- 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.PreprocessBaseStagePrepare NLP input DataFrames for inference.
- Parameters
- c
morpheus.config.Config - vocab_hash_filestr
- truncationbool
- do_lower_casebool
- add_special_tokensbool
- strideint
- columnstr
Pipeline configuration instance.
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_vocabfunction.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.
If set to true, original text will be lowercased before encoding.
Whether or not to encode the sequences with the special tokens of the BERT classification model.
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.Name of the column containing the data that needs to be preprocessed.
- c
- Attributes
has_multi_input_portshas_multi_output_portsinput_portsis_builtnameoutput_portsunique_name
Indicates if this stage has multiple input ports.
Indicates if this stage has multiple output ports.
Input ports to this stage.
Indicates if this stage has been built.
The name of the stage.
Output ports from this stage.
Unique name of stage.
Methods
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 to this stage.
Get all input senders to this stage.
Get all output stages from this stage.
Get all output receivers from this stage.
Stages which need to have columns inserted into the dataframe, should populate the
self._needed_columnsdictionary with mapping of column names tomorpheus.common.TypeId.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.
This function is called along with on_start during stage initialization.
stop()Stages can implement this to perform cleanup steps when pipeline is stopped.
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.SegmentObjectobject. The input of this function contains the returned value from the upstream stage.The input values are the
mrc.Builderfor this stage and aStreamPairtuple which contain the inputmrc.SegmentObjectobject and the message data type.- Parameters
- builder
mrc.Builder - in_ports_streams
morpheus.pipeline.pipeline.StreamPair
mrc.Builderobject for the pipeline. This should be used to construct/attach the internalmrc.SegmentObject.List of tuples containing the input
mrc.SegmentObjectobject and the message data type.- builder
- Returns
typing.List[morpheus.pipeline.pipeline.StreamPair]
List of tuples containing the output
mrc.SegmentObjectobject 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
mrc.Builder - do_propagatebool, optional
MRC segment for this stage.
Whether to propagate to build output stages, by default True.
- builder
- 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.
- typing.List[
- get_all_inputs()[source]
Get all input senders to this stage.
- Returns
- typing.List[
morpheus.pipeline.pipeline.Sender]
All input senders.
- typing.List[
- get_all_output_stages()[source]
Get all output stages from this stage.
- Returns
- typing.List[
morpheus.pipeline.pipeline.StreamWrapper]
All output stages.
- typing.List[
- get_all_outputs()[source]
Get all output receivers from this stage.
- Returns
- typing.List[
morpheus.pipeline.pipeline.Receiver]
All output receivers.
- typing.List[
- get_needed_columns()[source]
Stages which need to have columns inserted into the dataframe, should populate the
self._needed_columnsdictionary with mapping of column names tomorpheus.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[morpheus.pipeline.receiver.Receiver]
Input ports to this stage.
- Returns
- typing.List[
morpheus.pipeline.pipeline.Receiver]
Input ports to this stage.
- typing.List[
- 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
stopduring 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.
- typing.List[
- 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
morpheus.pipeline.messages.MultiMessage - vocab_hashfilestr
- do_lower_casebool
- seq_lenint
- strideint
- truncationbool
- add_special_tokensbool
- columnstr
Input rows received from Deserialized stage.
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_vocabfunction.If set to true, original text will be lowercased before encoding.
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.
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.
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.
Whether or not to encode the sequences with the special tokens of the BERT classification model.
Name of the column containing the data that needs to be preprocessed.
- x
- 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.
