Error when setting display to true

[njfdiem]

When I set display = True I get the error below. These are the versions I have for the known dependencies: Python (3.6) OpenAI gym (0.10.5) tensorflow (1.8.0) numpy (1.14.5)

  File "C:\Users\AAJ\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py", line 1322, in _do_call
    return fn(*args)
  File "C:\Users\AAJ\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py", line 1307, in _run_fn
    options, feed_dict, fetch_list, target_list, run_metadata)
  File "C:\Users\AAJ\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py", line 1409, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [4,64] rhs shape= [16,64]
         [[Node: save/Assign_39 = Assign[T=DT_FLOAT, _class=["loc:@agent_0/target_p_func/fully_connected/weights"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](agent_0/target_p_func/fully_connected/weights, save/RestoreV2:39)]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "train.py", line 193, in <module>
    train(arglist)
  File "train.py", line 96, in train
    U.load_state(arglist.load_dir)
  File "d:\red mirror\dr so\multi agent examples\maddpg-master\maddpg\common\tf_util.py", line 230, in load_state
    saver.restore(get_session(), fname)
  File "C:\Users\AAJ\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\training\saver.py", line 1802, in restore
    {self.saver_def.filename_tensor_name: save_path})
  File "C:\Users\AAJ\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py", line 900, in run
    run_metadata_ptr)
  File "C:\Users\AAJ\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py", line 1135, in _run
    feed_dict_tensor, options, run_metadata)
  File "C:\Users\AAJ\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py", line 1316, in _do_run
    run_metadata)
  File "C:\Users\AAJ\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py", line 1335, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [4,64] rhs shape= [16,64]
         [[Node: save/Assign_39 = Assign[T=DT_FLOAT, _class=["loc:@agent_0/target_p_func/fully_connected/weights"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](agent_0/target_p_func/fully_connected/weights, save/RestoreV2:39)]]

Caused by op 'save/Assign_39', defined at:
  File "train.py", line 193, in <module>
    train(arglist)
  File "train.py", line 96, in train
    U.load_state(arglist.load_dir)
  File "d:\red mirror\dr so\multi agent examples\maddpg-master\maddpg\common\tf_util.py", line 229, in load_state
    saver = tf.train.Saver()
  File "C:\Users\AAJ\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\training\saver.py", line 1338, in __init__
    self.build()
  File "C:\Users\AAJ\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\training\saver.py", line 1347, in build
    self._build(self._filename, build_save=True, build_restore=True)
  File "C:\Users\AAJ\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\training\saver.py", line 1384, in _build
    build_save=build_save, build_restore=build_restore)
  File "C:\Users\AAJ\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\training\saver.py", line 835, in _build_internal
    restore_sequentially, reshape)
  File "C:\Users\AAJ\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\training\saver.py", line 494, in _AddRestoreOps
    assign_ops.append(saveable.restore(saveable_tensors, shapes))
  File "C:\Users\AAJ\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\training\saver.py", line 185, in restore
    self.op.get_shape().is_fully_defined())
  File "C:\Users\AAJ\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\state_ops.py", line 283, in assign
    validate_shape=validate_shape)
  File "C:\Users\AAJ\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\gen_state_ops.py", line 63, in assign
    use_locking=use_locking, name=name)
  File "C:\Users\AAJ\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 787, in _apply_op_helper
    op_def=op_def)
  File "C:\Users\AAJ\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\framework\ops.py", line 3392, in create_op
    op_def=op_def)
  File "C:\Users\AAJ\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\framework\ops.py", line 1718, in __init__
    self._traceback = self._graph._extract_stack()  # pylint: disable=protected-access

InvalidArgumentError (see above for traceback): Assign requires shapes of both tensors to match. lhs shape= [4,64] rhs shape= [16,64]
         [[Node: save/Assign_39 = Assign[T=DT_FLOAT, _class=["loc:@agent_0/target_p_func/fully_connected/weights"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](agent_0/target_p_func/fully_connected/weights, save/RestoreV2:39)]]

[dch133]

Did you find a solution?

[ElizabethDuo]

Hi I solved this problem by using python train.py --scenario simple --display instead. --diaplay is set as a bool switch, so changing the default bool of it won't work. You can find more info about it by google argparse action store_true

Good day!

[lionel-xie]

delete this code :if arglist.display or arglist.restore or arglist.benchmark: add this code: if arglist.restore or arglist.benchmark: