tf.tpu.experimental.StochasticGradientDescentParameters
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Optimization parameters for stochastic gradient descent for TPU embeddings.
tf.tpu.experimental.StochasticGradientDescentParameters(
learning_rate, clip_weight_min=None, clip_weight_max=None
)
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_config_spec=tf.estimator.tpu.experimental.EmbeddingConfigSpec(
...
optimization_parameters=(
tf.tpu.experimental.StochasticGradientDescentParameters(0.1))))
Args |
|---|
learning_rate
|
a floating point value. The learning rate.
|
clip_weight_min
|
the minimum value to clip by; None means -infinity.
|
clip_weight_max
|
the maximum value to clip by; None means +infinity.
|
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Last updated 2020-10-01 UTC.
[null,null,["Last updated 2020-10-01 UTC."],[],[],null,["# tf.tpu.experimental.StochasticGradientDescentParameters\n\n\u003cbr /\u003e\n\n|---------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/tpu/tpu_embedding.py#L377-L406) |\n\nOptimization parameters for stochastic gradient descent for TPU embeddings.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.tpu.experimental.StochasticGradientDescentParameters`](/api_docs/python/tf/compat/v1/tpu/experimental/StochasticGradientDescentParameters)\n\n\u003cbr /\u003e\n\n tf.tpu.experimental.StochasticGradientDescentParameters(\n learning_rate, clip_weight_min=None, clip_weight_max=None\n )\n\nPass this to [`tf.estimator.tpu.experimental.EmbeddingConfigSpec`](../../../tf/estimator/tpu/experimental/EmbeddingConfigSpec) via the\n`optimization_parameters` argument to set the optimizer and its parameters.\nSee the documentation for [`tf.estimator.tpu.experimental.EmbeddingConfigSpec`](../../../tf/estimator/tpu/experimental/EmbeddingConfigSpec)\nfor more details. \n\n estimator = tf.estimator.tpu.TPUEstimator(\n ...\n embedding_config_spec=tf.estimator.tpu.experimental.EmbeddingConfigSpec(\n ...\n optimization_parameters=(\n tf.tpu.experimental.StochasticGradientDescentParameters(0.1))))\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-------------------|-----------------------------------------------------|\n| `learning_rate` | a floating point value. The learning rate. |\n| `clip_weight_min` | the minimum value to clip by; None means -infinity. |\n| `clip_weight_max` | the maximum value to clip by; None means +infinity. |\n\n\u003cbr /\u003e"]]
View source on GitHub