TypeError: while_loop() got an unexpected keyword argument 'maximum_iterations'

[SeekPoint]

(venv) mldl@mldlUB1604:~/ub16_prj/Named-Entity-Recognition-with-Bidirectional-LSTM-CNNs$ python3 nn.py
Using TensorFlow backend.
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcublas.so.8.0 locally
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcudnn.so.5 locally
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcufft.so.8.0 locally
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcurand.so.8.0 locally
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:910] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
I tensorflow/core/common_runtime/gpu/gpu_device.cc:885] Found device 0 with properties:
name: GeForce GTX 950M
major: 5 minor: 0 memoryClockRate (GHz) 1.124
pciBusID 0000:01:00.0
Total memory: 3.95GiB
Free memory: 3.56GiB
I tensorflow/core/common_runtime/gpu/gpu_device.cc:906] DMA: 0
I tensorflow/core/common_runtime/gpu/gpu_device.cc:916] 0: Y
I tensorflow/core/common_runtime/gpu/gpu_device.cc:975] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 950M, pci bus id: 0000:01:00.0)
Traceback (most recent call last):
File "nn.py", line 109, in
output = Bidirectional(LSTM(200, return_sequences=True, dropout=0.50, recurrent_dropout=0.25))(output)
File "/home/mldl/ub16_prj/VENV_host/py3tf1.0/venv/lib/python3.5/site-packages/keras/layers/wrappers.py", line 426, in call
return super(Bidirectional, self).call(inputs, **kwargs)
File "/home/mldl/ub16_prj/VENV_host/py3tf1.0/venv/lib/python3.5/site-packages/keras/engine/base_layer.py", line 460, in call
output = self.call(inputs, **kwargs)
File "/home/mldl/ub16_prj/VENV_host/py3tf1.0/venv/lib/python3.5/site-packages/keras/layers/wrappers.py", line 504, in call
y = self.forward_layer.call(inputs, **kwargs)
File "/home/mldl/ub16_prj/VENV_host/py3tf1.0/venv/lib/python3.5/site-packages/keras/layers/recurrent.py", line 2112, in call
initial_state=initial_state)
File "/home/mldl/ub16_prj/VENV_host/py3tf1.0/venv/lib/python3.5/site-packages/keras/layers/recurrent.py", line 609, in call
input_length=timesteps)
File "/home/mldl/ub16_prj/VENV_host/py3tf1.0/venv/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py", line 2957, in rnn
maximum_iterations=input_length)
TypeError: while_loop() got an unexpected keyword argument 'maximum_iterations'

[kamalkraj]

Use Keras 2.1.2 Tensorflow 1.4.1

…

On Sat 7 Jul, 2018, 6:35 PM yk_data, ***@***.***> wrote: (venv) ***@***.***:~/ub16_prj/Named-Entity-Recognition-with-Bidirectional-LSTM-CNNs$ python3 nn.py Using TensorFlow backend. I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcublas.so.8.0 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcudnn.so.5 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcufft.so.8.0 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcuda.so.1 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcurand.so.8.0 locally W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations. I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:910] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero I tensorflow/core/common_runtime/gpu/gpu_device.cc:885] Found device 0 with properties: name: GeForce GTX 950M major: 5 minor: 0 memoryClockRate (GHz) 1.124 pciBusID 0000:01:00.0 Total memory: 3.95GiB Free memory: 3.56GiB I tensorflow/core/common_runtime/gpu/gpu_device.cc:906] DMA: 0 I tensorflow/core/common_runtime/gpu/gpu_device.cc:916] 0: Y I tensorflow/core/common_runtime/gpu/gpu_device.cc:975] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 950M, pci bus id: 0000:01:00.0) Traceback (most recent call last): File "nn.py", line 109, in output = Bidirectional(LSTM(200, return_sequences=True, dropout=0.50, recurrent_dropout=0.25))(output) File "/home/mldl/ub16_prj/VENV_host/py3tf1.0/venv/lib/python3.5/site-packages/keras/layers/wrappers.py", line 426, in *call* return super(Bidirectional, self).*call*(inputs, **kwargs) File "/home/mldl/ub16_prj/VENV_host/py3tf1.0/venv/lib/python3.5/site-packages/keras/engine/base_layer.py", line 460, in *call* output = self.call(inputs, **kwargs) File "/home/mldl/ub16_prj/VENV_host/py3tf1.0/venv/lib/python3.5/site-packages/keras/layers/wrappers.py", line 504, in call y = self.forward_layer.call(inputs, **kwargs) File "/home/mldl/ub16_prj/VENV_host/py3tf1.0/venv/lib/python3.5/site-packages/keras/layers/recurrent.py", line 2112, in call initial_state=initial_state) File "/home/mldl/ub16_prj/VENV_host/py3tf1.0/venv/lib/python3.5/site-packages/keras/layers/recurrent.py", line 609, in call input_length=timesteps) File "/home/mldl/ub16_prj/VENV_host/py3tf1.0/venv/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py", line 2957, in rnn maximum_iterations=input_length) TypeError: while_loop() got an unexpected keyword argument 'maximum_iterations' — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#6>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AQTgmgLglOfTZted5UN--103tMgcw-CDks5uELIzgaJpZM4VGWms> .

[SeekPoint]

it works with right version

[davidalbertonogueira]

Keras 2.1.2
Tensorflow 1.4.1

It solved

[onurbarut]

I have the same problem. just installed keras using pip. keras 2.2.2 and tensorflow 1.3.0. is my tf causing this error? will updating to 1.4.1 help?

[sravyaysk]

Initially I am using Keras version 2.2.4 which resulted in the above issue. But when I downgraded my keras to version 2.1.2 as per the above mentioned solutions, it is resulting a new error:
ImportError: cannot import name 'normalize_data_format' while importing keras_contrib. For this error the solution states that keras_contrib works for keras with version 2.2.0 or higher.
Can anyone help in fixing this issue?

[mibdennis]

changed to the suggested versions but still the same error...

[Aishwaryabaskaran]

I downgraded keras to 2.0.8 and it is compatible with tensorflow 1.4

[YoungjaeKim]

I ended up by changing to cntk backend.

[xiaozhouliu]

keras 2.1.2, tensorflow 1.2.1.

[xieyj17]

Use Keras 2.1.2 Tensorflow 1.4.1
…
On Sat 7 Jul, 2018, 6:35 PM yk_data, @.***> wrote: (venv) @.***UB1604:~/ub16_prj/Named-Entity-Recognition-with-Bidirectional-LSTM-CNNs$ python3 nn.py Using TensorFlow backend. I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcublas.so.8.0 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcudnn.so.5 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcufft.so.8.0 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcuda.so.1 locally I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcurand.so.8.0 locally W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations. I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:910] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero I tensorflow/core/common_runtime/gpu/gpu_device.cc:885] Found device 0 with properties: name: GeForce GTX 950M major: 5 minor: 0 memoryClockRate (GHz) 1.124 pciBusID 0000:01:00.0 Total memory: 3.95GiB Free memory: 3.56GiB I tensorflow/core/common_runtime/gpu/gpu_device.cc:906] DMA: 0 I tensorflow/core/common_runtime/gpu/gpu_device.cc:916] 0: Y I tensorflow/core/common_runtime/gpu/gpu_device.cc:975] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 950M, pci bus id: 0000:01:00.0) Traceback (most recent call last): File "nn.py", line 109, in output = Bidirectional(LSTM(200, return_sequences=True, dropout=0.50, recurrent_dropout=0.25))(output) File "/home/mldl/ub16_prj/VENV_host/py3tf1.0/venv/lib/python3.5/site-packages/keras/layers/wrappers.py", line 426, in call return super(Bidirectional, self).call(inputs, **kwargs) File "/home/mldl/ub16_prj/VENV_host/py3tf1.0/venv/lib/python3.5/site-packages/keras/engine/base_layer.py", line 460, in call output = self.call(inputs, **kwargs) File "/home/mldl/ub16_prj/VENV_host/py3tf1.0/venv/lib/python3.5/site-packages/keras/layers/wrappers.py", line 504, in call y = self.forward_layer.call(inputs, **kwargs) File "/home/mldl/ub16_prj/VENV_host/py3tf1.0/venv/lib/python3.5/site-packages/keras/layers/recurrent.py", line 2112, in call initial_state=initial_state) File "/home/mldl/ub16_prj/VENV_host/py3tf1.0/venv/lib/python3.5/site-packages/keras/layers/recurrent.py", line 609, in call input_length=timesteps) File "/home/mldl/ub16_prj/VENV_host/py3tf1.0/venv/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py", line 2957, in rnn maximum_iterations=input_length) TypeError: while_loop() got an unexpected keyword argument 'maximum_iterations' — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#6>, or mute the thread https://github.com/notifications/unsubscribe-auth/AQTgmgLglOfTZted5UN--103tMgcw-CDks5uELIzgaJpZM4VGWms .

How should I thank you? It's like magic!