Question

我的Keras模型的BatchNormalization层（使用Tensorflow）不起作用，并且在训练时返回了InternalError异常。

这是在我的模型中定义BatchNormalization层的行：

bn = BatchNormalization(axis=3)(grid)

我创建2个模型（之前1个，之后1个）以调试模型：

debug = Model(inputs=[question1, question2], outputs=grid)
debug.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])

bn = BatchNormalization(axis=3)(grid)

debug2 = Model(inputs=[question1, question2], outputs=bn)
debug2.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])

然后我预测一些随机数据，只是为了实际预测任何东西：

pred = debug.predict([Q1_test_debug, Q2_test_debug], verbose=1, batch_size=1)
print(pred[0].shape)
pred = debug2.predict([Q1_test_debug, Q2_test_debug], verbose=1, batch_size=1)
print(pred[0].shape)

结果是：

(2, 25)
2/2 [==============================] - 2s 1s/step
(25, 25, 600)
---------------------------------------------------------------------------
InternalError                             Traceback (most recent call last)
~/.local/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
   1291     try:
-> 1292       return fn(*args)
   1293     except errors.OpError as e:

~/.local/lib/python3.5/site-packages/tensorflow/python/client/session.py in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
   1276       return self._call_tf_sessionrun(
-> 1277           options, feed_dict, fetch_list, target_list, run_metadata)
   1278 

~/.local/lib/python3.5/site-packages/tensorflow/python/client/session.py in _call_tf_sessionrun(self, options, feed_dict, fetch_list, target_list, run_metadata)
   1366         self._session, options, feed_dict, fetch_list, target_list,
-> 1367         run_metadata)
   1368 

InternalError: cuDNN launch failure : input shape ([1,600,25,25])
     [[{{node batch_normalization_1/FusedBatchNorm}} = FusedBatchNorm[T=DT_FLOAT, _class=["loc:@batch_normalization_1/cond/Switch_1"], data_format="NCHW", epsilon=0.001, is_training=true, _device="/job:localhost/replica:0/task:0/device:GPU:0"](batch_normalization_1/FusedBatchNorm-0-TransposeNHWCToNCHW-LayoutOptimizer, batch_normalization_1/gamma/read, batch_normalization_1/beta/read, batch_normalization_1/Const_4, batch_normalization_1/Const_4)]]
     [[{{node batch_normalization_1/cond/Merge/_949}} = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_133_batch_normalization_1/cond/Merge", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]

During handling of the above exception, another exception occurred:

InternalError                             Traceback (most recent call last)
<ipython-input-11-748dc132eac2> in <module>()
      4 pred = debug.predict([Q1_test_debug, Q2_test_debug], verbose=1, batch_size=1)
      5 print(pred[0].shape)
----> 6 pred = debug2.predict([Q1_test_debug, Q2_test_debug], verbose=1, batch_size=1)
      7 print(pred[0].shape)

~/.local/lib/python3.5/site-packages/keras/engine/training.py in predict(self, x, batch_size, verbose, steps)
   1833         f = self.predict_function
   1834         return self._predict_loop(f, ins, batch_size=batch_size,
-> 1835                                   verbose=verbose, steps=steps)
   1836 
   1837     def train_on_batch(self, x, y,

~/.local/lib/python3.5/site-packages/keras/engine/training.py in _predict_loop(self, f, ins, batch_size, verbose, steps)
   1329                     ins_batch[i] = ins_batch[i].toarray()
   1330 
-> 1331                 batch_outs = f(ins_batch)
   1332                 if not isinstance(batch_outs, list):
   1333                     batch_outs = [batch_outs]

~/.local/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py in __call__(self, inputs)
   2480         session = get_session()
   2481         updated = session.run(fetches=fetches, feed_dict=feed_dict,
-> 2482                               **self.session_kwargs)
   2483         return updated[:len(self.outputs)]
   2484 

~/.local/lib/python3.5/site-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
    885     try:
    886       result = self._run(None, fetches, feed_dict, options_ptr,
--> 887                          run_metadata_ptr)
    888       if run_metadata:
    889         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

~/.local/lib/python3.5/site-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
   1108     if final_fetches or final_targets or (handle and feed_dict_tensor):
   1109       results = self._do_run(handle, final_targets, final_fetches,
-> 1110                              feed_dict_tensor, options, run_metadata)
   1111     else:
   1112       results = []

~/.local/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
   1284     if handle is None:
   1285       return self._do_call(_run_fn, feeds, fetches, targets, options,
-> 1286                            run_metadata)
   1287     else:
   1288       return self._do_call(_prun_fn, handle, feeds, fetches)

~/.local/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
   1306           self._config.experimental.client_handles_error_formatting):
   1307         message = error_interpolation.interpolate(message, self._graph)
-> 1308       raise type(e)(node_def, op, message)
   1309 
   1310   def _extend_graph(self):

InternalError: cuDNN launch failure : input shape ([1,600,25,25])
     [[{{node batch_normalization_1/FusedBatchNorm}} = FusedBatchNorm[T=DT_FLOAT, _class=["loc:@batch_normalization_1/cond/Switch_1"], data_format="NCHW", epsilon=0.001, is_training=true, _device="/job:localhost/replica:0/task:0/device:GPU:0"](batch_normalization_1/FusedBatchNorm-0-TransposeNHWCToNCHW-LayoutOptimizer, batch_normalization_1/gamma/read, batch_normalization_1/beta/read, batch_normalization_1/Const_4, batch_normalization_1/Const_4)]]
     [[{{node batch_normalization_1/cond/Merge/_949}} = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_133_batch_normalization_1/cond/Merge", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]

Caused by op 'batch_normalization_1/FusedBatchNorm', 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 "/home/remondn/.local/lib/python3.5/site-packages/ipykernel_launcher.py", line 16, in <module>
    app.launch_new_instance()
  File "/home/remondn/.local/lib/python3.5/site-packages/traitlets/config/application.py", line 658, in launch_instance
    app.start()
  File "/home/remondn/.local/lib/python3.5/site-packages/ipykernel/kernelapp.py", line 497, in start
    self.io_loop.start()
  File "/home/remondn/.local/lib/python3.5/site-packages/tornado/platform/asyncio.py", line 132, in start
    self.asyncio_loop.run_forever()
  File "/usr/lib/python3.5/asyncio/base_events.py", line 345, in run_forever
    self._run_once()
  File "/usr/lib/python3.5/asyncio/base_events.py", line 1312, in _run_once
    handle._run()
  File "/usr/lib/python3.5/asyncio/events.py", line 125, in _run
    self._callback(*self._args)
  File "/home/remondn/.local/lib/python3.5/site-packages/tornado/platform/asyncio.py", line 122, in _handle_events
    handler_func(fileobj, events)
  File "/home/remondn/.local/lib/python3.5/site-packages/tornado/stack_context.py", line 300, in null_wrapper
    return fn(*args, **kwargs)
  File "/home/remondn/.local/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 450, in _handle_events
    self._handle_recv()
  File "/home/remondn/.local/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 480, in _handle_recv
    self._run_callback(callback, msg)
  File "/home/remondn/.local/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 432, in _run_callback
    callback(*args, **kwargs)
  File "/home/remondn/.local/lib/python3.5/site-packages/tornado/stack_context.py", line 300, in null_wrapper
    return fn(*args, **kwargs)
  File "/home/remondn/.local/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 283, in dispatcher
    return self.dispatch_shell(stream, msg)
  File "/home/remondn/.local/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 233, in dispatch_shell
    handler(stream, idents, msg)
  File "/home/remondn/.local/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 399, in execute_request
    user_expressions, allow_stdin)
  File "/home/remondn/.local/lib/python3.5/site-packages/ipykernel/ipkernel.py", line 208, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "/home/remondn/.local/lib/python3.5/site-packages/ipykernel/zmqshell.py", line 537, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "/home/remondn/.local/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2662, in run_cell
    raw_cell, store_history, silent, shell_futures)
  File "/home/remondn/.local/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2785, in _run_cell
    interactivity=interactivity, compiler=compiler, result=result)
  File "/home/remondn/.local/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2901, in run_ast_nodes
    if self.run_code(code, result):
  File "/home/remondn/.local/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2961, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-10-44a967130b40>", line 87, in <module>
    bn = BatchNormalization(axis=3)(grid)
  File "/home/remondn/.local/lib/python3.5/site-packages/keras/engine/topology.py", line 619, in __call__
    output = self.call(inputs, **kwargs)
  File "/home/remondn/.local/lib/python3.5/site-packages/keras/layers/normalization.py", line 181, in call
    epsilon=self.epsilon)
  File "/home/remondn/.local/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py", line 1831, in normalize_batch_in_training
    epsilon=epsilon)
  File "/home/remondn/.local/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py", line 1806, in _fused_normalize_batch_in_training
    data_format=tf_data_format)
  File "/home/remondn/.local/lib/python3.5/site-packages/tensorflow/python/ops/nn_impl.py", line 909, in fused_batch_norm
    name=name)
  File "/home/remondn/.local/lib/python3.5/site-packages/tensorflow/python/ops/gen_nn_ops.py", line 3466, in _fused_batch_norm
    is_training=is_training, name=name)
  File "/home/remondn/.local/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
    op_def=op_def)
  File "/home/remondn/.local/lib/python3.5/site-packages/tensorflow/python/util/deprecation.py", line 488, in new_func
    return func(*args, **kwargs)
  File "/home/remondn/.local/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 3272, in create_op
    op_def=op_def)
  File "/home/remondn/.local/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1768, in __init__
    self._traceback = tf_stack.extract_stack()

InternalError (see above for traceback): cuDNN launch failure : input shape ([1,600,25,25])
     [[{{node batch_normalization_1/FusedBatchNorm}} = FusedBatchNorm[T=DT_FLOAT, _class=["loc:@batch_normalization_1/cond/Switch_1"], data_format="NCHW", epsilon=0.001, is_training=true, _device="/job:localhost/replica:0/task:0/device:GPU:0"](batch_normalization_1/FusedBatchNorm-0-TransposeNHWCToNCHW-LayoutOptimizer, batch_normalization_1/gamma/read, batch_normalization_1/beta/read, batch_normalization_1/Const_4, batch_normalization_1/Const_4)]]
     [[{{node batch_normalization_1/cond/Merge/_949}} = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_133_batch_normalization_1/cond/Merge", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]

我不明白的几件事：

我们可以看到（(25, 25, 600)），上一层的输出/ BatchNormalization输入的格式为channels_last。但是错误报告input shape ([1,600,25,25])的格式为channels_first。为什么突然改变了？
我在BatchNormalization层的声明axis = 3中进行了指定，但是在错误中，我们有FusedBatchNorm [...] data_format="NCHW"，表示channels_first格式。无论我选择哪个轴（我尝试过1、2、0，-1），此data_format都会出现此错误。更改BatchNormalization的轴时未更改的内容

有人知道如何解决此问题吗？

Answer 1

结果是，我正在使用的库版本被弄乱了。

我不知道为什么，但是其他所有东西都在工作（实际上，删除BatchNormalization层导致网络正常工作...）

无论如何，我更新了程序包以将CUDA 9.0与cuDNN 7.0.5和tensorflow-gpu 1.10.0一起使用

我用来获取所有这些版本之间匹配版本的链接：

Tensorflow-gpu versions
List of cuDNN versions depending on CUDA version（需要nvidia开发者帐户）

Answer 2

我进入此线程是因为遇到类似的错误。事实证明，它已链接到我的新硬件，对于库而言太新。因此，使用2080 RTX Ti，我可以通过以下配置摆脱错误：

Cuda 10.0（与其架构兼容）
CuDNN 7.4.1.5
tensorflow 1.13（当时的候选版本，我使用了“ pip3 install tf-nightly-gpu”，支持cuda 10.0的版本）
我在代码中添加了以下内容（请参见https://github.com/tensorflow/tensorflow/issues/24496）：

PROCEDURE update_subscriber_config (p_app_id             VARCHAR2,
                                    p_service_id         VARCHAR2,
                                    p_pubsub_id          VARCHAR2,
                                    p_first_column       VARCHAR2,
                                    p_second_column      VARCHAR2,
                                    --column_list     string_array,
                                    i_array           IN my_array_type)
AS
BEGIN
   FORALL i IN 1 .. i_array.COUNT
      UPDATE bolt_oracle_pubsub_config
         SET your_first_column =
                TREAT (i_array (i) AS my_array_type).column_array_name,
             your_second_column =
                TREAT (i_array (i) AS my_array_type).second_column_array_name
       WHERE     APP_ID = p_app_id
             AND SERVICE_ID = p_service_id
             AND PUBSUB_ID = p_pubsub_id;

END update_subscriber_config;

希望它对其他人有帮助。

Answer 3

我有同样的问题，但事实证明这是由于内存不足所致。我的模型太大。当我减少batch size时，问题就解决了。

Keras BatchNormalization层：InternalError：cuDNN启动失败

3 个答案: