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input.yaml
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input.yaml
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# yaml file for running eDNNs
# the name of your model
name: 'eDNN'
# the number of epochs to run
n_epoch: 50
# batch size of images
batch_size: 64
# learning rate for model
learning_rate: 0.0001
# number of GPUs to use
# set to one if using CPUs
n_gpu: 1
# number of threads to use for data queuing
n_threads: auto
forces: false
x_label: 'images'
y_label: 'labels'
# value of validation size (from 0 to 1)
validation_size: 0.1
# new feature! multi-scale DNN! tiles are not defined here
multi-scale: true
# type of channels: only support for default and fft for now...
branches:
- {type: default, focus: [128, 128], context: [32, 32], padding: wrap}
# - {type: pooled, size: [8,8], focus: [1, 1], context: [1, 1], padding: wrap}
# - {type: fftr, focus: [16, 16], context: [16, 16], padding: wrap} # real part
# - {type: ffti, focus: [16, 16], context: [16, 16], padding: wrap} # imaginary part