{"action":"created","issue":{"url":"https://api.github.com/repos/tensorflow/tensorflow/issues/675","repository_url":"https://api.github.com/repos/tensorflow/tensorflow","labels_url":"https://api.github.com/repos/tensorflow/tensorflow/issues/675/labels{/name}","comments_url":"https://api.github.com/repos/tensorflow/tensorflow/issues/675/comments","events_url":"https://api.github.com/repos/tensorflow/tensorflow/issues/675/events","html_url":"https://github.com/tensorflow/tensorflow/issues/675","id":124740366,"node_id":"MDU6SXNzdWUxMjQ3NDAzNjY=","number":675,"title":"Gradients of non-scalars (higher rank Jacobians)","user":{"login":"zackchase","id":2390222,"node_id":"MDQ6VXNlcjIzOTAyMjI=","avatar_url":"https://avatars0.githubusercontent.com/u/2390222?v=4","gravatar_id":"","url":"https://api.github.com/users/zackchase","html_url":"https://github.com/zackchase","followers_url":"https://api.github.com/users/zackchase/followers","following_url":"https://api.github.com/users/zackchase/following{/other_user}","gists_url":"https://api.github.com/users/zackchase/gists{/gist_id}","starred_url":"https://api.github.com/users/zackchase/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/zackchase/subscriptions","organizations_url":"https://api.github.com/users/zackchase/orgs","repos_url":"https://api.github.com/users/zackchase/repos","events_url":"https://api.github.com/users/zackchase/events{/privacy}","received_events_url":"https://api.github.com/users/zackchase/received_events","type":"User","site_admin":false},"labels":[{"id":404586594,"node_id":"MDU6TGFiZWw0MDQ1ODY1OTQ=","url":"https://api.github.com/repos/tensorflow/tensorflow/labels/stat:awaiting%20tensorflower","name":"stat:awaiting tensorflower","color":"b60205","default":false},{"id":473173272,"node_id":"MDU6TGFiZWw0NzMxNzMyNzI=","url":"https://api.github.com/repos/tensorflow/tensorflow/labels/type:feature","name":"type:feature","color":"c2e0c6","default":false}],"state":"open","locked":false,"assignee":{"login":"skye","id":88808,"node_id":"MDQ6VXNlcjg4ODA4","avatar_url":"https://avatars1.githubusercontent.com/u/88808?v=4","gravatar_id":"","url":"https://api.github.com/users/skye","html_url":"https://github.com/skye","followers_url":"https://api.github.com/users/skye/followers","following_url":"https://api.github.com/users/skye/following{/other_user}","gists_url":"https://api.github.com/users/skye/gists{/gist_id}","starred_url":"https://api.github.com/users/skye/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/skye/subscriptions","organizations_url":"https://api.github.com/users/skye/orgs","repos_url":"https://api.github.com/users/skye/repos","events_url":"https://api.github.com/users/skye/events{/privacy}","received_events_url":"https://api.github.com/users/skye/received_events","type":"User","site_admin":false},"assignees":[{"login":"skye","id":88808,"node_id":"MDQ6VXNlcjg4ODA4","avatar_url":"https://avatars1.githubusercontent.com/u/88808?v=4","gravatar_id":"","url":"https://api.github.com/users/skye","html_url":"https://github.com/skye","followers_url":"https://api.github.com/users/skye/followers","following_url":"https://api.github.com/users/skye/following{/other_user}","gists_url":"https://api.github.com/users/skye/gists{/gist_id}","starred_url":"https://api.github.com/users/skye/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/skye/subscriptions","organizations_url":"https://api.github.com/users/skye/orgs","repos_url":"https://api.github.com/users/skye/repos","events_url":"https://api.github.com/users/skye/events{/privacy}","received_events_url":"https://api.github.com/users/skye/received_events","type":"User","site_admin":false}],"milestone":null,"comments":67,"created_at":"2016-01-04T11:16:43Z","updated_at":"2018-06-27T18:46:32Z","closed_at":null,"author_association":"CONTRIBUTOR","body":"Currently if you call gradients(ys, xs), it will return the sum of dy/dx over all ys for each x in xs. I believe this doesn't accord with an a priori mathematical notion of the derivative of a vector. I'd like the way to take the derivative of ys wrt xs where both are vectors and have a Jacobian matrix returned. By extension, I'd like to take the derivative of a vector wrt a matrix and get back a 3-tensor. There doesn't seem to be a convenient tensorflow function to compute the Jacobian or higher order derivatives. Am I missing something or is this functionality that we could add? \n"},"comment":{"url":"https://api.github.com/repos/tensorflow/tensorflow/issues/comments/400789603","html_url":"https://github.com/tensorflow/tensorflow/issues/675#issuecomment-400789603","issue_url":"https://api.github.com/repos/tensorflow/tensorflow/issues/675","id":400789603,"node_id":"MDEyOklzc3VlQ29tbWVudDQwMDc4OTYwMw==","user":{"login":"tensorflowbutler","id":28546240,"node_id":"MDQ6VXNlcjI4NTQ2MjQw","avatar_url":"https://avatars2.githubusercontent.com/u/28546240?v=4","gravatar_id":"","url":"https://api.github.com/users/tensorflowbutler","html_url":"https://github.com/tensorflowbutler","followers_url":"https://api.github.com/users/tensorflowbutler/followers","following_url":"https://api.github.com/users/tensorflowbutler/following{/other_user}","gists_url":"https://api.github.com/users/tensorflowbutler/gists{/gist_id}","starred_url":"https://api.github.com/users/tensorflowbutler/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/tensorflowbutler/subscriptions","organizations_url":"https://api.github.com/users/tensorflowbutler/orgs","repos_url":"https://api.github.com/users/tensorflowbutler/repos","events_url":"https://api.github.com/users/tensorflowbutler/events{/privacy}","received_events_url":"https://api.github.com/users/tensorflowbutler/received_events","type":"User","site_admin":false},"created_at":"2018-06-27T18:46:32Z","updated_at":"2018-06-27T18:46:32Z","author_association":"MEMBER","body":"Nagging Assignee @skye: It has been 14 days with no activity and this issue has an assignee. Please update the label and/or status accordingly."}}
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