Source code for imagepypelines.core.block_subclasses

# @Email: jmaggio14@gmail.com
# @Website: https://www.imagepypelines.org/
# @License: https://github.com/jmaggio14/imagepypelines/blob/master/LICENSE
# @github: https://github.com/jmaggio14/imagepypelines
#
# Copyright (c) 2018 - 2020 Jeff Maggio, Jai Mehra, Ryan Hartzell
#
import sys
import inspect
from abc import abstractmethod
import copy
from types import FunctionType
from functools import wraps

from .Block import Block


################################################################################
[docs]class PipelineBlock(Block): """Block which runs a pipeline internally (used for nesting pipelines within pipelines) Attributes: pipeline(:obj:`Pipeline`): pipeline to process with fetch(:obj:`tuple` of :obj:`str`): variables to fetch from the pipeline in the order to retrieve them in Batch Size: "each" """ def __init__(self, pipeline, fetch): """instantiates the PipelineBlock Args: pipeline(:obj:`Pipeline`): pipeline to process with fetch(:obj:`tuple` of :obj:`str`): variables to fetch from the pipeline in the order to retrieve them in """ # check to make sure all the fetch vars are actually in the pipeline if not all((fet in pipeline.vars) for fet in fetch): msg = "Invalid Pipeline fetch, must be one of %s" % pipeline.vars.keys() raise BlockError(msg) # instantiate block args self.fetch = fetch self.pipeline = pipeline # NOTE: do something here to support arg checking for the pipeline!!! super().__init__(name=pipeline.name, batch_type="all") ############################################################################
[docs] def process(self, *args): """Runs the pipeline and fetches the desired variables""" # NOTE: we might want to make the pipeline's logger a child of this # block's logger in here? processed = self.pipeline.process(*args, fetch=self.fetch) # turn processed dict into a tuple of fetches return tuple(processed[fet] for fet in self.fetch)
############################################################################ @property def args(self): """:obj:`list` of :obj:`str`: arg names for the pipeline""" return self.pipeline.args
################################################################################
[docs]class FuncBlock(Block): """Block that will run any function you give it, either unfettered through the __call__ function, or with optional hardcoded parameters for use in a pipeline. Typically the FuncBlock is only used in the :obj:`blockify` decorator method. Attributes: func(function): the function to call internally preset_kwargs(dict): preset keyword arguments, typically used for arguments that are not data to process """ def __new__(cls, func=None, preset_kwargs={}, **block_kwargs): """Generates the new function block Args: func (function): the function you desire to turn into a block preset_kwargs (dict): preset keyword arguments, typically used for arguments that are not data to process **block_kwargs: keyword arguments for :obj:`Block` instantiation """ obj = super().__new__(cls) # copy the method to avoid and any possible edge-case weirdness func = copy.copy(func) obj.func = func return obj def __init__(self, func, preset_kwargs={}, **block_kwargs): """instantiates the function block Args: func (function): the function you desire to turn into a block preset_kwargs (dict): preset keyword arguments, typically used for arguments that are not data to process **block_kwargs: keyword arguments for :obj:`Block` instantiation """ self._arg_spec = inspect.getfullargspec(func) # we can't allow varargs at all because a block must have a known # number of inputs if (self._arg_spec.varargs or self._arg_spec.varkw): raise TypeError("function cannot accept a variable number of args") self.preset_kwargs = preset_kwargs if self._arg_spec.defaults is not None: tmp_kwargs = {k:v for k,v in zip(self._arg_spec.args[-len(self._arg_spec.defaults):], self._arg_spec.defaults)} tmp_kwargs.update(self.preset_kwargs) self.preset_kwargs = tmp_kwargs super().__init__(self.func.__name__, **block_kwargs)
[docs] def process(self, *args): return self.func(*args, **self.preset_kwargs)
[docs] def __call__(self, *args, **kwargs): """returns the exact output of the user defined function without any interference or interaction with the class """ return self.func(*args,**kwargs)
@property def args(self): """:obj:`list` of :obj:`str`: arguments in the order they are expected""" # save the argspec in an instance variable if it hasn't been computed pos_args = ([] if (self._arg_spec.args is None) else self._arg_spec.args).copy() for idx,preset in enumerate(self.preset_kwargs.keys()): pos_args.remove(preset) return pos_args
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[docs]class Input(Block): """An object to inject data into the graph Attributes: data(any type): loaded(bool): where """ def __init__(self, index=None): """instantiates the Input Args: index(int,None): index of the input into the Pipeline """ self.set_index(index) self.data = None super().__init__(name=self.name, batch_type="all") ############################################################################
[docs] def process(self): """returns the loaded data""" if self.data is None: msg = "data not loaded" self.logger.error(msg) raise RuntimeError(msg) return self.data
############################################################################
[docs] def load(self, data): """loads the given data for distribution into the pipeline""" self.data = data
############################################################################
[docs] def unload(self): """unloads the data""" self.data = None
############################################################################
[docs] def get_default_node_attrs(self): """retrieves default node attributes for the Input""" attrs = super().get_default_node_attrs() attrs['color'] = 'blue' attrs['shape'] = 'pentagon' return attrs
############################################################################
[docs] def set_index(self, index): """sets the input index""" self.index = index self.name = "Input" + str(self.index)
############################################################################ # properties ############################################################################ @property def loaded(self): """bool: whether or not data has been loaded""" return (self.data is not None)
################################################################################
[docs]class Leaf(Block): """a block to act as a leaf node in the Pipeline Graph. Used to complete final outgoing edges from processing blocks Attributes: var_name(str): the name of the variable this leaf represents """ def __init__(self,var_name): """instantiates the leaf Args: var_name(str): the name of the variable this leaf represents """ self.var_name = var_name super().__init__(self.var_name, batch_type="all") ############################################################################
[docs] def process(self,*data): """does nothing in a leaf""" pass
# return data ############################################################################ def _pipeline_process(self,*data, **kwargs): return data[0] ############################################################################
[docs] def get_default_node_attrs(self): """retrieves default node attributes for the Leaf""" attrs = super().get_default_node_attrs() attrs['color'] = 'green' attrs['shape'] = 'ellipsis' return attrs
############################################################################ # properties ############################################################################ @property def args(self): """:obj:`list` of :obj:`str`: returns a 1-element list for this leaf's input""" return [self.var_name]
# END