class_docstr: Represents a multi-task kernel whose computations are independent of task.
class_docstr_tok: ["Represents","a","multi-task","kernel","whose","computations","are","independent","of","task","."]
code: def __init__(
      self,
      num_tasks,
      base_kernel,
      validate_args=False,
      name="Independent",
  ):
      parameters = dict(locals())
      with tf.name_scope(name):
          self._base_kernel = base_kernel
          super(Independent, self).__init__(
              num_tasks=num_tasks,
              dtype=base_kernel.dtype,
              feature_ndims=base_kernel.feature_ndims,
              name=name,
              validate_args=validate_args,
              parameters=parameters,
          )
  
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 1 to create a new Independent object from inherited base classes: MultiTaskKernel with example: obj = Independent(num_tasks, base_kernel, validate_args, name)