{"id":23434,"date":"2024-03-16T01:25:15","date_gmt":"2024-03-16T01:25:15","guid":{"rendered":"https:\/\/www.silicloud.com\/blog\/what-is-the-usage-of-unsqueeze-in-numpy\/"},"modified":"2024-03-22T01:15:44","modified_gmt":"2024-03-22T01:15:44","slug":"what-is-the-usage-of-unsqueeze-in-numpy","status":"publish","type":"post","link":"https:\/\/www.silicloud.com\/blog\/what-is-the-usage-of-unsqueeze-in-numpy\/","title":{"rendered":"What is the usage of unsqueeze in NumPy?"},"content":{"rendered":"

The `unsqueeze` function in numpy is used to add a dimension at the specified axis. Here is how it is used:<\/p>\n

numpy.unsqueeze(arr, axis)\r\n<\/code><\/pre>\n
Explanation of Parameters:<\/p>\n
    \n
  1. arr: input array or matrix.<\/li>\n
  2. Axis: The index of the dimension where a new dimension will be inserted in its position.<\/li>\n<\/ol>\n
    In reality, the unsqueeze function is implemented using the reshape function. It allows for inserting a dimension of size 1 at a specified dimension, thus increasing the dimensions of an array or matrix.<\/p>\n
    “\u4ed6\u5f88\u61d2\uff0c\u4ece\u6765\u4e0d\u505a\u5bb6\u52a1\u3002”
    \n“He is so lazy, he never does any housework.”<\/p>\n
    import<\/span> numpy as<\/span> np\r\n\r\n# \u521b\u5efa\u4e00\u4e2a\u4e00\u7ef4\u6570\u7ec4<\/span>\r\na = np.array([1<\/span>, 2<\/span>, 3<\/span>, 4<\/span>, 5<\/span>])\r\n\r\n# \u4f7f\u7528unsqueeze\u5728\u7ef4\u5ea60\u4e0a\u589e\u52a0\u4e00\u4e2a\u7ef4\u5ea6<\/span>\r\nb = np.unsqueeze(a, axis=0<\/span>)\r\nprint<\/span>(b.shape)  # \u8f93\u51fa(1, 5)<\/span>\r\n\r\n# \u4f7f\u7528unsqueeze\u5728\u7ef4\u5ea61\u4e0a\u589e\u52a0\u4e00\u4e2a\u7ef4\u5ea6<\/span>\r\nc = np.unsqueeze(a, axis=1<\/span>)\r\nprint<\/span>(c.shape)  # \u8f93\u51fa(5, 1)<\/span>\r\n<\/code><\/pre>\n
    In the above example, the unsqueeze function adds a dimension at dimension 0, turning a one-dimensional array with a shape of (5,) into a two-dimensional array with a shape of (1, 5). Then, it adds a dimension at dimension 1, turning the original one-dimensional array into a two-dimensional array with a shape of (5, 1).<\/p>\n","protected":false},"excerpt":{"rendered":"
    The `unsqueeze` function in numpy is used to add a dimension at the specified axis. Here is how it is used: numpy.unsqueeze(arr, axis) Explanation of Parameters: arr: input array or matrix. Axis: The index of the dimension where a new dimension will be inserted in its position. In reality, the unsqueeze function is implemented using […]<\/p>\n","protected":false},"author":14,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_import_markdown_pro_load_document_selector":0,"_import_markdown_pro_submit_text_textarea":"","footnotes":""},"categories":[1],"tags":[],"class_list":["post-23434","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"\nWhat is the usage of unsqueeze in NumPy? - Blog - Silicon Cloud<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.silicloud.com\/blog\/what-is-the-usage-of-unsqueeze-in-numpy\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"What is the usage of unsqueeze in NumPy?\" \/>\n<meta property=\"og:description\" content=\"The `unsqueeze` function in numpy is used to add a dimension at the specified axis. Here is how it is used: numpy.unsqueeze(arr, axis) Explanation of Parameters: arr: input array or matrix. Axis: The index of the dimension where a new dimension will be inserted in its position. In reality, the unsqueeze function is implemented using […]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.silicloud.com\/blog\/what-is-the-usage-of-unsqueeze-in-numpy\/\" \/>\n<meta property=\"og:site_name\" content=\"Blog - Silicon Cloud\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/SiliCloudGlobal\/\" \/>\n<meta property=\"article:published_time\" content=\"2024-03-16T01:25:15+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-03-22T01:15:44+00:00\" \/>\n<meta name=\"author\" content=\"Noah Thompson\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@SiliCloudGlobal\" \/>\n<meta name=\"twitter:site\" content=\"@SiliCloudGlobal\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Noah Thompson\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.silicloud.com\/blog\/what-is-the-usage-of-unsqueeze-in-numpy\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.silicloud.com\/blog\/what-is-the-usage-of-unsqueeze-in-numpy\/\"},\"author\":{\"name\":\"Noah Thompson\",\"@id\":\"https:\/\/www.silicloud.com\/blog\/#\/schema\/person\/2e83cc6ab9f60d36921c2d0f9f280f4a\"},\"headline\":\"What is the usage of unsqueeze in NumPy?\",\"datePublished\":\"2024-03-16T01:25:15+00:00\",\"dateModified\":\"2024-03-22T01:15:44+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.silicloud.com\/blog\/what-is-the-usage-of-unsqueeze-in-numpy\/\"},\"wordCount\":142,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/www.silicloud.com\/blog\/#organization\"},\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.silicloud.com\/blog\/what-is-the-usage-of-unsqueeze-in-numpy\/\",\"url\":\"https:\/\/www.silicloud.com\/blog\/what-is-the-usage-of-unsqueeze-in-numpy\/\",\"name\":\"What is the usage of unsqueeze in NumPy? 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