code: def alphas_like(tensor, alpha_value, name=None, optimize=True):
      """Creates a tensor with all elements set to `alpha_value`.
      Given a single tensor (`tensor`), this operation returns a tensor of the same
      type and shape as `tensor` with all elements set to `alpha_value`.
  
      Parameters
      ----------
      tensor: tf.Tensor
          The Tensorflow Tensor that will be used as a template.
      alpha_value: `float32`, `float64`, `int8`, `uint8`, `int16`, `uint16`, int32`, `int64`
          The value used to fill the resulting `Tensor`.
      name: str
          A name for the operation (optional).
      optimize: bool
          if true, attempt to statically determine the shape of 'tensor' and encode it as a constant.
  
      Returns
      -------
      A `Tensor` with all elements set to `alpha_value`.
  
      Examples
      --------
      >>> tensor = tf.constant([[1, 2, 3], [4, 5, 6]])
      >>> tl.alphas_like(tensor, 0.5)  # [[0.5, 0.5, 0.5], [0.5, 0.5, 0.5]]
      """
      with ops.name_scope(name, "alphas_like", [tensor]) as name:
          tensor = ops.convert_to_tensor(tensor, name="tensor")
  
          if (
              context.in_eager_mode()
          ):  # and dtype is not None and dtype != tensor.dtype:
              ret = alphas(
                  shape_internal(tensor, optimize=optimize),
                  alpha_value=alpha_value,
                  name=name,
              )
  
          else:  # if context.in_graph_mode():
              # For now, variant types must be created via zeros_like; as we need to
              # pass the input variant object to the proper zeros callback.
  
              if optimize and tensor.shape.is_fully_defined():
                  # We can produce a zeros tensor independent of the value of 'tensor',
                  # since the shape is known statically.
                  ret = alphas(
                      tensor.shape, alpha_value=alpha_value, name=name
                  )
  
              # elif dtype is not None and dtype != tensor.dtype and dtype != dtypes.variant:
              else:
                  ret = alphas(
                      shape_internal(tensor, optimize=optimize),
                      alpha_value=alpha_value,
                      name=name,
                  )
  
              ret.set_shape(tensor.get_shape())
  
          return ret
  
imports: from tensorflow.python.eager import context
  from tensorflow.python.framework import constant_op, dtypes, ops, tensor_shape
  from tensorflow.python.framework.constant_op import constant
  from tensorflow.python.framework.ops import convert_to_tensor
  from tensorflow.python.ops.array_ops import shape_internal
  from tensorflow.python.ops.gen_array_ops import fill, reshape
label_desc: Use image node_id 2 for calling a global function with example usage: alphas_like(tensor, alpha_value, name, optimize) and returns: ret