tflearn.layers.core.input_data (shape=None, placeholder=None, dtype=tf.float32, data_preprocessing=None, data_augmentation=None, name=’InputData’)
In TFLearn, the input_data is the input layer to the neural network. It is used to specify how the input looks like, before adding any of the usual layer in the sequential model.
For example, in the MNIST data set where a 784 array represents 28×28 images with a shape (None, 28, 28, 1] with one color channel. Usually None could be interpreted as the batch_size.