code: def cdf(x, df, loc, scale):
      """Compute cumulative density function of Student T distribution.
  
      Note that scale can be negative.
  
      Args:
        x: Floating-point `Tensor`. Where to compute the cumulative
          distribution function.
        df: Floating-point `Tensor`. The degrees of freedom of the
          distribution(s). `df` must contain only positive values.
        loc: Floating-point `Tensor`; the location(s) of the distribution(s).
        scale: Floating-point `Tensor`; the scale(s) of the distribution(s).
  
      Returns:
        A `Tensor` with shape broadcast according to the arguments.
      """
      dtype = dtype_util.common_dtype([x, df, loc, scale], tf.float32)
  
      x, df, loc, scale = [
          tf.convert_to_tensor(param, dtype=dtype)
          for param in (x, df, loc, scale)
      ]
  
      t = (x - loc) / tf.math.abs(scale)
      return stdtr(df, t)
  
imports: import functools
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import custom_gradient
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import reparameterization
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import special_math
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.math import generic
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.math import numeric
  from tensorflow_probability.python.math import special
label_desc: Use image node_id 12 for calling a global function with example usage: cdf(x, df, loc, scale) and returns: stdtr