code: def LSTM_sequence_classifier_net(
      input, num_output_classes, embedding_dim, LSTM_dim, cell_dim
  ):
      lstm_classifier = Sequential(
          [
              Embedding(embedding_dim),
              Recurrence(LSTM(LSTM_dim, cell_dim)),
              sequence.last,
              Dense(num_output_classes),
          ]
      )
      return lstm_classifier(input)
  
file_path: CNTK/bindings/python/doc/simplernn.py
imports: import sys
  import os
  from cntk import Trainer, Axis
  from cntk.io import MinibatchSource, CTFDeserializer, StreamDef, StreamDefs, INFINITELY_REPEAT
  from cntk.learners import sgd, learning_parameter_schedule_per_sample
  from cntk import input_variable, cross_entropy_with_softmax, classification_error, sequence
  from cntk.logging import ProgressPrinter
  from cntk.layers import Sequential, Embedding, Recurrence, LSTM, Dense
label_desc: Use image node_id 2 for calling a global function with example usage: LSTM_sequence_classifier_net(input, num_output_classes, embedding_dim, LSTM_dim, cell_dim) and returns: lstm_classifier