Machine learning
Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
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>>> a = torch.randn(3,2,0,2)
>>> torch.flip(a, dims=())
tensor([], size=(3, 2, 0, 2))
>>> b = a.cuda()
>>> torch.flip(b, dims=())
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
IndexError: flip dims size out of range, got flip dims size=0
Describe the bug
In grid_to_graph, you expect the vertices to correspond to the implicit order defined by the mask. This is not always the case, due to the occurrence of isolated vertices that are dismissed in the reindexing of the vertices.
Steps/Code to Reproduce
import numpy as np
from sklearn.feature_extraction import grid_to_graph
mask = np.zeros((2, 3)).ast
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Reference: JuliaLang/julia#38892 (comment)
We accidentally exported HTML
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Currently many more Python projects like dask and optuna are using Python type hints. With the Python package of xgboost gaining more and more features, we should also adopt mypy as a safe guard against some type errors and for better code documentation.
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