alsrgv

# Copyright 2018 Uber Technologies, Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

BIGBALLON

import keras
import numpy as np
from keras.datasets import cifar10
from keras.preprocessing.image import ImageDataGenerator
from keras.layers.normalization import BatchNormalization
from keras.layers import Conv2D, Dense, Input, add, Activation, GlobalAveragePooling2D
from keras.callbacks import LearningRateScheduler, TensorBoard, ModelCheckpoint
from keras.models import Model
from keras import optimizers, regularizers
from keras import backend as K

jganzabal

This configuration worked for me, hope it helps

It is based on: https://becominghuman.ai/deep-learning-gaming-build-with-nvidia-titan-xp-and-macbook-pro-with-thunderbolt2-5ceee7167f8b

and on: https://stackoverflow.com/questions/44744737/tensorflow-mac-os-gpu-support

Hardware

pbugnion

Multiple selection with checkboxes and search field

Often, you want the user to choose n options (where n is small-ish) from a very large (hundreds or thousands) number of possibilities. Good UX around this dictates that the user should be able to search for the options they want.

This gist puts together a minimal example of binding a search field with multiple checkboxes using ipywidgets.

Usage

mrry

# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

joelthchao

import numpy as np
import tensorflow as tf
from keras.callbacks import TensorBoard
from keras.layers import Input, Dense
from keras.models import Model


def write_log(callback, names, logs, batch_no):
    for name, value in zip(names, logs):
        summary = tf.Summary()

Sebelino

#!/usr/bin/env python

# The following is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.

from pykeyboard import PyKeyboardEvent
from pymouse import PyMouseEvent
from threading import Thread

robintw

from bokeh.plotting import figure, ColumnDataSource
from bokeh.models import HoverTool


def scatter_with_hover(df, x, y,
                       fig=None, cols=None, name=None, marker='x',
                       fig_width=500, fig_height=500, **kwargs):
    """
    Plots an interactive scatter plot of `x` vs `y` using bokeh, with automatic
    tooltips showing columns from `df`.

ajfriend

ntezak

import sympy
from collections import defaultdict

def walk_exprs(exprs, subexpr=None):
    """
    Return a dict {expr: frequency} for all subexpressions in the sequence of expressions `expr`.
    """
    if subexpr is None:
        subexpr = defaultdict(int)
    for e in exprs: