{"action":"created","comment":{"url":"https://api.github.com/repos/pytorch/pytorch/pulls/comments/206998833","pull_request_review_id":142522090,"id":206998833,"node_id":"MDI0OlB1bGxSZXF1ZXN0UmV2aWV3Q29tbWVudDIwNjk5ODgzMw==","diff_hunk":"@@ -64,22 +48,20 @@ def broadcast_all(*values):\n         ValueError: if any of the values is not a `numbers.Number` or\n             `torch.*Tensor` instance\n     \"\"\"\n-    values = list(values)\n-    scalar_idxs = [i for i in range(len(values)) if isinstance(values[i], Number)]\n-    tensor_idxs = [i for i in range(len(values)) if values[i].__class__.__name__ == 'Tensor']\n-    if len(scalar_idxs) + len(tensor_idxs) != len(values):\n+    if not all(map(lambda v: torch.is_tensor(v) or isinstance(v, Number), values)):\n         raise ValueError('Input arguments must all be instances of numbers.Number or torch.tensor.')\n-    if tensor_idxs:\n-        broadcast_shape = _broadcast_shape([values[i].size() for i in tensor_idxs])\n-        for idx in tensor_idxs:\n-            values[idx] = values[idx].expand(broadcast_shape)\n-        template = values[tensor_idxs[0]]\n-        for idx in scalar_idxs:\n-            values[idx] = template.new(template.size()).fill_(values[idx])\n-    else:\n-        for idx in scalar_idxs:\n-            values[idx] = torch.tensor(float(values[idx]))\n-    return values\n+    if not all(map(torch.is_tensor, values)):\n+        # promote numbers to tensors of dtype torch.get_default_dtype()\n+        def default_promotion(v):","path":"torch/distributions/utils.py","position":56,"original_position":56,"commit_id":"f28068f6bd427d20fff40e77bb370e73a5f7f1db","original_commit_id":"f28068f6bd427d20fff40e77bb370e73a5f7f1db","user":{"login":"fritzo","id":648532,"node_id":"MDQ6VXNlcjY0ODUzMg==","avatar_url":"https://avatars0.githubusercontent.com/u/648532?v=4","gravatar_id":"","url":"https://api.github.com/users/fritzo","html_url":"https://github.com/fritzo","followers_url":"https://api.github.com/users/fritzo/followers","following_url":"https://api.github.com/users/fritzo/following{/other_user}","gists_url":"https://api.github.com/users/fritzo/gists{/gist_id}","starred_url":"https://api.github.com/users/fritzo/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/fritzo/subscriptions","organizations_url":"https://api.github.com/users/fritzo/orgs","repos_url":"https://api.github.com/users/fritzo/repos","events_url":"https://api.github.com/users/fritzo/events{/privacy}","received_events_url":"https://api.github.com/users/fritzo/received_events","type":"User","site_admin":false},"body":"nit: We should define this at file level to avoid the overhead of creating a new function on each invocation.\r\n```py\r\ndef _default_promotion(v):\r\n    return torch.tensor(v, dtype=torch.get_default_dtype())\r\n```","created_at":"2018-08-01T19:09:44Z","updated_at":"2018-08-01T19:10:04Z","html_url":"https://github.com/pytorch/pytorch/pull/10075#discussion_r206998833","pull_request_url":"https://api.github.com/repos/pytorch/pytorch/pulls/10075","author_association":"CONTRIBUTOR","_links":{"self":{"href":"https://api.github.com/repos/pytorch/pytorch/pulls/comments/206998833"},"html":{"href":"https://github.com/pytorch/pytorch/pull/10075#discussion_r206998833"},"pull_request":{"href":"https://api.github.com/repos/pytorch/pytorch/pulls/10075"}}},"pull_request":{"url":"https://api.github.com/repos/pytorch/pytorch/pulls/10075","id":205155426,"node_id":"MDExOlB1bGxSZXF1ZXN0MjA1MTU1NDI2","html_url":"https://github.com/pytorch/pytorch/pull/10075","diff_url":"https://github.com/pytorch/pytorch/pull/10075.diff","patch_url":"https://github.com/pytorch/pytorch/pull/10075.patch","issue_url":"https://api.github.com/repos/pytorch/pytorch/issues/10075","number":10075,"state":"open","locked":false,"title":"Implement torch.broadcast_tensors","user":{"login":"zou3519","id":5652049,"node_id":"MDQ6VXNlcjU2NTIwNDk=","avatar_url":"https://avatars3.githubusercontent.com/u/5652049?v=4","gravatar_id":"","url":"https://api.github.com/users/zou3519","html_url":"https://github.com/zou3519","followers_url":"https://api.github.com/users/zou3519/followers","following_url":"https://api.github.com/users/zou3519/following{/other_user}","gists_url":"https://api.github.com/users/zou3519/gists{/gist_id}","starred_url":"https://api.github.com/users/zou3519/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/zou3519/subscriptions","organizations_url":"https://api.github.com/users/zou3519/orgs","repos_url":"https://api.github.com/users/zou3519/repos","events_url":"https://api.github.com/users/zou3519/events{/privacy}","received_events_url":"https://api.github.com/users/zou3519/received_events","type":"User","site_admin":false},"body":"This exposes expand_outplace to python. Fixes #8076. Fixes #10041.\r\n\r\nI didn't name it torch.broadcast because numpy.broadcast does something\r\nslightly different (it returns an object with the correct shape\r\ninformation).\r\n\r\nTest Plan: new test_torch, test_autograd tests.\r\n\r\ncc @soumith @fritzo 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