class tf.ConditionalAccumulatorBase
See the guide: Inputs and Readers > Conditional Accumulators
A conditional accumulator for aggregating gradients.
Up-to-date gradients (i.e., time step at which gradient was computed is equal to the accumulator's time step) are added to the accumulator.
Extraction of the average gradient is blocked until the required number of gradients has been accumulated.
accumulator_ref
The underlying accumulator reference.
dtype
The datatype of the gradients accumulated by this accumulator.
name
The name of the underlying accumulator.
__init__(dtype, shape, accumulator_ref)
Creates a new ConditionalAccumulator.
dtype
: Datatype of the accumulated gradients.shape
: Shape of the accumulated gradients.accumulator_ref
: A handle to the conditional accumulator, created by sub- classesnum_accumulated(name=None)
Number of gradients that have currently been aggregated in accumulator.
name
: Optional name for the operation.Number of accumulated gradients currently in accumulator.
set_global_step(new_global_step, name=None)
Sets the global time step of the accumulator.
The operation logs a warning if we attempt to set to a time step that is lower than the accumulator's own time step.
new_global_step
: Value of new time step. Can be a variable or a constantname
: Optional name for the operation.Operation that sets the accumulator's time step.
Defined in tensorflow/python/ops/data_flow_ops.py
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© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/ConditionalAccumulatorBase