PyTensor Scan Dimension Mismatch

Hi there, I’ve been developing a model for user based repetition wear and restoration effects in online advertising. I’m having some confusion on the dimensions mismatch error within pytensor.scan:

Here’s some of the code excerpt:

coords = {"user_ids": imps_df.index, "weeks": imps_df.columns}

with pm.Model(coords=coords) as model1:
    imps = pm.MutableData("imps", imps_df, dims={"user_ids", "weeks"})
    wks_since_last_imp = pm.MutableData("wks_since_last_imp", wks_since_last_imp_df, dims={"user_ids", "weeks"})

    #repetition wear
    delta_1 = pm.Uniform("delta_1", lower=0, upper=1)
    #restoration effects - Universal
    rho_1 = pm.Uniform("rho_1", lower=0, upper=1)
    #geometric decay rate
    adstock_decay = pm.Uniform("adstock_decay", lower=.4, upper=.8)
    ## Add restoration and wear to adstock transformation
    R1 = pm.Deterministic("r1", (rho_1*wks_since_last_imp)/(1+rho_1*wks_since_last_imp))
    wearout = pm.Deterministic("wearout", 1 - delta_1**imps)
    eit = pm.Deterministic("eit", advertising_effect*(1 - wearout + R1 * wearout))
    # Recursively Compute Adstock Efficiently via pytensor trace
    adstock0 = pt.zeros(nusers) 

    # def update_adstoc(eit, prior_result, adstock_decay):

    adstock, __ = pytensor.scan(fn=lambda eit, prior_result, adstock_decay: prior_result * adstock_decay + eit,
                                outputs_info=adstock0, #initialize results adstock is equal to eit at wk 1
                                sequences = [eit],

My model graph lines up with what I’m envisioning:

But am getting the error:
ValueError: Input dimension mismatch: (input[0].shape[0] = 10000, input[2].shape[0] = 45

I believe this is coming from the prior_value supplied through the scan function. I want to make sure the function is looking back to the adstock from previous weeks not of previous users. Input dataframe was indexed by user_id with columns for successive weeks.

Any thoughts? Do I just need to transpose the input features to the scan function? Appreciate the active community and help moving further along.

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Scan iterates over the leftmost dimensions of sequences

Thanks! That makes sense based on the error message I’m seeing where the value error is showing slicing the 0th index of shape:

ValueError: Input dimension mismatch: (input[1].shape[0] = 45, input[4].shape[0] = 10000)

Still hitting some convergence issues but making progress

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