tfm.vision.configs.maskrcnn.Parser

Inherits From: Config, ParamsDict

tfm.vision.configs.maskrcnn.Parser(
    default_params: dataclasses.InitVar[Optional[Mapping[str, Any]]] = None,
    restrictions: dataclasses.InitVar[Optional[List[str]]] = None,
    num_channels: int = 3,
    match_threshold: float = 0.5,
    unmatched_threshold: float = 0.5,
    aug_rand_hflip: bool = False,
    aug_rand_vflip: bool = False,
    aug_scale_min: float = 1.0,
    aug_scale_max: float = 1.0,
    aug_type: Optional[tfm.vision.configs.common.Augmentation] = None,
    skip_crowd_during_training: bool = True,
    max_num_instances: int = 100,
    rpn_match_threshold: float = 0.7,
    rpn_unmatched_threshold: float = 0.3,
    rpn_batch_size_per_im: int = 256,
    rpn_fg_fraction: float = 0.5,
    mask_crop_size: int = 112,
    pad: bool = True
)

BUILDER

default_params Dataclass field
restrictions Dataclass field
num_channels Dataclass field
match_threshold Dataclass field
unmatched_threshold Dataclass field
aug_rand_hflip Dataclass field
aug_rand_vflip Dataclass field
aug_scale_min Dataclass field
aug_scale_max Dataclass field
aug_type Dataclass field
skip_crowd_during_training Dataclass field
max_num_instances Dataclass field
rpn_match_threshold Dataclass field
rpn_unmatched_threshold Dataclass field
rpn_batch_size_per_im Dataclass field
rpn_fg_fraction Dataclass field
mask_crop_size Dataclass field
pad Dataclass field

Methods

as_dict

View source

as_dict()

Returns a dict representation of params_dict.ParamsDict.

For the nested params_dict.ParamsDict, a nested dict will be returned.

from_args

View source

@classmethod
from_args(
    *args, **kwargs
)

Builds a config from the given list of arguments.

from_json

View source

@classmethod
from_json(
    file_path: str
)

Wrapper for from_yaml.

from_yaml

View source

@classmethod
from_yaml(
    file_path: str
)

get

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get(
    key, value=None
)

Accesses through built-in dictionary get method.

lock

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lock()

Makes the ParamsDict immutable.

override

View source

override(
    override_params, is_strict=True
)

Override the ParamsDict with a set of given params.

Args
override_params a dict or a ParamsDict specifying the parameters to be overridden.
is_strict a boolean specifying whether override is strict or not. If True, keys in override_params must be present in the ParamsDict. If False, keys in override_params can be different from what is currently defined in the ParamsDict. In this case, the ParamsDict will be extended to include the new keys.

replace

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replace(
    **kwargs
)

Overrides/returns a unlocked copy with the current config unchanged.

validate

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validate()

Validate the parameters consistency based on the restrictions.

This method validates the internal consistency using the pre-defined list of restrictions. A restriction is defined as a string which specifies a binary operation. The supported binary operations are {'==', '!=', '<', '<=', '>', '>='}. Note that the meaning of these operators are consistent with the underlying Python immplementation. Users should make sure the define restrictions on their type make sense.

For example, for a ParamsDict like the following

a:
  a1: 1
  a2: 2
b:
  bb:
    bb1: 10
    bb2: 20
  ccc:
    a1: 1
    a3: 3

one can define two restrictions like this ['a.a1 == b.ccc.a1', 'a.a2 <= b.bb.bb2']

What it enforces are

  • a.a1 = 1 == b.ccc.a1 = 1
  • a.a2 = 2 <= b.bb.bb2 = 20

Raises
KeyError if any of the following happens (1) any of parameters in any of restrictions is not defined in ParamsDict, (2) any inconsistency violating the restriction is found.
ValueError if the restriction defined in the string is not supported.

__contains__

View source

__contains__(
    key
)

Implements the membership test operator.

__eq__

__eq__(
    other
)

IMMUTABLE_TYPES (<class 'str'>, <class 'int'>, <class 'float'>, <class 'bool'>, <class 'NoneType'>)
RESERVED_ATTR ['_locked', '_restrictions']
SEQUENCE_TYPES (<class 'list'>, <class 'tuple'>)
aug_rand_hflip False
aug_rand_vflip False
aug_scale_max 1.0
aug_scale_min 1.0
aug_type None
default_params None
mask_crop_size 112
match_threshold 0.5
max_num_instances 100
num_channels 3
pad True
restrictions None
rpn_batch_size_per_im 256
rpn_fg_fraction 0.5
rpn_match_threshold 0.7
rpn_unmatched_threshold 0.3
skip_crowd_during_training True
unmatched_threshold 0.5