模块 'tensorboard.summary._tf.summary' 没有属性 'FileWriter'
module 'tensorboard.summary._tf.summary' has no attribute 'FileWriter'
为什么每次我尝试 运行 我的 MCP 神经元时,张量流都会抛出这个异常“模块 'tensorboard.summary._tf.summary' 没有属性 'FileWriter'”,我该如何解决手头的问题?我在堆栈上进行了搜索,但找不到适合我的问题的任何解决方案。谁能帮帮我。
# McCulloch Pitt Neuron built with Tensorflow and represented with
# Tensorboard
import tensorflow as tf
import numpy as np
import os
PATH = os.getcwd()
LOG_DIR = PATH+ '/output/'
tf.compat.v1.disable_eager_execution()
# 1.Configuration to optimize CPU performance by defining
# thread pools. For this example 4 is enough. A variable
# replace the constant
config = tf.compat.v1.ConfigProto(
inter_op_parallelism_threads=4,
intra_op_parallelism_threads=4
)
# 2.Defining the x values, their w weights,the b bias,y weight calculation
# and the s sigmoid activation function
x = tf.compat.v1.placeholder(tf.float32, shape=(1, 5), name='x')
w = tf.compat.v1.placeholder(tf.float32, shape=(5, 1), name='w')
b = tf.compat.v1.placeholder(tf.float32, shape=(1), name='b')
y = tf.matmul(x, w) + b
s = tf.nn.sigmoid(y)
# 3.Starting a session providing constants as weight inputs
# The Perceptron,a neuron that can learn its weights, will provide with our present day
# automatic weight calculations
with tf.compat.v1.Session(config=config) as tfs:
tfs.run(tf.compat.v1.global_variables_initializer())
w_t = [[.1, .7, .75, .60, .20]]
x_1 = [[10, 2, 1., 6., 2.]]
b_1 = [1]
w_1 = np.transpose(w_t)
value = tfs.run(s,
feed_dict={
x: x_1,
w: w_1,
b: b_1
}
)
print ('value for threshold calculation',value)
print ('Availability of lx',1-value)
#___________Tensorboard________________________
#with tf.Session() as sess:
Writer = tf.summary.FileWriter(LOG_DIR, tfs.graph)
Writer.close()
def launchTensorBoard():
import os
os.system('tensorboard --logdir='+LOG_DIR)
return
import threading
t = threading.Thread(target=launchTensorBoard, args=([]))
t.start()
tfs.close()
尝试使用:
Writer = tf.summary.create_file_writer(LOG_DIR)
或者,如果你还想传递图表,请执行以下操作:
Writer = tf.compat.v1.summary.FileWriter(LOG_DIR, tfs.graph)
有关详细信息,请参阅 docs。
为什么每次我尝试 运行 我的 MCP 神经元时,张量流都会抛出这个异常“模块 'tensorboard.summary._tf.summary' 没有属性 'FileWriter'”,我该如何解决手头的问题?我在堆栈上进行了搜索,但找不到适合我的问题的任何解决方案。谁能帮帮我。
# McCulloch Pitt Neuron built with Tensorflow and represented with
# Tensorboard
import tensorflow as tf
import numpy as np
import os
PATH = os.getcwd()
LOG_DIR = PATH+ '/output/'
tf.compat.v1.disable_eager_execution()
# 1.Configuration to optimize CPU performance by defining
# thread pools. For this example 4 is enough. A variable
# replace the constant
config = tf.compat.v1.ConfigProto(
inter_op_parallelism_threads=4,
intra_op_parallelism_threads=4
)
# 2.Defining the x values, their w weights,the b bias,y weight calculation
# and the s sigmoid activation function
x = tf.compat.v1.placeholder(tf.float32, shape=(1, 5), name='x')
w = tf.compat.v1.placeholder(tf.float32, shape=(5, 1), name='w')
b = tf.compat.v1.placeholder(tf.float32, shape=(1), name='b')
y = tf.matmul(x, w) + b
s = tf.nn.sigmoid(y)
# 3.Starting a session providing constants as weight inputs
# The Perceptron,a neuron that can learn its weights, will provide with our present day
# automatic weight calculations
with tf.compat.v1.Session(config=config) as tfs:
tfs.run(tf.compat.v1.global_variables_initializer())
w_t = [[.1, .7, .75, .60, .20]]
x_1 = [[10, 2, 1., 6., 2.]]
b_1 = [1]
w_1 = np.transpose(w_t)
value = tfs.run(s,
feed_dict={
x: x_1,
w: w_1,
b: b_1
}
)
print ('value for threshold calculation',value)
print ('Availability of lx',1-value)
#___________Tensorboard________________________
#with tf.Session() as sess:
Writer = tf.summary.FileWriter(LOG_DIR, tfs.graph)
Writer.close()
def launchTensorBoard():
import os
os.system('tensorboard --logdir='+LOG_DIR)
return
import threading
t = threading.Thread(target=launchTensorBoard, args=([]))
t.start()
tfs.close()
尝试使用:
Writer = tf.summary.create_file_writer(LOG_DIR)
或者,如果你还想传递图表,请执行以下操作:
Writer = tf.compat.v1.summary.FileWriter(LOG_DIR, tfs.graph)
有关详细信息,请参阅 docs。