{"action":"opened","issue":{"url":"https://api.github.com/repos/fchollet/keras/issues/6797","repository_url":"https://api.github.com/repos/fchollet/keras","labels_url":"https://api.github.com/repos/fchollet/keras/issues/6797/labels{/name}","comments_url":"https://api.github.com/repos/fchollet/keras/issues/6797/comments","events_url":"https://api.github.com/repos/fchollet/keras/issues/6797/events","html_url":"https://github.com/fchollet/keras/issues/6797","id":232226486,"number":6797,"title":"resnet50.py and AveragePooling2D","user":{"login":"dineshbvadhia","id":720948,"avatar_url":"https://avatars3.githubusercontent.com/u/720948?v=3","gravatar_id":"","url":"https://api.github.com/users/dineshbvadhia","html_url":"https://github.com/dineshbvadhia","followers_url":"https://api.github.com/users/dineshbvadhia/followers","following_url":"https://api.github.com/users/dineshbvadhia/following{/other_user}","gists_url":"https://api.github.com/users/dineshbvadhia/gists{/gist_id}","starred_url":"https://api.github.com/users/dineshbvadhia/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/dineshbvadhia/subscriptions","organizations_url":"https://api.github.com/users/dineshbvadhia/orgs","repos_url":"https://api.github.com/users/dineshbvadhia/repos","events_url":"https://api.github.com/users/dineshbvadhia/events{/privacy}","received_events_url":"https://api.github.com/users/dineshbvadhia/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2017-05-30T11:47:36Z","updated_at":"2017-05-30T11:47:36Z","closed_at":null,"body":"The code doc says:\r\n```\r\n `avg` means that global average pooling will be applied to the output of the last convolutional layer, and thus the output of the model will be a 2D tensor.\r\n```\r\nStarting at ln232, the code is:\r\n```\r\n    x = AveragePooling2D((7, 7), name='avg_pool')(x)\r\n\r\n    if include_top:\r\n        x = Flatten()(x)\r\n        x = Dense(classes, activation='softmax', name='fc1000')(x)\r\n    else:\r\n        if pooling == 'avg':\r\n            x = GlobalAveragePooling2D()(x)\r\n        elif pooling == 'max':\r\n            x = GlobalMaxPooling2D()(x)\r\n```\r\nAveragePooling2D is applied to the output of the last convolutional layer and then GlobalAveragePooling2D is applied. Is that correct?\r\n\r\nI ask because I get the same extracted vector for 'None', 'avg' and 'max'."}}
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