Preparing feeding data to 1D CNN - keras

Question

I am getting into a similar problem with reshaping data for 1-D CNN:
I am loading data (training and testing data sets ) from a csv file with 24,325 lines. Each line is a vector of 256 numbers - independent variables plus 11 numbers of expected outcome ( labels ) [0,0,0,0,1,0,0,0,0,0,0]
I am using TensorFlow backend.
The code looks like that:
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
#Importing training set
training_set = pd.read_csv("Data30.csv")
X_train = training_set.iloc[:20000, 3 :-11].values
y_train = training_set.iloc[:20000, -11:-1].values
#Importing test set
test_set = pd.read_csv("Data30.csv")
X_test = training_set.iloc[ 20001:, 3 :-11].values
y_test = training_set.iloc[ 20001:, -11:].values
X_train /= np.max(X_train) # Normalise data to [0, 1] range
X_test /= np.max(X_test) # Normalise data to [0, 1] range
print("X_train.shape[0] = " + str(X_train.shape[0]))
print("X_train.shape[1] = " + str(X_train.shape[1]))
print("y_train.shape[0] = " + str(y_train.shape[0]))
print("y_train.shape[1] = " + str(y_train.shape[1]))
print("X_test.shape[0] = " + str(X_test.shape[0]))
print("X_test.shape[1] = " + str(X_test.shape[1]))
This is what I get:
X_train.shape[0] = 20000
X_train.shape1 = 256
y_train.shape[0] = 20000
y_train.shape1 = 11
X_test.shape[0] = 4325
X_test.shape1 = 256
#Convert data into 3d tensor
# Old Version
# X_train = np.reshape(X_train,(1,X_train.shape[0],X_train.shape[1]))
# X_test = np.reshape(X_test,(1,X_test.shape[0],X_test.shape[1]))
**# New Correct Version based on the Answer:**
X_train = np.reshape(X_train,( X_train.shape[0],X_train.shape[1], 1 ))
X_test = np.reshape(X_test,( X_test.shape[0],X_test.shape[1], 1 ))
print("X_train.shape[0] = " + str(X_train.shape[0]))
print("X_train.shape[1] = " + str(X_train.shape[1]))
print("X_test.shape[0] = " + str(X_test.shape[0]))
print("X_test.shape[1] = " + str(X_test.shape[1]))
This is result of the reshaping:
X_train.shape[0] = 1
X_train.shape1 = 20000
X_test.shape[0] = 1
X_test.shape1 = 4325
#Importing convolutional layers
from keras.models import Sequential
from keras.layers import Convolution1D
from keras.layers import MaxPooling1D
from keras.layers import Flatten
from keras.layers import Dense
from keras.layers import Dropout
from keras.layers.normalization import BatchNormalization
#Initialising the CNN
classifier = Sequential()
#1.Multiple convolution and max pooling
classifier.add(Convolution1D(filters=8, kernel_size=11, activation="relu", input_shape=( 256, 1 )))
classifier.add(MaxPooling1D(strides=4))
classifier.add(BatchNormalization())
classifier.add(Convolution1D(filters=16, kernel_size=11, activation='relu'))
classifier.add(MaxPooling1D(strides=4))
classifier.add(BatchNormalization())
classifier.add(Convolution1D(filters=32, kernel_size=11, activation='relu'))
classifier.add(MaxPooling1D(strides=4))
classifier.add(BatchNormalization())
#classifier.add(Convolution1D(filters=64, kernel_size=11,activation='relu'))
#classifier.add(MaxPooling1D(strides=4))
#2.Flattening
classifier.add(Flatten())
#3.Full Connection
classifier.add(Dropout(0.5))
classifier.add(Dense(64, activation='relu'))
classifier.add(Dropout(0.25))
classifier.add(Dense(64, activation='relu'))
classifier.add(Dense(1, activation='sigmoid'))
#Configure the learning process
classifier.compile(optimizer="adam", loss="binary_crossentropy", metrics=["accuracy"])
#Train!
classifier.fit_generator(training_set,
steps_per_epoch= 100,
nb_epoch = 200,
validation_data = (X_test,y_test),
validation_steps = 40)
score = classifier.evaluate(X_test, y_test)
This is the error I get:
Traceback (most recent call last):
File "C:/Conda/ML_Folder/CNN Data30.py", line 85, in
classifier.fit_generator(X_train, steps_per_epoch=10, epochs=10, validation_data=(X_test,y_test))
File "C:\Conda\lib\site-packages\keras\legacy\interfaces.py", line 87, in wrapper
return func(*args, **kwargs)
File "C:\Conda\lib\site-packages\keras\models.py", line 1121, in fit_generator
initial_epoch=initial_epoch)
File "C:\Conda\lib\site-packages\keras\legacy\interfaces.py", line 87, in wrapper
return func(*args, **kwargs)
File "C:\Conda\lib\site-packages\keras\engine\training.py", line 1978, in fit_generator
val_x, val_y, val_sample_weight)
File "C:\Conda\lib\site-packages\keras\engine\training.py", line 1378, in _standardize_user_data
exception_prefix='input')
File "C:\Conda\lib\site-packages\keras\engine\training.py", line 144, in _standardize_input_data
str(array.shape))
ValueError: Error when checking input: expected conv1d_1_input to have shape (None, 256, 1) but got array with shape (1, 4325, 256)
Can you please help me to fix the code?

Answer 1

Shapes should be (batchSize, length, channels)
So: (20000,256,1) and (20000,11)
Detail: your last Dense must output 11, so: Dense(11,...)