GitLab

Previously they were restored to default values, which had the effect of negating the current setting of the calling code (whether set in the compiler options or by pragma previously)

Improve the error a user gets when trying to build the pyhton extention on windows but they didn't install visual C++.

paths instead of relying on CUDA_PATH to be set.

* * Corrected interpolate_bilinear for non-RGB images not to collapse into grayscale (#2089)

* * interpolate_bilinear uses now pixel_to_vector for shorter code.

* pixels now have operator!=.

* * Explicitely float interpolation

* Using C++11 static_assert() in interpolation.

* * Corrected documentation for interpolate_bilinear, interpolate_quadratic

* * Corrected formatting near interpolate_bilinear

Changed C-style cast to static_cast.

Reduce code duplication a bit and make equal_error_rate() give correct results when called on data where all detection scores are identical.

Previously it would say the EER was 0, but really it should have said 1 in this case.

* wip: attempt to use cuda for loss mse channel

* wip: maybe this is a step in the right direction

* Try to fix dereferencing the truth data (#1)

* Try to fix dereferencing the truth data

* Fix memory layout

* fix loss scaling and update tests

* rename temp1 to temp

* readd lambda captures for output_width and output_height

clangd was complaining about this, and suggested me to remove them
in the first, place:

```
Lambda capture 'output_height' is not required to be captured for this use (fix available)
Lambda capture 'output_width' is not required to be captured for this use (fix available)
```

* add a weighted_loss typedef to loss_multiclass_log_weighted_ for consistency

* update docs for weighted losses

* refactor multi channel loss and add cpu-cuda tests

* make operator() const

* make error relative to the loss value
Co-authored-by: Juha Reunanen <juha.reunanen@tomaattinen.com>

The thread pool was initialized after the network, so it lead to a
reorder warning in GCC 9.3.0

* Remove outdated comment

That comment was there from when I was using a dnn_trainer to train
the discriminator network.

* Fix case

* fix some warnings when running tests

* rever changes in CMakeLists.txt

* update example make use of newly promoted method

* update tests to make use of newly promoted methods

* remove branch from cuda kernel

* promote lambda to a global function

Promote some of the sub-network methods into the add_loss_layer interface so users don't have to write .subnet() so often.