morpheus.messages.multi_ae_message.MultiAEMessage
- class MultiAEMessage(*, meta, mess_offset=0, mess_count=- 1, model, train_scores_mean=0.0, train_scores_std=1.0)[source]
Bases:
morpheus.messages.multi_message.MultiMessage
Subclass of
MultiMessage
specific to the AutoEncoder pipeline, which contains the model.- Attributes
Methods
copy_meta_ranges
(ranges[, mask])Perform a copy of the underlying dataframe for the given
ranges
of rows.copy_ranges
(ranges)Perform a copy of the current message instance for the given
ranges
of rows.from_message
(message, *[, meta, ...])Creates a new instance of a derived class from
MultiMessage
using an existing message as the template.get_meta
([columns])Return column values from
morpheus.pipeline.messages.MessageMeta.df
.get_meta_list
([col_name])Return a column values from morpheus.messages.MessageMeta.df as a list.
get_slice
(start, stop)Returns sliced batches based on offsets supplied.
set_meta
(columns, value)Set column values to
morpheus.pipelines.messages.MessageMeta.df
.- copy_meta_ranges(ranges, mask=None)[source]
Perform a copy of the underlying dataframe for the given
ranges
of rows.- Parameters
- rangestyping.List[typing.Tuple[int, int]]
- masktyping.Union[None, cupy.ndarray, numpy.ndarray]
Rows to include in the copy in the form of
[(`start_row
,stop_row
),…]` Thestop_row
isn’t included. For example to copy rows 1-2 & 5-7ranges=[(1, 3), (5, 8)]
Optionally specify rows as a cupy array (when using cudf Dataframes) or a numpy array (when using pandas Dataframes) of booleans. When not-None
ranges
will be ignored. This is useful as an optimization as this avoids needing to generate the mask on it’s own.- Returns
Dataframe
- copy_ranges(ranges)[source]
Perform a copy of the current message instance for the given
ranges
of rows.- Parameters
- rangestyping.List[typing.Tuple[int, int]]
Rows to include in the copy in the form of
[(`start_row
,stop_row
),…]` Thestop_row
isn’t included. For example to copy rows 1-2 & 5-7ranges=[(1, 3), (5, 8)]
- Returns
MultiMessage
- classmethod from_message(message, *, meta=None, mess_offset=- 1, mess_count=- 1, **kwargs)[source]
Creates a new instance of a derived class from
MultiMessage
using an existing message as the template. This is very useful when a new message needs to be created with a single change to an existingMessageMeta
.When creating the new message, all required arguments for the class specified by
cls
will be pulled frommessage
unless otherwise specified in theargs
orkwargs
. Special handling is performed depending on whether or not a newmeta
object is supplied. If one is supplied, the offset and count defaults will be 0 andmeta.count
respectively. Otherwise offset and count will be pulled from the inputmessage
.- Parameters
- clstyping.Type[Self]
- messageMultiMessage
- metaMessageMeta, optional
- mess_offsetint, optional
- mess_countint, optional
The class to create
An existing message to use as a template. Can be a base or derived from
cls
as long as all arguments can be pulled frommessage
or proveded inkwargs
A new
MessageMeta
to use, by default NoneA new
mess_offset
to use, by default -1A new
mess_count
to use, by default -1- Returns
- Self
A new instance of type
cls
- Raises
- ValueError
- AttributeError
If the incoming
message
is NoneIf some required arguments were not supplied by
kwargs
and could not be pulled frommessage
- get_meta(columns=None)[source]
Return column values from
morpheus.pipeline.messages.MessageMeta.df
.- Parameters
- columnstyping.Union[None, str, typing.List[str]]
Input column names. Returns all columns if
None
is specified. When a string is passed, aSeries
is returned. Otherwise aDataframe
is returned.- Returns
- Series or Dataframe
Column values from the dataframe.
- get_meta_list(col_name=None)[source]
Return a column values from morpheus.messages.MessageMeta.df as a list.
- Parameters
- col_namestr
Column name in the dataframe.
- Returns
- List[str]
Column values from the dataframe.
- get_slice(start, stop)[source]
Returns sliced batches based on offsets supplied. Automatically calculates the correct
mess_offset
andmess_count
.- Parameters
- startint
- stopint
Start offset address.
Stop offset address.
- Returns
MultiInferenceMessage
A new
MultiInferenceMessage
with sliced offset and count.
- property id: List[int]
Returns ID column values from
morpheus.pipeline.messages.MessageMeta.df
as list.- Returns
- List[int]
ID column values from the dataframe as list.
- property id_col
Returns ID column values from
morpheus.pipeline.messages.MessageMeta.df
.- Returns
- pandas.Series
ID column values from the dataframe.
- set_meta(columns, value)[source]
Set column values to
morpheus.pipelines.messages.MessageMeta.df
.- Parameters
- columnstyping.Union[None, str, typing.List[str]]
- valueAny
Input column names. Sets the value for the corresponding column names. If
None
is specified, all columns will be used. If the column does not exist, a new one will be created.Value to apply to the specified columns. If a single value is passed, it will be broadcast to all rows. If a
Series
orDataframe
is passed, rows will be matched by index.
- property timestamp: List[int]
Returns timestamp column values from morpheus.messages.MessageMeta.df as list.
- Returns
- List[int]
Timestamp column values from the dataframe as list.