code: def enable_numpy_behavior(
      prefer_float32=False, dtype_conversion_mode="legacy"
  ):
      """Enable NumPy behavior on Tensors.
  
      Enabling NumPy behavior has three effects:
      * It adds to `tf.Tensor` some common NumPy methods such as `T`,
        `reshape` and `ravel`.
      * It changes dtype promotion in `tf.Tensor` operators to be
        compatible with NumPy. For example,
        `tf.ones([], tf.int32) + tf.ones([], tf.float32)` used to throw a
        "dtype incompatible" error, but after this it will return a
        float64 tensor (obeying NumPy's promotion rules).
      * It enhances `tf.Tensor`'s indexing capability to be on par with
        [NumPy's](https://numpy.org/doc/stable/reference/arrays.indexing.html).
  
      Args:
        prefer_float32: Controls whether dtype inference will use float32 for Python
          floats, or float64 (the default and the NumPy-compatible behavior).
        dtype_conversion_mode: a string that specifies promotion mode. This string
          corresponds to a PromoMode Enum and can be 'off', 'legacy', 'safe', or
          'all'. 'safe' or 'all' mode enables the auto dtype conversion semantics.
      """
      if (
          dtype_conversion_mode == "safe"
          or dtype_conversion_mode == "all"
      ):
          tf_logging.warning(
              "UserWarning: enabling the new type promotion must happen at the"
              " beginning of the program. Please ensure no TF APIs have been used"
              " yet."
          )
      ops.set_dtype_conversion_mode(dtype_conversion_mode)
      ops.enable_numpy_style_slicing()
      np_math_ops.enable_numpy_methods_on_tensor()
      np_dtypes.set_prefer_float32(prefer_float32)
  
imports: from tensorflow.python.framework import ops
  from tensorflow.python.ops import weak_tensor_ops
  from tensorflow.python.ops.numpy_ops import np_dtypes
  from tensorflow.python.ops.numpy_ops import np_math_ops
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util import tf_export
label_desc: Use image node_id 1 for calling a global function with example usage: enable_numpy_behavior(prefer_float32, dtype_conversion_mode) without return types