Reporting a bug

• [x]

Problem:

_catboost.pyx in _catboost._set_features_order_data_pd_data_frame()

_catboost.pyx in _catboost.get_cat_factor_bytes_representation()

CatBoostError: Invalid type for cat_feature[non-default value idx=1,feature_idx=336]=2.0 : cat_features must be integer or string, real number values and NaN values should be converted to string.

Could you also print a feature name, not o

Description

https://numpy.org/doc/stable/reference/generated/numpy.corrcoef.html

https://docs.cupy.dev/en/stable/reference/generated/cupy.corrcoef.html

Seems args are different

Additional Information

dtype argument added in NumPy version 1.20.

The use of an mr parameter in inplace_bitmask_and, which calls inplace_bitmask_binop, is a little misleading. The allocations there are always temporary and are not part of the return value. It is only used for a few temporary arrays/scalars: https://github.com/rapidsai/cudf/blob/1f8a03e69704562dfac38de40b7172650280c6ea/cpp/include/cudf/detail/null_mask.cuh#L169-L171

It should be possible

请问可以直接training tmfile出来吗? 因为tengine-convert-tool covert 会有error

tengine-lite library version: 1.4-dev
Get input tensor failed

或是有例子能training出下面tmfile 呢?
![Screenshot from 2021-05-27 07-01-46](https://user-images.githubusercontent.com/40915044/11

I can't tell where the problem is. Why does the version of Thrust that I get with stdpar=gpu work, whereas the version from GitHub doesn't?

Thanks

MCVE

#include <thrust/universal_vector.h>

thrust::universal_vector<float> m_x ;

void AllocateNodePersistent(int numNode)
{
  m_x.resize(numNode);
}

It works with stdpar=gpu

$ nvc++ -std=c++17 -stdpar=gpu -c bug.

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.

你好，请问怎么装载 ONNX 模型，目前只看到 Oneflow->ONNX 工具，没有找到 ONNX->Oneflow 工具。

Location of incorrect documentation
Provide links and line numbers if applicable.](https://docs.rapids.ai/api/cuml/stable/api.html#cuml.cluster.HDBSCAN)

Describe the problems or issues found in the documentation
the metric default is euclidean but in the docs it states metric string or callable, optional (default='minkowski')

Suggested fix for documentation
good to include

Hey everyone!

mapd-core-cpu is already available on conda-forge (https://anaconda.org/conda-forge/omniscidb-cpu)

now we should add some instructions on the documentation.

at this moment it is available for linux and osx.

some additional information about the configuration:

1. for now, always install omniscidb-cpu inside a conda environment (also it is a good practice), eg:

In order to test manually altered IR, it would be nice to have a --skip-compilation flag for futhark test, just like we do for futhark bench.