def gather(seq, condition, name=''):
'''
Takes two sequences of the same length and returns a new sequence whose
elements are those elements of sequence `seq` whose corresponding element
in `condition` is True, preserving the ordering of `seq`.
This operation is also known as stream compaction, or copy_if.
Example:
>>> x = C.input_variable(shape=(3,2))
>>> z = C.greater(C.reduce_sum(x),60)
>>> y = C.sequence.gather(x,z)
>>> x0 = np.reshape(np.arange(24.0,dtype=np.float32),(4,3,2))
>>> y.eval({x:x0})
array([[[[ 12., 13.],
[ 14., 15.],
[ 16., 17.]],
<BLANKLINE>
[[ 18., 19.],
[ 20., 21.],
[ 22., 23.]]]], dtype=float32)
Args:
seq: the symbolic sequence from which elements will be selected
condition: the symbolic sequence of booleans which indicate which
elements should be selected
name (str): the name of the node in the network
Returns:
:class:`cntk.Function`
'''
from cntk.cntk_py import gather
seq = sanitize_input(seq, get_data_type(seq))
condition = sanitize_input(condition, get_data_type(condition))
return gather(seq, condition, name)
def gather(seq, condition, name=''):
'''
Takes two sequences of the same length and returns a new sequence whose
elements are those elements of sequence ``seq`` whose corresponding element
in ``condition`` is True, preserving the ordering of ``seq``.
This operation is also known as stream compaction, or copy_if.
Example:
>>> x = C.input_variable(shape=(3,2))
>>> z = C.greater(C.reduce_sum(x),60)
>>> y = C.sequence.gather(x,z)
>>> # create one sequence of 4 tensors each with shape (3,2)
>>> x0 = np.reshape(np.arange(24.0,dtype=np.float32),(1,4,3,2))
>>> y.eval({x:x0})
array([[[[ 12., 13.],
[ 14., 15.],
[ 16., 17.]],
<BLANKLINE>
[[ 18., 19.],
[ 20., 21.],
[ 22., 23.]]]], dtype=float32)
Args:
seq: the symbolic sequence from which elements will be selected
condition: the symbolic sequence of booleans which indicate which
elements should be selected
name (str): the name of the node in the network
Returns:
:class:`~cntk.ops.functions.Function`
'''
from cntk.cntk_py import gather
seq = sanitize_input(seq, get_data_type(seq))
condition = sanitize_input(condition, get_data_type(condition))
return gather(seq, condition, name)
def gather(seq, condition, new_sequence_axis_typeinfo=None, name=''):
'''
Takes two sequences of the same length and returns a new sequence whose
elements are those elements of sequence ``seq`` whose corresponding element
in ``condition`` is True, preserving the ordering of ``seq``.
This operation is also known as stream compaction, or copy_if.
Example:
>>> x = C.sequence.input(shape=(3,2))
>>> z = C.greater(C.reduce_sum(x),60)
>>> y = C.sequence.gather(x,z)
>>> # create one sequence of 4 tensors each with shape (3,2)
>>> x0 = np.reshape(np.arange(24.0,dtype=np.float32),(1,4,3,2))
>>> y.eval({x:x0})
[array([[[ 12., 13.],
[ 14., 15.],
[ 16., 17.]],
<BLANKLINE>
[[ 18., 19.],
[ 20., 21.],
[ 22., 23.]]], dtype=float32)]
Args:
seq: the symbolic sequence from which elements will be selected
condition: the symbolic sequence of booleans which indicate which
elements should be selected
new_sequence_axis_typeinfo: tuple of integers indicating
the scaling and additive factors for the length of the new sequence axis
w.r.t. the operand sequence. This is used to determine the sequence axis
to be used for the output of the gather operation. If this argument is left
unspecified, a new independent sequence axis is created.
name (str): the name of the node in the network
Returns:
:class:`~cntk.ops.functions.Function`
'''
from cntk.cntk_py import gather
seq = sanitize_input(seq, get_data_type(seq))
condition = sanitize_input(condition, get_data_type(condition))
if new_sequence_axis_typeinfo is None:
return gather(seq, condition, name)
else:
return gather(seq, condition, new_sequence_axis_typeinfo, name)
def gather(seq, condition, new_sequence_axis_typeinfo=None, name=''):
'''
Takes two sequences of the same length and returns a new sequence whose
elements are those elements of sequence ``seq`` whose corresponding element
in ``condition`` is True, preserving the ordering of ``seq``.
This operation is also known as stream compaction, or copy_if.
Example:
>>> x = C.sequence.input_variable(shape=(3,2))
>>> z = C.greater(C.reduce_sum(x),60)
>>> y = C.sequence.gather(x,z)
>>> # create one sequence of 4 tensors each with shape (3,2)
>>> x0 = np.reshape(np.arange(24.0,dtype=np.float32),(1,4,3,2))
>>> y.eval({x:x0})
[array([[[ 12., 13.],
[ 14., 15.],
[ 16., 17.]],
<BLANKLINE>
[[ 18., 19.],
[ 20., 21.],
[ 22., 23.]]], dtype=float32)]
Args:
seq: the symbolic sequence from which elements will be selected
condition: the symbolic sequence of booleans which indicate which
elements should be selected
new_sequence_axis_typeinfo: tuple of integers indicating
the scaling and additive factors for the length of the new sequence axis
w.r.t. the operand sequence. This is used to determine the sequence axis
to be used for the output of the gather operation. If this argument is left
unspecified, a new independent sequence axis is created.
name (str): the name of the node in the network
Returns:
:class:`~cntk.ops.functions.Function`
'''
from cntk.cntk_py import gather
seq = sanitize_input(seq, get_data_type(seq))
condition = sanitize_input(condition, get_data_type(condition))
if new_sequence_axis_typeinfo is None:
return gather(seq, condition, name)
else:
return gather(seq, condition, new_sequence_axis_typeinfo, name)
def gather(operand, condition, name=''):
'''
TBA
Example:
TBA
Args:
operand: the symbolic tensor operand denoting a sequence
condition: the symbolic tensor operand denoting a boolean condition flag for each step of a sequence
name (str): the name of the node in the network
Returns:
:class:`cntk.Function`
'''
from cntk.cntk_py import gather
operand = sanitize_input(operand, get_data_type(operand))
condition = sanitize_input(condition, get_data_type(condition))
return gather(operand, condition, name)
def gather(operand, condition, name=''):
'''
TBA
Example:
TBA
Args:
operand: the symbolic tensor operand denoting a sequence
condition: the symbolic tensor operand denoting a boolean condition flag for each step of a sequence
name (str): the name of the node in the network
Returns:
:class:`cntk.Function`
'''
from cntk.cntk_py import gather
operand = sanitize_input(operand, get_data_type(operand))
condition = sanitize_input(condition, get_data_type(condition))
return gather(operand, condition, name)