human
I am working on the file "LSTM/LSTM.ipynb".
The first task is:
LSTM class and functions
Can you write Python code for it?
 ... Can you provide a the Python code you requested?
assistant
#Here is the Python code you requested.

class LSTM_cell(object):

    """
    LSTM cell object which takes 3 arguments for initialization.
    input_size = Input Vector size
    hidden_layer_size = Hidden layer size
    target_size = Output vector size

    """

    def __init__(self, input_size, hidden_layer_size, target_size):

        # Initialization of given values
        self.input_size = input_size
        self.hidden_layer_size = hidden_layer_size
        self.target_size = target_size

        # Weights and Bias for input and hidden tensor
        self.Wi = tf.Variable(tf.zeros(
            [self.input_size, self.hidden_layer_size]))
        self.Ui = tf.Variable(tf.zeros(
            [self.hidden_layer_size, self.hidden_layer_size]))
        self.bi = tf.Variable(tf.zeros([self.hidden_layer_size]))

        
        self.Wf = tf.Variable(tf.zeros(
            [self.input_size, self.hidden_layer_size]))
        self.Uf = tf.Variable(tf.zeros(
            [self.hidden_layer_size, self.hidden_layer_size]))
        self.bf = tf.Variable(tf.zeros([self.hidden_layer_size]))        
        
        
        self.Wog = tf.Variable(tf.zeros(
            [self.input_size, self.hidden_layer_size]))
        self.Uog = tf.Variable(tf.zeros(
            [self.hidden_layer_size, self.hidden_layer_size]))
        self.bog = tf.Variable(tf.zeros([self.hidden_layer_size]))        
        
        
        self.Wc = tf.Variable(tf.zeros(
            [self.input_size, self.hidden_layer_size]))
        self.Uc = tf.Variable(tf.zeros(
            [self.hidden_layer_size, self.hidden_layer_size]))
        self.bc = tf.Variable(tf.zeros([self.hidden_layer_size]))        
        
        
        
        # Weights for output layers
        self.Wo = tf.Variable(tf.truncated_normal(
            [self.hidden_layer_size, self.target_size],mean=0,stddev=.01))
        self.bo = tf.Variable(tf.truncated_normal([self.target_size],mean=0,stddev=.01))

        # Placeholder for input vector with shape[batch, seq, embeddings]
        self._inputs =...