Module: tf.compat.v1.train.experimental

Public API for tf._api.v2.train.experimental namespace

Classes

class DynamicLossScale: Loss scale that dynamically adjusts itself.

class FixedLossScale: Loss scale with a fixed value.

class LossScale: Base class for all TF1 loss scales.

class MaxShardSizePolicy: Policy that splits tensors into shards with a max shard size.

class MixedPrecisionLossScaleOptimizer: An optimizer that applies loss scaling.

class PythonState: A mixin for putting Python state in an object-based checkpoint.

class ShardByTaskPolicy: Policy that splits tensors into shards based on their device spec task.

class ShardableTensor: Tensor wrapper containing data necessary for sharding.

class ShardingCallback: Checkpoint sharding callback function, along with a text description.

Functions

disable_mixed_precision_graph_rewrite(...): Disables the mixed precision graph rewrite.

enable_mixed_precision_graph_rewrite(...): Enable mixed precision via a graph rewrite.