wtime | Windows Benchmark Tool | Performance Testing library

Just ran your code, and it works if you use dist = np.concatenate(dist, axis=0) instead of dist = np.asarray(dist).ravel().reshape(num_row(data),-1) Same thing for memb

But i do not want to use

#pragma omp parallel num_threads(2)

You need to use #pragma omp parallel to create the threads.

Instead of:

There are some issues with your code, in the function my_function the iterations of the loop are not being assigned to threads as you wanted. Because you have added again the clause parallel to #pragma omp for, and assuming that you have nested parallelism disabled, which by default it is, each of the threads created in the outer parallel region will execute "sequentially" the code within that region. Consequently, for a n = 6 and number of threads = 4, you would have the following block of code:

The exact answer to your problem cannot be given without code snippets but here is an approach which I thought of:

You can use the

In order for it to work you need jquery support for your website

Try doing following:

1. Assume you are storing your variables in JS array like

var numbers = [45, 4, 9, 16, 25];

1. You can try using built-in JS funtion to cycle through the array like:

numbers.forEach(myFunction);

1. You define your function that you use in point 2, with ajax, smth like

Change the % operator to the format() method, and use {} placeholders. This doesn't require the corresponding parameter to be a specific type, it will use its __str__ operator to format it.

We can convert to Datetime class and use difftime with unit specified as min

1. Should we use time.time()?

Yes, it's fine for CPU

1. Should we use volatile?

As you said it's deprecated. Since 0.4.0 torch.Tensor was merged with torch.Variable (it's deprecated as well) and torch.no_grad context manager should be used.

1. Should the page cache be cleared?

I don't think so unless you know it's a problem

1. Should I remove nn.Sequential() and directly put in forward part

No, torch.nn.Sequential should have no or negligible performance burden on your model. It's forward is only:

1. Change the first line of the program to remove the period.