def main(modelName, phase):
# import json_maker, update json files and read requested json file
import Model_Settings.json_maker as json_maker
if not json_maker.recompile_json_files(modelName):
return
jsonToRead = modelName+'.json'
print("Reading %s" % jsonToRead)
with open('Model_Settings/'+jsonToRead) as dataFile:
modelParams = json.load(dataFile)
if phase == 'train':
jsonPath = modelParams['trainOutputDir']
elif phase == 'test':
jsonPath = modelParams['testOutputDir']
else:
print('Please enter proper phase')
return
resultsDict = _get_resultDict(jsonPath)
acc, confmatrix = evaluate(resultsDict)
print()
print(confmatrix)
print('----------------- Phase : ', phase)
print('----------------- Prediction result path : ', jsonPath)
return acc
def main(argv=None): # pylint: disable=unused-argumDt
if (len(argv) < 3):
print("Enter 'model name' and 'epoch number to load / 0 for new'")
return
modelName = argv[1]
epochNumber = int(argv[2])
# import json_maker, update json files and read requested json file
import Model_Settings.json_maker as json_maker
if not json_maker.recompile_json_files(modelName):
return
jsonToRead = modelName + '.json'
print("Reading %s" % jsonToRead)
with open('Model_Settings/' + jsonToRead) as data_file:
modelParams = json.load(data_file)
modelParams['phase'] = PHASE
modelParams = _set_control_params(modelParams)
print(modelParams['modelName'])
print('Testing steps = %.1f' % float(modelParams['testMaxSteps']))
print('Rounds on datase = %.1f' % float(
(modelParams['testBatchSize'] * modelParams['testMaxSteps']) /
modelParams['numTestDatasetExamples']))
print('lossFunction = ', modelParams['lossFunction'])
print('Test Input: %s' % modelParams['testDataDir'])
print('Test Logs Output: %s' % modelParams['testLogDir'])
print('')
print('')
train(modelParams, epochNumber)
def main(argv=None): # pylint: disable=unused-argumDt
if (len(argv)<4):
print("Enter 'model name' and 'iteration number' and 'epoch number to load / 0 for new'")
return
modelName = argv[1]
itrNum = int(argv[2])
epochNumber = int(argv[3])
if itrNum>4 or itrNum<0:
print('iteration number should only be from 1 to 4 inclusive')
return
# import json_maker, update json files and read requested json file
import Model_Settings.json_maker as json_maker
if not json_maker.recompile_json_files(modelName, itrNum):
return
jsonToRead = modelName+'_'+str(itrNum)+'.json'
print("Reading %s" % jsonToRead)
with open('Model_Settings/'+jsonToRead) as data_file:
modelParams = json.load(data_file)
modelParams = _set_control_params(modelParams)
print(modelParams['modelName'])
print('Training steps = %.1f' % float(modelParams['trainMaxSteps']))
print('Rounds on datase = %.1f' % float((modelParams['trainBatchSize']*modelParams['trainMaxSteps'])/modelParams['numTrainDatasetExamples']))
print('lossFunction = ', modelParams['lossFunction'])
print('Train Input: %s' % modelParams['trainDataDir'])
#print('Test Input: %s' % modelParams['testDataDir'])
print('Train Logs Output: %s' % modelParams['trainLogDir'])
#print('Test Logs Output: %s' % modelParams['testLogDir'])
print('Train Warp Output: %s' % modelParams['warpedTrainDataDir'])
#print('Test Warp Output: %s' % modelParams['warpedTestDataDir'])
print('')
print('')
if modelParams.get('lastTuple'):
print('!!! Training model is built to use only the the last 2 tuples from the existing ',modelParams['numTuple'],' tuples !!!')
else:
print('!!! Training model is built to use all of the ', modelParams['numTuple'],' tuples !!!')
print('')
if epochNumber == 0:
if not tf.gfile.Exists(modelParams['trainDataDir']):
print("Train input data folder doesn't exist...")
print(modelParams['trainDataDir'])
return
#if input("(Overwrite WARNING) Did you change logs directory? (y) ") != "y":
# print("Please consider changing logs directory in order to avoid overwrite!")
# return
if tf.gfile.Exists(modelParams['trainLogDir']):
tf.gfile.DeleteRecursively(modelParams['trainLogDir'])
tf.gfile.MakeDirs(modelParams['trainLogDir'])
train(modelParams, epochNumber)
def main(argv=None): # pylint: disable=unused-argumDt
if (len(argv) < 3):
print("Enter 'model name' and 'iteration number'")
return
modelName = argv[1]
itrNum = int(argv[2])
if itrNum > 4 or itrNum < 0:
print('iteration number should only be from 1 to 4 inclusive')
return
# import json_maker, update json files and read requested json file
import Model_Settings.json_maker as json_maker
if not json_maker.recompile_json_files(modelName, itrNum):
return
jsonToRead = modelName + '_' + str(itrNum) + '.json'
print("Reading %s" % jsonToRead)
with open('Model_Settings/' + jsonToRead) as data_file:
modelParams = json.load(data_file)
modelParams = _set_control_params(modelParams)
print(modelParams['modelName'])
print('Rounds on datase = %.1f' % float(
(modelParams['trainBatchSize'] * modelParams['trainMaxSteps']) /
modelParams['numTrainDatasetExamples']))
print('lossFunction = ', modelParams['lossFunction'])
print('Train Input: %s' % modelParams['trainDataDir'])
#print('Test Input: %s' % modelParams['testDataDir'])
print('Train Logs Output: %s' % modelParams['trainLogDir'])
#print('Test Logs Output: %s' % modelParams['testLogDir'])
print('Train Warp Output: %s' % modelParams['warpedTrainDataDir'])
#print('Test Warp Output: %s' % modelParams['warpedTestDataDir'])
print('')
print('')
print('Train Main is built and Dataset is complied with n = 2 tuples!!!')
print('')
#if input("(Overwrite WARNING) Did you change logs directory? (y) ") != "y":
# print("Please consider changing logs directory in order to avoid overwrite!")
# return
#if tf.gfile.Exists(modelParams['trainLogDir']):
# tf.gfile.DeleteRecursively(modelParams['trainLogDir'])
#tf.gfile.MakeDirs(modelParams['trainLogDir'])
train(modelParams)
def main(argv=None): # pylint: disable=unused-argumDt
if (len(argv) < 3):
print("Enter 'model name' and 'epoch number to load / 0 for new'")
return
modelName = argv[1]
epochNumber = int(argv[2])
# import json_maker, update json files and read requested json file
import Model_Settings.json_maker as json_maker
if not json_maker.recompile_json_files(modelName):
return
jsonToRead = modelName + '.json'
print("Reading %s" % jsonToRead)
with open('Model_Settings/' + jsonToRead) as data_file:
modelParams = json.load(data_file)
global PHASE
modelParams['phase'] = PHASE
modelParams = _set_control_params(modelParams)
print(modelParams['modelName'])
print('Training steps = %.1f' % float(modelParams['trainMaxSteps']))
print('Rounds on datase = %.1f' % float(
(modelParams['trainBatchSize'] * modelParams['trainMaxSteps']) /
modelParams['numTrainDatasetExamples']))
print('lossFunction = ', modelParams['lossFunction'])
print('Train Input: %s' % modelParams['trainDataDir'])
#print('Test Input: %s' % modelParams['testDataDir'])
print('Train Logs Output: %s' % modelParams['trainLogDir'])
#print('Test Logs Output: %s' % modelParams['testLogDir'])
print('')
print('')
if epochNumber == 0:
#if input("(Overwrite WARNING) Did you change logs directory? (y) ") != "y":
# print("Please consider changing logs directory in order to avoid overwrite!")
# return
if tf.gfile.Exists(modelParams['trainLogDir']):
tf.gfile.DeleteRecursively(modelParams['trainLogDir'])
tf.gfile.MakeDirs(modelParams['trainLogDir'])
train(modelParams, epochNumber)
import os.path
import time
import logging
import json
import csv
import importlib
import numpy as np
from six.moves import xrange # pylint: disable=redefined-builtin
import tensorflow as tf
#import tensorflow.python.debug as tf_debug
PHASE = 'test'
# import json_maker, update json files and read requested json file
import Model_Settings.json_maker as json_maker
json_maker.recompile_json_files()
jsonToRead = 'GPUX_170301_ITR_B_4.json'
print("Reading %s" % jsonToRead)
with open('Model_Settings/'+jsonToRead) as data_file:
modelParams = json.load(data_file)
# import input & output modules
import Data_IO.data_input as data_input
import Data_IO.data_output as data_output
# import corresponding model name as model_cnn, specifed at json file
model_cnn = importlib.import_module('Model_Factory.'+modelParams['modelName'])
####################################################
FLAGS = tf.app.flags.FLAGS
tf.app.flags.DEFINE_integer('printOutStep', 10,
