morpheus.stages.preprocess.train_ae_stage.TrainAEStage

Bases: morpheus.pipeline.multi_message_stage.MultiMessageStage

Train an Autoencoder model on incoming data.

This stage is used to train an Autoencoder model on incoming data a supply that model to downstream stages. The Autoencoder workflows use this stage as a pre-processing step to build the model for inference.

Parameters

c

Pipeline configuration instance.

pretrained_filename

Loads a single pre-trained model for all users.

train_data_glob

On startup, all files matching this glob pattern will be loaded and used to train a model for each unique user ID.

source_stage_class

If train_data_glob provided, use source stage to batch training data per user.

train_epochs

The number of epochs to train user models for. Passed in as the epoch parameter to AutoEncoder.fit causes data to be trained in train_epochs batches.

train_min_history

Minimum number of rows to train user model.

train_max_history

Maximum amount of rows that will be retained in history. As new data arrives, models will be retrained with a maximum number of rows specified by this value.

seed

Seed to use when training. When not None, ensure random number generators are seeded with seed to control reproducibility of user model training.

sort_glob

If true the list of files matching input_glob will be processed in sorted order.

models_output_filename

The location to write trained models to.

Attributes

has_multi_input_ports

Indicates if this stage has multiple input ports.

has_multi_output_ports

Indicates if this stage has multiple output ports.

input_ports

Input ports to this stage.

is_built

Indicates if this stage has been built.

is_pre_built

Indicates if this stage has been built.

name

The name of the stage.

output_ports

Output ports from this stage.

unique_name

Unique name of stage.

Methods

_build(builder, input_nodes)[source]

This function is responsible for constructing this stage’s internal mrc.SegmentObject object. The input of this function contains the returned value from the upstream stage.

The input values are the mrc.Builder for this stage and a list of parent nodes.

Parameters

builder : mrc.Builder

mrc.Builder object for the pipeline. This should be used to construct/attach the internal mrc.SegmentObject.

input_nodes : list[mrc.SegmentObject]

List containing the input mrc.SegmentObject objects.

Returns

list[mrc.SegmentObject]

List of tuples containing the output mrc.SegmentObject object from this stage.

accepted_types()[source]

Returns accepted input types for this stage.

build(builder, do_propagate=True)[source]

Build this stage.

Parameters

builder : mrc.Builder

MRC segment for this stage.

do_propagate

Whether to propagate to build output stages, by default True.

can_build(check_ports=False)[source]

Determines if all inputs have been built allowing this node to be built.

Parameters

check_ports

Check if we can build based on the input ports, by default False.

Returns

bool

True if we can build, False otherwise.

can_pre_build(check_ports=False)[source]

Determines if all inputs have been built allowing this node to be built.

Parameters

check_ports

Check if we can build based on the input ports, by default False.

Returns

bool

True if we can build, False otherwise.

compute_schema(schema)[source]

Compute the schema for this stage based on the incoming schema from upstream stages.

Incoming schema and type information from upstream stages is available via the schema.input_schemas and schema.input_types properties.

Derived classes need to override this method, can set the output type(s) on schema by calling set_type for all output ports. For example a simple pass-thru stage might perform the following:

If the port types in upstream_schema are incompatible the stage should raise a RuntimeError.

get_all_input_stages()[source]

Get all input stages to this stage.

Returns

list[morpheus.pipeline.pipeline.StageBase]

All input stages.

get_all_inputs()[source]

Get all input senders to this stage.

Returns

list[morpheus.pipeline.pipeline.Sender]

All input senders.

get_all_output_stages()[source]

Get all output stages from this stage.

Returns

list[morpheus.pipeline.pipeline.StageBase]

All output stages.

get_all_outputs()[source]

Get all output receivers from this stage.

Returns

list[morpheus.pipeline.pipeline.Receiver]

All output receivers.

get_needed_columns()[source]

Stages which need to have columns inserted into the dataframe, should populate the self._needed_columns dictionary with mapping of column names to morpheus.common.TypeId. This will ensure that the columns are allocated and populated with null values.

property has_multi_input_ports: bool

Indicates if this stage has multiple input ports.

Returns

bool

True if stage has multiple input ports, False otherwise.

property has_multi_output_ports: bool

Indicates if this stage has multiple output ports.

Returns

bool

True if stage has multiple output ports, False otherwise.

property input_ports: list[morpheus.pipeline.receiver.Receiver]

Input ports to this stage.

Returns

list[morpheus.pipeline.pipeline.Receiver]

Input ports to this stage.

property is_built: bool

Indicates if this stage has been built.

Returns

bool

True if stage is built, False otherwise.

property is_pre_built: bool

Indicates if this stage has been built.

Returns

bool

True if stage is built, False otherwise.

async join()[source]

Awaitable method that stages can implement this to perform cleanup steps when pipeline is stopped. Typically this is called after stop during a graceful shutdown, but may not be called if the pipeline is terminated.

property name: str

The name of the stage. Used in logging. Each derived class should override this property with a unique name.

Returns

str

Name of a stage.

property output_ports: list[morpheus.pipeline.sender.Sender]

Output ports from this stage.

Returns

list[morpheus.pipeline.pipeline.Sender]

Output ports from this stage.

async start_async()[source]

This function is called along with on_start during stage initialization. Allows stages to utilize the asyncio loop if needed.

stop()[source]

Stages can implement this to perform cleanup steps when pipeline is stopped.

supports_cpp_node()[source]

Specifies whether this Stage is capable of creating C++ nodes. During the build phase, this value will be combined with CppConfig.get_should_use_cpp() to determine whether or not a C++ node is created. This is an instance method to allow runtime decisions and derived classes to override base implementations.

property unique_name: str

Unique name of stage. Generated by appending stage id to stage name.

Returns

str

Unique name of stage.