Reference from TensorFlow: https://www.tensorflow.org/api_docs/cc/class/tensorflow/ops/matrix-band-part

This op is used by the Music Transformer model.

Howdy folks,

GPyTorch provides Gaussian likelihood objects for fixed noise (FixedNoiseGaussianLikelihood) and for multi-task models (MultitaskGaussianLikelihood). I was wondering if someone could provide me some guidance on how to get a fixed noise multi-task Gaussian likelihood?

Thanks in advance

Galto

There are several internal things that make Emu's performance potentially suboptimal. This issue is a place to discuss them.

• wgpu::Device::poll is used here and right now it blocks in an async context. I'm not sure what the solution is but there is some discussion [here](gfx-rs/wgpu-rs#214 (comment)

Report incorrect documentation

Location of incorrect documentation

• Source code (for help(bc.BlazingContext))
• https://docs.blazingdb.com/docs (no API section??)

Describe the problems or issues found in the documentation

When using cudf & bc together, unclear if/how the rapids memory manager gets shared and how to separately+jointly control. Does blazing get its own? Wh

Example:

>>> import numpy as np

>>> np.arctanh(np.array([0], dtype='int8')).dtype
dtype('float16')

>>> np.arctanh(np.array([0], dtype='int16')).dtype
dtype('float32')

>>> np.arctanh(np.array([0], dtype='int32')).dtype
dtype('float64')

vs.

>>> import bohrium as bh

>>> bh.arctanh(bh.array([0], dtype='int8')).dtype
dtype('float32')

>>> bh.arctanh

It seems that there is a bug with the call to gpufit within Matlab when including the user_info parameter. Using the included linear_1d model (which utilizes the user_info parameter), I created a simple program in Matlab to model the equation y=x from x=0 to x=10 and called gpufit on the data. This should return the parameters 0 and 1, but results in 4.3467 and 0.8711 instead.

Additionally, if

I have seen the new BERT-related changes and I'm trying to use this model. Will be the documentation updated with the BERT parameters and an example of pre-training or fine-tuning?

I will happily add this to the documentation, but I need help figuring out how to use it ;).

Basically I want to extract a quadrilateral region from an image and perspective transform it to be a rectangle. Per my other open issue, I've been pointed to the undocumented gm.perspectiveProjection.

Per this operation
https://github.com/PeculiarVentures/GammaCV/blob/8ffa723ef54b297cda8ffb5b21b027

Documentation on how to use the software is currently missing.

Some links we could share:

Vahana VR introduction video:
https://www.youtube.com/watch?v=nR0qD2ELInU

3rd party Vahana tutorials:
https://www.youtube.com/watch?v=rDXbYDr4Pm8
https://www.youtube.com/watch?v=suQvrlTp-iM

VideoStitch Studio PDF user guide:
https://docplayer.net/64441394-Videostitch-studio-v2-3...
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