Searched refs:exponential_decay (Results 1 – 15 of 15) sorted by relevance
| /external/tensorflow/tensorflow/python/training/ |
| D | learning_rate_decay_test.py | 38 decayed_lr = learning_rate_decay.exponential_decay(0.05, step, 10, 0.96)
47 decayed_lr = learning_rate_decay.exponential_decay(
70 decayed_lr = learning_rate_decay.exponential_decay(
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| D | learning_rate_decay.py | 29 def exponential_decay(learning_rate, function
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| /external/tensorflow/tensorflow/examples/learn/ |
| D | iris_custom_decay_dnn.py | 55 learning_rate = tf.train.exponential_decay(
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| /external/tensorflow/tensorflow/contrib/eager/python/examples/l2hmc/ |
| D | main.py | 56 learning_rate = tf.train.exponential_decay(
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| /external/tensorflow/tensorflow/contrib/model_pruning/examples/cifar10/ |
| D | cifar10_pruning.py | 342 lr = tf.train.exponential_decay(
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| /external/tensorflow/tensorflow/contrib/gan/python/estimator/python/ |
| D | stargan_estimator_test.py | 216 lr = learning_rate_decay.exponential_decay(1.0, gstep, 10, 0.9)
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| D | tpu_gan_estimator_test.py | 159 lr = learning_rate_decay.exponential_decay(1.0, gstep, 10, 0.9)
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| D | gan_estimator_test.py | 218 lr = learning_rate_decay.exponential_decay(1.0, gstep, 10, 0.9)
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| /external/tensorflow/tensorflow/examples/udacity/ |
| D | 3_regularization.ipynb | 293 " learning_rate = tf.train.exponential_decay(0.5, global_step, ...)\n",
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| D | 6_lstm.ipynb | 583 " learning_rate = tf.train.exponential_decay(\n",
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| /external/tensorflow/tensorflow/contrib/tpu/ |
| D | tpu_estimator.md | 58 learning_rate = tf.train.exponential_decay(
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.train.pbtxt | 300 name: "exponential_decay"
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| /external/tensorflow/tensorflow/python/grappler/ |
| D | hierarchical_controller.py | 1061 return learning_rate_decay.exponential_decay(lr_init, lr_gstep,
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| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| D | dnn_linear_combined_test.py | 745 learning_rate = learning_rate_decay.exponential_decay(
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| /external/tensorflow/tensorflow/tools/docker/notebooks/ |
| D | 3_mnist_from_scratch.ipynb | 1152 … adjust the learning rate during training -- that's handled by the `exponential_decay` operation, …
1223 "learning_rate = tf.train.exponential_decay(\n",
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