text: import state_space_parameters as ssp
  
  MODEL_NAME = 'cifar10'
  
  #Re-Inference Times
  INFERENCE_TIMES = 5
  #Inference time constrain in ms (milliseconds)
  INFERENCE_CONSTRAIN = ssp.inference_constrain
  
  # Number of output neurons
  NUM_CLASSES = 10                                                                    # Number of output neurons
  
  #Final Image Size
  IMAGE_HEIGHT = 32                                                                   # Final Image Height NOTE: code only supports square images right now o_O
  IMAGE_WIDTH = 32                                                                    # Final Image Width  NOTE: code only supports square images right now o_O
  
  #Batch Queue parameters
  TRAIN_BATCH_SIZE = 128                                                              # Batch size for training
  NUM_EXAMPLES_PER_EPOCH_FOR_TRAIN = 45000                                            # Number of training examples
  NUM_ITER_PER_EPOCH_TRAIN = NUM_EXAMPLES_PER_EPOCH_FOR_TRAIN / TRAIN_BATCH_SIZE      
  EVAL_BATCH_SIZE = 100                                                               # Batch size for validation
  NUM_EXAMPLES_PER_EPOCH_FOR_EVAL = 5000                                              # Number of validation examples
  NUM_ITER_TO_TRY_LR = NUM_ITER_PER_EPOCH_TRAIN                                       # Number of iterations to try learning rate (based on ACC_THRESHOLD)
                                                                                      # Please make an integer multiple of NUM_ITER_PER_EPOCH_TRAIN
  
  TEST_INTERVAL_EPOCHS = 1                                                            # Num epochs to test on, should really always be 1                                      
  MAX_EPOCHS = 20                                                                     # Max number of epochs to train model
  MAX_STEPS = MAX_EPOCHS * NUM_ITER_PER_EPOCH_TRAIN                                   
  
  
  #Training Parameters
  OPTIMIZER = 'Adam'                                                                  # Optimizer (should be in caffe format string)
  MOMENTUM = 0.9                                                                      # Momentum
  WEIGHT_DECAY_RATE = 0.0005                                                          # Weight decay factor   
  
  
  # Learning Rate
  INITIAL_LEARNING_RATES = [0.001 * (0.4**i) for i in range(5)]                       # List of initial learning rates to try before giving up on model
  ACC_THRESHOLD = 0.15                                                                # Model must achieve greater than ACC_THRESHOLD performance in NUM_ITER_TO_TRY_LR or it is killed and next initial learning rate is tried.
  LEARNING_RATE_DECAY_FACTOR = 0.2                                                    # Learning rate decay factor.
  NUM_EPOCHS_PER_DECAY = 5                                                            # Epochs after which learning rate decays.
  LR_POLICY = "step"                                                                  # Caffe Default
  
  # Print every?
  DISPLAY_ITER = 100                                                                  # Number of batches to print between
  SAVE_EPOCHS = 1                                                                     # Number of epochs between snapshots
  
  MIRROR = True                                                                       # Randomly mirror images during training
  CROP = False                                                                        # Randomly Crop input images to final image size
  GCN_APPROX = False                                                                  # subtract 128 and scale
  #Train files
  TRAIN_FILE = '/path/to/train/lmdb'                                                  # Path to training lmdb file -- YOU NEED TO CHANGE THIS
  VAL_FILE = '/path/to/train/lmdb'                                                    # Path to validation lmdb file -- YOU NEED TO CHANGE THIS
  
  CAFFE_ROOT = '/path/to/caffe/instillation/directory'                                # Path to caffe root directory -- YOU NEED TO CHANGE THIS
  
  # For training caffe checkpoints
  CHECKPOINT_DIR = 'trained_models/' + MODEL_NAME                                     # Path to where model snapshots are saved
  