class_docstr: Represents a multi-task kernel whose kernel can be separated as a product.
class_docstr_tok: ["Represents","a","multi-task","kernel","whose","kernel","can","be","separated","as","a","product","."]
code: def _parameter_properties(cls, dtype, num_classes=None):
      return dict(
          base_kernel=parameter_properties.BatchedComponentProperties(),
          task_kernel_matrix_linop=(
              parameter_properties.BatchedComponentProperties()
          ),
          task_kernel_scale_linop=(
              parameter_properties.BatchedComponentProperties()
          ),
      )
  
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import nest_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.math.psd_kernels import positive_semidefinite_kernel
label_desc: Use image node_id 5 for calling the Separable obj's underlying member method code with example usage: obj._parameter_properties(cls, dtype, num_classes) and returns: dict