Entry points are a way to interface with ML.NET components, by specifying an execution graph of connected inputs and outputs of those components. Both the manifest describing available components and their inputs/outputs, and an "experiment" graph description, are expressed in JSON. The recommended way of interacting with ML.NET through other, non-.NET programming languages, is by composing, and exchanging pipelines or experiment graphs.
Through the documentation, we also refer to entry points as 'entry points nodes', and that is because they are the nodes of the graph representing the experiment. The graph 'variables', the various values of the experiment graph JSON properties, serve to describe the relationship between the entry point nodes. The 'variables' are therefore the edges of the DAG (Directed Acyclic Graph).
All of ML.NET entry points are described by their manifest. The manifest is another JSON object that documents and describes the structure of an entry points. Manifests are referenced to understand what an entry point does, and how it should be constructed, in a graph.
This document briefly describes the structure of the entry points, the structure of an entry point manifest, and mentions the ML.NET classes that help construct an entry point graph.
The components manifest is build by scanning the ML.NET assemblies through reflection and searching for types having the: SignatureEntryPointModule
signature in their LoadableClass
assembly attribute definition.
An example of an entry point manifest object, specifically for the ColumnTypeConverter
transform, is:
{
"Name": "Transforms.ColumnTypeConverter",
"Desc": "Converts a column to a different type, using standard conversions.",
"FriendlyName": "Convert Transform",
"ShortName": "Convert",
"Inputs": [
{ "Name": "Column",
"Type": {
"Kind": "Array",
"ItemType": {
"Kind": "Struct",
"Fields": [
{
"Name": "ResultType",
"Type": {
"Kind": "Enum",
"Values": [ "I1","I2","U2","I4","U4","I8","U8","R4","Num","R8","TX","Text","TXT","BL","Bool","TimeSpan","TS","DT","DateTime","DZ","DateTimeZone","UG","U16" ]
},
"Desc": "The result type",
"Aliases": [ "type" ],
"Required": false,
"SortOrder": 150,
"IsNullable": true,
"Default": null
},
{ "Name": "Range",
"Type": "String",
"Desc": "For a key column, this defines the range of values",
"Aliases": [ "key" ],
"Required": false,
"SortOrder": 150,
"IsNullable": false,
"Default": null
},
{ "Name": "Name",
"Type": "String",
"Desc": "Name of the new column",
"Aliases": [ "name" ],
"Required": false,
"SortOrder": 150,
"IsNullable": false,
"Default": null
},
{ "Name": "Source",
"Type": "String",
"Desc": "Name of the source column",
"Aliases": [ "src" ],
"Required": false,
"SortOrder": 150,
"IsNullable": false,
"Default": null
}
]
}
},
"Desc": "New column definition(s) (optional form: name:type:src)",
"Aliases": [ "col" ],
"Required": true,
"SortOrder": 1,
"IsNullable": false
},
{ "Name": "Data",
"Type": "DataView",
"Desc": "Input dataset",
"Required": true,
"SortOrder": 2,
"IsNullable": false
},
{ "Name": "ResultType",
"Type": {
"Kind": "Enum",
"Values": [ "I1","I2","U2","I4","U4","I8","U8","R4","Num","R8","TX","Text","TXT","BL","Bool","TimeSpan","TS","DT","DateTime","DZ","DateTimeZone","UG","U16" ]
},
"Desc": "The result type",
"Aliases": [ "type" ],
"Required": false,
"SortOrder": 2,
"IsNullable": true,
"Default": null
},
{ "Name": "Range",
"Type": "String",
"Desc": "For a key column, this defines the range of values",
"Aliases": [ "key" ],
"Required": false,
"SortOrder": 150,
"IsNullable": false,
"Default": null
}
],
"Outputs": [
{
"Name": "OutputData",
"Type": "DataView",
"Desc": "Transformed dataset"
},
{
"Name": "Model",
"Type": "TransformModel",
"Desc": "Transform model"
}
],
"InputKind": ["ITransformInput" ],
"OutputKind": [ "ITransformOutput" ]
}
The respective entry point, constructed based on this manifest would be:
{
"Name": "Transforms.ColumnTypeConverter",
"Inputs": {
"Column": [{
"Name": "Features",
"Source": "Features"
}],
"Data": "$data0",
"ResultType": "R4"
},
"Outputs": {
"OutputData": "$Convert_Output",
"Model": "$Convert_TransformModel"
}
}
This class encapsulates the list of nodes (EntryPointNode
) and edges
(EntryPointVariable
inside a RunContext
) of the graph.
This class represents a node in the graph, and wraps an entry point call. It
has methods for creating and running entry points. It also has a reference to
the RunContext
to allow it to get and set values from EntryPointVariable
s.
To express the inputs that are set through variables, a set of dictionaries
are used. The InputBindingMap
maps an input parameter name to a list of
ParameterBinding
s. The InputMap
maps a ParameterBinding
to a
VariableBinding
. For example, if the JSON looks like this:
'foo': '$bar'
the InputBindingMap
will have one entry that maps the string "foo" to a list
that has only one element, a SimpleParameterBinding
with the name "foo" and
the InputMap
will map the SimpleParameterBinding
to a
SimpleVariableBinding
with the name "bar". For a more complicated example,
let's say we have this JSON:
'foo': [ '$bar[3]', '$baz']
the InputBindingMap
will have one entry that maps the string "foo" to a list
that has two elements, an ArrayIndexParameterBinding
with the name "foo" and
index 0 and another one with index 1. The InputMap
will map the first
ArrayIndexParameterBinding
to an ArrayIndexVariableBinding
with name "bar"
and index 3 and the second ArrayIndexParameterBinding
to a
SimpleVariableBinding
with the name "baz".
For outputs, a node assumes that an output is mapped to a variable, so the
OutputMap
is a simple dictionary from string to string.
This class represents an edge in the entry point graph. It has a name, a type and a value. Variables can be simple, arrays and/or dictionaries. Currently, only data views, file handles, predictor models and transform models are allowed as element types for a variable.
This class is just a container for all the variables in a graph.
The abstract base class represents a "pointer to a (part of a) variable". It
is used in conjunction with ParameterBinding
s to specify inputs to an entry
point node. The SimpleVariableBinding
is a pointer to an entire variable,
the ArrayIndexVariableBinding
is a pointer to a specific index in an array
variable, and the DictionaryKeyVariableBinding
is a pointer to a specific
key in a dictionary variable.
The abstract base class represents a "pointer to a (part of a) parameter". It
parallels the VariableBinding
hierarchy and it is used to specify the inputs
to an entry point node. The SimpleParameterBinding
is a pointer to a
non-array, non-dictionary parameter, the ArrayIndexParameterBinding
is a
pointer to a specific index of an array parameter and the
DictionaryKeyParameterBinding
is a pointer to a specific key of a dictionary
parameter.
- Add a
LoadableClass
assembly attribute with theSignatureEntryPointModule
signature as shown here. - Create a public static method, that:
- Takes an object representing the arguments of the component you want to expose as shown here
- Initializes and runs the component, returning one of the nested classes of
Microsoft.ML.EntryPoints.CommonOutputs
- Is annotated with the
TlcModule.EntryPoint
attribute
For an example of a transformer as an entrypoint, see OneHotVectorizer. For a trainer-estimator, see LogisticRegression.