In [1]:

    

from proton_decay_study.generators.gen3d import Gen3D
from proton_decay_study.models.kevnet import Kevnet
import tensorflow as tf
import logging
import glob


    

    




Using TensorFlow backend.

In [2]:

    

logging.basicConfig(level=logging.DEBUG)
logger = logging.getLogger()

generator = Gen3D(glob.glob('../../*.h5'), 'image/wires','label/type', batch_size=1)
model = Kevnet(generator)


    

    




INFO:pdk.gen.gen3d:Initializing h5 file object with value: ../../prod_pdk_nubarkplus_49.h5
INFO:pdk.kevnet:Assembling Model
DEBUG:pdk.gen.gen3d:Getting called in next
DEBUG:pdk.gen.gen3d:returning value with shape: (1, 1, 3, 9600, 3600)
INFO:pdk.kevnet:Tensor("input_1:0", shape=(?, 1, 3, 9600, 3600), dtype=float32)
INFO:pdk.kevnet:(?, 1, 3, 9600, 3600)
INFO:pdk.kevnet:(?, 2, 3, 1067, 720)
INFO:pdk.kevnet:(?, 2, 3, 533, 360)
INFO:pdk.kevnet:(?, 2, 3, 533, 360)
DEBUG:pdk.gen.gen3d:Getting called in next
DEBUG:pdk.gen.gen3d:returning value with shape: (1, 1, 3, 9600, 3600)
INFO:pdk.kevnet:(?, 10)
INFO:pdk.kevnet:Compiling Model

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#for i in range(11):
#    generator.next()


    

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X,Y = generator.next()
model.fit(X, Y, batch_size=1, epochs=1, verbose=1, callbacks=None, 
          validation_split=0.0, validation_data=None,
          shuffle=True, class_weight=None, sample_weight=None, initial_epoch=0)


    

    




DEBUG:pdk.gen.gen3d:Getting called in next
DEBUG:pdk.gen.gen3d:returning value with shape: (1, 1, 3, 9600, 3600)






    




Epoch 1/1

In [ ]:

    

"""
training_output = model.fit_generator(generator, 
                                      steps_per_epoch=1, 
                                      epochs=1,
                                      workers=1,
                                      verbose=0,
                                      max_q_size=1,
                                      pickle_safe=False
                                     )
"""