如果我分别运行tf.concat操作或tf.while_loop操作，它们执行得很好，但是如果我一起运行它们，则会收到错误消息。
这是再现错误的最少代码
@Valid
@ConvertGroup.List( {
@ConvertGroup(from=New.class, to=Pk.class),
@ConvertGroup(from=LocationGroup.class, to=Pk.class)
} )
// Other constraints
private BuildingDto building;
这是结果输出
import tensorflow as tf
import numpy as np
#Initialize matrix
testData = np.random.randint(0, 20, size=(4, 5 ))
print(testData)
#Convert matrix to tensorflow tensor
testData2 = tf.convert_to_tensor(testData, dtype=tf.int64)
step = tf.constant(1)
#Tensors that I want to concatinate in a while loop. Extracts values from testData2
yAll = tf.py_func(lambda x, s: np.random.choice(x.reshape(-1),s, replace=False), [testData2[0], 2], tf.int64)
yNew = tf.py_func(lambda x, s: np.random.choice(x.reshape(-1),s, replace=False), [testData2[0], 2], tf.int64)
#Define while loop condition
def cond(step, yAll, yNew):
return step < 4
#Define while loop body
def body(step, yAll, yNew):
p=7
print('huh')
yNew = tf.py_func(lambda x, s: np.random.choice(x.reshape(-1),s, replace=False), [testData2[step], 2], tf.int64)
yAll = tf.concat( [[yAll], [yNew]], axis=0)
return step + 1, yAll, yNew
#define while loop
u = tf.while_loop(cond, body, loop_vars=[step, yAll, yNew], shape_invariants=[step.get_shape(), yAll.get_shape() , yNew.get_shape()])
#Print data
with tf.Session( ) as sess:
sess.run(tf.global_variables_initializer())
print(sess.run([ u] ))
这里只是在没有tf.while_loop的情况下运行concat操作，效果很好
[[ 1 6 2 7 7]
[ 6 8 2 16 2]
[13 18 5 6 8]
[ 7 15 7 7 16]]
huh
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1333 try:
-> 1334 return fn(*args)
1335 except errors.OpError as e:
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
1318 return self._call_tf_sessionrun(
-> 1319 options, feed_dict, fetch_list, target_list, run_metadata)
1320
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _call_tf_sessionrun(self, options, feed_dict, fetch_list, target_list, run_metadata)
1406 self._session, options, feed_dict, fetch_list, target_list,
-> 1407 run_metadata)
1408
InvalidArgumentError: ConcatOp : Ranks of all input tensors should match: shape[0] = [1,2,2] vs. shape[1] = [1,2]
[[{{node while_1/concat}}]]
During handling of the above exception, another exception occurred:
InvalidArgumentError Traceback (most recent call last)
<ipython-input-2-45e2bf149017> in <module>()
25 with tf.Session( ) as sess:
26 sess.run(tf.global_variables_initializer())
---> 27 print(sess.run([ u] ))
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
927 try:
928 result = self._run(None, fetches, feed_dict, options_ptr,
--> 929 run_metadata_ptr)
930 if run_metadata:
931 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
1150 if final_fetches or final_targets or (handle and feed_dict_tensor):
1151 results = self._do_run(handle, final_targets, final_fetches,
-> 1152 feed_dict_tensor, options, run_metadata)
1153 else:
1154 results = []
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1326 if handle is None:
1327 return self._do_call(_run_fn, feeds, fetches, targets, options,
-> 1328 run_metadata)
1329 else:
1330 return self._do_call(_prun_fn, handle, feeds, fetches)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1346 pass
1347 message = error_interpolation.interpolate(message, self._graph)
-> 1348 raise type(e)(node_def, op, message)
1349
1350 def _extend_graph(self):
InvalidArgumentError: ConcatOp : Ranks of all input tensors should match: shape[0] = [1,2,2] vs. shape[1] = [1,2]
[[node while_1/concat (defined at <ipython-input-2-45e2bf149017>:18) ]]
Errors may have originated from an input operation.
Input Source operations connected to node while_1/concat:
Const_2 (defined at <ipython-input-2-45e2bf149017>:6)
strided_slice_2/stack (defined at <ipython-input-2-45e2bf149017>:9)
Const_3 (defined at <ipython-input-2-45e2bf149017>:7)
Original stack trace for 'while_1/concat':
File "/usr/lib/python3.6/runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "/usr/lib/python3.6/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py", line 16, in <module>
app.launch_new_instance()
File "/usr/local/lib/python3.6/dist-packages/traitlets/config/application.py", line 658, in launch_instance
app.start()
File "/usr/local/lib/python3.6/dist-packages/ipykernel/kernelapp.py", line 477, in start
ioloop.IOLoop.instance().start()
File "/usr/local/lib/python3.6/dist-packages/tornado/ioloop.py", line 888, in start
handler_func(fd_obj, events)
File "/usr/local/lib/python3.6/dist-packages/tornado/stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/zmq/eventloop/zmqstream.py", line 450, in _handle_events
self._handle_recv()
File "/usr/local/lib/python3.6/dist-packages/zmq/eventloop/zmqstream.py", line 480, in _handle_recv
self._run_callback(callback, msg)
File "/usr/local/lib/python3.6/dist-packages/zmq/eventloop/zmqstream.py", line 432, in _run_callback
callback(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/tornado/stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/ipykernel/kernelbase.py", line 283, in dispatcher
return self.dispatch_shell(stream, msg)
File "/usr/local/lib/python3.6/dist-packages/ipykernel/kernelbase.py", line 235, in dispatch_shell
handler(stream, idents, msg)
File "/usr/local/lib/python3.6/dist-packages/ipykernel/kernelbase.py", line 399, in execute_request
user_expressions, allow_stdin)
File "/usr/local/lib/python3.6/dist-packages/ipykernel/ipkernel.py", line 196, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/usr/local/lib/python3.6/dist-packages/ipykernel/zmqshell.py", line 533, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py", line 2718, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py", line 2822, in run_ast_nodes
if self.run_code(code, result):
File "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py", line 2882, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-2-45e2bf149017>", line 21, in <module>
u = tf.while_loop(cond, body, loop_vars=[step, yAll, yNew], shape_invariants=[step.get_shape(), yAll.get_shape() , yNew.get_shape()])
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/control_flow_ops.py", line 3560, in while_loop
return_same_structure)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/control_flow_ops.py", line 3089, in BuildLoop
pred, body, original_loop_vars, loop_vars, shape_invariants)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/control_flow_ops.py", line 3024, in _BuildLoop
body_result = body(*packed_vars_for_body)
File "<ipython-input-2-45e2bf149017>", line 18, in body
yAll = tf.concat( [[yAll], [yNew]], axis=0)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/util/dispatch.py", line 180, in wrapper
return target(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/array_ops.py", line 1256, in concat
return gen_array_ops.concat_v2(values=values, axis=axis, name=name)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/gen_array_ops.py", line 1149, in concat_v2
"ConcatV2", values=values, axis=axis, name=name)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/op_def_library.py", line 788, in _apply_op_helper
op_def=op_def)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/util/deprecation.py", line 501, in new_func
return func(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py", line 3300, in create_op
op_def=op_def)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py", line 1801, in __init__
self._traceback = tf_stack.extract_stack()
这是输出
testData = np.random.randint(0, 20, size=(4, 5 ))
print(testData)
testData2 = tf.convert_to_tensor(testData, dtype=tf.int64)
yAll = tf.py_func(lambda x, s: np.random.choice(x.reshape(-1),s, replace=False), [testData2[0], 2], tf.int64)
yNew = tf.py_func(lambda x, s: np.random.choice(x.reshape(-1),s, replace=False), [testData2[2], 2], tf.int64)
yAll = tf.concat( [[yAll], [yNew]], axis=0)
#Print data
with tf.Session( ) as sess:
sess.run(tf.global_variables_initializer())
print(sess.run([ yAll] ))
这里只是运行while循环，没有tf.while_loop，这很好用
[[ 6 13 10 7 17]
[17 13 8 1 3]
[ 6 18 0 12 0]
[14 14 0 19 19]]
[array([[ 7, 13],
[ 0, 0]])]
这是输出
testData = np.random.randint(0, 20, size=(4, 5 ))
print(testData)
testData2 = tf.convert_to_tensor(testData, dtype=tf.int64)
step = tf.constant(1)
yAll = tf.py_func(lambda x, s: np.random.choice(x.reshape(-1),s, replace=False), [testData2[0], 2], tf.int64)
yNew = tf.py_func(lambda x, s: np.random.choice(x.reshape(-1),s, replace=False), [testData2[0], 2], tf.int64)
def cond(step, yAll, yNew):
return step < 4
def body(step, yAll, yNew):
p=7
print('huh')
yNew = tf.py_func(lambda x, s: np.random.choice(x.reshape(-1),s, replace=False), [testData2[step], 2], tf.int64)
# yAll = tf.concat( [[yAll], [yNew]], axis=0)
return step + 1, yAll, yNew
u = tf.while_loop(cond, body, loop_vars=[step, yAll, yNew], shape_invariants=[step.get_shape(), yAll.get_shape() , yNew.get_shape()])
#Print data
with tf.Session( ) as sess:
sess.run(tf.global_variables_initializer())
print(sess.run([ u] ))
因此，以某种方式在tf while循环中组合tf concat操作会导致错误，也许是循环以某种方式转换了数据，但不确定它到底在做什么。
答案 0 :(得分：0)
while循环的第一次迭代工作正常，因为yAll和yNew的形状相同
yAll = tf.concat( [[yAll], [yNew]], axis=0)
但是，在此之后，yAll会得到一个与yNew不同的新形状。因此，在第一步之后，应改为
yAll = tf.concat( [yAll, [yNew]], axis=0)
对于while循环，我通过使用
解决了此问题yAll = tf.cond(step < 2, lambda: tf.concat( [[yAll], [yNew]], axis=0), lambda:tf.concat( [yAll, [yNew]], axis=0))