Aidan Gomez aidangomez

## 1m-primes.txt
2
3
5
7
11
13
17
19
23
29

## rnn.py
def cw_rnn(cells, strides, inputs, initial_states=None, dtype=None,
        sequence_length=None, scope=None):
  """Creates a recurrent neural network specified by RNNCell "cell".
  Args:
    cells: C instances of RNNCells.
    inputs: A length C list of lists, each with length[c] = T // strides[c], containing tensors of shape
      [batch_size, cell.input_size].
    strides: C ints.
    initial_states: (optional) An initial state for the RNN.  This must be
      a tensor of appropriate type and shape [batch_size x cell.state_size].
	def cw_rnn(cells, strides, inputs, initial_states=None, dtype=None,
	sequence_length=None, scope=None):
	"""Creates a recurrent neural network specified by RNNCell "cell".
	Args:
	cells: C instances of RNNCells.
	inputs: A length C list of lists, each with length[c] = T // strides[c], containing tensors of shape
	[batch_size, cell.input_size].
	strides: C ints.
	initial_states: (optional) An initial state for the RNN. This must be
	a tensor of appropriate type and shape [batch_size x cell.state_size].