tf.raw_ops.SparseAccumulatorApplyGradient

Applies a sparse gradient to a given accumulator.

tf.raw_ops.SparseAccumulatorApplyGradient(
    handle, local_step, gradient_indices, gradient_values, gradient_shape,
    has_known_shape, name=None
)

Does not add if local_step is smaller than the accumulator's global_step.

Args:

  • handle: A Tensor of type mutable string. The handle to a accumulator.
  • local_step: A Tensor of type int64. The local_step value at which the sparse gradient was computed.
  • gradient_indices: A Tensor of type int64. Indices of the sparse gradient to be accumulated. Must be a vector.
  • gradient_values: A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, complex64, int64, qint8, quint8, qint32, bfloat16, uint16, complex128, half, uint32, uint64. Values are the non-zero slices of the gradient, and must have the same first dimension as indices, i.e., the nnz represented by indices and values must be consistent.
  • gradient_shape: A Tensor of type int64. Shape of the sparse gradient to be accumulated.
  • has_known_shape: A bool. Boolean indicating whether gradient_shape is unknown, in which case the input is ignored during validation.
  • name: A name for the operation (optional).

Returns:

The created Operation.