Morpheus CLI Overview

This section focuses on the Morpheus CLI and illustrates how the CLI can be used to configure and run a Morpheus Pipeline.

The Morpheus CLI is built on the Click Python package which allows for nested commands and chaining multiple commands together. At a high level, the CLI is broken up into two main sections:

  • run
    • For running AE, FIL, NLP or OTHER pipelines.

  • tools
    • Tools/Utilities to help set up, configure and run pipelines and external resources.

Users can get help on any command by passing --help to a command or sub-command. For example, to get help on the run:

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$ morpheus run --help Usage: morpheus run [OPTIONS] COMMAND [ARGS]... Options: --num_threads INTEGER RANGE Number of internal pipeline threads to use [default: 12; x>=1] --pipeline_batch_size INTEGER RANGE Internal batch size for the pipeline. Can be much larger than the model batch size. Also used for Kafka consumers [default: 256; x>=1] --model_max_batch_size INTEGER RANGE Max batch size to use for the model [default: 8; x>=1] --edge_buffer_size INTEGER RANGE The size of buffered channels to use between nodes in a pipeline. Larger values reduce backpressure at the cost of memory. Smaller values will push messages through the pipeline quicker. Must be greater than 1 and a power of 2 (i.e. 2, 4, 8, 16, etc.) [default: 128; x>=2] --use_cpp BOOLEAN Whether or not to use C++ node and message types or to prefer python. Only use as a last resort if bugs are encountered [default: True] --help Show this message and exit. Commands: pipeline-ae Run the inference pipeline with an AutoEncoder model pipeline-fil Run the inference pipeline with a FIL model pipeline-nlp Run the inference pipeline with a NLP model pipeline-other Run a custom inference pipeline without a specific model type

Currently, Morpheus pipeline can be operated in four different modes.

  • pipeline-ae
    • This pipeline mode is used to run training/inference on the AutoEncoder model.

  • pipeline-fil
    • This pipeline mode is used to run inference on FIL (Forest Inference Library) models such as XGBoost, RandomForestClassifier, etc.

  • pipeline-nlp
    • This pipeline mode is used to run inference on NLP models, it offers the ability to tokenize the input data prior to submitting the inference requests.

  • pipeline-other
    • Run a customized inference pipeline without using a specific model type.

Similar to the run command, we can get help on the tools:

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$ morpheus tools --help Usage: morpheus tools [OPTIONS] COMMAND [ARGS]... Tools subcommand Options: --help Show this message and exit. Commands: autocomplete Utility for installing/updating/removing shell completion for Morpheus onnx-to-trt Converts an ONNX model to a TRT engine

The help text will show arguments, options and all possible sub-commands. Help for each of these sub-commands can be queried in the same manner:

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$ morpheus tools onnx-to-trt --help Usage: morpheus tools onnx-to-trt [OPTIONS] Converts an ONNX model to a TRT engine Options: --input_model PATH [required] --output_model PATH [required] --batches <INTEGER INTEGER>... [required] --seq_length INTEGER [required] --max_workspace_size INTEGER [default: 16000] --help Show this message and exit.

The Morpheus CLI supports bash, fish, zsh, and powershell autocompletion. To set up autocomplete, it must first be installed. Morpheus comes with a tool to assist with this:

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$ morpheus tools autocomplete install bash completion installed in ~/.bash_completion $ source ~/.bash_completion

After autocomplete has been installed, [TAB] can be used to show all commands, options and arguments when building pipelines via the CLI:

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$ morpheus run pipeline- # [TAB][TAB] pipeline-fil pipeline-nlp

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