ValueError: Not all estimated parameters are finite, your model may have diverged

Hi,

I’m running this very simple code:

def csr_values_analysis(values):
   num_zeros = 0
   num_ones = 0
   num_other = 0

   for v in values:
       if v == 0:
           num_zeros += 1
       elif v == 1:
           num_ones += 1
       else:
           num_other += 1

   return num_zeros, num_ones, num_other


print("Reading user_features.npz")
with open("/path/to/user_features.npz", "rb") as in_file:
    user_features_csr = sp.load_npz(in_file)
    print("User features read, shape: {}".format(user_features_csr.shape))
    print("Data values analysis: zeros: %i, ones: %i, other: %i" % csr_values_analysis(user_features_csr.data))

print("Reading item_features.npz")
with open("/path/to/item_features.npz", "rb") as in_file:
    item_features_csr = sp.load_npz(in_file)
    print("Item features read, shape: {}".format(item_features_csr.shape))
    print("Data values analysis: zeros: %i, ones: %i, other: %i" % csr_values_analysis(item_features_csr.data))

print("Reading interactions.npz")
with open("/path/to/interactions.npz", "rb") as in_file:
    interactions_csr = sp.load_npz(in_file)
    print("Interactions read, shape: {}".format(interactions_csr.shape))
    print("Data values analysis: zeros: %i, ones: %i, other: %i" % csr_values_analysis(interactions_csr.data))
    interactions_coo = interactions_csr.tocoo()

# Run lightfm

print("Running lightfm...")
model = LightFM(loss='warp')
model.fit(interactions_coo, user_features=user_features_csr, item_features=item_features_csr, epochs=20, num_threads=2, verbose=True)

With the following output:

Reading user_features.npz
User features read, shape: (827568, 105)
Data values analysis: zeros: 0, ones: 3153032, other: 0
Reading item_features.npz
Item features read, shape: (67339359, 36)
Data values analysis: zeros: 0, ones: 25259081, other: 0
Reading interactions.npz
Interactions read, shape: (827568, 67339359)
Data values analysis: zeros: 0, ones: 172388, other: 0
Running lightfm...
Epoch 0
Traceback (most recent call last):
  File "training.py", line 92, in <module>
    model.fit(interactions_coo, user_features=user_features_csr, item_features=item_features_csr, epochs=20, num_threads=2, verbose=True)
  File "/usr/lib64/python3.6/site-packages/lightfm/lightfm.py", line 479, in fit
    verbose=verbose)
  File "/usr/lib64/python3.6/site-packages/lightfm/lightfm.py", line 578, in fit_partial
    self._check_finite()
  File "/usr/lib64/python3.6/site-packages/lightfm/lightfm.py", line 413, in _check_finite
    raise ValueError("Not all estimated parameters are finite,"
ValueError: Not all estimated parameters are finite, your model may have diverged. Try decreasing the learning rate or normalising feature values and sample weights

All my Scipy matrices are normalized (i.e. the values are 0 or 1).

I’ve tried to change the learning schedule and the learning rate with no results.

I’ve checked this only occurs when I add the item features to the equation. There is no error when running lightfm only with interactions, or intereactions + user features.

AFAIK, I’ve installed the latest version:

$ pip freeze | grep lightfm
lightfm==1.15

Any idea? Thanks!

[maciejkula]

That’s some great debugging! It may be useful to add this cause as another suggestion in the error message.

[SimonCW]

Hi @dbalabka , the comments can still be discovered in the closed issues. The idea for closing issues that haven’t seen much activity, is to keep the focus on issues people are willing to work on and contribute. I added the enhancement label to make it easier to find in the future.