gpu

🚀 Feature

Teach torch.Tensor.scatter_ to handle index.size(d) > src.size(d).

Motivation

Currently, torch.Tensor.scatter_ requires index.size(d) <= src.size(d) for all dimensions d, unless src is float-valued. This constraint seems artificial.

import math
import torch

device = 'cuda'  # fail

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.

It would be great to have FBeta, F2, or F0.5 metrics to be implemented without the need for a custom metric class defined by user.

catboost version: 0.26

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 think we should drop the many references to ancient John or Jumbo versions, and simply describe the current Jumbo version.

The depth configuration defined on this line:

https://github.com/intel-isl/Open3D/blob/master/examples/python/reconstruction_system/sensors/realsense_recorder.py#L114

is not compatible with the RealSense L515 camera. The following exception is raised:

Traceback (most recent call last):
  File "./examples/python/reconstruction_system/sensors/realsense_recorder.py", line 126, in <m

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

https://github.com/brendangregg/FlameGraph

Describe the bug
Clipping a DataFrame or Series using ints causes a cudf Failure because it won't handle the different dtypes (int and float)

Steps/Code to reproduce bug

data = cudf.Series([-0.43, 0.1234, 1.5, -1.31])
data.clip(0, 1)

...
  File "cudf/_lib/replace.pyx", line 216, in cudf._lib.replace.clip
  File "cudf/_lib/replace.pyx", line 198, in cudf._lib.replace.clamp

Describe the Problem

plot_model currently has the save argument which can be used to save the plots. It does not provide the functionality to decide where to save the plot and with what name. Right now it saves the plot with predefined names in the current working directory.

Describe the solution you'd like

We can have another argument save_path which is used whenever the `

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.