def _create_executor(ctx, executor):
'''
'''
name, network, remap = \
executor['name'], ctx.networks[executor['network']], \
executor.get('remp', {})
generator_variables = executor.get('generator_variables', [])
proto_network = ctx.proto_graphs[executor['network']].default_graph()
e = nnabla_pb2.Executor()
e.name = name
e.network_name = network.name
for vname in executor.get('data', proto_network.inputs):
if vname not in proto_network.variables:
raise ValueError("{} is not found in networks!".format(vname))
dv = e.data_variable.add()
dv.variable_name = vname
dv.data_name = remap.get(vname, vname)
for vname in executor.get('output', proto_network.outputs):
if vname not in proto_network.variables:
raise ValueError("{} is not found in networks!".format(vname))
ov = e.output_variable.add()
ov.variable_name = vname
ov.data_name = remap.get(vname, vname)
for param in proto_network.parameters.keys():
d = e.parameter_variable.add()
d.variable_name = param
for vname in generator_variables:
d = e.generator_variable.add()
d.type = 'Constant'
d.multiplier = 0
d.variable_name = vname
return e
def _create_executor(name, network, data, output, remap=None):
'''
'''
if remap is None:
remap = {}
e = nnabla_pb2.Executor()
e.name = name
e.network_name = network.name
_, _, params = _get_net_variables(network)
var_dict = {v.name: v for v in network.variable}
for vname in data:
try:
_ = var_dict[vname]
except KeyError:
raise KeyError("{} not found in {}".format(vname, network.name))
dv = e.data_variable.add()
dv.variable_name = vname
dv.data_name = remap.get(vname, vname)
for vname in output:
try:
_ = var_dict[vname]
except KeyError:
raise KeyError("{} not found in {}".format(vname, network.name))
ov = e.output_variable.add()
ov.variable_name = vname
ov.data_name = remap.get(vname, vname)
for param in params:
d = e.parameter_variable.add()
d.variable_name = param
return e
def _create_executor(name, network, input_names):
e = nnabla_pb2.Executor()
e.name = name
e.network_name = network.name
inputs, outputs, params = _get_net_variables(network)
count = 0
for inp in inputs:
d = e.data_variable.add()
d.variable_name = inp
d.data_name = input_names[count]
count += 1
for out in outputs:
d = e.output_variable.add()
d.variable_name = out
d.data_name = input_names[count]
count += 1
for param in params:
d = e.parameter_variable.add()
d.variable_name = param
return e