class=\"token function\">compile<\/span><span class=\"token punctuation\">(<\/span>loss<span class=\"token operator\">=<\/span><span class=\"token string\">'mean_squared_error'<\/span><span class=\"token punctuation\">,<\/span> optimizer<span class=\"token operator\">=<\/span><span class=\"token string\">'adam'<\/span><span class=\"token punctuation\">)<\/span>\r\n<span class=\"token function\">print<\/span><span class=\"token punctuation\">(<\/span>model<span class=\"token punctuation\">.<\/span><span class=\"token function\">summary<\/span><span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\r\n# train LSTM\r\nmodel<span class=\"token punctuation\">.<\/span><span class=\"token function\">fit<\/span><span class=\"token punctuation\">(<\/span>X<span class=\"token punctuation\">,<\/span> y<span class=\"token punctuation\">,<\/span> epochs<span class=\"token operator\">=<\/span>n_epoch<span class=\"token punctuation\">,<\/span> batch_size<span class=\"token operator\">=<\/span>n_batch<span class=\"token punctuation\">,<\/span> verbose<span class=\"token operator\">=<\/span><span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span>\r\n# evaluate\r\nresult <span class=\"token operator\">=<\/span> model<span class=\"token punctuation\">.<\/span><span class=\"token function\">predict<\/span><span class=\"token punctuation\">(<\/span>X<span class=\"token punctuation\">,<\/span> batch_size<span class=\"token operator\">=<\/span>n_batch<span class=\"token punctuation\">,<\/span> verbose<span class=\"token operator\">=<\/span><span class=\"token number\">0<\/span><span class=\"token punctuation\">)<\/span>\r\n<span class=\"token keyword\">for<\/span> value <span class=\"token keyword\">in<\/span> result<span class=\"token punctuation\">[<\/span><span class=\"token number\">0<\/span><span class=\"token punctuation\">,<\/span><span class=\"token punctuation\">:<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">:<\/span>\r\n    <span class=\"token function\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">'%.1f'<\/span> <span class=\"token operator\">%<\/span> value<span class=\"token punctuation\">)<\/span><\/pre>\n<p>\u8fd0\u884c\u8be5\u793a\u4f8b\u9996\u5148\u6253\u5370\u914d\u7f6e\u7f51\u7edc\u7684\u6458\u8981\u3002<\/p>\n<p>\u6211\u4eec\u53ef\u4ee5\u770b\u5230LSTM\u5c42\u6709140\u4e2a\u53c2\u6570\uff0c\u5982\u4e0a\u4e00\u8282\u6240\u8ff0\u3002<\/p>\n<p>LSTM\u5355\u5143\u5df2\u88ab\u762b\u75ea\u6389\uff0c\u5e76\u4e14\u5c06\u5404\u81ea\u8f93\u51fa\u4e00\u4e2a\u5355\u503c\uff0c\u5411\u5b8c\u5168\u8fde\u63a5\u7684\u5c42\u63d0\u4f9b5\u4e2a\u503c\u7684\u5411\u91cf\u4f5c\u4e3a\u8f93\u5165\u3002\u65f6\u95f4\u7ef4\u5ea6\u6216\u5e8f\u5217\u4fe1\u606f\u5df2\u88ab\u4e22\u5f03\uff0c\u5e76\u574d\u7f29\u62105\u4e2a\u503c\u7684\u5411\u91cf\u3002<\/p>\n<p>\u6211\u4eec\u53ef\u4ee5\u770b\u5230\uff0c\u5b8c\u5168\u8fde\u63a5\u7684\u8f93\u51fa\u5c42\u67095\u4e2a\u8f93\u5165\uff0c\u9884\u671f\u8f93\u51fa5\u4e2a\u503c\u3002\u6211\u4eec\u53ef\u4ee5\u89e3\u91ca30\u4e2a\u88ab\u5b66\u4e60\u7684\u6743\u91cd\u5982\u4e0b\uff1a<\/p>\n<pre class=\"prism-token token language-js\">n <span class=\"token operator\">=<\/span> inputs <span class=\"token operator\">*<\/span> outputs <span class=\"token operator\">+<\/span> outputs\r\nn <span class=\"token operator\">=<\/span> <span class=\"token number\">5<\/span> <span class=\"token operator\">*<\/span> <span class=\"token number\">5<\/span> <span class=\"token operator\">+<\/span> <span class=\"token number\">5<\/span>\r\nn <span class=\"token operator\">=<\/span> <span class=\"token number\">30<\/span><\/pre>\n<p>\u7f51\u7edc\u6458\u8981\u62a5\u544a\u5982\u4e0b\uff1a<\/p>\n<pre class=\"prism-token token language-js\">_________________________________________________________________\r\n<span class=\"token function\">Layer<\/span> <span class=\"token punctuation\">(<\/span>type<span class=\"token punctuation\">)<\/span>                 Output Shape              Param #\r\n<span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">==<\/span>\r\n<span class=\"token function\">lstm_1<\/span> <span class=\"token punctuation\">(<\/span>LSTM<span class=\"token punctuation\">)<\/span>                <span class=\"token punctuation\">(<\/span>None<span class=\"token punctuation\">,<\/span> <span class=\"token number\">5<\/span><span class=\"token punctuation\">)<\/span>                 <span class=\"token number\">140<\/span>\r\n_________________________________________________________________\r\n<span class=\"token function\">dense_1<\/span> <span class=\"token punctuation\">(<\/span>Dense<span class=\"token punctuation\">)<\/span>              <span class=\"token punctuation\">(<\/span>None<span class=\"token punctuation\">,<\/span> <span class=\"token number\">5<\/span><span class=\"token punctuation\">)<\/span>                 <span class=\"token number\">30<\/span>\r\n<span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">==<\/span>\r\nTotal params<span class=\"token punctuation\">:<\/span> <span class=\"token number\">170.0<\/span>\r\nTrainable params<span class=\"token punctuation\">:<\/span> <span class=\"token number\">170<\/span>\r\nNon<span class=\"token operator\">-<\/span>trainable params<span class=\"token punctuation\">:<\/span> <span class=\"token number\">0.0<\/span>\r\n_________________________________________________________________<\/pre>\n<p>\u5728\u5b8c\u6210\u548c\u6253\u5370\u9884\u6d4b\u5e8f\u5217\u4e4b\u524d\uff0c\u8be5\u6a21\u578b\u662f\u9002\u914d\u7684\uff0c\u4f1a\u6253\u5370\u51fa\u635f\u5931\u4fe1\u606f\uff0c\u3002<\/p>\n<p>\u5e8f\u5217\u88ab\u6b63\u786e\u5730\u91cd\u73b0\uff0c\u4f46\u662f\u4f5c\u4e3a\u4e00\u4e2a\u6574\u4f53\uff0c\u800c\u4e0d\u662f\u50cf\u9010\u6b65\u5730\u8f93\u5165\u6570\u636e(\u90a3\u6837)\u3002\u6211\u4eec\u53ef\u80fd\u5df2\u7ecf\u4f7f\u7528\u4e00\u4e2a\u5bc6\u96c6\u5c42(Dense layer)\u4f5c\u4e3a\u7b2c\u4e00\u9690\u85cf\u5c42\u800c\u4e0d\u662fLSTM\uff0c\u56e0\u4e3a\u8fd9\u79cdLSTM\u7684\u4f7f\u7528(\u65b9\u5f0f)\u6ca1\u6709\u5145\u5206\u5229\u7528\u5b83\u4eec\u7684\u5e8f\u5217\u5b66\u4e60\u548c\u5904\u7406\u7684\u5168\u90e8\u6027\u80fd\u3002<\/p>\n<pre class=\"prism-token token language-js\"><span class=\"token number\">0.0<\/span>\r\n<span class=\"token number\">0.2<\/span>\r\n<span class=\"token number\">0.4<\/span>\r\n<span class=\"token number\">0.6<\/span>\r\n<span class=\"token number\">0.8<\/span><\/pre>\n<h2 id=\"%E7%94%A8%E4%BA%8E%E5%BA%8F%E5%88%97%E9%A2%84%E6%B5%8B%E7%9A%84%E5%A4%9A%E5%AF%B9%E5%A4%9ALSTM(%E5%B8%A6TimeDistributed)\"><span class=\"ez-toc-section\" id=\"%E7%94%A8%E4%BA%8E%E5%BA%8F%E5%88%97%E9%A2%84%E6%B5%8B%E7%9A%84%E5%A4%9A%E5%AF%B9%E5%A4%9ALSTM%E5%B8%A6TimeDistributed\"><\/span>\u7528\u4e8e\u5e8f\u5217\u9884\u6d4b\u7684\u591a\u5bf9\u591aLSTM(\u5e26TimeDistributed)<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u5728\u672c\u5c0f\u8282\u4e2d\uff0c\u6211\u4eec\u5c06\u4f7f\u7528TimeDistributed\u56fe\u5c42\u6765\u5904\u7406\u6765\u81eaLSTM\u9690\u85cf\u5c42\u7684\u8f93\u51fa\u3002<\/p>\n<p>\u4f7f\u7528TimeDistributed\u88c5\u9970\u5668\u5c42\u65f6\u8981\u8bb0\u4f4f\u4e24\u70b9\uff1a<\/p>\n<ul class=\"ul-level-0\">\n<li><strong>\u8f93\u5165\u5fc5\u987b(\u81f3\u5c11)\u662f3D<\/strong>\u3002\u8fd9\u901a\u5e38\u610f\u5473\u7740\u60a8\u9700\u8981\u5728TimeDistributed \u88c5\u9970\u7684Dense\u5c42\u4e4b\u524d\u914d\u7f6e\u4e0a\u4e00\u4e2aLSTM\u56fe\u5c42\u4ee5\u8fd4\u56de\u5e8f\u5217(\u4f8b\u5982\uff0c\u5c06\u201creturn_sequences\u201d\u53c2\u6570\u8bbe\u7f6e\u4e3a\u201cTrue\u201d)\u3002<\/li>\n<li><strong>\u8f93\u51fa\u5c06\u662f3D<\/strong>\u3002\u8fd9\u610f\u5473\u7740\u5982\u679cTimeDistributed\u5305\u88c5\u7684Dense\u5c42\u662f\u8f93\u51fa\u5c42\uff0c\u5e76\u4e14\u60a8\u6b63\u5728\u9884\u6d4b\u4e00\u4e2a\u5e8f\u5217\uff0c\u5219\u9700\u8981\u5c06y\u9635\u5217\u8c03\u6574\u4e3a3D\u77e2\u91cf\u3002<\/li>\n<\/ul>\n<p>\u6211\u4eec\u53ef\u4ee5\u5c06\u8f93\u51fa\u7684\u6837\u5f0f\u5b9a\u4e49\u4e3a\u5177\u67091\u4e2a\u6837\u672c\uff0c5\u4e2a\u65f6\u95f4\u6b65\u548c1\u4e2a\u7279\u5f81\uff0c\u5c31\u50cf\u8f93\u5165\u5e8f\u5217\u4e00\u6837\uff0c\u5982\u4e0b\u6240\u793a\uff1a<\/p>\n<pre class=\"prism-token token language-js\">y <span class=\"token operator\">=<\/span> seq<span class=\"token punctuation\">.<\/span><span class=\"token function\">reshape<\/span><span class=\"token punctuation\">(<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> length<span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span><\/pre>\n<p>\u901a\u8fc7\u8bbe\u7f6e\u201c<em>return_sequences<\/em>\u201d\u53c2\u6570\u4e3atrue\uff0c\u6211\u4eec\u53ef\u4ee5\u5b9a\u4e49LSTM\u9690\u85cf\u5c42\u6765\u8fd4\u56de\u5e8f\u5217\u800c\u4e0d\u662f\u5355\u4e2a\u503c\u3002<\/p>\n<pre class=\"prism-token token language-js\">model<span class=\"token punctuation\">.<\/span><span class=\"token function\">add<\/span><span class=\"token punctuation\">(<\/span><span class=\"token function\">LSTM<\/span><span class=\"token punctuation\">(<\/span>n_neurons<span class=\"token punctuation\">,<\/span> input_shape<span class=\"token operator\">=<\/span><span class=\"token punctuation\">(<\/span>length<span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">,<\/span> return_sequences<span class=\"token operator\">=<\/span>True<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span><\/pre>\n<p>\u8fd9\u6837\uff0c\u6bcf\u4e2aLSTM\u5355\u5143\u90fd\u4f1a\u8fd4\u56de\u4e00\u4e2a\u67095\u4e2a\u8f93\u51fa\u7684\u5e8f\u5217\uff0c\u4e00\u4e2a(\u8f93\u51fa)\u5bf9\u5e94\u8f93\u5165\u6570\u636e\u7684\u4e00\u4e2a\u65f6\u95f4\u6b65\uff0c\u800c\u4e0d\u662f\u50cf\u524d\u9762\u7684\u4f8b\u5b50\u90a3\u6837\u8f93\u51fa\u5355\u4e2a\u8f93\u51fa\u503c\u3002<\/p>\n<p>\u6211\u4eec\u4e5f\u53ef\u4ee5\u5728\u8f93\u51fa\u5c42\u4e0a\u4f7f\u7528TimeDistributed\u6765\u88c5\u9970\u4e00\u4e2a\u5b8c\u5168\u8fde\u63a5\u7684Dense\u5c42\uff0c\u5e76\u4e14\u53ea\u5e26\u6709\u4e00\u4e2a\u8f93\u51fa\u3002<\/p>\n<pre class=\"prism-token token language-js\">model<span class=\"token punctuation\">.<\/span><span class=\"token function\">add<\/span><span class=\"token punctuation\">(<\/span><span class=\"token function\">TimeDistributed<\/span><span class=\"token punctuation\">(<\/span><span class=\"token function\">Dense<\/span><span class=\"token punctuation\">(<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span><\/pre>\n<p>\u8f93\u51fa\u5c42\u4e2d\u7684\u5355\u4e2a\u8f93\u51fa\u503c\u662f\u5173\u952e\u3002\u5b83\u5f3a\u8c03\u6211\u4eec\u6253\u7b97\u4ece\u8f93\u5165\u5e8f\u5217\u4e2d\u7684\u6bcf\u4e2a\u65f6\u95f4\u6b65\u4e2d\u8f93\u51fa\u4e00\u4e2a\u65f6\u95f4\u6b65\u3002\u6070\u597d\u6211\u4eec\u4f1a\u4e00\u6b21\u6027\u5904\u7406\u8f93\u5165\u5e8f\u5217\u76845\u4e2a\u65f6\u95f4\u6b65\u3002<\/p>\n<p>TimeDistributed\u901a\u8fc7\u4e00\u6b21\u4e00\u4e2a\u65f6\u95f4\u6b65\u5728LSTM\u8f93\u51fa\u4e0a\u5e94\u7528\u76f8\u540c\u7684Dense\u5c42(\u76f8\u540c\u7684\u6743\u91cd)\u6765\u5b9e\u73b0\u8fd9\u4e2a\u6280\u5de7\u3002\u901a\u8fc7\u8fd9\u79cd\u65b9\u6cd5\uff0c\u8f93\u51fa\u5c42\u53ea\u9700\u8981\u4e00\u4e2a\u8fde\u63a5\u5230\u6bcf\u4e2aLSTM\u5355\u5143(\u52a0\u4e0a\u4e00\u4e2abias)\u7684\u8fde\u63a5\u3002<\/p>\n<p>\u51fa\u4e8e\u8fd9\u4e2a\u8003\u8651\uff0c\u9700\u8981\u589e\u52a0\u8bad\u7ec3\u7684epoch(\u8fed\u4ee3\u6b21\u6570)\u4ee5\u517c\u987e\u5230\u8f83\u5c0f\u7684\u7f51\u7edc\u5bb9\u91cf\u3002\u6211\u628a\u5b83\u4ece500\u500d\u589e\u52a0\u52301000\u500d\uff0c\u4ee5\u5339\u914d\u8d77\u521d\u7684\u4e00\u5bf9\u4e00\u7684\u4f8b\u5b50\u3002<\/p>\n<p>\u7efc\u4e0a\u6240\u8ff0\uff0c\u4e0b\u9762\u63d0\u4f9b\u4e86\u5b8c\u6574\u7684\u4ee3\u7801\u6e05\u5355\u3002<\/p>\n<pre class=\"prism-token token language-js\"><span class=\"token keyword\">from<\/span> numpy <span class=\"token keyword\">import<\/span> array\r\n<span class=\"token keyword\">from<\/span> keras<span class=\"token punctuation\">.<\/span>models <span class=\"token keyword\">import<\/span> Sequential\r\n<span class=\"token keyword\">from<\/span> keras<span class=\"token punctuation\">.<\/span>layers <span class=\"token keyword\">import<\/span> Dense\r\n<span class=\"token keyword\">from<\/span> keras<span class=\"token punctuation\">.<\/span>layers <span class=\"token keyword\">import<\/span> TimeDistributed\r\n<span class=\"token keyword\">from<\/span> keras<span class=\"token punctuation\">.<\/span>layers <span class=\"token keyword\">import<\/span> LSTM\r\n# prepare sequence\r\nlength <span class=\"token operator\">=<\/span> <span class=\"token number\">5<\/span>\r\nseq <span class=\"token operator\">=<\/span> <span class=\"token function\">array<\/span><span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">[<\/span>i<span class=\"token operator\">\/<\/span><span class=\"token function\">float<\/span><span class=\"token punctuation\">(<\/span>length<span class=\"token punctuation\">)<\/span> <span class=\"token keyword\">for<\/span> i <span class=\"token keyword\">in<\/span> <span class=\"token function\">range<\/span><span class=\"token punctuation\">(<\/span>length<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">)<\/span>\r\nX <span class=\"token operator\">=<\/span> seq<span class=\"token punctuation\">.<\/span><span class=\"token function\">reshape<\/span><span class=\"token punctuation\">(<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> length<span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span>\r\ny <span class=\"token operator\">=<\/span> seq<span class=\"token punctuation\">.<\/span><span class=\"token function\">reshape<\/span><span class=\"token punctuation\">(<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> length<span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span>\r\n# define LSTM configuration\r\nn_neurons <span class=\"token operator\">=<\/span> length\r\nn_batch <span class=\"token operator\">=<\/span> <span class=\"token number\">1<\/span>\r\nn_epoch <span class=\"token operator\">=<\/span> <span class=\"token number\">1000<\/span>\r\n# create LSTM\r\nmodel <span class=\"token operator\">=<\/span> <span class=\"token function\">Sequential<\/span><span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span>\r\nmodel<span class=\"token punctuation\">.<\/span><span class=\"token function\">add<\/span><span class=\"token punctuation\">(<\/span><span class=\"token function\">LSTM<\/span><span class=\"token punctuation\">(<\/span>n_neurons<span class=\"token punctuation\">,<\/span> input_shape<span class=\"token operator\">=<\/span><span class=\"token punctuation\">(<\/span>length<span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">,<\/span> return_sequences<span class=\"token operator\">=<\/span>True<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\r\nmodel<span class=\"token punctuation\">.<\/span><span class=\"token function\">add<\/span><span class=\"token punctuation\">(<\/span><span class=\"token function\">TimeDistributed<\/span><span class=\"token punctuation\">(<\/span><span class=\"token function\">Dense<\/span><span class=\"token punctuation\">(<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\r\nmodel<span class=\"token punctuation\">.<\/span><span class=\"token function\">compile<\/span><span class=\"token punctuation\">(<\/span>loss<span class=\"token operator\">=<\/span><span class=\"token string\">'mean_squared_error'<\/span><span class=\"token punctuation\">,<\/span> optimizer<span class=\"token operator\">=<\/span><span class=\"token string\">'adam'<\/span><span class=\"token punctuation\">)<\/span>\r\n<span class=\"token function\">print<\/span><span class=\"token punctuation\">(<\/span>model<span class=\"token punctuation\">.<\/span><span class=\"token function\">summary<\/span><span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\r\n# train LSTM\r\nmodel<span class=\"token punctuation\">.<\/span><span class=\"token function\">fit<\/span><span class=\"token punctuation\">(<\/span>X<span class=\"token punctuation\">,<\/span> y<span class=\"token punctuation\">,<\/span> epochs<span class=\"token operator\">=<\/span>n_epoch<span class=\"token punctuation\">,<\/span> batch_size<span class=\"token operator\">=<\/span>n_batch<span class=\"token punctuation\">,<\/span> verbose<span class=\"token operator\">=<\/span><span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span>\r\n# evaluate\r\nresult <span class=\"token operator\">=<\/span> model<span class=\"token punctuation\">.<\/span><span class=\"token function\">predict<\/span><span class=\"token punctuation\">(<\/span>X<span class=\"token punctuation\">,<\/span> batch_size<span class=\"token operator\">=<\/span>n_batch<span class=\"token punctuation\">,<\/span> verbose<span class=\"token operator\">=<\/span><span class=\"token number\">0<\/span><span class=\"token punctuation\">)<\/span>\r\n<span class=\"token keyword\">for<\/span> value <span class=\"token keyword\">in<\/span> result<span class=\"token punctuation\">[<\/span><span class=\"token number\">0<\/span><span class=\"token punctuation\">,<\/span><span class=\"token punctuation\">:<\/span><span class=\"token punctuation\">,<\/span><span class=\"token number\">0<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">:<\/span>\r\n    <span class=\"token function\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">'%.1f'<\/span> <span class=\"token operator\">%<\/span> value<span class=\"token punctuation\">)<\/span><\/pre>\n<p>\u8fd0\u884c\u8fd9\u4e2a\u4f8b\u5b50\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\u914d\u7f6e\u7f51\u7edc\u7684\u7ed3\u6784\u3002<\/p>\n<p>\u6211\u4eec\u53ef\u4ee5\u770b\u5230\uff0c\u8ddf\u524d\u9762\u7684\u4f8b\u5b50\u4e00\u6837\uff0c\u6211\u4eec\u5728LSTM\u9690\u85cf\u5c42\u4e2d\u6709140\u4e2a\u53c2\u6570\u3002<\/p>\n<p>\u5b8c\u5168\u8fde\u63a5\u7684\u8f93\u51fa\u5219\u5c42\u662f\u4e00\u4e2a\u975e\u5e38\u4e0d\u540c\u7684\u7ed3\u679c\u3002\u5b9e\u9645\u4e0a\uff0c\u5b83\u5b8c\u5168\u7b26\u5408\u4e00\u5bf9\u4e00\u7684\u4f8b\u5b50\u3002\u4e00\u4e2a\u795e\u7ecf\u5143\u5bf9\u4e8e\u524d\u4e00\u5c42\u4e2d\u7684\u6bcf\u4e2aLSTM\u5355\u5143\u6709\u4e00\u4e2a\u6743\u91cd\uff0c\u53e6\u5916\u4e00\u4e2a\u7528\u4e8ebias\u8f93\u5165\u3002<\/p>\n<p>\u8fd9\u505a\u4e86\u4e24\u4ef6\u91cd\u8981\u7684\u4e8b\u60c5\uff1a<\/p>\n<ul class=\"ul-level-0\">\n<li>\u5141\u8bb8\u5c06\u95ee\u9898\u91cd\u6784\u5e76\u50cf\u5b83\u88ab\u5b9a\u4e49\u90a3\u6837\u6765\u5b66\u4e60\uff0c\u5373\u4e00\u4e2a\u8f93\u5165\u5bf9\u5e94\u4e00\u4e2a\u8f93\u51fa\uff0c\u4fdd\u6301\u6bcf\u4e2a\u65f6\u95f4\u6b65\u7684\u5185\u90e8\u8fc7\u7a0b\u5206\u79bb\u3002<\/li>\n<li>\u901a\u8fc7\u8981\u6c42\u5c11\u5f97\u591a\u7684\u6743\u91cd\u6765\u7b80\u5316\u7f51\u7edc\uff0c\u4f7f\u5f97\u4e00\u6b21\u53ea\u5904\u7406\u4e00\u4e2a\u65f6\u95f4\u6b65\u3002<\/li>\n<\/ul>\n<p>\u4e00\u4e2a\u66f4\u7b80\u5355\u7684\u5b8c\u5168\u8fde\u63a5\u5c42\u88ab\u5e94\u7528\u5230\u4ece\u524d\u4e00\u5c42\u63d0\u4f9b\u7684\u5e8f\u5217\u4e2d\u7684\u6bcf\u4e2a\u65f6\u95f4\u6b65\u9aa4\uff0c\u4ee5\u5efa\u7acb\u8f93\u51fa\u5e8f\u5217\u3002<\/p>\n<pre class=\"prism-token token language-js\">_________________________________________________________________\r\n<span class=\"token function\">Layer<\/span> <span class=\"token punctuation\">(<\/span>type<span class=\"token punctuation\">)<\/span>                 Output Shape              Param #\r\n<span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">==<\/span>\r\n<span class=\"token function\">lstm_1<\/span> <span class=\"token punctuation\">(<\/span>LSTM<span class=\"token punctuation\">)<\/span>                <span class=\"token punctuation\">(<\/span>None<span class=\"token punctuation\">,<\/span> <span class=\"token number\">5<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">5<\/span><span class=\"token punctuation\">)<\/span>              <span class=\"token number\">140<\/span>\r\n_________________________________________________________________\r\n<span class=\"token function\">time_distributed_1<\/span> <span class=\"token punctuation\">(<\/span><span class=\"token function\">TimeDist<\/span> <span class=\"token punctuation\">(<\/span>None<span class=\"token punctuation\">,<\/span> <span class=\"token number\">5<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span>              <span class=\"token number\">6<\/span>\r\n<span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">===<\/span><span class=\"token operator\">==<\/span>\r\nTotal params<span class=\"token punctuation\">:<\/span> <span class=\"token number\">146.0<\/span>\r\nTrainable params<span class=\"token punctuation\">:<\/span> <span class=\"token number\">146<\/span>\r\nNon<span class=\"token operator\">-<\/span>trainable params<span class=\"token punctuation\">:<\/span> <span class=\"token number\">0.0<\/span>\r\n_________________________________________________________________<\/pre>\n<p>\u518d\u6b21\uff0c\u7f51\u7edc\u5b66\u4e60\u5230\u4e86\u5e8f\u5217\u3002<\/p>\n<pre class=\"prism-token token language-js\"><span class=\"token number\">0.0<\/span>\r\n<span class=\"token number\">0.2<\/span>\r\n<span class=\"token number\">0.4<\/span>\r\n<span class=\"token number\">0.6<\/span>\r\n<span class=\"token number\">0.8<\/span><\/pre>\n<p>\u5728\u7b2c\u4e00\u4e2a\u4f8b\u5b50\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u8003\u8651\u5c06\u95ee\u9898\u7528\u65f6\u95f4\u7247\u91cd\u6784\u5e76\u4e14\u5c06\u4e00\u4e2aTime Distrubuted layer\u4f5c\u4e3a\u4e00\u4e2a\u66f4\u4e3a\u7d27\u5bc6\u7684\u5b9e\u73b0\u4e00\u5bf9\u4e00\u7f51\u7edc\u7684\u65b9\u6cd5\u3002\u5b83\u751a\u81f3\u53ef\u80fd\u5728\u66f4\u5927\u7684\u89c4\u6a21(\u7a7a\u95f4\u6216\u65f6\u95f4)\u4e0a\u66f4\u6709\u6548\u7387\u3002<\/p>\n<h2 id=\"%E8%BF%9B%E4%B8%80%E6%AD%A5%E9%98%85%E8%AF%BB\"><span class=\"ez-toc-section\" id=\"%E8%BF%9B%E4%B8%80%E6%AD%A5%E9%98%85%E8%AF%BB\"><\/span>\u8fdb\u4e00\u6b65\u9605\u8bfb<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u4ee5\u4e0b\u662f\u60a8\u53ef\u80fd\u60f3\u8981\u6df1\u5165\u4e86\u89e3\u7684TimeDistributed layer\u7684\u4e00\u4e9b\u8d44\u6e90\u548c\u8ba8\u8bba\u3002<\/p>\n<ul class=\"ul-level-0\">\n<li><a href=\"https:\/\/keras.io\/layers\/wrappers\/#timedistributed\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" data-from=\"10680\">TimeDistributed Layer<\/a> in the Keras API<\/li>\n<li><a href=\"https:\/\/github.com\/fchollet\/keras\/blob\/master\/keras\/layers\/wrappers.py#L56\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" data-from=\"10680\">TimeDistributed<\/a>code on GitHub<\/li>\n<li><a href=\"http:\/\/datascience.stackexchange.com\/questions\/10836\/the-difference-between-dense-and-timedistributeddense-of-keras\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" data-from=\"10680\">The difference between \u2018Dense\u2019 and \u2018TimeDistributedDense\u2019 of \u2018Keras\u2019 <\/a>on StackExchange\u5728StackExchange\u4e0a\u7684\u533a\u522b<\/li>\n<li><a href=\"https:\/\/github.com\/fchollet\/keras\/issues\/1029\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" data-from=\"10680\">When and How to use TimeDistributedDense<\/a> on GitHub<\/li>\n<\/ul>\n<h2 id=\"%E6%A6%82%E8%A6%81\"><span class=\"ez-toc-section\" id=\"%E6%A6%82%E8%A6%81\"><\/span>\u6982\u8981<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u5728\u672c\u6559\u7a0b\u4e2d\uff0c\u60a8\u4e86\u89e3\u4e86\u5982\u4f55\u5f00\u53d1\u7528\u4e8e\u5e8f\u5217\u9884\u6d4b\u7684LSTM\u7f51\u7edc\u4ee5\u53caTimeDistributed\u5c42\u7684\u4f5c\u7528\u3002<\/p>\n<p>\u5177\u4f53\u6765\u8bf4\uff0c\u4f60\u4e86\u89e3\u5230\uff1a<\/p>\n<ul class=\"ul-level-0\">\n<li>\u5982\u4f55\u8bbe\u8ba1\u4e00\u5bf9\u4e00\u7684LSTM\u8fdb\u884c\u5e8f\u5217\u9884\u6d4b\u3002<\/li>\n<li>\u5982\u4f55\u5728\u4e0d\u4f7f\u7528TimeDistributed\u5c42\u7684\u60c5\u51b5\u4e0b\u8bbe\u8ba1\u591a\u5bf9\u4e00\u7684LSTM\u8fdb\u884c\u5e8f\u5217\u9884\u6d4b\u3002<\/li>\n<li>\u5982\u4f55\u5229\u7528TimeDistributed\u5c42\u8bbe\u8ba1\u4e00\u4e2a\u591a\u5bf9\u591a\u7684LSTM\u8fdb\u884c\u5e8f\u5217\u9884\u6d4b\u3002<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<h2 style=\"margin:0px 0px 20px;padding:0px;font-size:18px;box-sizing:border-box;list-style:inherit;line-height:1.5;min-height:1.5em;font-family:&quot;white-space:pre-wrap;\">\n\t<span style=\"font-size:14px;\">How to Use the TimeDistributed Layer for Long Short-Term Memory Networks in Python<\/span><br \/>\n<\/h2>\n<p style=\"margin-top:15px;margin-bottom:15px;padding:0px;box-sizing:border-box;list-style:inherit;font-family:&quot;min-height:0px;color:#333333;font-size:16px;white-space:pre-wrap;\">\n\t<span style=\"font-size:14px;\">\u539f\u6587\u4f5c\u8005\uff1aJason Brownlee<\/span>\n<\/p>\n<p style=\"margin-top:15px;margin-bottom:15px;padding:0px;box-sizing:border-box;list-style:inherit;font-family:&quot;min-height:0px;color:#333333;font-size:16px;white-space:pre-wrap;\">\n\t<span style=\"font-size:14px;\">\u539f\u6587\u5730\u5740\uff1a<\/span><a href=\"https:\/\/machinelearningmastery.com\/timedistributed-layer-for-long-short-term-memory-networks-in-python\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" style=\"text-decoration:none;box-sizing:border-box;list-style:inherit;color:#00A4FF;\"><span style=\"font-size:14px;\">https:\/\/machinelearningmastery.com\/timedistributed-layer-for-long-short-term-memory-networks-i&#8230;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":403,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[337],"tags":[],"class_list":["post-259","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v16.9 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>[\u8f6c] \u5982\u4f55\u5728Python\u4e2d\u5c06TimeDistributed\u5c42\u7528\u4e8eLong Short-Term Memory Networks - Wayne&#039;s Blog<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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