model fit return ValueError ?

Question

#Dataset divide into two 
x_val = x_features[:10000]
partial_x_train = x_features[10000:]   # Features

y_val = y_samples[:10000]
partial_y_train = y_samples[10000:]     #Labels

#Training on Dataset
history = model.fit(x=partial_x_train,y=partial_y_train,batch_size=512,epochs=20,validation_data=(x_val,y_val))

Traceback (most recent call last):
File "BinaryClassification.py", line 55, in <module>
history = model.fit(x=partial_x_train,y=partial_y_train,batch_size=512,epochs=20,validation_data=(x_val,y_val))
File "C:\Python36\lib\site-packages\tensorflow\python\keras_impl\keras\engine\training.py", line 1143, in fit
batch_size=batch_size)
File "C:\Python36\lib\site-packages\tensorflow\python\keras_impl\keras\engine\training.py", line 765, in _standardize_user_data
exception_prefix='input')
File "C:\Python36\lib\site-packages\tensorflow\python\keras_impl\keras\engine\training_utils.py", line 192, in standardize_input_data
' but got array with shape ' + str(data_shape))
ValueError: Error when checking input: expected dense_1_input to have shape (10000,) but got array with shape (1,)

i don't understand why fit function ValueError? Kindly help me to resolve this nasty error

Answer 1

The error resolve "whenever this error you can see in your console, always check where model take input from", this is because model expected something and provided input are according to the model expectation... in my case , my model expected 10,000 train_features and i pass by mistake list in which only 10 elements exit

Answer 2

expected dense_1_input to have shape (10000,) but got array with shape (1,)

Something wrong with the shape of the input.
The code for making the model is needed for futher comment.

Comments

[AliHassan]

i know this error, but how to resolve it

[mkgrei]

I cannot say anything unless the code to construct the model is provided.

What are the shapes of x and input?

[AliHassan]

thanks for your help