| #!/usr/bin/env python | |
| # -*- coding: utf-8 -*- | |
| import urllib2 | |
| gh_url = 'https://api.github.com' | |
| req = urllib2.Request(gh_url) | |
| password_manager = urllib2.HTTPPasswordMgrWithDefaultRealm() |
| # The blog post that started it all: https://neocities.org/blog/the-fcc-is-now-rate-limited | |
| # | |
| # Current known FCC address ranges: | |
| # https://news.ycombinator.com/item?id=7716915 | |
| # | |
| # Confirm/locate FCC IP ranges with this: http://whois.arin.net/rest/net/NET-165-135-0-0-1/pft | |
| # | |
| # In your nginx.conf: | |
| location / { |
| upstream myapp { | |
| server 127.0.0.1:8081; | |
| } | |
| limit_req_zone $binary_remote_addr zone=login:10m rate=1r/s; | |
| server { | |
| listen 443 ssl spdy; | |
| server_name _; | |
| import torch | |
| import torch._inductor.config | |
| import time | |
| torch._inductor.config.triton.cudagraphs = False | |
| torch.set_float32_matmul_precision('high') | |
| def bench(f, name=None, iters=100, warmup=5, display=True, profile=False): | |
| for _ in range(warmup): | |
| f() |
| // set-up a connection between the client and the server | |
| var socket = io.connect(); | |
| // let's assume that the client page, once rendered, knows what room it wants to join | |
| var room = "abc123"; | |
| socket.on('connect', function() { | |
| // Connected, let's sign-up for to receive messages for this room | |
| socket.emit('room', room); | |
| }); |
| license: gpl-3.0 | |
| redirect: https://observablehq.com/@mbostock/mobile-patent-suits |
| import numpy as np | |
| from numba import jit | |
| from numba import float64 | |
| from numba import int64 | |
| @jit((float64[:], int64), nopython=True, nogil=True) | |
| def _ewma(arr_in, window): | |
| r"""Exponentialy weighted moving average specified by a decay ``window`` | |
| to provide better adjustments for small windows via: |
| from transformers import ( | |
| AutoConfig, | |
| AutoTokenizer, | |
| BitsAndBytesConfig, | |
| GenerationConfig, | |
| AutoModelForCausalLM, | |
| LlamaTokenizerFast, | |
| PreTrainedModel, | |
| TextIteratorStreamer, | |
| StoppingCriteria, |
| """Kernel K-means""" | |
| # Author: Mathieu Blondel <mathieu@mblondel.org> | |
| # License: BSD 3 clause | |
| import numpy as np | |
| from sklearn.base import BaseEstimator, ClusterMixin | |
| from sklearn.metrics.pairwise import pairwise_kernels | |
| from sklearn.utils import check_random_state |
##VGG16 model for Keras
This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.
It has been obtained by directly converting the Caffe model provived by the authors.
Details about the network architecture can be found in the following arXiv paper:
Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan, A. Zisserman