Simple ML Algo not working: ValueError: Error when checking input: expected dense_4_input to have shape (None, 5) but got array with shape (5, 1)

Question

I have an incredible simple algorithm that is erroring with, "ValueError: Error when checking input: expected dense_4_input to have shape (None, 5) but got array with shape (5, 1)".... Here is the code I am running.

import numpy as np
import matplotlib.pyplot as plt
from keras.models import Sequential
from keras.layers import Dense
x = np.array([[1],[2],[3],[4],[5]])

y = np.array([[1],[2],[3],[4],[5]])
x_val = np.array([[6],[7]])
x_val = np.array([[6],[7]])
model = Sequential()
model.add(Dense(1, input_dim=5))
model.compile(optimizer='rmsprop', loss='mse')
model.fit(x, y, epochs=2, validation_data=(x_val, y_val))

Skyy2010 · Accepted Answer · 2017-10-21 10:31:58Z

2

There are two problems:

First: As the output already says: "ValueError: Error when checking input: expected dense_4_input to have shape (None, 5) but got array with shape (5, 1)" This means, that the Neural Network expects an array of shape (*, 5). With the asterisk I want to indicate that the dimensions is free to choose by the user. Say if you have tons of data and every example is a vector of shape (1, 5) you can stack them all underneath and pass one big chunk of data to the neural net, it will know how to handle it. Therefore you have to make x a row vector as follows:

x = np.array([[1,2,3,4,5]])

See also in the Keras docs- Specifying the input shape.

Second: You specify the output of the first Layer to be one. This means, the 5 dimensional input will be connected to only one neuron. Your output vector y however has 5 values. So your output vector dimension and your neural net output don't fit together. So you have to go with a scalar y:

y = np.array([1])

Furthermore, your validation data and training data should have the same dimensions. Additionaly there is a typo in your code: y_val is never defined.

edited Oct 21, 2017 at 10:31

answered Oct 21, 2017 at 9:59

Skyy2010

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1 Comment

user2162942 Over a year ago

Thank you so much!

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