Function trace

tensorflow/python/ops/math_ops.py:2524–2562

Compute the trace of a tensor `x`. `trace(x)` returns the sum along the main diagonal of each inner-most matrix in x. If x is of rank `k` with shape `[I, J, K, ..., L, M, N]`, then output is a tensor of rank `k-2` with dimensions `[I, J, K, ..., L]` where `output[i, j, k, ..., l] = trace(x

(x, name=None)

@deprecation.deprecated_endpoints("trace")
@dispatch.add_dispatch_support
def trace(x, name=None):
  """Compute the trace of a tensor `x`.

  `trace(x)` returns the sum along the main diagonal of each inner-most matrix
  in x. If x is of rank `k` with shape `[I, J, K, ..., L, M, N]`, then output
  is a tensor of rank `k-2` with dimensions `[I, J, K, ..., L]` where

  `output[i, j, k, ..., l] = trace(x[i, j, i, ..., l, :, :])`

  For example:

  ```python
  x = tf.constant([[1, 2], [3, 4]])
  tf.linalg.trace(x)  # 5

  x = tf.constant([[1, 2, 3],
                   [4, 5, 6],
                   [7, 8, 9]])
  tf.linalg.trace(x)  # 15

  x = tf.constant([[[1, 2, 3],
                    [4, 5, 6],
                    [7, 8, 9]],
                   [[-1, -2, -3],
                    [-4, -5, -6],
                    [-7, -8, -9]]])
  tf.linalg.trace(x)  # [15, -15]
  ```

  Args:
    x: tensor.
    name: A name for the operation (optional).

  Returns:
    The trace of input tensor.
  """
  with ops.name_scope(name, "Trace", [x]) as name:
    x = ops.convert_to_tensor(x, name="x")
    return reduce_sum(array_ops.matrix_diag_part(x), [-1], name=name)


@tf_export("linalg.matmul", "matmul")