def local_csm_grad_c(node):
""" csm_grad(None) -> csm_grad_c """
if node.op == csm_grad(None):
return [csm_grad_c(*node.inputs)]
return False
from basic import _is_sparse_variable
# This is tested in tests/test_basic.py:UsmmTests
local_usmm = gof.opt.PatternSub(
(theano.tensor.sub, 'z',
(theano.tensor.mul,
{'pattern': 'alpha',
'constraint': lambda expr: numpy.all(expr.type.broadcastable)},
(sparse._dot, 'x', 'y'))),
(usmm, (theano.tensor.neg, 'alpha'), 'x', 'y', 'z'))
register_specialize(local_usmm, name="local_usmm")
# This is tested in tests/test_opt.py:test_local_csm_grad_c
@gof.local_optimizer([csm_grad(None)])
def local_csm_grad_c(node):
""" csm_grad(None) -> csm_grad_c """
if node.op == csm_grad(None):
return [csm_grad_c(*node.inputs)]
return False
register_specialize(local_csm_grad_c)
# This is tested in tests/test_opt.py:test_local_csm_properties_csm
@gof.local_optimizer([csm_properties])
def local_csm_properties_csm(node):
"""if we find csm_properties(CSM(*args)), then we can replace that with the
*args directly"""
if node.op == csm_properties:
csm, = node.inputs
