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:
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.
I am working on creating a WandbCallback for Weights and Biases. I am glad that CatBoost has a callback system in place but it would be great if we can extend the interface.
The current callback only supports after_iteration that takes info. Taking inspiration from XGBoost callback system it would be great if we can have before iteration that takes info, before_training, and `after
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?)
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
dtype argument added in NumPy version 1.20.
Is your feature request related to a problem? Please describe.
The current value of alpha value is hardcoded in many places to 0.05.
Describe the solution you'd like
Take this as a setup argument and use it everywhere for consistency. The default value can be 0.05.
Is your feature request related to a problem? Please describe.
While reviewing PR #9817 to introduce DataFrame.diff, I noticed that it is restricted to acting on numeric types.
A time-series diff is probably a very common user need, if provided a series of timestamps and seeking the durations between observations.
Pandas supports diffs on non-numeric types like timestamps:
Description
I'm trying to port an existing application using GLSL to wgpu, so I have existing complex shaders I want to modify to be compatible. While trying to get them working, I have found that if the shader has (something which naga considers) a syntax error, wgpu will panic via .unwrap():
https://github.com/gfx-rs/wgpu/blob/326af60df8623e93b47a0de090e6cb449c8507f5/wgpu/src/bac
1.系统环境：
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.
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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)
A simple check on chang