gonn | Building a simple neural network in Go | Machine Learning library

You need to be careful when using -1 in views, since it just uses the remaining size and if that doesn't correspond to your intentions, you won't immediately know that it didn't behave as expected. You should particularly avoid -1 for the batch dimension, because you can mistakenly change the batch size, which should not change and their data should be independent from each other.

Given an input of size [32, 3, 256, 256] the output after the convolutions has size [32, 24, 14, 14], which can be flattened to [32, 4704], as you anticipated in the first version. When you change the input to size [32, 3, 50, 50], the output after the convolutions has size [32, 24, 1, 1], which can clearly not be converted to size [32, 768], because flattening it, would result in a size of [32, 24]. Given that 32 * 24 = 768, you incorrectly combine the batches into one, creating a tensor of size [1, 768], and if you had used a different batch size, it wouldn't even work.

The correct input size to the first linear should be 24:

Firstly, the issue is the browser will not interpret the PDF data as a PDF in that way. srcdoc is treated as raw HTML.

There are a couple of different ways to accomplish your "generate on click" functionality:

1) You could just drop the AJAX entirely and just use HTML form markup to accomplish this. Using the target attribute on the form element to target your PDF viewer iframe.

You indeed want to get rid of k. To do this, you want to find the lower bound on the minimum of M(k) + M(n - k - 1). In general it can be arbitrarily tricky, but in this case the standard approach works: take derivative by k.

Rather than approach this with JavaScript, you might find a CSS based solution using mix-blend-mode to be a more robust and flexible alternative.

The mix-blend-mode property allows you to control the blending behavior of an element against it's background. In your case, the contrasted appearance can be achieved via the "difference" blend mode to ensure the burger bars are visible in most cases.

The difference blend mode can be thought of as "color inversion" - when applied to your burger menu, this would ensure that the menu is visible under most backgrounds. The other nice thing about this approach is that it will work against most solid color, image or gradient backgrounds.

You can make use of blending for your menu by adding the following CSS:

To pass references to std::vector or other C++ collections across DLL boundaries, you need to do following.

1. Use same C++ compiler for both modules, and same version of the compiler.

2. In project settings, set up same value to the setting General / Platform Toolset.

3. In project settings, set up C/C++ / Code Generation / Runtime Library value to “Multi-threaded DLL (/MD)”, or Multi-threaded Debug DLL (/MDd) for debug config. If one of the projects have a dependency which requires static CRT setting, sorry you’re out of luck, it won’t work.

4. Use same configuration in both sides: if you’ve built debug version of the DLL, don’t link with release version of the consuming EXE. Also don’t change preprocessor defines like _ITERATOR_DEBUG_LEVEL or _SCL_SECURE_NO_WARNINGS, or if you did, change them to the same value for both projects.

The reason for these complications, C++ doesn’t have standardized ABI. The memory layout of std::vector and other classes changes based on many things. Operators new and delete are also in C++ standard library, i.e. you can’t allocate memory with C++ in one module, free in different one.

If you can’t satisfy these conditions, there’re several workarounds, here’s a nice summary: https://www.codeproject.com/Articles/28969/HowTo-Export-C-classes-from-a-DLL

The code

You can do git log --all --full-history -- **/theFile.*

I don't really understand the part with the Tabs but to fix the empty cells just remove this line: