tfm.vision.configs.semantic_segmentation.SemanticSegmentationTask

The model config.

Inherits From: TaskConfig, Config, ParamsDict

BUILDER

default_params Dataclass field
restrictions Dataclass field
init_checkpoint Dataclass field
model Dataclass field
train_data Dataclass field
validation_data Dataclass field
name Dataclass field
differential_privacy_config Dataclass field
losses Dataclass field
evaluation Dataclass field
train_input_partition_dims Dataclass field
eval_input_partition_dims Dataclass field
init_checkpoint_modules Dataclass field

Methods

as_dict

View source

Returns a dict representation of params_dict.ParamsDict.

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

from_args

View source

Builds a config from the given list of arguments.

from_json

View source

Wrapper for from_yaml.

from_yaml

View source

get

View source

Accesses through built-in dictionary get method.

lock

View source

Makes the ParamsDict immutable.

override

View source

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

View source

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

validate

View source

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 specfiies 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

Implements the membership test operator.

__eq__

IMMUTABLE_TYPES (<class 'str'>, <class 'int'>, <class 'float'>, <class 'bool'>, <class 'NoneType'>)
RESERVED_ATTR ['_locked', '_restrictions']
SEQUENCE_TYPES (<class 'list'>, <class 'tuple'>)
default_params None
differential_privacy_config None
evaluation Instance of tfm.vision.configs.semantic_segmentation.Evaluation
init_checkpoint None
init_checkpoint_modules 'all'
losses Instance of tfm.vision.configs.semantic_segmentation.Losses
model Instance of tfm.vision.configs.semantic_segmentation.SemanticSegmentationModel
name None
restrictions None
train_data Instance of tfm.vision.configs.semantic_segmentation.DataConfig
validation_data Instance of tfm.vision.configs.semantic_segmentation.DataConfig