While running a sentdex tutorial script of a cryptocurrency RNN, link here
YouTube Tutorial: Cryptocurrency-predicting RNN Model,
but have encountered an err
may be it will help someone. First check your data type if it is numpy array & possibly ur algo required a DF.
print(X.shape, X.dtype)
print(y.shape, y.dtype)
convert your numpy array into Pandas DF
train_x = pd.DataFrame(train_x)
train_y = pd.DataFrame(train_y)
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):
...
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.
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)
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(...)