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| import tflearn | |
| from tflearn.layers.core import input_data, dropout, fully_connected | |
| from tflearn.layers.conv import conv_2d, max_pool_2d | |
| from tflearn.layers.normalization import local_response_normalization | |
| from tflearn.layers.estimator import regression | |
| # Data loading and preprocessing | |
| import tflearn.datasets.mnist as mnist | |
| X, Y, testX, testY = mnist.load_data(one_hot=True) | |
| X = X.reshape([-1, 28, 28, 1]) |
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| project(Testing) | |
| cmake_minimum_required(VERSION 2.8) | |
| add_executable(${PROJECT_NAME} main.cpp) |