docstr: Executes SVDF test run.
  
  Checks svdf produces the same outputs (activations/gradients) and
  parameters.
  
  Arguments:
    num_units: int or long, the number of units in the layer.
    memory_size: int or long, the size of the SVDF cell memory.
    rank: int or long, the rank of the SVD approximation.
    inputs: the input Tensor to use in the run.
    use_bias: bool, whether the layer uses a bias.
    activation: callable, the activation function to use.
    expected: dictionary with the expected variable name as key, and value.
code: def _runTest(
      self,
      num_units,
      memory_size,
      rank,
      inputs,
      use_bias,
      activation,
      expected,
  ):
      """Executes SVDF test run.
  
      Checks svdf produces the same outputs (activations/gradients) and
      parameters.
  
      Arguments:
        num_units: int or long, the number of units in the layer.
        memory_size: int or long, the size of the SVDF cell memory.
        rank: int or long, the rank of the SVD approximation.
        inputs: the input Tensor to use in the run.
        use_bias: bool, whether the layer uses a bias.
        activation: callable, the activation function to use.
        expected: dictionary with the expected variable name as key, and value.
  
      """
      # _runSvdf will provide the outputs after iterating over as many inputs
      # there are in time; thus we validate that final state and activations.
      svdf_outputs = self._runSvdf(
          inputs, num_units, memory_size, rank, use_bias, activation
      )
  
      for name, value in expected.items():
          svdf_output = np.squeeze(
              svdf_outputs[name]
          )  # Remove dummy batch dim.
          logging.debug("expected [%s]  value = \n%s", name, value)
          logging.debug("SVDF [%s]  value = \n%s", name, svdf_output)
          self.assertAllClose(value, svdf_output)
  
file_path: model_search/model_search/ops/svdf_cell_test.py
imports: import collections
  from absl import logging
  from model_search.ops import svdf_cell
  import numpy
  import tensorflow.compat.v2
label_desc: Use image node_id 4 for calling the SvdfCellTest obj's underlying member method code with example usage: obj._runTest(num_units, memory_size, rank, inputs, use_bias, activation, expected) without return types