CNTK_MNIST_Create_Trainer.py

'''
----------------------
Setting up the trainer
----------------------
'''
# Define the label as the other input parameter of the trainer
labels = cntk.ops.input_variable(output_dim, np.float32)

#Initialize the parameters for the trainer
train_minibatch_size = 50
learning_rate = 1e-4
momentum = 0.9

# Define the loss function
loss = cntk.ops.cross_entropy_with_softmax(output, labels)

# Define the function that calculates classification error
label_error = cntk.ops.classification_error(output, labels)

# Instantiate the trainer object to drive the model training
learner = cntk.adam_sgd(output.parameters, learning_rate, momentum)
trainer = cntk.Trainer(output, loss, label_error, [learner])