ArthurDelannoyazerty

import gpxpy
import matplotlib.pyplot as plt
import os
import re

from itertools import accumulate


size = 1.2
gpx_folderpath = "gpx/"

ArthurDelannoyazerty

files = [f for f in os.listdir(gpx_folderpath) if os.path.isfile(os.path.join(gpx_folderpath, f))]

def sort_key(file):
    num = re.search(r'(\d+)', file).group(1)
    num = num.replace('-', ' ')
    num = int(num) if num.isdigit() else 0
    return (num, file)

files.sort(key=sort_key)

ArthurDelannoyazerty

N = 4
x = torch.randn(N, 3)
out = torch.Tensor([1,0,1,0]).float().requires_grad_(True)

res1 = x * out[:, None]
idx = res1.nonzero()[:, 0].unique()
res2 = res1[idx]

# perform your operation here
res = res2.mean()

ArthurDelannoyazerty

ArthurDelannoyazerty

Things to do to break the computation graph

By using the output of the following code in the flow of the model.

torch.tensor(existing_tensor)

existing_tensor.item()

existing_tensor.detach()

ArthurDelannoyazerty

import ctypes
import tkinter

def get_dpi():
    ctypes.windll.shcore.SetProcessDpiAwareness(1)
    root = tkinter.Tk()
    dpi = ctypes.windll.user32.GetDpiForWindow(root.winfo_id())
    root.destroy()
    return dpi

ArthurDelannoyazerty

def rotanimate(ax, output_filename:str, angles:list=None, elevation:list=None, width:float=8, height:float=8, filename_prefix:str='tmprot_', nb_image:int=120, fps:int=30):
    if angles==None: angles = np.linspace(0, 360, nb_image+1)
    if elevation==None: elevation = np.linspace(20, 20, nb_image+1)
    
    ax.figure.set_size_inches(width,height)
    
    files = []
    for i, angle in enumerate(angles):
        ax.view_init(elev = elevation[i], azim=angle)
        fname = '%s%03d.jpeg'%(filename_prefix,i)

ArthurDelannoyazerty

class CustomImageDatasetNumpy(Dataset):
    def __init__(self, dir_path:str):
        self.dir_path = dir_path
        self.filenames = os.listdir(dir_path)

    def __len__(self):
        return len(self.filenames)

    def __getitem__(self, idx):
        np_path = self.dir_path + "/" + self.filenames[idx]

ArthurDelannoyazerty

def create_data_loader(dirpath:str, test_split:float=0.1, shuffle_dataset:bool=True):
    """Create a dataset and split+shuffle it."""
    dataset = CustomImageDatasetNumpy(dirpath)
    dataset_size = len(dataset)
    
    indices = list(range(dataset_size))
    split = int(np.floor(test_split * dataset_size))
    if shuffle_dataset: np.random.shuffle(indices)

    train_indices, val_indices = indices[split:], indices[:split]

ArthurDelannoyazerty

def delete_content_folder(folder:str):
    for filename in tqdm(os.listdir(folder), desc="Erasing Temporary Data", leave=False):
        file_path = os.path.join(folder, filename)
        try:
            if os.path.isfile(file_path) or os.path.islink(file_path):
                os.unlink(file_path)
            elif os.path.isdir(file_path):
                shutil.rmtree(file_path)
        except Exception as e:
            print('Failed to delete %s. Reason: %s' % (file_path, e))