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Surah Taha Full Pdf Version (April-2022)







A: You can use : sub2 # Save the input data to the output space. output_data = self._output(input_data) # Return the data after applying the specified number of blocks. return output_data class MNIST(LearningModelBase): """ This is the standard MNIST model. This is the default model for tensor2tensor. This is a learning model that learns by backpropagation. Parameters ---------- training : bool If True, it loads data from training set and create a model for it. If False, it loads data from test set and create a model for it. input_dim : int Dimension of the input to the model. hidden_dim : int Dimension of the hidden layer. num_classes : int Number of output classes. def __init__(self, training=True, input_dim=784, hidden_dim=100, num_classes=10): # Initialize the model super(MNIST, self).__init__( training=training, input


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