DougGregor

extension Collection {
  func parallelMap<T>(
    parallelism requestedParallelism: Int? = nil,
    _ transform: @escaping (Element) async throws -> T
  ) async throws -> [T] {
    let defaultParallelism = 2
    let parallelism = requestedParallelism ?? defaultParallelism

    let n = self.count
    if n == 0 {

staceysv

{
  "$schema": "https://vega.github.io/schema/vega/v5.json",
  "padding": 5,
  "signals": [
    {
      "name": "binOffset",
      "value": 0
    },
    {
      "name": "binStep",

chychen

import tensorflow as tf
import tensorflow_datasets as tfds
import numpy as np
import os
import matplotlib.pyplot as plt
from tensorflow.keras.utils import to_categorical
from absl import flags, logging
from tqdm.auto import tqdm

FLAGS = flags.FLAGS

louiskirsch

import tensorflow as tf
import tensorflow.contrib as tfc
import numpy as np
import matplotlib.pyplot as plt
import observations
from functools import lru_cache

tf.reset_default_graph()

train_data, test_data = observations.cifar10('data/cifar',)

Aaronmacaron

#!/bin/bash

# This installs alacritty terminal on ubuntu (https://github.com/jwilm/alacritty)
# You have to have rust/cargo installed for this to work

# Install required tools
sudo apt-get install -y cmake libfreetype6-dev libfontconfig1-dev xclip

# Download, compile and install Alacritty
git clone https://github.com/jwilm/alacritty

louiskirsch

class RingBuffer:

    def __init__(self, scope_name, components, size):
        """
        Create a new ring buffer of size `size`.
        Each item in the ring buffer is a tuple of variables of size `len(components)`.
        
        :param scope_name: A scope name for the newly created variables
        :param components: Defines the type of items in the buffer. An iterable of tuples (name: str, shape: Iterable, dtype)
        :param size: The maximum size of the buffer

gyglim

"""Simple example on how to log scalars and images to tensorboard without tensor ops.

License: BSD License 2.0
"""
__author__ = "Michael Gygli"

import tensorflow as tf
from StringIO import StringIO
import matplotlib.pyplot as plt
import numpy as np

crittermike

git log -L 1,1:some-file.txt

yrevar

{0: 'tench, Tinca tinca',
 1: 'goldfish, Carassius auratus',
 2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias',
 3: 'tiger shark, Galeocerdo cuvieri',
 4: 'hammerhead, hammerhead shark',
 5: 'electric ray, crampfish, numbfish, torpedo',
 6: 'stingray',
 7: 'cock',
 8: 'hen',
 9: 'ostrich, Struthio camelus',

kastnerkyle

import theano.tensor as T
import theano

a = T.vector()
b = T.matrix()
fa = a ** 2
f = theano.function([a], fa)
f2 = theano.function([b], theano.clone(fa, replace={a: b}, strict=False))
print(f([2]))
print(f2([[2]]))