slice_input_producer（q.deque（））が動作しない

Question

slice_input_producer（）の引数はTensorなので、q.dequeue（）をslice_input_producer（）に渡しましたが、slice_input_producerはただちにキューを閉じます（私はそれが内部キューまたは私のq）。

何かがエンキューされるまでハングすることが予想されました。このコードは、動的テンソルとinput_producerの未定義の動作を再現

INFO:tensorflow:Error reported to Coordinator: <class 'tensorflow.python.framework.errors_impl.InvalidArgumentError'>, slice index 0 of dimension 0 out of bounds. 
    [[Node: input_producer/strided_slice = StridedSlice[Index=DT_INT32, T=DT_INT32, begin_mask=0, ellipsis_mask=0, end_mask=0, new_axis_mask=0, shrink_axis_mask=1, _device="/job:localhost/replica:0/task:0/gpu:0"](input_producer/Shape/_1, input_producer/strided_slice/stack, input_producer/strided_slice/stack_1, input_producer/strided_slice/stack_2)]] 
    [[Node: input_producer/input_producer/range/_3 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_13_input_producer/input_producer/range", tensor_type=DT_INT32, _device="/job:localhost/replica:0/task:0/cpu:0"]()]] 

Caused by op 'input_producer/strided_slice', defined at: 
    File "/usr/lib/python3.5/runpy.py", line 184, in _run_module_as_main 
    "__main__", mod_spec) 
    File "/usr/lib/python3.5/runpy.py", line 85, in _run_code 
    exec(code, run_globals) 
    File "/usr/local/lib/python3.5/dist-packages/ipykernel/__main__.py", line 3, in <module> 
    app.launch_new_instance() 
    File "/usr/local/lib/python3.5/dist-packages/traitlets/config/application.py", line 658, in launch_instance 
    app.start() 
    File "/usr/local/lib/python3.5/dist-packages/ipykernel/kernelapp.py", line 474, in start 
    ioloop.IOLoop.instance().start() 
    File "/usr/local/lib/python3.5/dist-packages/zmq/eventloop/ioloop.py", line 177, in start 
    super(ZMQIOLoop, self).start() 
    File "/usr/local/lib/python3.5/dist-packages/tornado/ioloop.py", line 887, in start 
    handler_func(fd_obj, events) 
    File "/usr/local/lib/python3.5/dist-packages/tornado/stack_context.py", line 275, in null_wrapper 
    return fn(*args, **kwargs) 
    File "/usr/local/lib/python3.5/dist-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events 
    self._handle_recv() 
    File "/usr/local/lib/python3.5/dist-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv 
    self._run_callback(callback, msg) 
    File "/usr/local/lib/python3.5/dist-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback 
    callback(*args, **kwargs) 
    File "/usr/local/lib/python3.5/dist-packages/tornado/stack_context.py", line 275, in null_wrapper 
    return fn(*args, **kwargs) 
    File "/usr/local/lib/python3.5/dist-packages/ipykernel/kernelbase.py", line 276, in dispatcher 
    return self.dispatch_shell(stream, msg) 
    File "/usr/local/lib/python3.5/dist-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell 
    handler(stream, idents, msg) 
    File "/usr/local/lib/python3.5/dist-packages/ipykernel/kernelbase.py", line 390, in execute_request 
    user_expressions, allow_stdin) 
    File "/usr/local/lib/python3.5/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/python3.5/dist-packages/ipykernel/zmqshell.py", line 501, in run_cell 
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs) 
    File "/usr/local/lib/python3.5/dist-packages/IPython/core/interactiveshell.py", line 2717, in run_cell 
    interactivity=interactivity, compiler=compiler, result=result) 
    File "/usr/local/lib/python3.5/dist-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes 
    if self.run_code(code, result): 
    File "/usr/local/lib/python3.5/dist-packages/IPython/core/interactiveshell.py", line 2881, in run_code 
    exec(code_obj, self.user_global_ns, self.user_ns) 
    File "<ipython-input-2-f15ef75111e3>", line 4, in <module> 
    producer = tf.train.slice_input_producer([deq], shuffle=False) 
    File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/input.py", line 300, in slice_input_producer 
    range_size = array_ops.shape(tensor_list[0])[0] 
    File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/array_ops.py", line 482, in _SliceHelper 
    name=name) 
    File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/array_ops.py", line 636, in strided_slice 
    shrink_axis_mask=shrink_axis_mask) 
    File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/gen_array_ops.py", line 3503, in strided_slice 
    shrink_axis_mask=shrink_axis_mask, name=name) 
    File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/op_def_library.py", line 759, in apply_op 
    op_def=op_def) 
    File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 2240, in create_op 
    original_op=self._default_original_op, op_def=op_def) 
    File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 1128, in __init__ 
    self._traceback = _extract_stack() 

InvalidArgumentError (see above for traceback): slice index 0 of dimension 0 out of bounds. 
    [[Node: input_producer/strided_slice = StridedSlice[Index=DT_INT32, T=DT_INT32, begin_mask=0, ellipsis_mask=0, end_mask=0, new_axis_mask=0, shrink_axis_mask=1, _device="/job:localhost/replica:0/task:0/gpu:0"](input_producer/Shape/_1, input_producer/strided_slice/stack, input_producer/strided_slice/stack_1, input_producer/strided_slice/stack_2)]] 
    [[Node: input_producer/input_producer/range/_3 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_13_input_producer/input_producer/range", tensor_type=DT_INT32, _device="/job:localhost/replica:0/task:0/cpu:0"]()]] 

---

更新

：

import tensorflow as tf 

q = tf.FIFOQueue(capacity=1000, dtypes=tf.int32) 
enq = q.enqueue(3) 
deq = q.dequeue() 
producer = tf.train.slice_input_producer([deq], shuffle=False) 


sess = tf.Session() 

sess.run([tf.global_variables_initializer(), tf.local_variables_initializer()]) 

print(sess.run(enq)) 
print('enqueued') 

coord = tf.train.Coordinator() 
threads = tf.train.start_queue_runners(sess, coord) 

print(sess.run(producer)) 
print('got slice_input_producer') 

coord.request_stop() 
coord.join(threads) 

sess.close() 

は、しかし、これはエラーを得ました。

import tensorflow as tf 
import numpy as np 
q = tf.FIFOQueue(capacity=1000, dtypes=tf.int32, shapes=[1]) 
enq = q.enqueue_many(np.array([[3], [4], [5], [6], [7], [8]])) 
deq = q.dequeue_many(2) 
producer = tf.train.slice_input_producer([deq], shuffle=False) 


sess = tf.Session() 

sess.run([tf.global_variables_initializer(), tf.local_variables_initializer()]) 

sess.run(enq) 
print('enqueued') 

coord = tf.train.Coordinator() 
threads = tf.train.start_queue_runners(sess, coord) 

print('reading slice_input_producer') 
print(sess.run(producer)) 
print(sess.run(producer)) 

coord.request_stop() 
coord.join(threads) 

sess.close() 

結果：

enqueued 
reading slice_input_producer 
[array([3])] 
got slice_input_producer 
[array([6])] 
got slice_input_producer 

Answer 1

TL; DR：tf.train.slice_input_producer(tensor_list)からtensor_list引数でテンソルは、1（すなわち、ベクター）以上のランクを有していなければなりません。

tf.train.slice_input_producer()関数は、その入力テンソルを次元0の& mdashに沿ったスライスに分割し、一度に1つのスライスを生成します。たとえば、入力テンソルが行列の場合、行列の行が生成されます。

あなたの例では、tf.train.slice_input_producer()への入力はスカラーテンソルであり、それに沿ってスライスする次元0はありません。この値がキューから来るという事実は無関係です（しかし、キューに宣言されたシェイプがないので、グラフ構成–時間エラーではなくランタイムエラーが発生します）。以下の定義は等価であること、また、エラーを生成します：

producer = tf.train.slice_input_producer([3], shuffle=False) 

N.B.キューからtf.train.slice_input_producer()を定義すると予期しない結果が生じることがあります。特に、現在の実装では、スライスを消費するたびにtensor_listのテンソルが評価されます。これは静的なテンソルでうまく動作しますが、プログラムでは各スライスのキューから新しい要素をデキューします。これは意図したとおりではありません。