increase prefetch distributed example (#833)

tensorlayer · Sep 10, 2018 · 4621cc7 · 4621cc7
1 parent 00e8dc3
commit 4621cc7
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Showing 2 changed files with 4 additions and 4 deletions.
diff --git a/examples/distributed_training/tutorial_cifar10_distributed_trainer.py b/examples/distributed_training/tutorial_cifar10_distributed_trainer.py
@@ -99,8 +99,8 @@ def build_validation(x, y_):
     # validation_dataset = make_dataset(X_test, y_test)
     # validation_dataset = training_dataset.map(data_aug_valid, num_parallel_calls=multiprocessing.cpu_count())
     trainer = tl.distributed.Trainer(
-        build_training_func=build_train, training_dataset=training_dataset, batch_size=128,
-        optimizer=tf.train.RMSPropOptimizer, optimizer_args={'learning_rate': 0.0001}
+        build_training_func=build_train, training_dataset=training_dataset, optimizer=tf.train.AdamOptimizer,
+        optimizer_args={'learning_rate': 0.0001}, batch_size=128, num_epochs=50000, prefetch_buffer_size=4096
         # validation_dataset=validation_dataset, build_validation_func=build_validation
     )
 

diff --git a/examples/distributed_training/tutorial_mnist_distributed_trainer.py b/examples/distributed_training/tutorial_mnist_distributed_trainer.py
@@ -52,8 +52,8 @@ def build_validation(x, y_):
     training_dataset = make_dataset(X_train, y_train)
     # validation_dataset = make_dataset(X_val, y_val)
     trainer = tl.distributed.Trainer(
-        build_training_func=build_train, training_dataset=training_dataset, batch_size=32,
-        optimizer=tf.train.RMSPropOptimizer, optimizer_args={'learning_rate': 0.001}
+        build_training_func=build_train, training_dataset=training_dataset, optimizer=tf.train.AdamOptimizer,
+        optimizer_args={'learning_rate': 0.001}, batch_size=500, num_epochs=500, prefetch_buffer_size=4096
         # validation_dataset=validation_dataset, build_validation_func=build_validation
     )