module nb_helper#

Inheritance diagram of mlprodict.nb_helper

Short summary#

module mlprodict.nb_helper

Helpers for notebooks.

source on GitHub

Classes#

class

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OnnxNotebook

Defines magic commands to help with notebooks

Functions#

function

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onnxview

Displays an ONNX graph into a notebook.

register_onnx_magics

Register magics function, can be called from a notebook.

Properties#

property

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Context

return the context or None

cross_validation_lock

A contextmanager for running a block with our cross validation lock set to True. At the end of the block, …

Methods#

method

truncated documentation

onnxview

Defines %onnxview which displays an ONNX graph.

Documentation#

Helpers for notebooks.

source on GitHub

class mlprodict.nb_helper.OnnxNotebook(**kwargs: Any)#

Bases: MagicClassWithHelpers

Defines magic commands to help with notebooks

New in version 1.1.

source on GitHub

Create a configurable given a config config.

Parameters#

configConfig

If this is empty, default values are used. If config is a Config instance, it will be used to configure the instance.

parentConfigurable instance, optional

The parent Configurable instance of this object.

Notes#

Subclasses of Configurable must call the __init__() method of Configurable before doing anything else and using super():

class MyConfigurable(Configurable):
    def __init__(self, config=None):
        super(MyConfigurable, self).__init__(config=config)
        # Then any other code you need to finish initialization.

This ensures that instances will be configured properly.

_cross_validation_lock: bool#
_trait_default_generators = {}#
_trait_notifiers: Dict[str, Any]#
_trait_validators: Dict[str, Any]#
_trait_values: Dict[str, Any]#
onnxview(line)#

Defines %onnxview which displays an ONNX graph.

onnxview

The magic command %onnxview model_onnx is equivalent to function onnxview:

onnx_view(model_onnx)

It displays a visual representation of an ONNX graph.

source on GitHub

mlprodict.nb_helper.onnxview(graph, recursive=False, local=False, add_rt_shapes=False, runtime='python', size=None, html_size=None)#

Displays an ONNX graph into a notebook.

Parameters:
  • graph – filename, bytes, or onnx graph.

  • recursive – display subgraph

  • local – use local path to javascript dependencies, recommanded option if used on MyBinder)

  • add_rt_shapes – add information about the shapes the runtime was able to find out, the runtime has to be ‘python’

  • runtime – the view fails if a runtime does not implement a specific node unless runtime is ‘empty’

  • size – graph size

  • html_size – html size

Changed in version 0.6: Parameter runtime was added.

source on GitHub

mlprodict.nb_helper.register_onnx_magics(ip=None)#

Register magics function, can be called from a notebook.

Parameters:

ip – from get_ipython()

source on GitHub