blockify

imagepypelines.blockify(kwargs={}, batch_type='each', types=None, shapes=None, containers=None, void=False)

decorator which converts a normal function into a un-trainable block which can be added to a pipeline. The function can still be used as normal after blockification (the __call__ method is setup such that unfettered access to the function is permitted)

Parameters

• **kwargs – hardcode keyword arguments for a function, these arguments will not have to be used to. defaults to {}

• types (dict,None) – Dictionary of input types. If arg doesn’t exist as a key, or if the value is None, then no checking is done. If not provided, then will default to args as keys, None as values.

• shapes (dict,None) – Dictionary of input shapes. If arg doesn’t exist as a key, or if the value is None, then no checking is done. If not provided, then will default to args as keys, None as values.

• containers (dict,None) – Dictionary of input containers. If arg doesn’t exist as a key, or if the value is None, then no checking is done. If not provided, then will default to args as keys, None as values. if batch_type is “each”, then the container is irrelevant and can be safely ignored!

• batch_type (str, int) – the type of the batch processing for your process function. Either “all” or “each”. all means that all argument data will be passed into to your function at once, each means that each argument datum will be passed in individually

• void (bool) – Boolean value. By default all blocks return a value or values as output. However, if printing to screen, plotting, or saving data to a file, a block may not have a meaningful output that should be stored in a pipeline’s output dictionary. In this case, void should be set to True, so that the output of the block is ignored. The associated var key in the pipeline output will contain a value of None.

Example

>>> import imagepypelines as ip
>>>
>>> @ip.blockify( kwargs=dict(value=10) )
>>> def add_value(datum, value):
...    return datum + value
>>>
>>> type(add_value)
<class 'FuncBlock'>