morpheus.stages.general.monitor_stage.MonitorStage#

class MonitorStage( c, description='Progress', smoothing=0.05, unit='messages', delayed_start=True, determine_count_fn=None, text_color=<IndicatorsTextColor.cyan: 6>, font_style=<IndicatorsFontStyle.bold: 0>, log_level=LogLevels.INFO, )[source]#

Bases: PassThruTypeMixin, GpuAndCpuMixin, SinglePortStage

Display throughput numbers at a specific point in the pipeline.

Monitor stage used to monitor stage performance metrics using Tqdm. Each Monitor Stage will represent one line in the console window showing throughput statistics. Can be set up to show an instantaneous throughput or average input.

Parameters:

cmorpheus.config.Config: Pipeline configuration instance.
descriptionstr, default = “Progress”: Name to show for this Monitor Stage in the console window.
smoothingfloat: Smoothing parameter to determine how much the throughput should be averaged. 0 = Instantaneous, 1 = Average.
unitstr: Units to show in the rate value.
delayed_startbool: When delayed_start is enabled, the progress bar will not be shown until the first message is received. Otherwise, the progress bar is shown on pipeline startup and will begin timing immediately. In large pipelines, this option may be desired to give a more accurate timing.
determine_count_fntyping.Callable[[typing.Any], int]: Custom function for determining the count in a message. Gets called for each message. Allows for correct counting of batched and sliced messages.
log_levelmorpheus.utils.logger.LogLevels, default = ‘INFO’: Enable this stage when the configured log level is at log_level or lower.

Attributes:

df_type_str: Returns the DataFrame module that should be used for the given execution mode.
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

`accepted_types`()	Accepted input types for this stage are returned.
`build`(builder[, do_propagate])	Build this stage.
`can_build`([check_ports])	Determines if all inputs have been built allowing this node to be built.
`can_pre_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_df_class`()	Returns the DataFrame class that should be used for the given execution mode.
`get_df_pkg`()	Returns the DataFrame package that should be used for the given execution mode.
`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`()	Clean up and close the progress bar.
`start_async`()	Starts the pipeline stage's progress bar.
`stop`()	Stages can implement this to perform cleanup steps when pipeline is stopped.
`supported_execution_modes`()	Returns a tuple of supported execution modes of this stage.
`supports_cpp_node`()	Specifies whether this Stage is capable of creating C++ nodes.

compute_schema

_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:

buildermrc.Builder: mrc.Builder object for the pipeline. This should be used to construct/attach the internal mrc.SegmentObject.
input_nodeslist[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]#

Accepted input types for this stage are returned.

Returns:

typing.Tuple: Accepted input types.

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.

can_pre_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.

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:

>>> for (port_idx, port_schema) in enumerate(schema.input_schemas):
...     schema.output_schemas[port_idx].set_type(port_schema.get_type())
>>>

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

property df_type_str: Literal['cudf', 'pandas']#: Returns the DataFrame module that should be used for the given execution mode.

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_df_class()[source]#

Returns the DataFrame class that should be used for the given execution mode.

get_df_pkg()[source]#

Returns the DataFrame package that should be used for the given execution mode.

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[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]#: Clean up and close the progress bar.

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[Sender]#

Output ports from this stage.

Returns:

list[morpheus.pipeline.pipeline.Sender]: Output ports from this stage.

async start_async()[source]#: Starts the pipeline stage’s progress bar.

stop()[source]#: Stages can implement this to perform cleanup steps when pipeline is stopped.

supported_execution_modes()[source]#

Returns a tuple of supported execution modes of this stage.

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.