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#neural-forecast
Title
# neural-forecast
p

Pascal Schindler

05/09/2023, 9:29 AM
Hey everyone! I often receive the following error while training AutoNHITS
IntegerGreaterThan(lower_bound=0)
with the following config: What are the reasosns?
Copy code
horizon = 60

config_nhits = {
    "input_size": tune.choice([14 ,28, 28*2, 28*3, 28*5, 2 * horizon]),              # Length of input window
    "n_blocks": 5*[1],                                              # Length of input window
    "mlp_units": 5 * [[512, 512]],                                  # Length of input window
    "interpolation_mode": tune.choice(['linear']), 
    "n_pool_kernel_size": tune.choice([5*[1], 5*[2], 5*[4],         
                                      [8, 4, 2, 1, 1], [16, 8, 1]]),            # MaxPooling Kernel size
    "n_freq_downsample": tune.choice([[8, 4, 2, 1, 1],
                                      [1, 1, 1, 1, 1],
                                      [168, 24, 1], 
                                      [24, 12, 1], 
                                      [1, 1, 1]]),            # Interpolation expressivity ratios
    "learning_rate": tune.loguniform(1e-4, 1e-2),                   # Initial Learning rate
    "scaler_type": tune.choice([None]),                             # Scaler type
    "max_steps": tune.choice([1000]),                               # Max number of training iterations
    "batch_size": tune.choice([16, 32, 64, 128, 256, 512]),                  # Number of series in batch
    "windows_batch_size": tune.choice([32, 64, 128, 256, 512, 1024, 2048]),       # Number of windows in batch
    "random_seed": tune.randint(1, 20), 
    "scaler_type": tune.choice(["robust", None]),                            # Random seed
    "hist_exog_list": ["week_day", "month", "trends"],
    "futr_exog_list": ["week_day", "month"]
}
I am using the Poisson distribution
c

Cristian (Nixtla)

05/09/2023, 2:21 PM
Hi @Pascal Schindler. I see 3 bugs in the code: 1. You have defined
scaler_type
two times 2. If you want to use 5 stacks, you should also modify
stack_types
to 5*["identity"] 3. Some
n_freq_downsample
entries have 3 components, they should all have 5 (it has to match number of stacks).