File size: 3,069 Bytes
28c6826
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
""" Model / Layer Config singleton state
"""
from typing import Any, Optional

__all__ = [
    'is_exportable', 'is_scriptable', 'is_no_jit',
    'set_exportable', 'set_scriptable', 'set_no_jit', 'set_layer_config'
]

# Set to True if prefer to have layers with no jit optimization (includes activations)
_NO_JIT = False

# Set to True if prefer to have activation layers with no jit optimization
# NOTE not currently used as no difference between no_jit and no_activation jit as only layers obeying
# the jit flags so far are activations. This will change as more layers are updated and/or added.
_NO_ACTIVATION_JIT = False

# Set to True if exporting a model with Same padding via ONNX
_EXPORTABLE = False

# Set to True if wanting to use torch.jit.script on a model
_SCRIPTABLE = False


def is_no_jit():
    return _NO_JIT


class set_no_jit:
    def __init__(self, mode: bool) -> None:
        global _NO_JIT
        self.prev = _NO_JIT
        _NO_JIT = mode

    def __enter__(self) -> None:
        pass

    def __exit__(self, *args: Any) -> bool:
        global _NO_JIT
        _NO_JIT = self.prev
        return False


def is_exportable():
    return _EXPORTABLE


class set_exportable:
    def __init__(self, mode: bool) -> None:
        global _EXPORTABLE
        self.prev = _EXPORTABLE
        _EXPORTABLE = mode

    def __enter__(self) -> None:
        pass

    def __exit__(self, *args: Any) -> bool:
        global _EXPORTABLE
        _EXPORTABLE = self.prev
        return False


def is_scriptable():
    return _SCRIPTABLE


class set_scriptable:
    def __init__(self, mode: bool) -> None:
        global _SCRIPTABLE
        self.prev = _SCRIPTABLE
        _SCRIPTABLE = mode

    def __enter__(self) -> None:
        pass

    def __exit__(self, *args: Any) -> bool:
        global _SCRIPTABLE
        _SCRIPTABLE = self.prev
        return False


class set_layer_config:
    """ Layer config context manager that allows setting all layer config flags at once.
    If a flag arg is None, it will not change the current value.
    """
    def __init__(
            self,
            scriptable: Optional[bool] = None,
            exportable: Optional[bool] = None,
            no_jit: Optional[bool] = None,
            no_activation_jit: Optional[bool] = None):
        global _SCRIPTABLE
        global _EXPORTABLE
        global _NO_JIT
        global _NO_ACTIVATION_JIT
        self.prev = _SCRIPTABLE, _EXPORTABLE, _NO_JIT, _NO_ACTIVATION_JIT
        if scriptable is not None:
            _SCRIPTABLE = scriptable
        if exportable is not None:
            _EXPORTABLE = exportable
        if no_jit is not None:
            _NO_JIT = no_jit
        if no_activation_jit is not None:
            _NO_ACTIVATION_JIT = no_activation_jit

    def __enter__(self) -> None:
        pass

    def __exit__(self, *args: Any) -> bool:
        global _SCRIPTABLE
        global _EXPORTABLE
        global _NO_JIT
        global _NO_ACTIVATION_JIT
        _SCRIPTABLE, _EXPORTABLE, _NO_JIT, _NO_ACTIVATION_JIT = self.prev
        return False