Python tensorflow.foldr() Examples

The following are 13 code examples of tensorflow.foldr(). 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 tensorflow , or try the search function .
Example #1
Source File: functional_ops_test.py    From deep_image_model with Apache License 2.0 6 votes vote down vote up 
def testFoldr_Scoped(self):
    with self.test_session() as sess:
      with tf.variable_scope("root") as varscope:
        elems = tf.constant([1, 2, 3, 4, 5, 6], name="data")

        r = tf.foldr(simple_scoped_fn, elems)
        # Check that we have the one variable we asked for here.
        self.assertEqual(len(tf.trainable_variables()), 1)
        self.assertEqual(tf.trainable_variables()[0].name, "root/body/two:0")
        sess.run([tf.global_variables_initializer()])
        self.assertAllEqual(450, r.eval())

        # Now let's reuse our single variable.
        varscope.reuse_variables()
        r = tf.foldr(simple_scoped_fn, elems, initializer=10)
        self.assertEqual(len(tf.trainable_variables()), 1)
        self.assertAllEqual(1282, r.eval())
Example #2
Source File: tensorflow_backend.py    From GraphicDesignPatternByPython with MIT License 5 votes vote down vote up 
def foldr(fn, elems, initializer=None, name=None):
    """Reduce elems using fn to combine them from right to left.

    # Arguments
        fn: Callable that will be called upon each element in elems and an
            accumulator, for instance `lambda acc, x: acc + x`
        elems: tensor
        initializer: The first value used (`elems[-1]` in case of None)
        name: A string name for the foldr node in the graph

    # Returns
        Tensor with same type and shape as `initializer`.
    """
    return tf.foldr(fn, elems, initializer=initializer, name=name)
Example #3
Source File: functional_ops_test.py    From deep_image_model with Apache License 2.0 5 votes vote down vote up 
def testFoldr_Simple(self):
    with self.test_session():
      elems = tf.constant([1, 2, 3, 4, 5, 6], name="data")

      r = tf.foldr(lambda a, x: tf.mul(tf.add(a, x), 2), elems)
      self.assertAllEqual(450, r.eval())

      r = tf.foldr(
          lambda a, x: tf.mul(tf.add(a, x), 2), elems, initializer=10)
      self.assertAllEqual(1282, r.eval())
Example #4
Source File: functional_ops_test.py    From deep_image_model with Apache License 2.0 5 votes vote down vote up 
def testFold_Grad(self):
    with self.test_session():
      elems = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], name="data")
      v = tf.constant(2.0, name="v")

      r = tf.foldl(
          lambda a, x: tf.mul(a, x), elems, initializer=v)
      r = tf.gradients(r, v)[0]
      self.assertAllEqual(720.0, r.eval())

      r = tf.foldr(
          lambda a, x: tf.mul(a, x), elems, initializer=v)
      r = tf.gradients(r, v)[0]
      self.assertAllEqual(720.0, r.eval())
Example #5
Source File: tensorflow_backend.py    From DeepLearning_Wavelet-LSTM with MIT License 5 votes vote down vote up 
def foldr(fn, elems, initializer=None, name=None):
    """Reduce elems using fn to combine them from right to left.

    # Arguments
        fn: Callable that will be called upon each element in elems and an
            accumulator, for instance `lambda acc, x: acc + x`
        elems: tensor
        initializer: The first value used (`elems[-1]` in case of None)
        name: A string name for the foldr node in the graph

    # Returns
        Tensor with same type and shape as `initializer`.
    """
    return tf.foldr(fn, elems, initializer=initializer, name=name)
Example #6
Source File: tensorflow_backend.py    From DeepLearning_Wavelet-LSTM with MIT License 5 votes vote down vote up 
def foldr(fn, elems, initializer=None, name=None):
    """Reduce elems using fn to combine them from right to left.

    # Arguments
        fn: Callable that will be called upon each element in elems and an
            accumulator, for instance `lambda acc, x: acc + x`
        elems: tensor
        initializer: The first value used (`elems[-1]` in case of None)
        name: A string name for the foldr node in the graph

    # Returns
        Tensor with same type and shape as `initializer`.
    """
    return tf.foldr(fn, elems, initializer=initializer, name=name)
Example #7
Source File: tensorflow_backend.py    From DeepLearning_Wavelet-LSTM with MIT License 5 votes vote down vote up 
def foldr(fn, elems, initializer=None, name=None):
    """Reduce elems using fn to combine them from right to left.

    # Arguments
        fn: Callable that will be called upon each element in elems and an
            accumulator, for instance `lambda acc, x: acc + x`
        elems: tensor
        initializer: The first value used (`elems[-1]` in case of None)
        name: A string name for the foldr node in the graph

    # Returns
        Tensor with same type and shape as `initializer`.
    """
    return tf.foldr(fn, elems, initializer=initializer, name=name)
Example #8
Source File: tensorflow_backend.py    From DeepLearning_Wavelet-LSTM with MIT License 5 votes vote down vote up 
def foldr(fn, elems, initializer=None, name=None):
    """Reduce elems using fn to combine them from right to left.

    # Arguments
        fn: Callable that will be called upon each element in elems and an
            accumulator, for instance `lambda acc, x: acc + x`
        elems: tensor
        initializer: The first value used (`elems[-1]` in case of None)
        name: A string name for the foldr node in the graph

    # Returns
        Tensor with same type and shape as `initializer`.
    """
    return tf.foldr(fn, elems, initializer=initializer, name=name)
Example #9
Source File: tensorflow_backend.py    From DeepLearning_Wavelet-LSTM with MIT License 5 votes vote down vote up 
def foldr(fn, elems, initializer=None, name=None):
    """Reduce elems using fn to combine them from right to left.

    # Arguments
        fn: Callable that will be called upon each element in elems and an
            accumulator, for instance `lambda acc, x: acc + x`
        elems: tensor
        initializer: The first value used (`elems[-1]` in case of None)
        name: A string name for the foldr node in the graph

    # Returns
        Tensor with same type and shape as `initializer`.
    """
    return tf.foldr(fn, elems, initializer=initializer, name=name)
Example #10
Source File: tensorflow_backend.py    From DeepLearning_Wavelet-LSTM with MIT License 5 votes vote down vote up 
def foldr(fn, elems, initializer=None, name=None):
    """Reduce elems using fn to combine them from right to left.

    # Arguments
        fn: Callable that will be called upon each element in elems and an
            accumulator, for instance `lambda acc, x: acc + x`
        elems: tensor
        initializer: The first value used (`elems[-1]` in case of None)
        name: A string name for the foldr node in the graph

    # Returns
        Tensor with same type and shape as `initializer`.
    """
    return tf.foldr(fn, elems, initializer=initializer, name=name)
Example #11
Source File: tensorflow_backend.py    From DeepLearning_Wavelet-LSTM with MIT License 5 votes vote down vote up 
def foldr(fn, elems, initializer=None, name=None):
    """Reduce elems using fn to combine them from right to left.

    # Arguments
        fn: Callable that will be called upon each element in elems and an
            accumulator, for instance `lambda acc, x: acc + x`
        elems: tensor
        initializer: The first value used (`elems[-1]` in case of None)
        name: A string name for the foldr node in the graph

    # Returns
        Tensor with same type and shape as `initializer`.
    """
    return tf.foldr(fn, elems, initializer=initializer, name=name)
Example #12
Source File: tensorflow_backend.py    From deepQuest with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def foldr(fn, elems, initializer=None, name=None):
    """Reduce elems using fn to combine them from right to left.

    # Arguments
        fn: Callable that will be called upon each element in elems and an
            accumulator, for instance `lambda acc, x: acc + x`
        elems: tensor
        initializer: The first value used (`elems[-1]` in case of None)
        name: A string name for the foldr node in the graph

    # Returns
        Tensor with same type and shape as `initializer`.
    """
    return tf.foldr(fn, elems, initializer=initializer, name=name)
Example #13
Source File: tensorflow_backend.py    From keras-lambda with MIT License 5 votes vote down vote up 
def foldr(fn, elems, initializer=None, name=None):
    """Reduce elems using fn to combine them from right to left.

    # Arguments
        fn: Callable that will be called upon each element in elems and an
            accumulator, for instance `lambda acc, x: acc + x`
        elems: tensor
        initializer: The first value used (`elems[-1]` in case of None)
        name: A string name for the foldr node in the graph

    # Returns
        Tensor with same type and shape as `initializer`.
    """
    return tf.foldr(fn, elems, initializer=initializer, name=name)