来自 jupyter/Ipython 的 Tensorflow 运行个动画

Question

我正在研究水滴在水面上的张量流示例，代码：

#Import libraries for simulation
import tensorflow as tf
import numpy as np

#Imports for visualization
import PIL.Image
from io import BytesIO
from IPython.display import clear_output, Image, display

#A function for displaying the state of the pond's surface as an image.
def DisplayArray(a, fmt='jpeg', rng=[0,1]):
  """Display an array as a picture."""
  a = (a - rng[0])/float(rng[1] - rng[0])*255
  a = np.uint8(np.clip(a, 0, 255))
  f = BytesIO()
  PIL.Image.fromarray(a).save(f, fmt)
  clear_output(wait = True)
  display(Image(data=f.getvalue()))

sess = tf.InteractiveSession()

def make_kernel(a):
  """Transform a 2D array into a convolution kernel"""
  a = np.asarray(a)
  a = a.reshape(list(a.shape) + [1,1])
  return tf.constant(a, dtype=1)

def simple_conv(x, k):
  """A simplified 2D convolution operation"""
  x = tf.expand_dims(tf.expand_dims(x, 0), -1)
  y = tf.nn.depthwise_conv2d(x, k, [1, 1, 1, 1], padding='SAME')
  return y[0, :, :, 0]

def laplace(x):
  """Compute the 2D laplacian of an array"""
  laplace_k = make_kernel([[0.5, 1.0, 0.5],
                           [1.0, -6., 1.0],
                           [0.5, 1.0, 0.5]])
  return simple_conv(x, laplace_k)

N = 500

# Initial Conditions -- some rain drops hit a pond

# Set everything to zero
u_init = np.zeros([N, N], dtype=np.float32)
ut_init = np.zeros([N, N], dtype=np.float32)

# Some rain drops hit a pond at random points
for n in range(40):
  a,b = np.random.randint(0, N, 2)
  u_init[a,b] = np.random.uniform()

DisplayArray(u_init, rng=[-0.1, 0.1])

# Parameters:
# eps -- time resolution
# damping -- wave damping
eps = tf.placeholder(tf.float32, shape=())
damping = tf.placeholder(tf.float32, shape=())

# Create variables for simulation state
U  = tf.Variable(u_init)
Ut = tf.Variable(ut_init)

# Discretized PDE update rules
U_ = U + eps * Ut
Ut_ = Ut + eps * (laplace(U) - damping * Ut)

# Operation to update the state
step = tf.group(
  U.assign(U_),
  Ut.assign(Ut_))

# Initialize state to initial conditions
tf.global_variables_initializer().run()

# Run 1000 steps of PDE
for i in range(1000):
  # Step simulation
  step.run({eps: 0.03, damping: 0.04})
  DisplayArray(U.eval(), rng=[-0.1, 0.1])

然后从 Ipython 我 import partial_d 但它不生成动画。

用过tensorflow的人知道怎么解决吗？ Google 提到 Ipython Notebook，不能 find/set，但我确实安装了 jupyter 和最新的 Ipython。

Answer 1

你以前用过jupyter吗？我认为您需要启动您的笔记本服务器并运行那里的代码。尝试运行ning jupyter notebook，然后将您的代码导入到笔记本中。或者，您可以将代码复制并粘贴到代码单元格中，然后跳过导入。

我不熟悉你提到的例子，但我不认为这是一个 TF 问题。查看如何通过 jupyter（iPython 的新名称来消除任何混淆）对其进行运行处理。

Answer 2

This 让我快速了解如何使用 jupyter 和 tensorflow 生成涟漪动画。

来自 jupyter/Ipython 的 Tensorflow 运行个动画

Tensorflow running animations from jupyter/Ipython

ipython

ipython-notebook

tensorflow

jupyter-notebook

来自 jupyter/Ipython 的 Tensorflow 运行 个动画

Tensorflow running animations from jupyter/Ipython

ipython

ipython-notebook

tensorflow

jupyter-notebook

来自 jupyter/Ipython 的 Tensorflow 运行个动画