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Runner.md

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Python Runner

Overview

Python Runner is one of the benchmark runners described in Architecture.md. Python runner loads and runs testing modules, which in this case are modules in the sense of Python language.

Every testing module contains an implementation of some algorithm computing objective functions and their derivatives. Every objective should be supported by both the runner and the module to be benchmarked.

A module doesn't have to support all of the objective types. If a user asks the runner to benchmark an unsupported objective, the runner prints an error and stops.

Every module, for every objective it supports, defines a class implementing the abstract ITest class.

Supported Objective Types

Currently supported objective types:

Full Name Short Name
Gaussian Mixture Model Fitting GMM
Bundle Adjustment BA
Hand Tracking Hand
Long short-term memory LSTM

Command Line

python3 /path/to/repo/src/python/runner/main.py test_type module_path input_filepath output_dir minimum_measurable_time nruns_F nruns_J time_limit [-rep]
  • test_type - the short type name of the objective function. It may also be equal to "Hand-Complicated" that designates the complicated case of the "Hand" objective, where the variable U is considered (see srajer-autodiff-screen.pdf, page 5).
  • module_path - an absolute or relative path to a .py file containing the module to be benchmarked.
  • input_filepath - an absolute or relative path to the input file.
  • output_dir - a directory where the output files should be stored.
  • minimum_measurable_time - minimum time that the computation needs to run to produce a reliable measurement.
  • nruns_F - maximum number of times to run the computation of the objective function for timing.
  • nruns_J - maximum number of times to run the computation of the considered derivative (gradient or Jacobian) for timing.
  • time_limit - soft (see Methodology.md) time limit for benchmarking the computation of either the objective function or its gradient/Jacobian.
  • -rep (applicable only for GMM) - if enabled, all input data points are expected to have one shared value.

Adding new modules

(see Modules.md)

Adding new objective types

  1. Define TInput and TOutput classes in the /src/python/shared/TData.py file where T is the name of a new objective.

    TInput is the data type for the new objective inputs, TOutput is a structure that contains outputs of both new objective function and its target jacobian. Also TOutput contains save_output_to_file function

    def save_output_to_file(
    self,
    output_prefix,
    input_basename,
    module_basename
)

    This function saves results of computations stored in a structure of the TOutput type to the output files:

    • output_prefix + input_basename + "_F_" + module_basename + ".txt" - stores the value of the objective function

    • output_prefix + input_basename + "_J_" + module_basename + ".txt" - stores the value of the objective function derivative

      The format of the output files is specific for each objective type.

  2. Add the following function to the /src/python/shared/input_utils.py file:

    def read_T_instance(fn):

    It opens input file fn and loads data to the structure of the TInput type.

  3. Add a new else-if branch to the Runner (/src/python/runner/main.py) as follows:

    if test_type == "GMM":
    # read gmm input
    _input = input_utils.read_gmm_instance(input_filepath, replicate_point)
elif
    ...
elif test_type == "T"
    _input = input_utils.read_T_instance(input_filepath)
else:
    raise RuntimeError("Python runner doesn't support tests of " + test_type + " type")

Input/Output files format

See FileFormat.md.