def _check_subgraph_exe3(sym, subgraph_backend, op_names):
"""Use the partitioned sym to bind an executor and compare the outputs
with those of the original executor"""
out = SymbolHandle()
check_call(_LIB.MXBuildSubgraphByOpNames(sym.handle, c_str(subgraph_backend), mx_uint(len(op_names)),
c_str_array(op_names), ctypes.byref(out)))
partitioned_sym = Symbol(out)
input_names = sym.list_inputs()
arg_names = sym.list_arguments()
aux_names = sym.list_auxiliary_states()
assert partitioned_sym.list_inputs() == input_names
assert partitioned_sym.list_arguments() == arg_names
assert partitioned_sym.list_auxiliary_states() == aux_names
arg_shapes, _, aux_shapes = sym.infer_shape()
arg_array = [mx.nd.random.uniform(shape=shape) for shape in arg_shapes]
aux_array = [mx.nd.random.uniform(shape=shape) for shape in aux_shapes]
exe = sym.bind(ctx=mx.current_context(), args=arg_array, aux_states=aux_array, grad_req='null')
partitioned_exe = partitioned_sym.bind(ctx=mx.current_context(), args=arg_array,
aux_states=aux_array, grad_req='null')
exe.forward()
partitioned_exe.forward()
assert len(exe.outputs) == len(partitioned_exe.outputs)
for i in range(len(exe.outputs)):
assert_almost_equal((exe.outputs[i] - partitioned_exe.outputs[i]).abs().sum().asnumpy(),
np.zeros(shape=(1,)))
def _check_subgraph_exe1(sym, subgraph_backend, op_names):
"""Use the partitioned sym to simple_bind an executor and compare the outputs
with those of the original executor"""
out = SymbolHandle()
check_call(_LIB.MXBuildSubgraphByOpNames(sym.handle, c_str(subgraph_backend), mx_uint(len(op_names)),
c_str_array(op_names), ctypes.byref(out)))
partitioned_sym = Symbol(out)
assert partitioned_sym.list_inputs() == sym.list_inputs()
assert partitioned_sym.list_arguments() == sym.list_arguments()
assert partitioned_sym.list_auxiliary_states() == sym.list_auxiliary_states()
exe = sym.simple_bind(ctx=mx.current_context(), grad_req='null')
partitioned_exe = partitioned_sym.simple_bind(ctx=mx.current_context(), grad_req='null')
input_names = sym.list_inputs()
for name in input_names:
if name in exe.arg_dict:
exe.arg_dict[name][:] = mx.nd.random.uniform(shape=exe.arg_dict[name].shape)
partitioned_exe.arg_dict[name][:] = exe.arg_dict[name]
else:
assert name in exe.aux_dict
exe.aux_dict[name][:] = mx.nd.random.uniform(shape=exe.aux_dict[name].shape)
partitioned_exe.aux_dict[name][:] = exe.aux_dict[name]
exe.forward()
partitioned_exe.forward()
assert len(exe.outputs) == len(partitioned_exe.outputs)
for i in range(len(exe.outputs)):
assert_almost_equal((exe.outputs[i] - partitioned_exe.outputs[i]).abs().sum().asnumpy(),
np.zeros(shape=(1,)))