File HDF5nya import h5py import numpy as np import keras from keras.models import Model from keras.layers import Input from keras.layers import Dense from keras.layers import Conv2D from keras.layers import MaxPooling2D from keras.layers import Flatten from keras.layers import Dropout f=h5py.File('MNIST.hdf5','r') a = np.array(f['normalized_full']['training']['default']) X_train = a.reshape(a.shape[1:4]) b = np.array(f['normalized_full']['test']['default']) X_test = b.reshape(b.shape[1:4]) c = np.array(f['normalized_full']['training']['targets']) y_train = c.reshape(c.shape[1:4]) d = np.array(f['normalized_full']['test']['targets']) y_test = d.reshape(d.shape[1:4]) X_train = X_train.reshape(X_train.shape[0], 28, 28, 1) X_test = X_test.reshape(X_test.shape[0], 28, 28, 1) num_classes = 10 y_train = keras.utils.to_categorical(y_train, num_classes) y_t...
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