class_docstr: Shared logic for amplitude/length_scale parameterized kernels.
class_docstr_tok: ["Shared","logic","for","amplitude\/length_scale","parameterized","kernels","."]
docstr: Shared init logic for `amplitude` and `length_scale` params.
  
  Args:
    amplitude: `Tensor` (or convertible) or `None` to convert, validate.
    length_scale: `Tensor` (or convertible) or `None` to convert, validate.
    inverse_length_scale: `Tensor` (or convertible) or `None` to convert,
      validate.
  
  Returns:
    dtype: The common `DType` of the parameters.
code: def _init_params(self, amplitude, length_scale, inverse_length_scale):
      """Shared init logic for `amplitude` and `length_scale` params.
  
      Args:
        amplitude: `Tensor` (or convertible) or `None` to convert, validate.
        length_scale: `Tensor` (or convertible) or `None` to convert, validate.
        inverse_length_scale: `Tensor` (or convertible) or `None` to convert,
          validate.
  
      Returns:
        dtype: The common `DType` of the parameters.
      """
      if (length_scale is not None) and (
          inverse_length_scale is not None
      ):
          raise ValueError(
              "Must specify at most one of `length_scale` and "
              "`inverse_length_scale`."
          )
      dtype = util.maybe_get_common_dtype(
          [amplitude, length_scale, inverse_length_scale]
      )
      self._amplitude = tensor_util.convert_nonref_to_tensor(
          amplitude, name="amplitude", dtype=dtype
      )
      self._length_scale = tensor_util.convert_nonref_to_tensor(
          length_scale, name="length_scale", dtype=dtype
      )
      self._inverse_length_scale = tensor_util.convert_nonref_to_tensor(
          inverse_length_scale, name="inverse_length_scale", dtype=dtype
      )
      return dtype
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.math import bessel
  from tensorflow_probability.python.math.psd_kernels import positive_semidefinite_kernel
  from tensorflow_probability.python.math.psd_kernels.internal import util
label_desc: Use image node_id 1 for calling the _AmplitudeLengthScaleMixin obj's underlying member method code with example usage: obj._init_params(amplitude, length_scale, inverse_length_scale) and returns: dtype