gpu

🚀 The feature, motivation and pitch

After the revert of pytorch/pytorch@7cf9b94 we've identified a need to add a lint that checks file names to ensure that they're compatible with Windows machines.

Observed error: (from example commit)

Error: error: invalid path 'test/test_ops_gradients.py '

A simple check on chang

The taichi.lang.util.warning function just prints the warning without consulting the current state of pythons standard library warnings module.

For example:

import warnings
import taichi as ti

with warnings.catch_warnings():
    warnings.simplefilter("ignore

At this moment relu_layer op doesn't allow threshold configuration, and legacy RELU op allows that.
We should add configuration option to relu_layer.

I want to preemptively start this thread to survey for suggestions. A cursory search lead me to this promising repository https://github.com/enigo-rs/enigo

Since closing the window is a common point of failure, that will be the focus for the first pass of testing as I learn how to use the library.

Components for testing:

• bridge
• editor
• renderer
• settings
• wind

Hi ,

I have tried out both loss.backward() and model_engine.backward(loss) for my code. There are several subtle differences that I have observed , for one retain_graph = True does not work for model_engine.backward(loss) . This is creating a problem since buffers are not being retained every time I run the code for some reason.

Please look into this if you could.

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

Our users are often confused by the output from programs such as zip2john sometimes being very large (multi-gigabyte). Maybe we should identify and enhance these programs to output a message to stderr to explain to users that it's normal for the output to be very large - maybe always or maybe only when the output size is above a threshold (e.g., 1 million bytes?)

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.

https://github.com/brendangregg/FlameGraph

Currently the checks reside in the time series module. It would be better to move them to base class so that all task types can benefit from it.

O, we went with a private method for now. Currently, it is in the time series module only. Later we may add it to the base class itself.

Originally posted by @ngupta23 in pycaret/pycaret#2354 (comment)

We have two similar methods with different names:

• structs_column_view::get_sliced_child
• structs_column_device_view::sliced_child

We should rename structs_column_view::get_sliced_child to structs_column_view::sliced_child to align with the other method and avoid unnecessary get_ prefixes as is the normal practice in libcudf.

_Originally posted by @bdice in https://github.com/r

Spec PR: gpuweb/gpuweb#2689

环境

1.系统环境：

• Ubuntu 20.04.2 LTS x86_64
• GLIBCXX: 3.4.28 (libstdc++.so.6.0.28)
• GPU:
  

2.MegEngine版本：1.6.0rc1
3.python版本：Python 3.8.10

The program stuck at net.load when I was trying to use the MegFlow. I wait for more than 10min and there is no sign of finishing it.