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202306_OneFlow_libai_Report_On_master
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## Summary
In order to train this model, the following key details are required:
- Required `fwd`, `bwd`, `loss` and `opt` ops are supported e2e
- tenstorrent/tt-mlir#77
- tenstorrent/tt-mli…
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For large samples the summary graphs need to be zoomed in to be usable. This can lead to highlighted cases being outside of the viewable range
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sigma.js released [v2](https://github.com/jacomyal/sigma.js/releases/) with webgl support, which can handle much larger graphs. it'd be really nice to update this package to sigma.js v2.
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I have an RDF graph with a large number of numeric literals. When I execute the below SPARQL query, it works, but it seems to be scanning the entire graph as opposed to using an index to grab the lim…
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It would be helpful if Data.Graph provided utility functions for detecting cycles in graphs, which may be problematic and represent infinite loops. (As there is no standard 'utility' module I see for …
gwern updated
1 month ago
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### 🐛 Describe the bug
```
import torch
class my_module(torch.nn.Module):
def __init__(self):
super(my_module, self).__init__()
def forward(self, x):
F = x**3 - 2*x**2 -…
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#### Context
It has become clear that many users run complex suites with an inordinate number of tasks for *dependency* visualisation, which is currently only manifest with our 'graph' (node-link) …
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Generating random walks from a graph is really useful for a range of algorithms for large scale graphs. E.g. many node embedding algorithms rely on random walks from a node to generate the node's embe…
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Consider the following script.
```
import openturns as ot
distribution = ot.Normal()
sample = distribution.getSample(1000)
sample[0,0] = -5. # Outlier
ot.VisualTest_DrawQQplot(sample,distr…