76 lines
3.6 KiB
Python
76 lines
3.6 KiB
Python
#!/usr/bin/env python
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import sys
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import PySimpleGUI as sg
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def MachineLearningGUI():
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sg.set_options(text_justification='right')
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flags = [[sg.CB('Normalize', size=(12, 1), default=True), sg.CB('Verbose', size=(20, 1))],
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[sg.CB('Cluster', size=(12, 1)), sg.CB(
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'Flush Output', size=(20, 1), default=True)],
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[sg.CB('Write Results', size=(12, 1)), sg.CB(
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'Keep Intermediate Data', size=(20, 1))],
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[sg.CB('Normalize', size=(12, 1), default=True),
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sg.CB('Verbose', size=(20, 1))],
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[sg.CB('Cluster', size=(12, 1)), sg.CB(
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'Flush Output', size=(20, 1), default=True)],
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[sg.CB('Write Results', size=(12, 1)), sg.CB('Keep Intermediate Data', size=(20, 1))], ]
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loss_functions = [[sg.Rad('Cross-Entropy', 'loss', size=(12, 1)), sg.Rad('Logistic', 'loss', default=True, size=(12, 1))],
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[sg.Rad('Hinge', 'loss', size=(12, 1)),
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sg.Rad('Huber', 'loss', size=(12, 1))],
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[sg.Rad('Kullerback', 'loss', size=(12, 1)),
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sg.Rad('MAE(L1)', 'loss', size=(12, 1))],
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[sg.Rad('MSE(L2)', 'loss', size=(12, 1)), sg.Rad('MB(L0)', 'loss', size=(12, 1))], ]
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command_line_parms = [[sg.Text('Passes', size=(8, 1)), sg.Spin(values=[i for i in range(1, 1000)], initial_value=20, size=(6, 1)),
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sg.Text('Steps', size=(8, 1), pad=((7, 3))), sg.Spin(values=[i for i in range(1, 1000)], initial_value=20, size=(6, 1))],
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[sg.Text('ooa', size=(8, 1)), sg.Input(default_text='6', size=(8, 1)), sg.Text('nn', size=(8, 1)),
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sg.Input(default_text='10', size=(10, 1))],
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[sg.Text('q', size=(8, 1)), sg.Input(default_text='ff', size=(8, 1)), sg.Text('ngram', size=(8, 1)),
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sg.Input(default_text='5', size=(10, 1))],
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[sg.Text('l', size=(8, 1)), sg.Input(default_text='0.4', size=(8, 1)), sg.Text('Layers', size=(8, 1)),
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sg.Drop(values=('BatchNorm', 'other'))], ]
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layout = [[sg.Frame('Command Line Parameteres', command_line_parms, title_color='green', font='Any 12')],
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[sg.Frame('Flags', flags, font='Any 12', title_color='blue')],
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[sg.Frame('Loss Functions', loss_functions,
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font='Any 12', title_color='red')],
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[sg.Submit(), sg.Cancel()]]
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sg.set_options(text_justification='left')
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window = sg.Window('Machine Learning Front End',
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layout, font=("Helvetica", 12))
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button, values = window.read()
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window.close()
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print(button, values)
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def CustomMeter():
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# layout the form
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layout = [[sg.Text('A custom progress meter')],
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[sg.ProgressBar(1000, orientation='h',
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size=(20, 20), key='progress')],
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[sg.Cancel()]]
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# create the form`
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window = sg.Window('Custom Progress Meter', layout)
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progress_bar = window['progress']
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# loop that would normally do something useful
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for i in range(1000):
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# check to see if the cancel button was clicked and exit loop if clicked
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event, values = window.read(timeout=0, timeout_key='timeout')
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if event == 'Cancel' or event == None:
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break
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# update bar with loop value +1 so that bar eventually reaches the maximum
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progress_bar.update_bar(i+1)
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# done with loop... need to destroy the window as it's still open
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window.CloseNonBlocking()
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if __name__ == '__main__':
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CustomMeter()
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MachineLearningGUI()
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