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steps_per_epoch = round(data_loader.num_train_examples)//BATCH_SIZE | |
validation_steps = 20 | |
loss1, accuracy1 = vgg16.evaluate(data_loader.validation_batches, steps = 20) | |
loss2, accuracy2 = googlenet.evaluate(data_loader.validation_batches, steps = 20) | |
loss3, accuracy3 = resnet.evaluate(data_loader.validation_batches, steps = 20) | |
print("--------VGG16---------") | |
print("Initial loss: {:.2f}".format(loss1)) | |
print("Initial accuracy: {:.2f}".format(accuracy1)) | |
print("---------------------------") | |
print("--------GoogLeNet---------") | |
print("Initial loss: {:.2f}".format(loss2)) | |
print("Initial accuracy: {:.2f}".format(accuracy2)) | |
print("---------------------------") | |
print("--------ResNet---------") | |
print("Initial loss: {:.2f}".format(loss3)) | |
print("Initial accuracy: {:.2f}".format(accuracy3)) | |
print("---------------------------") |
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