def show_multi_plot(y_bundle, batch_size_):
indep_test_axis = []
for i in range(batch_size_):
indep_test_axis.append(i)
p = PlotUtil("Accuracy Results on MNIST Dataset",
np.array(indep_test_axis), "Epoch iterations", "Accuracy")
p.show_plot(y_bundle)
test_accuracies = np.array(test_accuracies)
y = YaxisBundle(np.array(test_losses), "loss", "b")
y_bundle.append(y)
y = YaxisBundle(np.array(test_accuracies), "accuracy", "g")
y_bundle.append(y)
#p.show_plot(y_bundle)
if config.matplot_lib_for_single_ybundle:
if config.matplot_lib_for_accuracy:
return y_bundle[1]
else:
return y_bundle[0]
return y_bundle
if __name__ == '__main__':
if config.matplot_lib_enabled:
indep_test_axis = []
for i in range(config.training_epochs):
indep_test_axis.append(i)
p = PlotUtil("title", np.array(indep_test_axis), "x_label", "y_label")
y_bundle = run_with_config(config)
p.show_plot(y_bundle)
else:
run_with_config(config)
y = YaxisBundle(np.array(test_losses), "loss", "b")
y_bundle.append(y)
y = YaxisBundle(np.array(test_accuracies), "accuracy", "g")
y_bundle.append(y)
#p.show_plot(y_bundle)
if config.matplot_lib_for_single_ybundle:
if config.matplot_lib_for_accuracy:
return y_bundle[1]
else:
return y_bundle[0]
return y_bundle
if __name__ == '__main__':
if config.matplot_lib_enabled:
indep_test_axis = []
for i in range(config.training_epochs):
indep_test_axis.append(i)
p = PlotUtil("Highway LSTM(3 layers) on MNIST",
np.array(indep_test_axis), "Epoch iterations",
"Loss or Accuracy")
y_bundle = run_with_config(config)
p.show_plot(y_bundle)
else:
run_with_config(config)
y = YaxisBundle(np.array(test_losses), "loss", "b")
y_bundle.append(y)
y = YaxisBundle(np.array(test_accuracies), "accuracy", "g")
y_bundle.append(y)
#p.show_plot(y_bundle)
if config.matplot_lib_for_single_ybundle:
if config.matplot_lib_for_accuracy:
return y_bundle[1]
else:
return y_bundle[0]
return y_bundle
if __name__ == '__main__':
if config.matplot_lib_enabled:
indep_test_axis = []
for i in range(config.training_epochs):
indep_test_axis.append(i)
p = PlotUtil("Residual LSTM(3 layers) on HAR",
np.array(indep_test_axis), "Epoch iterations",
"Loss or Accuracy")
y_bundle = run_with_config(config)
p.show_plot(y_bundle)
else:
run_with_config(config)
def show_multi_plot(y_bundle, batch_size_):
indep_test_axis = []
for i in range(batch_size_):
indep_test_axis.append(i)
p = PlotUtil("title", np.array(indep_test_axis), "x_label", "y_label")
p.show_plot(y_bundle)
y = YaxisBundle(np.array(test_losses), "loss", "b")
y_bundle.append(y)
y = YaxisBundle(np.array(test_accuracies), "accuracy", "g")
y_bundle.append(y)
#p.show_plot(y_bundle)
if config.matplot_lib_for_single_ybundle:
if config.matplot_lib_for_accuracy:
return y_bundle[1]
else :
return y_bundle[0]
return y_bundle
if __name__ == '__main__':
if config.matplot_lib_enabled:
indep_test_axis = []
for i in range(config.training_epochs):
indep_test_axis.append(i)
p = PlotUtil("Deep LSTM(3 layers) on UCR ElectricDevices", np.array(indep_test_axis), "Epoch iterations", "Loss or Accuracy")
y_bundle = run_with_config(config)
p.show_plot(y_bundle)
else:
run_with_config(config)