生成多个Tensorboard目录

Question

我想在循环中运行相同的训练和测试，同时更改一些参数。每次培训完成后，Tensorflow都会生成一个新的Tensorboard目录。

而这正是我的问题：

........................ 
def generatingTBFolder(index): 
    global TB_Folder 
    TB_Folder ='TB_Graphs_'+str(index) 


with tf.device('/cpu:0'): 
    for k in range(2,5):## here is the problem 
     generatingTBFolder(k) 
     train(k,numberOFclasses) 

我不使用一个循环，如：

with tf.device('/cpu:0'): 
     generatingTBFolder(3) 
     train(3,numberOFclasses) 

程序正常工作并产生结果的TB文件夹。但使用循环提供了以下：

--------------------------------------------------------------------------- 
InvalidArgumentError      Traceback (most recent call last) 
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _do_call(self, fn, *args) 
    1038  try: 
-> 1039  return fn(*args) 
    1040  except errors.OpError as e: 

c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata) 
    1020         feed_dict, fetch_list, target_list, 
-> 1021         status, run_metadata) 
    1022 

c:\users\engine\appdata\local\programs\python\python35\lib\contextlib.py in __exit__(self, type, value, traceback) 
    65    try: 
---> 66     next(self.gen) 
    67    except StopIteration: 

c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\framework\errors_impl.py in raise_exception_on_not_ok_status() 
    465   compat.as_text(pywrap_tensorflow.TF_Message(status)), 
--> 466   pywrap_tensorflow.TF_GetCode(status)) 
    467 finally: 

InvalidArgumentError: You must feed a value for placeholder tensor 'input/Features_values' with dtype float 
    [[Node: input/Features_values = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]] 

During handling of the above exception, another exception occurred: 

InvalidArgumentError      Traceback (most recent call last) 
<ipython-input-2-54a526dfc682> in <module>() 
    238  for k in range(2,5): 
    239   generatingTBFolder(k) 
--> 240   train(k,numberOFclasses) 

<ipython-input-2-54a526dfc682> in train(numberOfFeatures, numberOFclasses) 
    208  for i in range(max_steps): 
    209   if i%5 ==0: # Record summarie and Test-set accruracy 
--> 210    summary, acc = sess.run([merged,accuracy], feed_dict=feed_dict(False)) 
    211    #summary, acc = sess.run([merged,accuracy], feed_dict={x:np.reshape(Test_Frame.values[:,indices[0:numberOfFeatures]],[len(Test_Frame),numberOfFeatures]),y_:np.asarray(Test_Frame.iloc[:,-1]),keep_prob:0.9}) 
    212    test_writer.add_summary(summary,i) 

c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in run(self, fetches, feed_dict, options, run_metadata) 
    776  try: 
    777  result = self._run(None, fetches, feed_dict, options_ptr, 
--> 778       run_metadata_ptr) 
    779  if run_metadata: 
    780   proto_data = tf_session.TF_GetBuffer(run_metadata_ptr) 

c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _run(self, handle, fetches, feed_dict, options, run_metadata) 
    980  if final_fetches or final_targets: 
    981  results = self._do_run(handle, final_targets, final_fetches, 
--> 982        feed_dict_string, options, run_metadata) 
    983  else: 
    984  results = [] 

c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata) 
    1030  if handle is None: 
    1031  return self._do_call(_run_fn, self._session, feed_dict, fetch_list, 
-> 1032       target_list, options, run_metadata) 
    1033  else: 
    1034  return self._do_call(_prun_fn, self._session, handle, feed_dict, 

c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _do_call(self, fn, *args) 
    1050   except KeyError: 
    1051   pass 
-> 1052  raise type(e)(node_def, op, message) 
    1053 
    1054 def _extend_graph(self): 

InvalidArgumentError: You must feed a value for placeholder tensor 'input/Features_values' with dtype float 
    [[Node: input/Features_values = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]] 

Caused by op 'input/Features_values', defined at: 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\runpy.py", line 184, in _run_module_as_main 
    "__main__", mod_spec) 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\runpy.py", line 85, in _run_code 
    exec(code, run_globals) 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\__main__.py", line 3, in <module> 
    app.launch_new_instance() 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\traitlets\config\application.py", line 658, in launch_instance 
    app.start() 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelapp.py", line 474, in start 
    ioloop.IOLoop.instance().start() 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\ioloop.py", line 177, in start 
    super(ZMQIOLoop, self).start() 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tornado\ioloop.py", line 887, in start 
    handler_func(fd_obj, events) 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tornado\stack_context.py", line 275, in null_wrapper 
    return fn(*args, **kwargs) 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\zmqstream.py", line 440, in _handle_events 
    self._handle_recv() 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\zmqstream.py", line 472, in _handle_recv 
    self._run_callback(callback, msg) 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\zmqstream.py", line 414, in _run_callback 
    callback(*args, **kwargs) 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tornado\stack_context.py", line 275, in null_wrapper 
    return fn(*args, **kwargs) 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelbase.py", line 276, in dispatcher 
    return self.dispatch_shell(stream, msg) 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelbase.py", line 228, in dispatch_shell 
    handler(stream, idents, msg) 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelbase.py", line 390, in execute_request 
    user_expressions, allow_stdin) 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\ipkernel.py", line 196, in do_execute 
    res = shell.run_cell(code, store_history=store_history, silent=silent) 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\zmqshell.py", line 501, in run_cell 
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs) 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\IPython\core\interactiveshell.py", line 2717, in run_cell 
    interactivity=interactivity, compiler=compiler, result=result) 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\IPython\core\interactiveshell.py", line 2821, in run_ast_nodes 
    if self.run_code(code, result): 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\IPython\core\interactiveshell.py", line 2881, in run_code 
    exec(code_obj, self.user_global_ns, self.user_ns) 
    File "<ipython-input-1-54a526dfc682>", line 240, in <module> 
    train(k,numberOFclasses) 
    File "<ipython-input-1-54a526dfc682>", line 90, in train 
    x =tf.placeholder(tf.float32,[None,numberOfFeatures],name='Features_values') 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\ops\array_ops.py", line 1507, in placeholder 
    name=name) 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 1997, in _placeholder 
    name=name) 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 768, in apply_op 
    op_def=op_def) 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\framework\ops.py", line 2336, in create_op 
    original_op=self._default_original_op, op_def=op_def) 
    File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\framework\ops.py", line 1228, in __init__ 
    self._traceback = _extract_stack() 

InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'input/Features_values' with dtype float 
    [[Node: input/Features_values = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]] 

我已经看到了这个错误，当我开始一个Tensorflow程序，它崩溃，因为形状误差或任何非语法错误，开始在同一个程序无需重新启动的蟒蛇内核传递相同的错误信息。 问题没有，我真的需要在循环中做到这一点（500是实际限制），所以没有办法手动完成。

任何想法如何解决这个问题？

Answer 1

我找到了一个解决方法，这个问题，通过一个又一个，使用一个循环开始整个脚本：

if __name__ == "__main__" : 
    with tf.device('/cpu:0'): 
     print("Got ", int(sys.argv[1])) 
     generatingTBFolder(int(sys.argv[1])) 
     train(int(sys.argv[1]),numberOFclasses) 

这里是脚本：

import os 
for i in range(2,456): 
    command="python TensorCode.py "+str(i) 
    os.system(command) 

结果看起来不错在Tensorboard。希望这可以帮助那里的人！