)]}'
{
  "commit": "cc46dc45e1b4b2a9ffab4ad5442f8b864148e45a",
  "tree": "435854815eae711821c749732564793ac36040ce",
  "parents": [
    "276cb8f501e9862446fd69ae7005286c55206ba0"
  ],
  "author": {
    "name": "Mike Iovine",
    "email": "mikeiovine@fb.com",
    "time": "Fri Dec 03 04:43:46 2021 -0800"
  },
  "committer": {
    "name": "Facebook GitHub Bot",
    "email": "facebook-github-bot@users.noreply.github.com",
    "time": "Fri Dec 03 04:45:27 2021 -0800"
  },
  "message": "[SR] Factor logic that determines managed tensors out of MemoryPlanner (#68295)\n\nSummary:\nPull Request resolved: https://github.com/pytorch/pytorch/pull/68295\n\nThere\u0027s no reason we can\u0027t figure out what tensors we need to manage at model load time. It\u0027s also useful to have the set of ranges available at load time for integrating the ranges algorithm introduced in the previous diff.\n\nTest Plan: `buck test caffe2/benchmarks/static_runtime/...`\n\nReviewed By: hlu1\n\nDifferential Revision: D32400593\n\nfbshipit-source-id: 0466b2641166ddc9c14f72774f4ba151407be400\n",
  "tree_diff": [
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