morpheus.stages.preprocess.preprocess_nlp_stage.PreprocessNLPStage

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class PreprocessNLPStage(c, vocab_hash_file='data/bert-base-cased-hash.txt', truncation=False, do_lower_case=False, add_special_tokens=False, stride=- 1, column='data')[source]

Bases: morpheus.stages.preprocess.preprocess_base_stage.PreprocessBaseStage

Prepare NLP input DataFrames for inference.

Parameters

c<bsp-code-inline code="<a href="morpheus.config.Config.html#morpheus.config.Config">morpheus.config.Config</a>"><a href="morpheus.config.Config.html#morpheus.config.Config">morpheus.config.Config</a></bsp-code-inline>: Pipeline configuration instance.
vocab_hash_filestr: Path to hash file containing vocabulary of words with token-ids. This can be created from the raw vocabulary using the cudf.utils.hash_vocab_utils.hash_vocab function.
truncationbool: If set to true, strings will be truncated and padded to max_length. Each input string will result in exactly one output sequence. If set to false, there may be multiple output sequences when the max_length is smaller than generated tokens.
do_lower_casebool: If set to true, original text will be lowercased before encoding.
add_special_tokensbool: Whether or not to encode the sequences with the special tokens of the BERT classification model.
strideint: If truncation == False and the tokenized string is larger than max_length, the sequences containing the overflowing token-ids can contain duplicated token-ids from the main sequence. If max_length is equal to stride there are no duplicated-id tokens. If stride is 80% of max_length, 20% of the first sequence will be repeated on the second sequence and so on until the entire sentence is encoded.
columnstr: Name of the column containing the data that needs to be preprocessed.

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.
`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.
`pre_process_batch`(x, vocab_hash_file, ...)	For NLP category usecases, this function performs pre-processing.
`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

builder<bsp-code-inline code="mrc.Builder">mrc.Builder</bsp-code-inline>: mrc.Builder object for the pipeline. This should be used to construct/attach the internal mrc.SegmentObject.
in_ports_streams<bsp-code-inline code="morpheus.pipeline.pipeline.StreamPair">morpheus.pipeline.pipeline.StreamPair</bsp-code-inline>: 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

builder<bsp-code-inline code="mrc.Builder">mrc.Builder</bsp-code-inline>: 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.

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.

static pre_process_batch(x, vocab_hash_file, do_lower_case, seq_len, stride, truncation, add_special_tokens, column)[source]

For NLP category usecases, this function performs pre-processing.

Parameters

x<bsp-code-inline code="morpheus.pipeline.messages.MultiMessage">morpheus.pipeline.messages.MultiMessage</bsp-code-inline>: Input rows received from Deserialized stage.
vocab_hashfilestr: Path to hash file containing vocabulary of words with token-ids. This can be created from the raw vocabulary using the cudf.utils.hash_vocab_utils.hash_vocab function.
do_lower_casebool: If set to true, original text will be lowercased before encoding.
seq_lenint: Limits the length of the sequence returned. If tokenized string is shorter than max_length, output will be padded with 0s. If the tokenized string is longer than max_length and do_truncate == False, there will be multiple returned sequences containing the overflowing token-ids.
strideint: If do_truncate == False and the tokenized string is larger than max_length, the sequences containing the overflowing token-ids can contain duplicated token-ids from the main sequence. If max_length is equal to stride there are no duplicated-id tokens. If stride is 80% of max_length, 20% of the first sequence will be repeated on the second sequence and so on until the entire sentence is encoded.
truncationbool: If set to true, strings will be truncated and padded to max_length. Each input string will result in exactly one output sequence. If set to false, there may be multiple output sequences when the max_length is smaller than generated tokens.
add_special_tokensbool: Whether or not to encode the sequences with the special tokens of the BERT classification model.
columnstr: Name of the column containing the data that needs to be preprocessed.

Returns

morpheus.pipeline.messages.MultiInferenceNLPMessage: NLP inference message.

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.