code: def scatter(indices, values, shape):
      """Returns a tensor of shape `shape` where `indices` are set to `values`.
  
      At a high level, this operation does `zeros[indices] = updates` and
      returns the output. It is equivalent to:
  
      ```python
      zeros = keras.ops.zeros(shape)
      output = keras.ops.scatter_update(zeros, indices, values)
      ```
  
      Args:
          indices: A tensor or list/tuple specifying
              indices for the values in `values`.
          values: A tensor, the values to be set at `indices`.
          shape: Shape of the output tensor.
  
      Example:
  
      >>> indices = [[0, 1], [1, 1]]
      >>> values = np.array([1., 1.])
      >>> keras.ops.scatter(indices, values, shape=(2, 2))
      array([[0., 1.],
             [0., 1.]])
      """
      if any_symbolic_tensors((indices, values, shape)):
          return Scatter().symbolic_call(indices, values, shape)
      return backend.core.scatter(indices, values, shape)
  
imports: import numpy
  from keras import backend
  from keras.api_export import keras_export
  from keras.backend import KerasTensor
  from keras.backend import any_symbolic_tensors
  from keras.ops.operation import Operation
  from keras.utils import traceback_utils
label_desc: Use image node_id 1 for calling a global function with example usage: scatter(indices, values, shape) and returns: backend, Scatter