__all__ = [
"ContextOperation",
"NEROperation",
"SegmentationOperation",
"CustomTextOpType",
"create_text_operation",
]
import abc
from enum import IntEnum
from typing import Any, Callable, List, Optional
from medkit.core.operation import Operation
from medkit.core.prov_tracer import ProvTracer
from medkit.core.text.annotation import Entity, Segment
[docs]class ContextOperation(Operation):
"""
Abstract operation for context detection.
It uses a list of segments as input for running the operation and creates attributes
that are directly appended to these segments.
"""
@abc.abstractmethod
def run(self, segments: List[Segment]) -> None:
raise NotImplementedError
[docs]class NEROperation(Operation):
"""
Abstract operation for detecting entities.
It uses a list of segments as input and produces a list of detected entities.
"""
@abc.abstractmethod
def run(self, segments: List[Segment]) -> List[Entity]:
raise NotImplementedError
[docs]class SegmentationOperation(Operation):
"""
Abstract operation for segmenting text.
It uses a list of segments as input and produces a list of new segments.
"""
@abc.abstractmethod
def run(self, segments: List[Segment]) -> List[Segment]:
raise NotImplementedError
[docs]class CustomTextOpType(IntEnum):
"""
Enum class listing all supported function types for creating custom text operations
Attributes
----------
CREATE_ONE_TO_N
Takes 1 data item, Return N new data items
EXTRACT_ONE_TO_N
Takes 1 data item, Return N existing data items
FILTER
Takes 1 data item, Returns True/False
"""
CREATE_ONE_TO_N = 1
EXTRACT_ONE_TO_N = 2
FILTER = 3
class _CustomTextOperation(Operation):
"""
Internal class representing a custom text operation.
This class may be only instantiated by `create_text_operation`.
It uses an user-defined function in the `run` method.
It handles all provenance settings based on the function type.
"""
def __init__(self, name: str, uid: Optional[str] = None):
"""
Parameters
----------
name
Name of the operation used for provenance info
uid
Identifier of the operation
"""
# Pass all arguments to super (remove self)
init_args = locals()
init_args.pop("self")
super().__init__(**init_args)
self._function = None
self._function_type = None
def set_prov_tracer(self, prov_tracer: ProvTracer):
self._prov_tracer = prov_tracer
def set_function(self, function: Callable, function_type: CustomTextOpType):
"""
Assign a user-defined fonction to the operation
Parameters
----------
function
User-defined function to be used in `run` method
function_type
Type of function.
Supported values are defined in :class:`~medkit.core.text.CustomTextOpType`
Returns
-------
"""
self._function = function
self._function_type = function_type
self.description.config["function_type"] = function_type.name
# TODO: check signature according to type
def run(self, all_input_data: List[Any]) -> List[Any]:
"""
Run the custom operation on a list of input data and outputs a list of data
This method uses the user-defined function depending on its type on a
batch of data.
Parameters
----------
all_input_data
List of input data
Returns
-------
List[Any]
Flat list of output data
"""
assert self._function is not None
assert self._function_type in set(CustomTextOpType)
if self._function_type in [
CustomTextOpType.CREATE_ONE_TO_N,
CustomTextOpType.EXTRACT_ONE_TO_N,
]:
return self._run_one_to_n_function(all_input_data, self._function_type)
elif self._function_type == CustomTextOpType.FILTER:
return self._run_filter_function(all_input_data)
def _run_one_to_n_function(
self, all_input_data: List[Any], function_type: CustomTextOpType
) -> List[Any]:
all_output_data = []
for input_data in all_input_data:
output_data = self._function(input_data)
if type(output_data) == list:
all_output_data.extend(output_data)
else:
all_output_data.append(output_data)
if (
function_type == CustomTextOpType.CREATE_ONE_TO_N
and self._prov_tracer is not None
):
if type(output_data) == list:
for data in output_data:
self._prov_tracer.add_prov(
data_item=data,
op_desc=self.description,
source_data_items=[input_data],
)
else:
self._prov_tracer.add_prov(
data_item=output_data,
op_desc=self.description,
source_data_items=[input_data],
)
return all_output_data
def _run_filter_function(self, all_input_data: List[Any]) -> List[Any]:
all_output_data = []
for input_data in all_input_data:
checked = self._function(input_data)
if checked:
all_output_data.append(input_data)
return all_output_data
[docs]def create_text_operation(
function: Callable,
function_type: CustomTextOpType,
name: Optional[str] = None,
) -> _CustomTextOperation:
"""
Function for instanciating a custom test operation from a user-defined function
Parameters
----------
function
User-defined function
function_type
Type of function.
Supported values are defined in :class:`~medkit.core.text.CustomTextOpType`
name
Name of the operation used for provenance info (default: function name)
Returns
-------
operation
An instance of a custom text operation
"""
if name is None:
name = function.__name__
operation = _CustomTextOperation(name=name)
operation.set_function(function=function, function_type=function_type)
return operation
