train.md

Basenji

Sequential regulatory activity predictions with deep convolutional neural networks.

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Learn

basenji_train.py

Train a convolutional neural network to make sequential predictions on the given data.

Argument	Type	Description
params_file	Text table	Model configuration parameters.
data_file	HDF5	Input training and validation data.

The model should be trained on a GPU so that it runs at a reasonable pace. When assigning ops to devices, TensorFlow gives priority to your gpu:0 device (over cpu:0) if the GPU is available and supported.

To print whether the model is being trained on the GPU, run basenji_train.py with the log_device_placement flag set to True. In this sample output, training happens on the CPU (The GPU is unsupported in this particular case.):

Device mapping:
...
2017-07-23 12:31:25.796354: I tensorflow/core/common_runtime/simple_placer.cc:847] cnn1/BatchNorm/Const: (Const)/job:localhost/replica:0/task:0/cpu:0
cnn0/BatchNorm/Const_1: (Const): /job:localhost/replica:0/task:0/cpu:0
2017-07-23 12:31:25.796361: I tensorflow/core/common_runtime/simple_placer.cc:847] cnn0/BatchNorm/Const_1: (Const)/job:localhost/replica:0/task:0/cpu:0
cnn0/BatchNorm/Const: (Const): /job:localhost/replica:0/task:0/cpu:0
2017-07-23 12:31:25.796368: I tensorflow/core/common_runtime/simple_placer.cc:847] cnn0/BatchNorm/Const: (Const)/job:localhost/replica:0/task:0/cpu:0
Initialization time 15.614956