LostTech.TensorFlow : API Documentation

Type AdagradParameters

Namespace tensorflow.tpu.experimental

Parent _OptimizationParameters

Interfaces IAdagradParameters

Optimization parameters for Adagrad with TPU embeddings.

Pass this to tf.estimator.tpu.experimental.EmbeddingConfigSpec via the `optimization_parameters` argument to set the optimizer and its parameters. See the documentation for tf.estimator.tpu.experimental.EmbeddingConfigSpec for more details.

``` estimator = tf.estimator.tpu.TPUEstimator( ... embedding_spec=tf.estimator.tpu.experimental.EmbeddingConfigSpec( ... optimization_parameters=tf.tpu.experimental.AdagradParameters(0.1), ...)) ```



Public static methods

AdagradParameters NewDyn(object learning_rate, ImplicitContainer<T> initial_accumulator, ImplicitContainer<T> use_gradient_accumulation, object clip_weight_min, object clip_weight_max)

Optimization parameters for Adagrad.
object learning_rate
used for updating embedding table.
ImplicitContainer<T> initial_accumulator
initial accumulator for Adagrad.
ImplicitContainer<T> use_gradient_accumulation
setting this to `False` makes embedding gradients calculation less accurate but faster. Please see `optimization_parameters.proto` for details. for details.
object clip_weight_min
the minimum value to clip by; None means -infinity.
object clip_weight_max
the maximum value to clip by; None means +infinity.

Public properties

object clip_weight_max get; set;

object clip_weight_min get; set;

double initial_accumulator get; set;

double learning_rate get; set;

object PythonObject get;

bool use_gradient_accumulation get; set;