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author | 2016-07-31 22:07:30 -0800 | |
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committer | 2016-07-31 23:17:46 -0700 | |
commit | abe9ab326625105adb3c9d46c027931aec947d1f (patch) | |
tree | d9fa7eb9a2fd9b37bc87f98cf353354391b9eb04 /tensorflow/python/training/learning_rate_decay.py | |
parent | c0637048dbc099eac1f75878b765220cd02ccfc0 (diff) |
Merge changes from github.
Change: 128958134
Diffstat (limited to 'tensorflow/python/training/learning_rate_decay.py')
-rw-r--r-- | tensorflow/python/training/learning_rate_decay.py | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/tensorflow/python/training/learning_rate_decay.py b/tensorflow/python/training/learning_rate_decay.py index f24f1f4a08..ef369e9095 100644 --- a/tensorflow/python/training/learning_rate_decay.py +++ b/tensorflow/python/training/learning_rate_decay.py @@ -54,7 +54,7 @@ def exponential_decay(learning_rate, global_step, decay_steps, decay_rate, 100000, 0.96, staircase=True) # Passing global_step to minimize() will increment it at each step. learning_step = ( - tf.GradientDescentOptimizer(learning_rate) + tf.train.GradientDescentOptimizer(learning_rate) .minimize(...my loss..., global_step=global_step) ) ``` @@ -195,7 +195,7 @@ def polynomial_decay(learning_rate, global_step, decay_steps, power=0.5) # Passing global_step to minimize() will increment it at each step. learning_step = ( - tf.GradientDescentOptimizer(learning_rate) + tf.train.GradientDescentOptimizer(learning_rate) .minimize(...my loss..., global_step=global_step) ) ``` @@ -268,7 +268,7 @@ def natural_exp_decay(learning_rate, global_step, decay_steps, decay_rate, # Passing global_step to minimize() will increment it at each step. learning_step = ( - tf.GradientDescentOptimizer(learning_rate) + tf.train.GradientDescentOptimizer(learning_rate) .minimize(...my loss..., global_step=global_step) ) ``` @@ -327,7 +327,7 @@ def inverse_time_decay(learning_rate, global_step, decay_steps, decay_rate, # Passing global_step to minimize() will increment it at each step. learning_step = ( - tf.GradientDescentOptimizer(learning_rate) + tf.train.GradientDescentOptimizer(learning_rate) .minimize(...my loss..., global_step=global_step) ) ``` |