When I run your Recurrent Neural Network.ipynb, I get the following error:
InvalidArgumentError Traceback (most recent call last)
~/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1321 try:
-> 1322 return fn(*args)
1323 except errors.OpError as e:
~/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/client/session.py in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
1304 # Ensure any changes to the graph are reflected in the runtime.
-> 1305 self._extend_graph()
1306 return self._call_tf_sessionrun(
~/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/client/session.py in _extend_graph(self)
1339 with self._graph._lock: # pylint: disable=protected-access
-> 1340 tf_session.ExtendSession(self._session)
1341 else:
InvalidArgumentError: No OpKernel was registered to support Op 'CudnnRNN' with these attrs. Registered devices: [CPU], Registered kernels:
<no registered kernels>
[[Node: cu_dnnlstm/CudnnRNN = CudnnRNN[T=DT_FLOAT, direction="unidirectional", dropout=0, input_mode="linear_input", is_training=true, rnn_mode="lstm", seed=0, seed2=0](cu_dnnlstm/transpose, cu_dnnlstm/ExpandDims_1, cu_dnnlstm/ExpandDims_2, cu_dnnlstm/concat)]]
During handling of the above exception, another exception occurred:
InvalidArgumentError Traceback (most recent call last)
<ipython-input-14-29326f3cbcc3> in <module>
8 steps_per_epoch=np.ceil(epoch_size/batch_size),
9 epochs=3)
---> 10 model.fit(X_train, y_train, callbacks=[lr_finder])
11
12 lr_finder.plot_loss()
~/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/keras/engine/training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, **kwargs)
1346 initial_epoch=initial_epoch,
1347 steps_per_epoch=steps_per_epoch,
-> 1348 validation_steps=validation_steps)
1349
1350 def evaluate(self,
~/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/keras/engine/training_arrays.py in fit_loop(model, inputs, targets, sample_weights, batch_size, epochs, verbose, callbacks, val_inputs, val_targets, val_sample_weights, shuffle, callback_metrics, initial_epoch, steps_per_epoch, validation_steps)
166 'metrics': callback_metrics or [],
167 })
--> 168 callbacks.on_train_begin()
169 callback_model.stop_training = False
170 for cbk in callbacks:
~/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/keras/callbacks.py in on_train_begin(self, logs)
145 logs = logs or {}
146 for callback in self.callbacks:
--> 147 callback.on_train_begin(logs)
148
149 def on_train_end(self, logs=None):
<ipython-input-10-98122f67f6ac> in on_train_begin(self, logs)
43 '''Initialize the learning rate to the minimum value at the start of training.'''
44 logs = logs or {}
---> 45 K.set_value(self.model.optimizer.lr, self.min_lr)
46
47 def on_batch_end(self, epoch, logs=None):
~/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/keras/backend.py in set_value(x, value)
2682 x._assign_placeholder = assign_placeholder
2683 x._assign_op = assign_op
-> 2684 get_session().run(assign_op, feed_dict={assign_placeholder: value})
2685
2686
~/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/keras/backend.py in get_session()
441 if not _MANUAL_VAR_INIT:
442 with session.graph.as_default():
--> 443 _initialize_variables(session)
444 return session
445
~/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/keras/backend.py in _initialize_variables(session)
665 # marked as initialized.
666 is_initialized = session.run(
--> 667 [variables_module.is_variable_initialized(v) for v in candidate_vars])
668 uninitialized_vars = []
669 for flag, v in zip(is_initialized, candidate_vars):
~/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
898 try:
899 result = self._run(None, fetches, feed_dict, options_ptr,
--> 900 run_metadata_ptr)
901 if run_metadata:
902 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
~/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
1133 if final_fetches or final_targets or (handle and feed_dict_tensor):
1134 results = self._do_run(handle, final_targets, final_fetches,
-> 1135 feed_dict_tensor, options, run_metadata)
1136 else:
1137 results = []
~/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1314 if handle is None:
1315 return self._do_call(_run_fn, feeds, fetches, targets, options,
-> 1316 run_metadata)
1317 else:
1318 return self._do_call(_prun_fn, handle, feeds, fetches)
~/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1333 except KeyError:
1334 pass
-> 1335 raise type(e)(node_def, op, message)
1336
1337 def _extend_graph(self):
InvalidArgumentError: No OpKernel was registered to support Op 'CudnnRNN' with these attrs. Registered devices: [CPU], Registered kernels:
<no registered kernels>
[[Node: cu_dnnlstm/CudnnRNN = CudnnRNN[T=DT_FLOAT, direction="unidirectional", dropout=0, input_mode="linear_input", is_training=true, rnn_mode="lstm", seed=0, seed2=0](cu_dnnlstm/transpose, cu_dnnlstm/ExpandDims_1, cu_dnnlstm/ExpandDims_2, cu_dnnlstm/concat)]]
Caused by op 'cu_dnnlstm/CudnnRNN', defined at:
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/runpy.py", line 170, in _run_module_as_main
"__main__", mod_spec)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/ipykernel_launcher.py", line 16, in <module>
app.launch_new_instance()
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/traitlets/config/application.py", line 658, in launch_instance
app.start()
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/ipykernel/kernelapp.py", line 505, in start
self.io_loop.start()
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tornado/platform/asyncio.py", line 132, in start
self.asyncio_loop.run_forever()
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/asyncio/base_events.py", line 301, in run_forever
self._run_once()
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/asyncio/base_events.py", line 1198, in _run_once
handle._run()
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/asyncio/events.py", line 125, in _run
self._callback(*self._args)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tornado/ioloop.py", line 758, in _run_callback
ret = callback()
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tornado/stack_context.py", line 300, in null_wrapper
return fn(*args, **kwargs)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tornado/gen.py", line 1233, in inner
self.run()
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tornado/gen.py", line 1147, in run
yielded = self.gen.send(value)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 357, in process_one
yield gen.maybe_future(dispatch(*args))
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tornado/gen.py", line 326, in wrapper
yielded = next(result)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 267, in dispatch_shell
yield gen.maybe_future(handler(stream, idents, msg))
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tornado/gen.py", line 326, in wrapper
yielded = next(result)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 534, in execute_request
user_expressions, allow_stdin,
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tornado/gen.py", line 326, in wrapper
yielded = next(result)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/ipykernel/ipkernel.py", line 294, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/ipykernel/zmqshell.py", line 536, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2819, in run_cell
raw_cell, store_history, silent, shell_futures)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2845, in _run_cell
return runner(coro)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/IPython/core/async_helpers.py", line 67, in _pseudo_sync_runner
coro.send(None)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 3020, in run_cell_async
interactivity=interactivity, compiler=compiler, result=result)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 3185, in run_ast_nodes
if (yield from self.run_code(code, result)):
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 3267, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-12-671884cecb64>", line 1, in <module>
model = build_model()
File "<ipython-input-11-a59f75026d23>", line 3, in build_model
model.add(CuDNNLSTM(256, input_shape=(X_train.shape[1:]), return_sequences=True))
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/keras/engine/sequential.py", line 163, in add
layer(x)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/keras/layers/recurrent.py", line 527, in __call__
return super(RNN, self).__call__(inputs, **kwargs)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/keras/engine/base_layer.py", line 703, in __call__
outputs = self.call(inputs, *args, **kwargs)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/keras/layers/cudnn_recurrent.py", line 109, in call
output, states = self._process_batch(inputs, initial_state)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/keras/layers/cudnn_recurrent.py", line 493, in _process_batch
is_training=True)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/ops/gen_cudnn_rnn_ops.py", line 115, in cudnn_rnn
is_training=is_training, name=name)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 3414, in create_op
op_def=op_def)
File "/home/zh/anaconda3/envs/AdaNet/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1740, in __init__
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access
InvalidArgumentError (see above for traceback): No OpKernel was registered to support Op 'CudnnRNN' with these attrs. Registered devices: [CPU], Registered kernels:
<no registered kernels>
[[Node: cu_dnnlstm/CudnnRNN = CudnnRNN[T=DT_FLOAT, direction="unidirectional", dropout=0, input_mode="linear_input", is_training=true, rnn_mode="lstm", seed=0, seed2=0](cu_dnnlstm/transpose, cu_dnnlstm/ExpandDims_1, cu_dnnlstm/ExpandDims_2, cu_dnnlstm/concat)]]
My environment is:
Tensorflow==1.9
Keras==2.2.4
@BenjiKCF
What is the cause of this? What should I do? There is no environmental requirement in your description.
BenjiKCF
commented
5 years ago
When I run your Recurrent Neural Network.ipynb, I get the following error:
My environment is: Tensorflow==1.9 Keras==2.2.4
@BenjiKCF What is the cause of this? What should I do? There is no environmental requirement in your description.