Tensorflow ERREUR: Méthode "FileWriter"

Question

from tensorflow.examples.tutorials.mnist import input_data 
mnist = input_data.read_data_sets("/tmp/data/", one_hot = True) 

import tensorflow as tf 

learning_rate = 0.01 
training_iteration = 30 
batch_size = 100 
display_step = 2 

x = tf.placeholder("float", [None, 784]) 
y = tf.placeholder("float", [None, 10]) 

W = tf.Variable(tf.zeros([784, 10])) 
b = tf.Variable(tf.zeros([10])) 

with tf.name_scope("Wx_b") as scope: 
    model = tf.nn.softmax(tf.matmul(x, W) + b) 

w_h = tf.summary.histogram("weights", W) 
b_h = tf.summary.histogram("biases", b) 

with tf.name_scope("cost_function") as scope: 
    cost_function = -tf.reduce_sum(y*tf.log(model)) 
    tf.summary.scalar("cost_function", cost_function) 

with tf.name_scope("train") as scope: 
    optimizer =   tf.train.GradientDescentOptimizer(learning_rate).minimize(cost_function) 

init = tf.global_variables_initializer() 
merged_summary_op = tf.summary.merge_all() 


with tf.Session() as sess: 
    sess.run(init) 
    summary_writer = tf.summary.FileWriter('/home/sergo/work/logs',graph_def = sess.graph_def) #I GET AN ERROR IN THIS FileWriter method 
    for iteration in range(training_iteration): 
      avg_cost = 0. 
      total_batch = int(mnist.train.num_examples/batch_size) 
      for i in range(total_batch): 
        batch_xs, batch_ys = mnist.train.next_batch(batch_size) 
        sess.run(optimizer, feed_dict = {x: batch_xs, y: batch_ys}) 
        avg_cost += sess.run(cost_function, feed_dict={x:batch_xs, y: batch_ys})/total_batch 

     # write logs for each iteration 
        sessummary_str = sess.run(merged_summary_op, feed_dict={x: batch_xs, y: batch_ys}) 
        summary_writer.add_summary(summary_str, interation*total_batch + i) 

    if iteration % display_step == 0: 
      print("Iteration:", '%04d' % (iteration + 1), "cost=", "{:.9f}".format(avg_cost)) 





    #When finished: 
    print("Turning completed!") 

    predictions = tf.equal(tf.argmax(model, 1), tf.argmax(y,1)) 

    accuracy = tf.reduce_mean(tf.cast(predictions, "float")) 
    print("Accuracy:", accuracy.eval({x: mnist.test.images, y: mnist.test.labels})) 

Bonjour, J'utilise un exemple de code python3.6 d'un tutoriel YouTube avec Tensorflow 1.0.

je reçois une erreur à la ligne 36 avec la méthode FileWriter comme suit:

Traceback (most recent call last): 
File "/Users/cliang/Desktop/tfclass.py", line 36, in <module> 
summary_writer = tf.summary.FileWriter('/home/sergo/work/logs',graph_def = sess.graph_def) 
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/summary/writer/writer.py", line 308, in __init__ 
event_writer = EventFileWriter(logdir, max_queue, flush_secs) 
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/summary/writer/event_file_writer.py", line 69, in __init__ 
gfile.MakeDirs(self._logdir) 
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/lib/io/file_io.py", line 301, in recursive_create_dir 
pywrap_tensorflow.RecursivelyCreateDir(compat.as_bytes(dirname), status) 
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/contextlib.py", line 89, in __exit__ 
next(self.gen) 
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py", line 469, in raise_exception_on_not_ok_status 
pywrap_tensorflow.TF_GetCode(status)) 
tensorflow.python.framework.errors_impl.UnimplementedError: /home/sergo 

Quelqu'un sait comment résoudre cette erreur et ce que le «/home/sergo/travail/logs » argument pathname veux dire?

Toute aide est très appréciée.

Merci!

(je suis sous Mac 0SX Yosemite 10.10.5)

Answer 1

Dans la ligne, summary_writer = tf.summary.FileWriter ('/ home/sergo/travail/logs', graph_def = sess.graph_def) #I OBTENIR uNE FAUTE méthode FileWriter

il mentionne explicitement un chemin/home/sergo/travail/logs

Ce chemin ne peut pas exister dans votre machine locale donc s'il vous plaît fournir un chemin qui existe et qui devrait résoudre votre problème

Merci