ssd-tensorflow | A Single Shot MultiBox Detector in TensorFlow | Machine Learning library

Since it does not have a parameter to set the value you want you would have to go into the source code and find where the batch size and test steps are set for the training set. The values you use for training batch size and training steps if determined by your model type and the size of your training data. For example if your were say classifying images and the image shape is (64,64,3) you can probably set a fairly large batch size without getting a resource exhaust error. Say batch_size=100. If your image shape is say (500, 500, 3) then you need a much smaller batch size say batch_size=20. Usually in model.fit you do not need to specify the value of steps. Leave it as None and model.fit will calculate the steps internally. Same is true for model.predict. If you really need to calculate the steps say for the test set you want to go through the test set exactly once. For this to happen batch_size X steps= number of samples in the test set. The code below will calculate that for you. Value bmax is a value you set as the maximum allowable batch_size based on the above discussion. For example below assume there are 10,000 samples in the test set.