Comments (3)
Hi, Sorry I'll only have time to fix this next week.
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Try manually making the NX graph into a CSRGraph by making G = cg.csrgraph(G). See if it crashes there.
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Try running the code in a normal .py file and monitor the RAM usage
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If the RAM usage is normal try running GGVec for one epoch with the smallest possible settings (embedding dimensions 1 or 2, negative_ratio = 0, etc.)
Please report back what you find
from nodevectors.
So the very first step of making a networkx graph object itself fails
from nodevectors.
RIght, you're running out of RAM making the networkX object then.
This is because networkX takes a large amount of memory per edge and per node, so trying to make a 7m edge graph on a machine without >1TB of RAM will crash the computer from lack of memory.
Since this particular issue is with networkX I'll close it (The other two are on my side).
from nodevectors.
Related Issues (20)
- Embedding a VERY LARGE graph, upcoming? HOT 2
- When saving large graph, creating a temporary folder will cause the system disk resources to be exhausted. HOT 1
- Issue with gensim 4.0.0+ HOT 3
- is it possible to split n2v to generate walks only? HOT 4
- node2vec uses CBOW instead of skip-gram HOT 4
- Setting value of seed to make Node2vec embedding repeatable. HOT 1
- Print training progression (node2vec)? HOT 1
- Continue fitting process HOT 2
- Has node2vec implementation been updated to use skip-gram as default? HOT 3
- About painting HOT 1
- defining random state or seed option parameters HOT 3
- Why is generating walks so slow with non-default parameters? HOT 3
- word2vec parameters changed HOT 3
- Problem with underlying Word2vec HOT 1
- G.mat got an asymmetric sparse matrix
- ProNE option: "inconsistent shapes" error
- Node2Vec:About the return_weight and neighbor_weight
- ProNE multithread HOT 1
- NetworkX 3.0 remove adj_matrix in version HOT 1
- Old parameter shows up in Word2Vec call
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from nodevectors.