sess.run(tf.global_variables_initializer())
else:
saver.restore(sess, load_path)
print("Model restored from %s." % load_path)
if outputPressure:
outputDataName = "pressure"
# load test data
tiCr.loadTestDataNpz(fromSim,
toSim,
emptyTileValue,
cropTileSizeLow,
cropOverlap,
0.95,
0.05,
load_vel=useVelocities,
low_res_size=simSizeLow,
upres=upRes,
keepAll=keepAll,
special_output_type=outputDataName,
bWidth=bWidth)
if useVelocities and not useDensity:
tiCr.reduceInputsToVelocity(dimensions=3)
tiCr.splitTileData(0.95, 0.05)
# create a summary to monitor cost tensor
lossTrain = tf.summary.scalar("loss", costFunc)
lossTest = tf.summary.scalar("lossTest", costFunc)
merged_summary_op = tf.summary.merge_all()
# create session and saver
sess = tf.InteractiveSession()
saver = tf.train.Saver()
# init vars or load model
if loadModelTest == -1:
sess.run(tf.global_variables_initializer())
else:
saver.restore(sess, load_path)
print("Model restored from %s." % load_path)
# load test data
if (fileFormat == "npz"):
tiCr.loadTestDataNpz(fromSim, toSim, emptyTileValue, cropTileSizeLow, cropOverlap, 0.95, 0.05, load_vel=useVelocities, low_res_size=simSizeLow, upres=upRes, keepAll=keepAll)
elif (fileFormat == "uni"):
tiCr.loadTestDataUni(fromSim, toSim, emptyTileValue, cropTileSizeLow, cropOverlap, 0.95, 0.05, load_vel=useVelocities, low_res_size=simSizeLow, upres=upRes)
else:
print("\n ERROR: Unknown file format \"" + fileFormat + "\". Use \"npz\" or \"uni\".")
exit()
#uniio.backupFile(__file__, test_path)
# create a summary to monitor cost tensor
lossTrain = tf.summary.scalar("loss", costFunc)
lossTest = tf.summary.scalar("lossTest", costFunc)
merged_summary_op = tf.summary.merge_all()
summary_writer = tf.summary.FileWriter(test_path, sess.graph)
# ---------------------------------------------