Tensorflow Data Adapter Error: ValueError: Failed to find data adapter that can handle input

Solution 1:

Have you checked whether your training/testing data and training/testing labels are all numpy arrays? It might be that you're mixing numpy arrays with lists.

Solution 2:

You can avoid this error by converting your labels to arrays before calling model.fit():

train_x = np.asarray(train_x)
train_y = np.asarray(train_y)
validation_x = np.asarray(validation_x)
validation_y = np.asarray(validation_y)

Solution 3:

If you encounter this problem while dealing with a custom generator inheriting from the keras.utils.Sequence class, you might have to make sure that you do not mix a Keras or a tensorflow - Keras-import.
This might especially happen when you have to switch to a previous tensorflow version for compatibility (like with cuDNN).

If you for example use this with a tensorflow-version > 2...

from keras.utils import Sequence

class generatorClass(Sequence):

    def __init__(self, x_set, y_set, batch_size):
        ...

    def __len__(self):
        ...

    def __getitem__(self, idx):
        return ...

... but you actually try to fit this generator in a tensorflow-version < 2, you have to make sure to import the Sequence-class from this version like:

keras = tf.compat.v1.keras
Sequence = keras.utils.Sequence

class generatorClass(Sequence):

    ...

Solution 4:

I had a similar problem. In my case it was a problem that I was using a tf.keras.Sequential model but a keras generator.

Wrong:

from keras.preprocessing.sequence import TimeseriesGenerator
gen = TimeseriesGenerator(...)

Correct:

gen = tf.keras.preprocessing.sequence.TimeseriesGenerator(...)

Solution 5:

This error occured when I updated tensorflow from 1.x to 2.x It was solved after changing my import from

import keras

import tensorflow.keras as keras