[英]Tensorflow running animations from jupyter/Ipython
我正在研究水滴上的tensorflow示例,代码为:
#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中import partial_d
但它不会生成动画。
任何使用过Tensorflow的人都知道如何解决这个问题? Google提到了Ipython Notebook
,找不到/设置了它,但是我确实安装了jupyter和最新的Ipython。
您以前使用过jupyter吗? 我认为您需要启动笔记本服务器并在其中运行代码。 尝试运行jupyter notebook
,然后将代码导入到笔记本中。 或者,您可以仅将代码复制并粘贴到代码单元中,然后跳过导入。
我不熟悉您所指的示例,但我认为这不是TF问题。 了解如何通过jupyter(iPython的新名称来消除任何混乱)运行它的方式。
这让我加快了如何使用jupyter和tensorflow生成波纹动画的速度。
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.