tf.raw_ops.SparseConditionalAccumulator

A conditional accumulator for aggregating sparse gradients.

tf.raw_ops.SparseConditionalAccumulator(
    dtype, shape, container='', shared_name='', reduction_type='MEAN', name=None
)

The accumulator accepts gradients marked with local_step greater or equal to the most recent global_step known to the accumulator. The average can be extracted from the accumulator, provided sufficient gradients have been accumulated. Extracting the average automatically resets the aggregate to 0, and increments the global_step recorded by the accumulator.

Args:

  • dtype: A tf.DType from: tf.float32, tf.float64, tf.int32, tf.uint8, tf.int16, tf.int8, tf.complex64, tf.int64, tf.qint8, tf.quint8, tf.qint32, tf.bfloat16, tf.uint16, tf.complex128, tf.half, tf.uint32, tf.uint64. The type of the value being accumulated.
  • shape: A tf.TensorShape or list of ints. The shape of the values.
  • container: An optional string. Defaults to "". If non-empty, this accumulator is placed in the given container. Otherwise, a default container is used.
  • shared_name: An optional string. Defaults to "". If non-empty, this accumulator will be shared under the given name across multiple sessions.
  • reduction_type: An optional string from: "MEAN", "SUM". Defaults to "MEAN".
  • name: A name for the operation (optional).

Returns:

A Tensor of type mutable string.