Comments (3)
Thank you for finding this! Did you encounter any issues with saving the model due to keeping the cluster keys as np.int64? Or was there another use case for which this is an issue?
from concept.
Hi, I've simply tried to json.dump() the cluster keys in an attempt to store all the gritty details from the analysis to inspect and save for later. What surprised me was that even default=str
failed to convince json to serialize the dict. That's when I found out that the default apparently (and somewhat sensibly) only applies to values, and having np.int64 as keys is not within the json spec.
from concept.
Ah, right, that makes sense! I am not entirely sure but I do not think it should be any problem to cast them as regular int
in that specific function. It seems that cluster
in representative_images[cluster]
is derived from items in self.cluster_labels
which I think can be regular int
.
from concept.
Related Issues (19)
- Index Error: index out of bounds error for visualize concepts HOT 7
- OSError: [Errno 24] Too many open files: 'photos/icnZ2R8PcDs.jpg' HOT 3
- ValueError: operands could not be broadcast together with shapes (4,224,224) (3,) HOT 9
- Pandas key error during model fitting HOT 9
- Multilingual support HOT 3
- TypeError: __init__() got an unexpected keyword argument 'cachedir' HOT 1
- How can we get probabilities for all clusters in transform function? HOT 3
- Saving the model HOT 2
- AttributeError: 'CountVectorizer' object has no attribute 'get_feature_names' HOT 5
- discussion on different concepts results HOT 2
- sentence-transformers version HOT 2
- AttributeError: 'ConceptModel' object has no attribute 'image_cluster_df' HOT 3
- TypeError: Cannot use scipy.linalg.eigh for sparse A with k >= N. Use scipy.linalg.eigh(A.toarray()) or reduce k. HOT 1
- TypeError: Cannot use scipy.linalg.eigh for sparse A with k >= N. Use scipy.linalg.eigh(A.toarray()) or reduce k. HOT 1
- Questions HOT 4
- Question about the Function transform HOT 7
- Saving the model HOT 2
- Using GPU while processing concepts HOT 2
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from concept.