2017-03-29 8 views
1

私はこのようなnumpyの使用して、カスタム・プーリング層を実装している:tf.py_funcにテンソルフローグラフの中間結果を[inp]としてどのように入力するのですか?

def pooling_np(input): 
#input:[batch,h,v,channel] 
#output:[batch,h/2,v/2,channel] 
pooling = np.empty([input.shape[0], input.shape[1]/2, input.shape[2]/2, input.shape[3]]) 
for i_batch in range(input.shape[0]): 
    for j_channel in range(input.shape[-1]): 
     max_id = np.argmax(input[i_batch,:,:,j_channel]) 
     #[i_batch,max_h,max_v,j_channel] 
     max_h = max_id/input.shape[1] 
     max_v = max_id % input.shape[1] 
     #begin point:(left,up) 
     left = max(min(max_h - input.shape[1]/4, input.shape[1]/2), 0) 
     up = max(min(max_v - input.shape[2]/4, input.shape[2]/2), 0) 
     pooling[i_batch,:,:,j_channel] = input[i_batch,left:left+input.shape[1]/2,up:up+input.shape[2]/2,j_channel] 
return pooling 

それから私はこのようtf.py_funcを使用してtensorflow alexnetグラフにこの新しいプーリング層を組み込みたい:

with graph.as_default(): 
... 
#conv5 
#conv(3, 3, 256, 1, 1, group=2, name='conv5') 
k_h = 3; k_w = 3; c_o = 256; s_h = 1; s_w = 1; group = 2 
conv5W = tf.Variable(net_data["conv5"][0]) 
conv5b = tf.Variable(net_data["conv5"][1]) 
conv5_in = conv(conv4, conv5W, conv5b, k_h, k_w, c_o, s_h, s_w, padding="SAME", group=group) 
conv5 = tf.nn.relu(conv5_in) 

#newpool5:custom a new pooling layer 
newpool5 = tf.py_func(adaptive_pooling_np, [conv5], tf.float32) 
adaptivepool5.set_shape([conv5.get_shape()[0],conv5.get_shape()[1]/2,conv5.get_shape()[2]/2,conv5.get_shape()[-1]]) 
adaptivepool5 = tf.cast(adaptivepool5, tf.float32) 

#fc6 
#fc(4096, name='fc6') 
fc6W = tf.Variable(net_data["fc6"][0]) 
fc6b = tf.Variable(net_data["fc6"][1]) 
fc6 = tf.nn.relu_layer(tf.reshape(newpool5, [-1, int(prod(newpool5.get_shape()[1:]))]), fc6W, fc6b) 
... 
with tf.Session(graph=graph, config = config) as session: 
tf.global_variables_initializer().run() 
print('Initialized') 
t = time.time() 
feed_dict = {x:testset} 
output = session.run(prob, feed_dict = feed_dict) 

私はtf.placeholderを作成することができず、tfセッションの始めにグラフの中間値(ここではconv5)を送ることができないので、conv5をtf.py_funcの[inp]として使いたいと思います。

しかし、このようなエラーがあります:

Initialized 
--------------------------------------------------------------------------- 
InvalidArgumentError      Traceback (most recent call last) 
<ipython-input-19-2b38ea266e1a> in <module>() 
     6  t = time.time() 
     7  feed_dict = {x:testset} 
----> 8  output = session.run(prob, feed_dict = feed_dict) 
     9  #adaptivepooling5 = session.run(adappool5, feed_dict = feed_dict) 
    10  print(conv5.shape) 

/home/yifan/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in run(self, fetches, feed_dict, options, run_metadata) 
    765  try: 
    766  result = self._run(None, fetches, feed_dict, options_ptr, 
--> 767       run_metadata_ptr) 
    768  if run_metadata: 
    769   proto_data = tf_session.TF_GetBuffer(run_metadata_ptr) 

/home/yifan/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in _run(self, handle, fetches, feed_dict, options, run_metadata) 
    963  if final_fetches or final_targets: 
    964  results = self._do_run(handle, final_targets, final_fetches, 
--> 965        feed_dict_string, options, run_metadata) 
    966  else: 
    967  results = [] 

/home/yifan/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata) 
    1013  if handle is None: 
    1014  return self._do_call(_run_fn, self._session, feed_dict, fetch_list, 
-> 1015       target_list, options, run_metadata) 
    1016  else: 
    1017  return self._do_call(_prun_fn, self._session, handle, feed_dict, 

/home/yifan/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in _do_call(self, fn, *args) 
    1033   except KeyError: 
    1034   pass 
-> 1035  raise type(e)(node_def, op, message) 
    1036 
    1037 def _extend_graph(self): 

InvalidArgumentError: 0-th value returned by pyfunc_8 is double, but expects float 
    [[Node: PyFunc = PyFunc[Tin=[DT_FLOAT], Tout=[DT_FLOAT], token="pyfunc_8", _device="/job:localhost/replica:0/task:0/cpu:0"](Relu_4/_3)]] 
    [[Node: PyFunc/_5 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/gpu:0", send_device="/job:localhost/replica:0/task:0/cpu:0", send_device_incarnation=1, tensor_name="edge_86_PyFunc", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/gpu:0"]()]] 

Caused by op u'PyFunc', defined at: 
    File "/usr/lib/python2.7/runpy.py", line 174, in _run_module_as_main 
    "__main__", fname, loader, pkg_name) 
    File "/usr/lib/python2.7/runpy.py", line 72, in _run_code 
    exec code in run_globals 
    File "/usr/local/lib/python2.7/dist-packages/ipykernel/__main__.py", line 3, in <module> 
    app.launch_new_instance() 
    File "/usr/local/lib/python2.7/dist-packages/traitlets/config/application.py", line 658, in launch_instance 
    app.start() 
    File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelapp.py", line 474, in start 
    ioloop.IOLoop.instance().start() 
    File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/ioloop.py", line 177, in start 
    super(ZMQIOLoop, self).start() 
    File "/usr/local/lib/python2.7/dist-packages/tornado/ioloop.py", line 887, in start 
    handler_func(fd_obj, events) 
    File "/usr/local/lib/python2.7/dist-packages/tornado/stack_context.py", line 275, in null_wrapper 
    return fn(*args, **kwargs) 
    File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events 
    self._handle_recv() 
    File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv 
    self._run_callback(callback, msg) 
    File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback 
    callback(*args, **kwargs) 
    File "/usr/local/lib/python2.7/dist-packages/tornado/stack_context.py", line 275, in null_wrapper 
    return fn(*args, **kwargs) 
    File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelbase.py", line 276, in dispatcher 
    return self.dispatch_shell(stream, msg) 
    File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell 
    handler(stream, idents, msg) 
    File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelbase.py", line 390, in execute_request 
    user_expressions, allow_stdin) 
    File "/usr/local/lib/python2.7/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/python2.7/dist-packages/ipykernel/zmqshell.py", line 501, in run_cell 
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs) 
    File "/usr/local/lib/python2.7/dist-packages/IPython/core/interactiveshell.py", line 2717, in run_cell 
    interactivity=interactivity, compiler=compiler, result=result) 
    File "/usr/local/lib/python2.7/dist-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes 
    if self.run_code(code, result): 
    File "/usr/local/lib/python2.7/dist-packages/IPython/core/interactiveshell.py", line 2881, in run_code 
    exec(code_obj, self.user_global_ns, self.user_ns) 
    File "<ipython-input-17-90b8573e003c>", line 91, in <module> 
    adaptivepool5 = tf.py_func(adaptive_pooling_np, [conv5], tf.float32) 
    File "/home/yifan/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/ops/script_ops.py", line 189, in py_func 
    input=inp, token=token, Tout=Tout, name=name) 
    File "/home/yifan/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/ops/gen_script_ops.py", line 40, in _py_func 
    name=name) 
    File "/home/yifan/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 763, in apply_op 
    op_def=op_def) 
    File "/home/yifan/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2327, in create_op 
    original_op=self._default_original_op, op_def=op_def) 
    File "/home/yifan/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1226, in __init__ 
    self._traceback = _extract_stack() 

InvalidArgumentError (see above for traceback): 0-th value returned by pyfunc_8 is double, but expects float 
    [[Node: PyFunc = PyFunc[Tin=[DT_FLOAT], Tout=[DT_FLOAT], token="pyfunc_8", _device="/job:localhost/replica:0/task:0/cpu:0"](Relu_4/_3)]] 
    [[Node: PyFunc/_5 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/gpu:0", send_device="/job:localhost/replica:0/task:0/cpu:0", send_device_incarnation=1, tensor_name="edge_86_PyFunc", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/gpu:0"]()]] 

私はtensorflowにこのnumpyの機能を使用するにはどうすればよいですか?

答えて

1

py_funcは、tf.float32の代わりにtf.float64を返します。これは、宣言された型です。

newpool5 = tf.py_func(adaptive_pooling_np, [conv5], tf.float64) 

と物事を言うために

変更ラインは罰金になります。

+0

ありがとうございました。 :-) – Evan

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