Python util.with_prefix() Examples

The following are 12 code examples of util.with_prefix(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module util , or try the search function .
Example #1
Source File: ptb_word_lm.py    From yolo_v2 with Apache License 2.0 6 votes vote down vote up 
def import_ops(self):
    """Imports ops from collections."""
    if self._is_training:
      self._train_op = tf.get_collection_ref("train_op")[0]
      self._lr = tf.get_collection_ref("lr")[0]
      self._new_lr = tf.get_collection_ref("new_lr")[0]
      self._lr_update = tf.get_collection_ref("lr_update")[0]
      rnn_params = tf.get_collection_ref("rnn_params")
      if self._cell and rnn_params:
        params_saveable = tf.contrib.cudnn_rnn.RNNParamsSaveable(
            self._cell,
            self._cell.params_to_canonical,
            self._cell.canonical_to_params,
            rnn_params,
            base_variable_scope="Model/RNN")
        tf.add_to_collection(tf.GraphKeys.SAVEABLE_OBJECTS, params_saveable)
    self._cost = tf.get_collection_ref(util.with_prefix(self._name, "cost"))[0]
    num_replicas = FLAGS.num_gpus if self._name == "Train" else 1
    self._initial_state = util.import_state_tuples(
        self._initial_state, self._initial_state_name, num_replicas)
    self._final_state = util.import_state_tuples(
        self._final_state, self._final_state_name, num_replicas)
Example #2
Source File: ptb_word_lm.py    From Gun-Detector with Apache License 2.0 6 votes vote down vote up 
def import_ops(self):
    """Imports ops from collections."""
    if self._is_training:
      self._train_op = tf.get_collection_ref("train_op")[0]
      self._lr = tf.get_collection_ref("lr")[0]
      self._new_lr = tf.get_collection_ref("new_lr")[0]
      self._lr_update = tf.get_collection_ref("lr_update")[0]
      rnn_params = tf.get_collection_ref("rnn_params")
      if self._cell and rnn_params:
        params_saveable = tf.contrib.cudnn_rnn.RNNParamsSaveable(
            self._cell,
            self._cell.params_to_canonical,
            self._cell.canonical_to_params,
            rnn_params,
            base_variable_scope="Model/RNN")
        tf.add_to_collection(tf.GraphKeys.SAVEABLE_OBJECTS, params_saveable)
    self._cost = tf.get_collection_ref(util.with_prefix(self._name, "cost"))[0]
    num_replicas = FLAGS.num_gpus if self._name == "Train" else 1
    self._initial_state = util.import_state_tuples(
        self._initial_state, self._initial_state_name, num_replicas)
    self._final_state = util.import_state_tuples(
        self._final_state, self._final_state_name, num_replicas)
Example #3
Source File: ptb_word_lm.py    From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 6 votes vote down vote up 
def import_ops(self):
    """Imports ops from collections."""
    if self._is_training:
      self._train_op = tf.get_collection_ref("train_op")[0]
      self._lr = tf.get_collection_ref("lr")[0]
      self._new_lr = tf.get_collection_ref("new_lr")[0]
      self._lr_update = tf.get_collection_ref("lr_update")[0]
      rnn_params = tf.get_collection_ref("rnn_params")
      if self._cell and rnn_params:
        params_saveable = tf.contrib.cudnn_rnn.RNNParamsSaveable(
            self._cell,
            self._cell.params_to_canonical,
            self._cell.canonical_to_params,
            rnn_params,
            base_variable_scope="Model/RNN")
        tf.add_to_collection(tf.GraphKeys.SAVEABLE_OBJECTS, params_saveable)
    self._cost = tf.get_collection_ref(util.with_prefix(self._name, "cost"))[0]
    num_replicas = FLAGS.num_gpus if self._name == "Train" else 1
    self._initial_state = util.import_state_tuples(
        self._initial_state, self._initial_state_name, num_replicas)
    self._final_state = util.import_state_tuples(
        self._final_state, self._final_state_name, num_replicas)
Example #4
Source File: ptb_word_lm.py    From object_detection_kitti with Apache License 2.0 6 votes vote down vote up 
def import_ops(self):
    """Imports ops from collections."""
    if self._is_training:
      self._train_op = tf.get_collection_ref("train_op")[0]
      self._lr = tf.get_collection_ref("lr")[0]
      self._new_lr = tf.get_collection_ref("new_lr")[0]
      self._lr_update = tf.get_collection_ref("lr_update")[0]
      rnn_params = tf.get_collection_ref("rnn_params")
      if self._cell and rnn_params:
        params_saveable = tf.contrib.cudnn_rnn.RNNParamsSaveable(
            self._cell,
            self._cell.params_to_canonical,
            self._cell.canonical_to_params,
            rnn_params,
            base_variable_scope="Model/RNN")
        tf.add_to_collection(tf.GraphKeys.SAVEABLE_OBJECTS, params_saveable)
    self._cost = tf.get_collection_ref(util.with_prefix(self._name, "cost"))[0]
    num_replicas = FLAGS.num_gpus if self._name == "Train" else 1
    self._initial_state = util.import_state_tuples(
        self._initial_state, self._initial_state_name, num_replicas)
    self._final_state = util.import_state_tuples(
        self._final_state, self._final_state_name, num_replicas)
Example #5
Source File: ptb_word_lm.py    From object_detection_with_tensorflow with MIT License 6 votes vote down vote up 
def import_ops(self):
    """Imports ops from collections."""
    if self._is_training:
      self._train_op = tf.get_collection_ref("train_op")[0]
      self._lr = tf.get_collection_ref("lr")[0]
      self._new_lr = tf.get_collection_ref("new_lr")[0]
      self._lr_update = tf.get_collection_ref("lr_update")[0]
      rnn_params = tf.get_collection_ref("rnn_params")
      if self._cell and rnn_params:
        params_saveable = tf.contrib.cudnn_rnn.RNNParamsSaveable(
            self._cell,
            self._cell.params_to_canonical,
            self._cell.canonical_to_params,
            rnn_params,
            base_variable_scope="Model/RNN")
        tf.add_to_collection(tf.GraphKeys.SAVEABLE_OBJECTS, params_saveable)
    self._cost = tf.get_collection_ref(util.with_prefix(self._name, "cost"))[0]
    num_replicas = FLAGS.num_gpus if self._name == "Train" else 1
    self._initial_state = util.import_state_tuples(
        self._initial_state, self._initial_state_name, num_replicas)
    self._final_state = util.import_state_tuples(
        self._final_state, self._final_state_name, num_replicas)
Example #6
Source File: ptb_word_lm.py    From g-tensorflow-models with Apache License 2.0 6 votes vote down vote up 
def import_ops(self):
    """Imports ops from collections."""
    if self._is_training:
      self._train_op = tf.get_collection_ref("train_op")[0]
      self._lr = tf.get_collection_ref("lr")[0]
      self._new_lr = tf.get_collection_ref("new_lr")[0]
      self._lr_update = tf.get_collection_ref("lr_update")[0]
      rnn_params = tf.get_collection_ref("rnn_params")
      if self._cell and rnn_params:
        params_saveable = tf.contrib.cudnn_rnn.RNNParamsSaveable(
            self._cell,
            self._cell.params_to_canonical,
            self._cell.canonical_to_params,
            rnn_params,
            base_variable_scope="Model/RNN")
        tf.add_to_collection(tf.GraphKeys.SAVEABLE_OBJECTS, params_saveable)
    self._cost = tf.get_collection_ref(util.with_prefix(self._name, "cost"))[0]
    num_replicas = FLAGS.num_gpus if self._name == "Train" else 1
    self._initial_state = util.import_state_tuples(
        self._initial_state, self._initial_state_name, num_replicas)
    self._final_state = util.import_state_tuples(
        self._final_state, self._final_state_name, num_replicas)
Example #7
Source File: ptb_word_lm.py    From yolo_v2 with Apache License 2.0 5 votes vote down vote up 
def export_ops(self, name):
    """Exports ops to collections."""
    self._name = name
    ops = {util.with_prefix(self._name, "cost"): self._cost}
    if self._is_training:
      ops.update(lr=self._lr, new_lr=self._new_lr, lr_update=self._lr_update)
      if self._rnn_params:
        ops.update(rnn_params=self._rnn_params)
    for name, op in ops.items():
      tf.add_to_collection(name, op)
    self._initial_state_name = util.with_prefix(self._name, "initial")
    self._final_state_name = util.with_prefix(self._name, "final")
    util.export_state_tuples(self._initial_state, self._initial_state_name)
    util.export_state_tuples(self._final_state, self._final_state_name)
Example #8
Source File: ptb_word_lm.py    From Gun-Detector with Apache License 2.0 5 votes vote down vote up 
def export_ops(self, name):
    """Exports ops to collections."""
    self._name = name
    ops = {util.with_prefix(self._name, "cost"): self._cost}
    if self._is_training:
      ops.update(lr=self._lr, new_lr=self._new_lr, lr_update=self._lr_update)
      if self._rnn_params:
        ops.update(rnn_params=self._rnn_params)
    for name, op in ops.items():
      tf.add_to_collection(name, op)
    self._initial_state_name = util.with_prefix(self._name, "initial")
    self._final_state_name = util.with_prefix(self._name, "final")
    util.export_state_tuples(self._initial_state, self._initial_state_name)
    util.export_state_tuples(self._final_state, self._final_state_name)
Example #9
Source File: ptb_word_lm.py    From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 5 votes vote down vote up 
def export_ops(self, name):
    """Exports ops to collections."""
    self._name = name
    ops = {util.with_prefix(self._name, "cost"): self._cost}
    if self._is_training:
      ops.update(lr=self._lr, new_lr=self._new_lr, lr_update=self._lr_update)
      if self._rnn_params:
        ops.update(rnn_params=self._rnn_params)
    for name, op in ops.items():
      tf.add_to_collection(name, op)
    self._initial_state_name = util.with_prefix(self._name, "initial")
    self._final_state_name = util.with_prefix(self._name, "final")
    util.export_state_tuples(self._initial_state, self._initial_state_name)
    util.export_state_tuples(self._final_state, self._final_state_name)
Example #10
Source File: ptb_word_lm.py    From object_detection_kitti with Apache License 2.0 5 votes vote down vote up 
def export_ops(self, name):
    """Exports ops to collections."""
    self._name = name
    ops = {util.with_prefix(self._name, "cost"): self._cost}
    if self._is_training:
      ops.update(lr=self._lr, new_lr=self._new_lr, lr_update=self._lr_update)
      if self._rnn_params:
        ops.update(rnn_params=self._rnn_params)
    for name, op in ops.iteritems():
      tf.add_to_collection(name, op)
    self._initial_state_name = util.with_prefix(self._name, "initial")
    self._final_state_name = util.with_prefix(self._name, "final")
    util.export_state_tuples(self._initial_state, self._initial_state_name)
    util.export_state_tuples(self._final_state, self._final_state_name)
Example #11
Source File: ptb_word_lm.py    From object_detection_with_tensorflow with MIT License 5 votes vote down vote up 
def export_ops(self, name):
    """Exports ops to collections."""
    self._name = name
    ops = {util.with_prefix(self._name, "cost"): self._cost}
    if self._is_training:
      ops.update(lr=self._lr, new_lr=self._new_lr, lr_update=self._lr_update)
      if self._rnn_params:
        ops.update(rnn_params=self._rnn_params)
    for name, op in ops.items():
      tf.add_to_collection(name, op)
    self._initial_state_name = util.with_prefix(self._name, "initial")
    self._final_state_name = util.with_prefix(self._name, "final")
    util.export_state_tuples(self._initial_state, self._initial_state_name)
    util.export_state_tuples(self._final_state, self._final_state_name)
Example #12
Source File: ptb_word_lm.py    From g-tensorflow-models with Apache License 2.0 5 votes vote down vote up 
def export_ops(self, name):
    """Exports ops to collections."""
    self._name = name
    ops = {util.with_prefix(self._name, "cost"): self._cost}
    if self._is_training:
      ops.update(lr=self._lr, new_lr=self._new_lr, lr_update=self._lr_update)
      if self._rnn_params:
        ops.update(rnn_params=self._rnn_params)
    for name, op in ops.items():
      tf.add_to_collection(name, op)
    self._initial_state_name = util.with_prefix(self._name, "initial")
    self._final_state_name = util.with_prefix(self._name, "final")
    util.export_state_tuples(self._initial_state, self._initial_state_name)
    util.export_state_tuples(self._final_state, self._final_state_name)