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Sep 2, 2020 - Makefile
cuda
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Sep 12, 2020 - Shell
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Problem:
catboost version: 0.23.2
Operating System: all
Tutorial: https://github.com/catboost/tutorials/blob/master/custom_loss/custom_metric_tutorial.md
Impossible to use custom metric (С++).
Code example
from catboost import CatBoost
train_data = [[1, 4, 5, 6],
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Sep 12, 2020 - C++
Current implementation of join can be improved by performing the operation in a single call to the backend kernel instead of multiple calls.
This is a fairly easy kernel and may be a good issue for someone getting to know CUDA/ArrayFire internals. Ping me if you want additional info.
There are (at least) two ways in which the reinterpret_cast is misused:
- Used instead of
static_cast:
https://github.com/rapidsai/cudf/blob/f7fbc1160b17b969db2708e0cf6033d3db9fc1cf/cpp/src/io/avro/avro_gpu.cu#L95
static cast should be used to cast fromvoid*. - The use causes undefined behavior:
https://github.com/rapidsai/cudf/blob/f7fbc1160b17b969db2708e0cf6033d3db9fc1cf/cpp/src/io
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Report needed documentation
We do not have documentation specifying the different treelite Operator values that FIL supports. (https://github.com/dmlc/treelite/blob/46c8390aed4491ea97a017d447f921efef9f03ef/include/treelite/base.h#L40)
Report needed documentation
https://github.com/rapidsai/cuml/blob/branch-0.15/cpp/test/sg/fil_test.cu
There are multiple places in the fil_test.cu file
I often use -v just to see that something is going on, but a progress bar (enabled by default) would serve the same purpose and be more concise.
We can just factor out the code from futhark bench for this.
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Apr 6, 2019 - Jupyter Notebook
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Thank you for this fantastic work!
Could it be possible the fit_transform() method returns the KL divergence of the run?
Thx!
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