- class MultiResponseAEMessage(*, meta, mess_offset=0, mess_count=- 1, memory=None, offset=0, count=- 1, id_tensor_name='seq_ids', probs_tensor_name='probs', user_id=None)[source]
Bases:
morpheus.messages.multi_response_message.MultiResponseMessageA stronger typed version of
MultiResponseProbsMessagethat is used for inference workloads that return a probability array. Helps ensure the proper outputs are set and eases debugging.- Attributes
idid_coloutputstensorstimestamp- user_id
Returns ID column values from
morpheus.pipeline.messages.MessageMeta.dfas list.Returns ID column values from
morpheus.pipeline.messages.MessageMeta.df.Get outputs stored in the TensorMemory container.
Get tensors stored in the TensorMemory container sliced according to
offsetandcount.Returns timestamp column values from morpheus.messages.MessageMeta.df as list.
Methods
copy_meta_ranges(ranges[, mask])Perform a copy of the underlying dataframe for the given
rangesof rows.copy_ranges(ranges)Perform a copy of the current message, dataframe and tensors for the given
rangesof rows.copy_tensor_ranges(ranges[, mask])Perform a copy of the underlying tensor tensors for the given
rangesof rows.from_message(message, *[, meta, ...])Creates a new instance of a derived class from
MultiMessageusing an existing message as the template.Get the tensor that holds message ID information.
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 the tensor that holds output probabilities.
get_slice(start, stop)Perform a slice of the current message from
start:stop(excludingstop)get_tensor(name)Get tensor stored in the TensorMemory container.
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
rangesof 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_rowisn’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
rangeswill 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, dataframe and tensors for the given
rangesof rows.- Parameters
- rangestyping.List[typing.Tuple[int, int]]
- ——-
- `MultiTensorMessage`
Rows to include in the copy in the form of
[(`start_row,stop_row),…]` Thestop_rowisn’t included. For example to copy rows 1-2 & 5-7ranges=[(1, 3), (5, 8)]
- copy_tensor_ranges(ranges, mask=None)[source]
Perform a copy of the underlying tensor tensors for the given
rangesof 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_rowisn’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
rangeswill 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]
- classmethod from_message(message, *, meta=None, mess_offset=- 1, mess_count=- 1, memory=None, offset=- 1, count=- 1, **kwargs)[source]
Creates a new instance of a derived class from
MultiMessageusing 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
clswill be pulled frommessageunless otherwise specified in theargsorkwargs. Special handling is performed depending on whether or not a newmetaobject is supplied. If one is supplied, the offset and count defaults will be 0 andmeta.countrespectively. Otherwise offset and count will be pulled from the inputmessage.- Parameters
- clstyping.Type[Self]
- messageMultiMessage
- metaMessageMeta, optional
- mess_offsetint, optional
- mess_countint, optional
- memoryTensorMemory, optional
- offsetint, optional
- countint, optional
The class to create
An existing message to use as a template. Can be a base or derived from
clsas long as all arguments can be pulled frommessageor proveded inkwargsA new
MessageMetato use, by default NoneA new
mess_offsetto use, by default -1A new
mess_countto use, by default -1A new
TensorMemoryto use. If supplied,offsetandcountdefault to0andmemory.countrespectively. By default NoneA new
offsetto use, by default -1A new
countto use, by default -1- Returns
- Self
A new instance of type
cls- Raises
- ValueError
If the incoming
messageis None
- get_id_tensor()[source]
Get the tensor that holds message ID information. Equivalent to
get_tensor(id_tensor_name)- Returns
- cupy.ndarray
Array containing the ID information
- Raises
- KeyError
If
self.id_tensor_nameis not found in the tensors
- 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
Noneis specified. When a string is passed, aSeriesis returned. Otherwise aDataframeis 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. Alias for
MultiResponseMessage.get_tensor.- Parameters
- namestr
Output key name.
- Returns
- cupy.ndarray
Inference output.
- get_probs_tensor()[source]
Get the tensor that holds output probabilities. Equivalent to
get_tensor(probs_tensor_name)- Returns
- cupy.ndarray
The probabilities tensor
- Raises
- KeyError
If
self.probs_tensor_nameis not found in the tensors
- get_slice(start, stop)[source]
Perform a slice of the current message from
start:stop(excludingstop)For example to slice from rows 1-3 use
m.get_slice(1, 4). The returnedMultiTensorMessagewill contain references to the same underlying Dataframe and tensor tensors, and this calling this method is reletively low cost compared toMultiTensorMessage.copy_ranges- Parameters
- startint
- stopint
- ——-
- `MultiTensorMessage`
Starting row of the slice
Stop of the slice
- get_tensor(name)[source]
Get tensor stored in the TensorMemory container.
- Parameters
- namestr
tensor key name.
- Returns
- cupy.ndarray
Inference tensor.
- property id: List[int]
Returns ID column values from
morpheus.pipeline.messages.MessageMeta.dfas 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. Alias for
MultiResponseMessage.tensors.- Returns
- cupy.ndarray
Inference outputs.
- 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
Noneis 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
SeriesorDataframeis passed, rows will be matched by index.
- property tensors
Get tensors stored in the TensorMemory container sliced according to
offsetandcount.- Returns
- cupy.ndarray
Inference tensors.
- 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.
