tf.compat.v1.train.GradientDescentOptimizer

Optimizer that implements the gradient descent algorithm.

Inherits From: Optimizer

Used in the notebooks

Used in the tutorials

learning_rate A Tensor or a floating point value. The learning rate to use.
use_locking If True use locks for update operations.
name Optional name prefix for the operations created when applying gradients. Defaults to "GradientDescent".

Methods

apply_gradients

View source

Apply gradients to variables.

This is the second part of minimize(). It returns an Operation that applies gradients.

Args
grads_and_vars List of (gradient, variable) pairs as returned by compute_gradients().
global_step Optional Variable to increment by one after the variables have been updated.
name Optional name for the returned operation. Default to the name passed to the Optimizer constructor.

Returns
An Operation that applies the specified gradients. If global_step was not None, that operation also increments global_step.

Raises
TypeError If grads_and_vars is malformed.
ValueError If none of the variables have gradients.