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E bivae = cornac.models.BiVAECF(
E k=LATENT_DIM,
E encoder_structure=ENCODER_DIMS,
E act_fn=ACT_FUNC,
E likelihood=LIKELIHOOD,
E n_epochs=NUM_EPOCHS,
E batch_size=BATCH_SIZE,
E learning_rate=LEARNING_RATE,
E seed=SEED,
E use_gpu=torch.cuda.is_available(),
E verbose=True
E )
E
E with Timer() as t:
E bivae.fit(train_set)
E print("Took *** seconds for training.".format(t))
E ------------------
E
E ----- stderr -----
E
0%| | 0/500 [00:00<?, ?it/s]
E ----- stderr -----
E
0%| | 0/500 [00:00<?, ?it/s]
E ----- stderr -----
E
E ------------------
E
E ---------------------------------------------------------------------------
E AttributeError Traceback (most recent call last)
E Cell In[6], line 15
E 1 bivae = cornac.models.BiVAECF(
E 2 k=LATENT_DIM,
E 3 encoder_structure=ENCODER_DIMS,
E (...)
E 11 verbose=True
E 12 )
E 14 with Timer() as t:
E ---> 15 bivae.fit(train_set)
E 16 print("Took *** seconds for training.".format(t))
E
E File /azureml-envs/azureml_adf614c86c43311fb41235e[662](https://github.com/recommenders-team/recommenders/actions/runs/9745905406/job/26897451776#step:3:669)27b9b3/lib/python3.10/site-packages/cornac/models/bivaecf/recom_bivaecf.py:178, in BiVAECF.fit(self, train_set, val_set)
E 166 num_users = train_set.matrix.shape[0]
E 167 self.bivae = BiVAE(
E 168 k=self.k,
E 169 user_encoder_structure=[num_items] + self.encoder_structure,
E (...)
E 175 batch_size=self.batch_size,
E 176 ).to(self.device)
E --> 178 learn(
E 179 self.bivae,
E 180 train_set,
E 181 n_epochs=self.n_epochs,
E 182 batch_size=self.batch_size,
E 183 learn_rate=self.learning_rate,
E 184 beta_kl=self.beta_kl,
E 185 verbose=self.verbose,
E 186 device=self.device,
E 187 )
E 188 elif self.verbose:
E 189 print("%s is trained already (trainable = False)" % (self.name))
E
E File /azureml-envs/azureml_adf614c86c43311fb41235e66227b9b3/lib/python3.10/site-packages/cornac/models/bivaecf/bivae.py:201, in learn(bivae, train_set, n_epochs, batch_size, learn_rate, beta_kl, verbose, device, dtype)
E 199 for i_ids in train_set.item_iter(batch_size, shuffle=False):
E 200 i_batch = tx[i_ids, :]
E --> 201 i_batch = i_batch.A
E 202 i_batch = torch.tensor(i_batch, dtype=dtype, device=device)
E 204 # Reconstructed batch
E
E AttributeError: 'csc_matrix' object has no attribute 'A'
@miguelgfierro@anargyri This issue is actually from cornac, and I found cornac fixed the issue by setting numpy<2.0.0 and scipy<=1.13.1 (Jun 29, 2024) in the master branch of cornac which is supposed to be in the next version of it. So I think we can do the same thing and wait until they solve the issue. Please let me know if you have other suggestions.
Description
In which platform does it happen?
VM
How do we replicate the issue?
https://github.com/recommenders-team/recommenders/actions/runs/9745905406/job/26897451776
Expected behavior (i.e. solution)
Other Comments
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