pytorch

1
## @package onnx
2
# Module caffe2.python.onnx.workspace
3

4

5

6

7

8

9
import uuid
10

11
from caffe2.python import workspace
12

13
# Separating out the context manager part so that users won't
14
# (mis-)use Workspace instances as context managers
15
class _WorkspaceCtx:
16
    def __init__(self, workspace_id):
17
        self.workspace_id = workspace_id
18
        # A stack, so that the context manager is reentrant.
19
        self.workspace_stack = []
20

21
    def __enter__(self):
22
        self.workspace_stack.append(workspace.CurrentWorkspace())
23
        workspace.SwitchWorkspace(self.workspace_id, create_if_missing=True)
24

25
    def __exit__(self, exc_type, exc_value, traceback):
26
        w = self.workspace_stack.pop()
27
        # Strictly speaking, create_if_missing here is unnecessary, since a user
28
        # is not supposed to be allowed to destruct a workspace while we're in
29
        # it.  However, empirically, it has been observed that during abnormal
30
        # shutdown, Caffe2 deletes its default workspace fairly early in the
31
        # final calls to destructors.  In this case, we may attempt to exit
32
        # to a default workspace which no longer exists.  create_if_missing=True
33
        # will (harmlessly) recreate the workspace before we finally quit.)
34
        workspace.SwitchWorkspace(w, create_if_missing=True)
35

36

37
class Workspace:
38
    """
39
    An object representing a Caffe2 workspace.  It is a context manager,
40
    so you can say 'with workspace:' to use the represented workspace
41
    as your global workspace.  It also supports every method supported
42
    by caffe2.python.workspace, but instead of running these operations
43
    in the global workspace, it runs them in the workspace represented
44
    by this object.  When this object goes dead, the workspace (and all
45
    nets and blobs within it) are freed.
46

47
    Why do we need this class?  Caffe2's workspace model is very "global state"
48
    oriented, in that there is always some ambient global workspace you are
49
    working in which holds on to all of your networks and blobs.  This class
50
    makes it possible to work with workspaces more locally, and without
51
    forgetting to deallocate everything in the end.
52
    """
53
    def __init__(self):
54
        # Caffe2 (apparently) doesn't provide any native method of generating
55
        # a fresh, unused workspace, so we have to fake it by generating
56
        # a unique ID and hoping it's not used already / will not be used
57
        # directly in the future.
58
        self._ctx = _WorkspaceCtx(str(uuid.uuid4()))
59

60
    def __getattr__(self, attr):
61
        def f(*args, **kwargs):
62
            with self._ctx:
63
                return getattr(workspace, attr)(*args, **kwargs)
64
        return f
65

66
    def __del__(self):
67
        # NB: This is a 'self' call because we need to switch into the workspace
68
        # we want to reset before we actually reset it.  A direct call to
69
        # workspace.ResetWorkspace() will reset the ambient workspace, which
70
        # is not want we want.
71
        self.ResetWorkspace()
72