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morpheus.stages.preprocess.train_ae_stage.TrainAEStage

class TrainAEStage(c, pretrained_filename=None, train_data_glob=None, source_stage_class=None, train_epochs=25, train_min_history=300, train_max_history=1000, seed=None, sort_glob=False, models_output_filename=None)[source]

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
cmorpheus.config.Config

Pipeline configuration instance.
pretrained_filenamepathlib.Path, default = None

Loads a single pre-trained model for all users.
train_data_globstr, default = None

On startup, all files matching this glob pattern will be loaded and used to train a model for each unique user ID.
source_stage_classstr, default = None

If train_data_glob provided, use source stage to batch training data per user.
train_epochsint, default = 25, min = 1

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_historyint, default = 300

Minimum number of rows to train user model.
train_max_historyint, default = 1000, min = 1

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.
seedint, default = None

Seed to use when training. When not None, ensure random number generators are seeded with seed to control reproducibility of user model training.
sort_globbool, default = False, is_flag = True

If true the list of files matching input_glob will be processed in sorted order.
models_output_filenamepathlib.Path, default = None, writable = True

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.
name

The name of the stage.
output_ports

Output ports from this stage.
unique_name

Unique name of stage.

Methods

accepted_types()

Returns accepted input types for this stage.

build(builder[, do_propagate])

Build this stage.

can_build([check_ports])

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

get_all_input_stages()

Get all input stages to this stage.

get_all_inputs()

Get all input senders to this stage.

get_all_output_stages()

Get all output stages from this stage.

get_all_outputs()

Get all output receivers from this stage.

get_needed_columns()

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.

join()

Awaitable method that stages can implement this to perform cleanup steps when pipeline is stopped.

on_start()

This function can be overridden to add usecase-specific implementation at the start of any stage in the pipeline.

start_async()

This function is called along with on_start during stage initialization.

stop()

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

supports_cpp_node()

Specifies whether this Stage is capable of creating C++ nodes.
_build(builder, in_ports_streams)[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 StreamPair tuple which contain the input mrc.SegmentObject object and the message data type.

Parameters
buildermrc.Builder

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

List of tuples containing the input mrc.SegmentObject object and the message data type.
Returns
typing.List[morpheus.pipeline.pipeline.StreamPair]

List of tuples containing the output mrc.SegmentObject object from this stage and the message data type.
accepted_types()[source]

Returns accepted input types for this stage.
build(builder, do_propagate=True)[source]

Build this stage.

Parameters
buildermrc.Builder

MRC segment for this stage.
do_propagatebool, optional

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_portsbool, optional

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

True if we can build, False otherwise.
get_all_input_stages()[source]

Get all input stages to this stage.

Returns
typing.List[morpheus.pipeline.pipeline.StreamWrapper]

All input stages.
get_all_inputs()[source]

Get all input senders to this stage.

Returns
typing.List[morpheus.pipeline.pipeline.Sender]

All input senders.
get_all_output_stages()[source]

Get all output stages from this stage.

Returns
typing.List[morpheus.pipeline.pipeline.StreamWrapper]

All output stages.
get_all_outputs()[source]

Get all output receivers from this stage.

Returns
typing.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
typing.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.
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.
on_start()[source]

This function can be overridden to add usecase-specific implementation at the start of any stage in the pipeline.
property output_ports: List[morpheus.pipeline.sender.Sender]

Output ports from this stage.

Returns
typing.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.
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