import functools
import tensorflow as tf



FLAGS = tf.app.flags.FLAGS

tf.app.flags.DEFINE_string("batch-size", 64, "")
tf.app.flags.DEFINE_float("dropout-prob", 0, "")
tf.app.flags.DEFINE_string("word-file", None, "")
tf.app.flags.DEFINE_integer("num-threads-per-queue", 2, "")
tf.app.flags.DEFINE_integer("queue-capacity", 2, "")
tf.app.flags.DEFINE_string("length-boundaries", "", "")
tf.app.flags.DEFINE_string("rnn-cell", "ln_lstm", "Default RNN cell")
tf.app.flags.DEFINE_string("float32", "", "")


@functools.lru_cache()
def words():
  with open(tf.app.flags.FLAGS.word_file) as file_:
    return sorted([line.strip() for line in file_.readlines()])


@functools.lru_cache()
def word_indices():
  # 0 -> null, 1 -> unknown
  return { word: index + 2 for index, word in enumerate(flags.words()) }


@functools.lru_cache()
def word_space_size():
  return len(words())


def rnn_cell():
  from .rnn import cell
  return getattr(cell, FLAGS.rnn_cell)


def float_type():
  return getattr(tf, FLAGS.float_type)

import functools
import tensorflow as tf



FLAGS = tf.app.flags.FLAGS

tf.app.flags.DEFINE_string("batch-size", 64, "")
tf.app.flags.DEFINE_float("dropout-prob", 0, "")
tf.app.flags.DEFINE_string("word-file", None, "")
tf.app.flags.DEFINE_integer("num-threads-per-queue", 2, "")
tf.app.flags.DEFINE_integer("queue-capacity", 2, "")
tf.app.flags.DEFINE_string("length-boundaries", "", "")
tf.app.flags.DEFINE_string("rnn-cell", "ln_lstm", "Default RNN cell")
tf.app.flags.DEFINE_string("float-type", "float32", "")


@functools.lru_cache()
def words():
  with open(tf.app.flags.FLAGS.word_file) as file_:
    return sorted([line.strip() for line in file_.readlines()])


@functools.lru_cache()
def word_indices():
  # 0 -> null, 1 -> unknown
  return { word: index + 2 for index, word in enumerate(flags.words()) }


@functools.lru_cache()
def word_space_size():
  return len(words())


def rnn_cell():
  from .rnn import cell
  return getattr(cell, FLAGS.rnn_cell)


def float_type():
  return getattr(tf, FLAGS.float_type)

Fix float type flag definition
Fix float type flag definition

  import functools
  import tensorflow as tf
  
  
  
  FLAGS = tf.app.flags.FLAGS
  
  tf.app.flags.DEFINE_string("batch-size", 64, "")
  tf.app.flags.DEFINE_float("dropout-prob", 0, "")
  tf.app.flags.DEFINE_string("word-file", None, "")
  tf.app.flags.DEFINE_integer("num-threads-per-queue", 2, "")
  tf.app.flags.DEFINE_integer("queue-capacity", 2, "")
  tf.app.flags.DEFINE_string("length-boundaries", "", "")
  tf.app.flags.DEFINE_string("rnn-cell", "ln_lstm", "Default RNN cell")
- tf.app.flags.DEFINE_string("float32", "", "")
+ tf.app.flags.DEFINE_string("float-type", "float32", "")
  
  
  @functools.lru_cache()
  def words():
    with open(tf.app.flags.FLAGS.word_file) as file_:
      return sorted([line.strip() for line in file_.readlines()])
  
  
  @functools.lru_cache()
  def word_indices():
    # 0 -> null, 1 -> unknown
    return { word: index + 2 for index, word in enumerate(flags.words()) }
  
  
  @functools.lru_cache()
  def word_space_size():
    return len(words())
  
  
  def rnn_cell():
    from .rnn import cell
    return getattr(cell, FLAGS.rnn_cell)
  
  
  def float_type():
    return getattr(tf, FLAGS.float_type)
  
Fix float type flag definition
## Code Before:
import functools
import tensorflow as tf



FLAGS = tf.app.flags.FLAGS

tf.app.flags.DEFINE_string("batch-size", 64, "")
tf.app.flags.DEFINE_float("dropout-prob", 0, "")
tf.app.flags.DEFINE_string("word-file", None, "")
tf.app.flags.DEFINE_integer("num-threads-per-queue", 2, "")
tf.app.flags.DEFINE_integer("queue-capacity", 2, "")
tf.app.flags.DEFINE_string("length-boundaries", "", "")
tf.app.flags.DEFINE_string("rnn-cell", "ln_lstm", "Default RNN cell")
tf.app.flags.DEFINE_string("float32", "", "")


@functools.lru_cache()
def words():
  with open(tf.app.flags.FLAGS.word_file) as file_:
    return sorted([line.strip() for line in file_.readlines()])


@functools.lru_cache()
def word_indices():
  # 0 -> null, 1 -> unknown
  return { word: index + 2 for index, word in enumerate(flags.words()) }


@functools.lru_cache()
def word_space_size():
  return len(words())


def rnn_cell():
  from .rnn import cell
  return getattr(cell, FLAGS.rnn_cell)


def float_type():
  return getattr(tf, FLAGS.float_type)

## Instruction:
Fix float type flag definition
## Code After:
import functools
import tensorflow as tf



FLAGS = tf.app.flags.FLAGS

tf.app.flags.DEFINE_string("batch-size", 64, "")
tf.app.flags.DEFINE_float("dropout-prob", 0, "")
tf.app.flags.DEFINE_string("word-file", None, "")
tf.app.flags.DEFINE_integer("num-threads-per-queue", 2, "")
tf.app.flags.DEFINE_integer("queue-capacity", 2, "")
tf.app.flags.DEFINE_string("length-boundaries", "", "")
tf.app.flags.DEFINE_string("rnn-cell", "ln_lstm", "Default RNN cell")
tf.app.flags.DEFINE_string("float-type", "float32", "")


@functools.lru_cache()
def words():
  with open(tf.app.flags.FLAGS.word_file) as file_:
    return sorted([line.strip() for line in file_.readlines()])


@functools.lru_cache()
def word_indices():
  # 0 -> null, 1 -> unknown
  return { word: index + 2 for index, word in enumerate(flags.words()) }


@functools.lru_cache()
def word_space_size():
  return len(words())


def rnn_cell():
  from .rnn import cell
  return getattr(cell, FLAGS.rnn_cell)


def float_type():
  return getattr(tf, FLAGS.float_type)
