This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
class Counter: | |
def __init__(self, n=3) -> None: | |
self.n = n | |
self._cnt = 0 | |
def __await__(self): | |
for _ in range(self.n): | |
r = yield self._cnt | |
print(f"incrementing by {r}") |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
from abc import ABC | |
from abc import abstractmethod | |
from abc import abstractproperty | |
from dataclasses import dataclass, field | |
from typing import Any | |
from typing import AsyncGenerator | |
from typing import Awaitable | |
from typing import Callable | |
from typing import Generator | |
from typing import Generic |
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
#!/usr/bin/env python3 | |
import zipfile | |
import sys | |
import re | |
import xml.etree.ElementTree as ET | |
namespaces = { | |
'a': 'http://schemas.openxmlformats.org/drawingml/2006/main', | |
'r': 'http://schemas.openxmlformats.org/officeDocument/2006/relationships', |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import torch | |
def jacobian(y, x, create_graph=False): | |
jac = [] | |
flat_y = y.reshape(-1) | |
grad_y = torch.zeros_like(flat_y) | |
for i in range(len(flat_y)): | |
grad_y[i] = 1. | |
grad_x, = torch.autograd.grad(flat_y, x, grad_y, retain_graph=True, create_graph=create_graph) | |
jac.append(grad_x.reshape(x.shape)) |
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import json | |
import glob | |
import os | |
from os.path import join, basename | |
# install this with "conda install -c conda-forge python-graphviz" | |
import graphviz as gv | |
# path to your conda environment | |
path = os.environ.get('CONDA_PREFIX') | |
if path is None: |
NewerOlder