Function make_zip_of_tests

tensorflow/lite/testing/generate_examples_lib.py:357–601

Helper to make a zip file of a bunch of TensorFlow models. This does a cartestian product of the dictionary of test_parameters and calls make_graph() for each item in the cartestian product set. If the graph is built successfully, then make_test_inputs() is called to build expected input/ou

(options,
                      test_parameters,
                      make_graph,
                      make_test_inputs,
                      extra_toco_options=ExtraTocoOptions(),
                      use_frozen_graph=False,
                      expected_tf_failures=0)

def make_zip_of_tests(options,
                      test_parameters,
                      make_graph,
                      make_test_inputs,
                      extra_toco_options=ExtraTocoOptions(),
                      use_frozen_graph=False,
                      expected_tf_failures=0):
  """Helper to make a zip file of a bunch of TensorFlow models.

  This does a cartestian product of the dictionary of test_parameters and
  calls make_graph() for each item in the cartestian product set.
  If the graph is built successfully, then make_test_inputs() is called to
  build expected input/output value pairs. The model is then converted to tflite
  with toco, and the examples are serialized with the tflite model into a zip
  file (2 files per item in the cartesian product set).

  Args:
    options: An Options instance.
    test_parameters: Dictionary mapping to lists for each parameter.
      e.g. `{"strides": [[1,3,3,1], [1,2,2,1]], "foo": [1.2, 1.3]}`
    make_graph: function that takes current parameters and returns tuple
      `[input1, input2, ...], [output1, output2, ...]`
    make_test_inputs: function taking `curr_params`, `session`, `input_tensors`,
      `output_tensors` and returns tuple `(input_values, output_values)`.
    extra_toco_options: Additional toco options.
    use_frozen_graph: Whether or not freeze graph before toco converter.
    expected_tf_failures: Number of times tensorflow is expected to fail in
      executing the input graphs. In some cases it is OK for TensorFlow to
      fail because the one or more combination of parameters is invalid.

  Raises:
    RuntimeError: if there are converter errors that can't be ignored.
  """
  zip_path = os.path.join(options.output_path, options.zip_to_output)
  parameter_count = 0
  for parameters in test_parameters:
    parameter_count += functools.reduce(
        operator.mul, [len(values) for values in parameters.values()])

  if parameter_count > _MAX_TESTS_PER_ZIP:
    raise RuntimeError(
        "Too many parameter combinations for generating '%s'.\n"
        "There are %d combinations while the upper limit is %d.\n"
        "Having too many combinations will slow down the tests.\n"
        "Please consider splitting the test into multiple functions.\n"
        % (zip_path, parameter_count, _MAX_TESTS_PER_ZIP))

  # TODO(aselle): Make this allow multiple inputs outputs.
  archive = zipfile.PyZipFile(zip_path, "w")
  zip_manifest = []
  convert_report = []
  toco_errors = 0

  processed_labels = set()

  if options.make_edgetpu_tests:
    extra_toco_options.inference_input_type = tf.lite.constants.QUANTIZED_UINT8
    extra_toco_options.inference_output_type = tf.lite.constants.QUANTIZED_UINT8