def local_max_and_argmax(node):
"""
If we don't use the argmax, change it to a max only.
"""
if isinstance(node.op, T.MaxAndArgmax):
axis = node.op.get_params(node)
if len(node.outputs[1].clients) == 0:
new = CAReduce(scal.maximum, axis)(node.inputs[0])
return [new, None]
if len(node.outputs[0].clients) == 0:
return [None, T._argmax(node.inputs[0], axis)]
def local_max_and_argmax(node):
"""
If we don't use the argmax, change it to a max only.
"""
if isinstance(node.op, T.MaxAndArgmax):
axis = node.op.get_params(node)
if len(node.outputs[1].clients) == 0:
new = CAReduce(scal.maximum, axis)(node.inputs[0])
return [new, None]
if len(node.outputs[0].clients) == 0:
return [None, T._argmax(node.inputs[0], axis)]
def local_max_and_argmax(node):
"""
If we don't use the argmax, change it to a max only.
"""
if node.op == T._max_and_argmax:
if len(node.outputs[1].clients) == 0:
# MaxAndArgmax support variable axis,
# but CAReduce support only constant axis.
if node.inputs[1].data is None:
axis = None
else:
try:
axis = get_scalar_constant_value(node.inputs[1])
except NotScalarConstantError:
axis = node.inputs[1]
if not isinstance(axis, T.TensorConstant):
return False
axis = axis.data
new = CAReduce(scal.maximum, axis)(node.inputs[0])
return [new, None]
if len(node.outputs[0].clients) == 0:
return [None, T._argmax(node.inputs[0], node.inputs[1])]
def local_max_and_argmax(node):
"""
If we don't use the argmax, change it to a max only.
"""
if node.op == T._max_and_argmax:
if len(node.outputs[1].clients) == 0:
# MaxAndArgmax support variable axis,
# but CAReduce support only constant axis.
if node.inputs[1].data is None:
axis = None
else:
try:
axis = get_scalar_constant_value(node.inputs[1])
except NotScalarConstantError:
axis = node.inputs[1]
if not isinstance(axis, T.TensorConstant):
return False
axis = axis.data
new = CAReduce(scal.maximum, axis)(node.inputs[0])
return [new, None]
if len(node.outputs[0].clients) == 0:
return [None, T._argmax(node.inputs[0], node.inputs[1])]
