morpheus.messages.multi_response_message.MultiResponseAEMessage

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class MultiResponseAEMessage(*args, **kwargs)[source]

Bases: morpheus.messages.multi_response_message.MultiResponseProbsMessage

A stronger typed version of MultiResponseProbsMessage that is used for inference workloads that return a probability array. Helps ensure the proper outputs are set and eases debugging.

Attributes

id: Returns ID column values from morpheus.pipeline.messages.MessageMeta.df as list.
id_col: Returns ID column values from morpheus.pipeline.messages.MessageMeta.df.
outputs: Get outputs stored in the TensorMemory container.
probs: Probabilities of prediction.
timestamp: Returns timestamp column values from morpheus.messages.MessageMeta.df as list.
user_id

Methods

`copy_meta_ranges`(ranges[, mask])	Perform a copy of the underlying dataframe for the given `ranges` of rows.
`copy_output_ranges`(ranges[, mask])	Perform a copy of the underlying output tensors for the given `ranges` of rows.
`copy_ranges`(ranges)	Perform a copy of the current message, dataframe and tensors for the given `ranges` of rows.
`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_output`(name)	Get output stored in the TensorMemory container.
`get_slice`(start, stop)	Perform a slice of the current message from `start`:`stop` (excluding `stop`)
`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]]: Rows to include in the copy in the form of [(`start_row, stop_row),…]` The stop_row isn’t included. For example to copy rows 1-2 & 5-7 ranges=[(1, 3), (5, 8)]
masktyping.Union[None, cupy.ndarray, numpy.ndarray]: 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_output_ranges(ranges, mask=None)[source]

Perform a copy of the underlying output tensors 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),…]` The stop_row isn’t included. For example to copy rows 1-2 & 5-7 ranges=[(1, 3), (5, 8)]
masktyping.Union[None, cupy.ndarray, numpy.ndarray]: 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

typing.Dict[str, cupy.ndarray]

copy_ranges(ranges)[source]

Perform a copy of the current message, dataframe and tensors 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),…]` The stop_row isn’t included. For example to copy rows 1-2 & 5-7 ranges=[(1, 3), (5, 8)]
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`MultiResponseAEMessage`

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, a Series is returned. Otherwise a Dataframe 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_output(name)[source]

Get output stored in the TensorMemory container.

Parameters

namestr: Output key name.

Returns

cupy.ndarray: Inference output.

get_slice(start, stop)[source]

Perform a slice of the current message from start:stop (excluding stop)

For example to slice from rows 1-3 use m.get_slice(1, 4). The returned MultiResponseMessage will contain references to the same underlying Dataframe and output tensors, and this calling this method is reletively low cost compared to MultiResponseAEMessage.copy_ranges

Parameters

startint: Starting row of the slice
stopint: Stop of the slice
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`MultiResponseAEMessage`

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.

property outputs

Get outputs stored in the TensorMemory container.

Returns

cupy.ndarray: Inference outputs.

property probs

Probabilities of prediction.

Returns

cupy.ndarray: probabilities

set_meta(columns, value)[source]

Set column values to morpheus.pipelines.messages.MessageMeta.df.

Parameters

columnstyping.Union[None, str, typing.List[str]]: 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.
valueAny: Value to apply to the specified columns. If a single value is passed, it will be broadcast to all rows. If a Series or Dataframe 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.