def f(local_opt):
name = (kwargs and kwargs.pop('name')) or local_opt.__name__
optdb.register(
name,
TopoOptimizer(local_opt,
failure_callback=TopoOptimizer.warn_inplace), 60,
'fast_run', 'inplace', *tags)
return local_opt
def f(local_opt):
name = (kwargs and kwargs.pop("name")) or local_opt.__name__
optdb.register(
name,
TopoOptimizer(local_opt,
failure_callback=TopoOptimizer.warn_inplace),
60,
"fast_run",
"inplace",
"gpuarray",
*tags,
)
return local_opt
def OpSubOptimizer(op1, op2, fail=NavigatorOptimizer.warn_ignore, ign=True):
return TopoOptimizer(OpSub(op1, op2),
ignore_newtrees=ign,
failure_callback=fail)
out_tmp_padded = tensor.zeros(dtype=out_tmp.dtype,
shape=(Ns, Ts + 2 * Tpad, Nf, Tf,
Hout, Wout))
out_tmp_padded = tensor.set_subtensor(
out_tmp_padded[:, Tpad:(Ts + Tpad), :, :, :, :], out_tmp)
out_5d = diagonal_subtensor(out_tmp_padded, 1, 3).sum(axis=3)
return out_5d
@theano.gof.local_optimizer([DiagonalSubtensor, IncDiagonalSubtensor])
def local_inplace_DiagonalSubtensor(fgraph, node):
"""Also work for IncDiagonalSubtensor."""
if (isinstance(node.op, (DiagonalSubtensor, IncDiagonalSubtensor))
and not node.op.inplace):
new_op = node.op.__class__(inplace=True)
new_node = new_op(*node.inputs)
copy_stack_trace(node.outputs[0], new_node)
return [new_node]
return False
theano.compile.optdb.register(
"local_inplace_DiagonalSubtensor",
TopoOptimizer(local_inplace_DiagonalSubtensor,
failure_callback=TopoOptimizer.warn_inplace),
60,
"fast_run",
"inplace",
)
def TopoPatternOptimizer(p1, p2, ign=True):
return TopoOptimizer(PatternSub(p1, p2), ignore_newtrees=ign)