ipython common

gpu_check.py

from tensorflow.python.client import device_lib
print(tf.__version__)
print("Num GPUs Available: ", len(tf.config.list_physical_devices('GPU')))
device_lib.list_local_devices()

gui.py

number_of_steps = 48000 #@param {type:"slider", min:2000, max:50000, step:100}
#@markdown (Default is 18000).
burnin = 25000 #@param {type:"slider", min:0, max:30000, step:100}
#@markdown (Default is 1000).
leapfrog_steps=2 #@param {type:"slider", min:1, max:9, step:1}
#@markdown (Default is 6).

ipython_common.py

# Python ≥3.5 is required
import sys
assert sys.version_info >= (3, 5)

# Scikit-Learn ≥0.20 is required
import sklearn
assert sklearn.__version__ >= "0.20"

# Common imports
import numpy as np
import pandas as pd
import os

# to make this notebook's output stable across runs
np.random.seed(42)

# To plot pretty figures
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns; sns.set()

tfp.py

import numpy as np
import pandas as pd
import os

#@markdown This sets the styles of the plotting (default is styled like plots from [FiveThirtyeight.com](https://fivethirtyeight.com/)
matplotlib_style = 'fivethirtyeight' #@param ['fivethirtyeight', 'bmh', 'ggplot', 'seaborn', 'default', 'Solarize_Light2', 'classic', 'dark_background', 'seaborn-colorblind', 'seaborn-notebook']
import matplotlib.pyplot as plt; plt.style.use(matplotlib_style)
import matplotlib.axes as axes;
from matplotlib.patches import Ellipse
from matplotlib import rcParams
rcParams['font.family'] = 'sans-serif'
rcParams['font.sans-serif'] = ['Hiragino Maru Gothic Pro', 'Yu Gothic', 'Meirio', 'Takao', 'IPAexGothic', 'IPAPGothic', 'VL PGothic', 'Noto Sans CJK JP']
#%matplotlib inline
import seaborn as sns; sns.set_context('notebook')
from IPython.core.pylabtools import figsize
#@markdown This sets the resolution of the plot outputs (`retina` is the highest resolution)
notebook_screen_res = 'retina' #@param ['retina', 'png', 'jpeg', 'svg', 'pdf']
#%config InlineBackend.figure_format = notebook_screen_res

import tensorflow as tf
import tensorflow.experimental.numpy as tnp
import tensorflow_probability as tfp
tfd = tfp.distributions
tfb = tfp.bijectors

class _TFColor(object):
    """Enum of colors used in TF docs."""
    red = '#F15854'
    blue = '#5DA5DA'
    orange = '#FAA43A'
    green = '#60BD68'
    pink = '#F17CB0'
    brown = '#B2912F'
    purple = '#B276B2'
    yellow = '#DECF3F'
    gray = '#4D4D4D'
    def __getitem__(self, i):
        return [
            self.red,
            self.orange,
            self.green,
            self.blue,
            self.pink,
            self.brown,
            self.purple,
            self.yellow,
            self.gray,
        ][i % 9]
TFColor = _TFColor()

print(tf.__version__)
tf.config.list_physical_devices('GPU')