我想知道如何讓Tensorflow只更新特定的矩陣元素?以下代碼來自Tensorflow教程(https://www.tensorflow.org/versions/r0.11/tutorials/pdes/index.html#partial-differential-equations)。Tensorflow PDE教程問題
#Import libraries for simulation
import tensorflow as tf
import numpy as np
#Imports for visualization
import PIL.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))
with open("fig/image.jpg","w") as f:
PIL.Image.fromarray(a).save(f, "jpeg")
#sess = tf.Session()
sess = tf.InteractiveSession()
# Computational Convenience Functions
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)
# Define the PDE
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.initialize_all_variables().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])
在step = tf.group(U.assign(U_),Ut.assign(Ut_))
,我想知道是否有可能以僅在U_更新的值[1:1,1:-1]和Ut_ [1:1,1:-1] ,並保留其餘的值作爲常量。
非常感謝!
這錯誤似乎無關。您需要在首次使用Tensorflow變量之前初始化Tensorflow變量。假設您有一個名爲'session'的Tensorflow會話,在第一次真正調用session.run()之前,嘗試在'session.run(tf.initialize_all_variables())'行添加一些代碼。 –
@彼得霍金斯感謝您的評論。更具體地說,我更新了我的問題。我實際上想更新'U_ [1:-1,1:-1]內的值,並保持其餘矩陣值不變。 – world2005