tf.keras.ops.slice_update

Update an input by slicing in a tensor of updated values.

tf.keras.ops.slice_update(
    inputs, start_indices, updates
)

At a high level, this operation does inputs[start_indices: start_indices + updates.shape] = updates. Assume inputs is a tensor of shape (D0, D1, ..., Dn), start_indices must be a list/tuple of n integers, specifying the starting indices. updates must have the same rank as inputs, and the size of each dim must not exceed Di - start_indices[i]. For example, if we have 2D inputs inputs = np.zeros((5, 5)), and we want to update the intersection of last 2 rows and last 2 columns as 1, i.e., inputs[3:, 3:] = np.ones((2, 2)), then we can use the code below:

inputs = np.zeros((5, 5))
start_indices = [3, 3]
updates = np.ones((2, 2))
inputs = keras.ops.slice_update(inputs, start_indices, updates)

inputs A tensor, the tensor to be updated.
start_indices A list/tuple of shape (inputs.ndim,), specifying the starting indices for updating.
updates A tensor, the new values to be put to inputs at indices. updates must have the same rank as inputs.

A tensor, has the same shape and dtype as inputs.