def eval(node, clean_up=True):
"""
It evaluates a node that has taken a numpy array as input. Note that sequences
are not supported yet by this method
Examples:
Plus with two matrices
>>> print (cntk.eval(cntk.ops.plus([[-30.,40.], [1.,2.]], [[-30.,40.], [1.,2.]])))
# [array([[[-60., 80.], [2., 4.]]])]
Times with broadcast of a scalar over a matrix
>>> print (cntk.eval(cntk.ops.element_times([[-30.,40.], [1.,2.]], 5)))
# [array([[[-150., 200.], [5., 10.]]])]
Args:
node (:class:`cntk.graph.ComputationNode`): the node to evaluate
clean_up (bool): whether the temporary directory should be removed when the context is left
Returns:
NumPy array containing the result
"""
from cntk.context import get_new_context
# call a helper method to get a context
with get_new_context() as ctx:
ctx.clean_up = clean_up
return ctx.eval(node)
def eval(node, clean_up=True):
"""
It evaluates a node that has taken a numpy array as input. Note that sequences
are not supported yet by this method
Examples:
Plus with two matrices
>>> print (cntk.eval(cntk.ops.plus([[-30.,40.], [1.,2.]], [[-30.,40.], [1.,2.]])))
# [array([[[-60., 80.], [2., 4.]]])]
Times with broadcast of a scalar over a matrix
>>> print (cntk.eval(cntk.ops.element_times([[-30.,40.], [1.,2.]], 5)))
# [array([[[-150., 200.], [5., 10.]]])]
Args:
node (:class:`cntk.graph.ComputationNode`): the node to evaluate
clean_up (bool): whether the temporary directory should be removed when the context is left
Returns:
NumPy array containing the result
"""
from cntk.context import get_new_context
from cntk.ops import input_numpy, constant
from cntk.graph import ComputationNode, _InputComputationNodeBase
import numpy as np
# call a helper method to get a context
with get_new_context() as ctx:
ctx.clean_up = clean_up
first = True
# The params are passed as arryas, e.g. plus([1,2], [3,4]), and we need to
# wrap them with input and parameter nodes.
if node.params:
for p in node.params:
if p in node.inputs:
val = getattr(node, p)
if not isinstance(val, ComputationNode):
# One param needs to be an Input() node. This will be fixed in
# CNTK soon, so that we can remove this workaround and evaluate a
# network with no inputs.
if first:
ir = input_numpy([val], alias=p, name=p)
setattr(node, p, ir)
first = False
else:
setattr(node, p, constant(getattr(node, p),
name=p))
else:
if isinstance(val,
_InputComputationNodeBase) and first:
first = False
return ctx.eval(node)
def eval(node, clean_up=True):
"""
It evaluates a node that has taken a numpy array as input. Note that sequences
are not supported yet by this method
Examples:
Plus with two matrices
>>> print (cntk.eval(cntk.ops.plus([[-30.,40.], [1.,2.]], [[-30.,40.], [1.,2.]])))
# [array([[[-60., 80.], [2., 4.]]])]
Times with broadcast of a scalar over a matrix
>>> print (cntk.eval(cntk.ops.element_times([[-30.,40.], [1.,2.]], 5)))
# [array([[[-150., 200.], [5., 10.]]])]
Args:
node (:class:`cntk.graph.ComputationNode`): the node to evaluate
clean_up (bool): whether the temporary directory should be removed when the context is left
Returns:
NumPy array containing the result
"""
from cntk.context import get_new_context
from cntk.ops import input_numpy, constant
from cntk.graph import ComputationNode, _InputComputationNodeBase
import numpy as np
# call a helper method to get a context
with get_new_context() as ctx:
ctx.clean_up = clean_up
first = True
# The params are passed as arryas, e.g. plus([1,2], [3,4]), and we need to
# wrap them with input and parameter nodes.
if node.params:
for p in node.params:
if p in node.inputs:
val = getattr(node, p)
if not isinstance(val, ComputationNode):
# One param needs to be an Input() node. This will be fixed in
# CNTK soon, so that we can remove this workaround and evaluate a
# network with no inputs.
if first:
ir = input_numpy([val], alias=p, name=p)
setattr(node, p, ir)
first = False
else:
setattr(node, p, constant(getattr(node, p), name=p))
else:
if isinstance(val, _InputComputationNodeBase) and first:
first = False
return ctx.eval(node)
def unittest_helper(root_node, input_numpy, expected, device_id=-1, precision="float",
clean_up=True, backward_pass=False, input_node=None):
from cntk.context import get_new_context
with get_new_context() as ctx:
ctx.clean_up = clean_up
ctx.device_id = device_id
ctx.precision = precision
assert not ctx.input_nodes
result = ctx.eval(root_node, input_numpy, backward_pass, input_node)
assert len(result) == len(expected)
for res, exp in zip(result, expected):
assert np.allclose(res, exp, atol=TOLERANCE_ABSOLUTE)
assert res.shape == AA(exp).shape
def unittest_helper(root_node,
input_numpy,
expected,
device_id=-1,
precision="float",
clean_up=True,
backward_pass=False,
input_node=None):
from cntk.context import get_new_context
with get_new_context() as ctx:
ctx.clean_up = clean_up
ctx.device_id = device_id
ctx.precision = precision
assert not ctx.input_nodes
result = ctx.eval(root_node, input_numpy, backward_pass, input_node)
assert len(result) == len(expected)
for res, exp in zip(result, expected):
assert np.allclose(res, exp, atol=TOLERANCE_ABSOLUTE)
assert res.shape == AA(exp).shape
