# Keras fails after upgrade

## post by bgold on Nov 2, 2020

Hi, I recently reinstalled everything on a Lambda workstation, to upgrade to Ubuntu 20.04 and installed the latest lambda-stack. But I’ve discovered that my Keras models no longer work, failing with

`AttributeError: module 'tensorflow.python.framework.ops' has no attribute '_TensorLike'` .

Since this seemed similar to other problems mentioned here, I’ve tried both upgrading protobuf and adding the lines

```lua
for device in tf.config.experimental.list_physical_devices('GPU'):
    tf.config.experimental.set_memory_growth(device, True)
```

as suggested elsewhere. Neither have had any effect.

I’ve attached the full error output in case there’s anything useful in there

```auto
2020-11-02 10:39:36.652480: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2020-11-02 10:39:36.655510: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
Invalid MIT-MAGIC-COOKIE-1 keyUsing TensorFlow backend.
2020-11-02 10:39:38.028832: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
2020-11-02 10:39:38.038570: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties:
pciBusID: 0000:1a:00.0 name: GeForce RTX 2080 Ti computeCapability: 7.5
coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s
2020-11-02 10:39:38.039058: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 1 with properties:
pciBusID: 0000:68:00.0 name: GeForce RTX 2080 Ti computeCapability: 7.5
coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s
2020-11-02 10:39:38.039076: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2020-11-02 10:39:38.041038: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2020-11-02 10:39:38.041774: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2020-11-02 10:39:38.041984: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2020-11-02 10:39:38.044095: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.11
2020-11-02 10:39:38.044564: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2020-11-02 10:39:38.044652: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2020-11-02 10:39:38.046506: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1858] Adding visible gpu devices: 0, 1
Traceback (most recent call last):
  File "cats.py", line 78, in <module>
    x = Dense(intermediate_dim//32, activation='relu',
  File "/usr/lib/python3/dist-packages/keras/backend/tensorflow_backend.py", line 75, in symbolic_fn_wrapper
    return func(*args, **kwargs)
  File "/usr/lib/python3/dist-packages/keras/engine/base_layer.py", line 446, in __call__
    self.assert_input_compatibility(inputs)
  File "/usr/lib/python3/dist-packages/keras/engine/base_layer.py", line 310, in assert_input_compatibility
    K.is_keras_tensor(x)
  File "/usr/lib/python3/dist-packages/keras/backend/tensorflow_backend.py", line 695, in is_keras_tensor
    if not is_tensor(x):
  File "/usr/lib/python3/dist-packages/keras/backend/tensorflow_backend.py", line 703, in is_tensor
    return isinstance(x, tf_ops._TensorLike) or tf_ops.is_dense_tensor_like(x)
AttributeError: module 'tensorflow.python.framework.ops' has no attribute '_TensorLike'
```

## post by bgold on Nov 9, 2020

Since this might be helpful to others, I finally chased down the source of this error.

There’s an incompatibility between the lambda-stack versions of tensorflow and Keras, but tensorflow includes it’s own keras module which can be used instead. So I changed all my imports that originally looked like

```javascript
from Keras import backend as K
```

to instead look like

```javascript
from tensorflow.keras import backend as K
```

and things started working again.

## post by sabalaba on Nov 13, 2020

Good find — it’s because if you do `import keras` it’s version `2.3.1` at the time of writing and if you do `import tensorflow.keras` it’s version `2.4.0` which aren’t compatible. It looks like your models were `2.4.0` compatible?