samskalicky commented on a change in pull request #15886: Graph Partition API
URL: https://github.com/apache/incubator-mxnet/pull/15886#discussion_r317711711
##########
File path: tests/python/unittest/test_subgraph_op.py
##########
@@ -146,11 +146,137 @@ def get_executor(sym, subgraph_backend=None,
op_names=None, original_exec=None):
for i in range(len(outputs1)):
assert_almost_equal((outputs1[i] -
outputs2[i]).abs().sum().asnumpy(), np.zeros(shape=(1,)))
+ def set_random_inputs(exe1, input_names):
+ """Sets random values to exe1's args and auxs"""
+ for name in input_names:
+ if name in exe1.arg_dict:
+ exe1.arg_dict[name][:] =
mx.nd.random.uniform(shape=exe1.arg_dict[name].shape)
+ else:
+ assert name in exe1.aux_dict
+ exe1.aux_dict[name][:] =
mx.nd.random.uniform(shape=exe1.aux_dict[name].shape)
+
+ def copy_inputs_between_executors(exe1, exe2, input_names):
+ """Copies values of args and auxs from exe1 to exe2"""
+ for name in input_names:
+ if name in exe2.arg_dict:
+ exe2.arg_dict[name][:] = exe1.arg_dict[name]
+ else:
+ assert name in exe2.aux_dict
+ exe2.aux_dict[name][:] = exe1.aux_dict[name]
+
+ def _check_subgraph_exe5(sym, subgraph_backend, op_names):
+ """Call optimize_for to trigger graph partitioning without infer
shapes/types before,
+ then simple_bind and compare results of the partitioned sym and the
original sym."""
+ # simple_bind
+ exe1 = sym.simple_bind(ctx=mx.current_context(), grad_req='null')
+ input_names = sym.list_inputs()
+ set_random_inputs(exe1, input_names)
+ exe1.forward()
+
+ # partition before simple_bind
+ check_call(_LIB.MXSetSubgraphPropertyOpNames(c_str(subgraph_backend),
mx_uint(len(op_names)),
+ c_str_array(op_names)))
+ part_sym = sym.optimize_for(subgraph_backend)
+
check_call(_LIB.MXRemoveSubgraphPropertyOpNames(c_str(subgraph_backend)))
+
+ exe2 = part_sym.simple_bind(ctx=mx.current_context(), grad_req='null')
+ copy_inputs_between_executors(exe1, exe2, input_names)
+ exe2.forward()
+
+ # compare outputs
+ outputs1 = exe1.outputs
+ outputs2 = exe2.outputs
+ assert len(outputs1) == len(outputs2)
+ for i in range(len(outputs1)):
+ assert_almost_equal((outputs1[i] -
outputs2[i]).abs().sum().asnumpy(), np.zeros(shape=(1,)))
+
+ def _check_subgraph_exe6(sym, subgraph_backend, op_names):
+ """Call optimize_for to trigger graph partitioning without infer
shapes/types before,
+ then simple_bind and compare results of the partitioned sym and the
original sym."""
+ # simple_bind
+ exe1 = sym.simple_bind(ctx=mx.current_context(), grad_req='null')
+ input_names = sym.list_inputs()
+ set_random_inputs(exe1, input_names)
+ exe1.forward()
+
+ # infer shape/type before partition before simple_bind
+ check_call(_LIB.MXSetSubgraphPropertyOpNames(c_str(subgraph_backend),
mx_uint(len(op_names)),
+ c_str_array(op_names)))
+ part_sym = sym.optimize_for(subgraph_backend, exe1.arg_dict)
+
check_call(_LIB.MXRemoveSubgraphPropertyOpNames(c_str(subgraph_backend)))
+
+ exe2 = part_sym.simple_bind(ctx=mx.current_context(), grad_req='null')
+ copy_inputs_between_executors(exe1, exe2, input_names)
+ exe2.forward()
+
+ # compare outputs
+ outputs1 = exe1.outputs
+ outputs2 = exe2.outputs
+ assert len(outputs1) == len(outputs2)
+ for i in range(len(outputs1)):
+ assert_almost_equal((outputs1[i] -
outputs2[i]).abs().sum().asnumpy(), np.zeros(shape=(1,)))
+
+ def _check_subgraph_exe7(sym, subgraph_backend, op_names):
+ """Call optimize_for to trigger graph partitioning without infer
shapes/types before,
+ then bind and compare results of the partitioned sym and the original
sym."""
+ # bind
+ 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]
+ exe1 = sym.bind(ctx=mx.current_context(), args=arg_array,
aux_states=aux_array, grad_req='null')
+ exe1.forward()
+
+ # partition before bind
+ check_call(_LIB.MXSetSubgraphPropertyOpNames(c_str(subgraph_backend),
mx_uint(len(op_names)),
+ c_str_array(op_names)))
+ part_sym = sym.optimize_for(subgraph_backend)
+
check_call(_LIB.MXRemoveSubgraphPropertyOpNames(c_str(subgraph_backend)))
+
+ exe2 = part_sym.bind(ctx=mx.current_context(), args=arg_array,
aux_states=aux_array, grad_req='null')
+ exe2.forward()
+
+ # compare outputs
+ outputs1 = exe1.outputs
+ outputs2 = exe2.outputs
+ assert len(outputs1) == len(outputs2)
+ for i in range(len(outputs1)):
+ assert_almost_equal((outputs1[i] -
outputs2[i]).abs().sum().asnumpy(), np.zeros(shape=(1,)))
+
+ def _check_subgraph_exe8(sym, subgraph_backend, op_names):
+ """Call optimize_for to infer shapes, types and dtypes followed by
graph partitioning,
+ then bind and compare results of the partitioned sym and the original
sym."""
+ # bind
+ 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]
+ exe1 = sym.bind(ctx=mx.current_context(), args=arg_array,
aux_states=aux_array, grad_req='null')
+ exe1.forward()
+
+ # infer shape/type before partition before bind
+ check_call(_LIB.MXSetSubgraphPropertyOpNames(c_str(subgraph_backend),
mx_uint(len(op_names)),
+ c_str_array(op_names)))
+ part_sym = sym.optimize_for(subgraph_backend, arg_array)
+
check_call(_LIB.MXRemoveSubgraphPropertyOpNames(c_str(subgraph_backend)))
+
+ exe2 = part_sym.bind(ctx=mx.current_context(), args=arg_array,
aux_states=aux_array, grad_req='null')
+ exe2.forward()
+
+ # compare outputs
+ outputs1 = exe1.outputs
+ outputs2 = exe2.outputs
+ assert len(outputs1) == len(outputs2)
+ for i in range(len(outputs1)):
+ assert_almost_equal((outputs1[i] -
outputs2[i]).abs().sum().asnumpy(), np.zeros(shape=(1,)))
+
def check_subgraph_exe(sym, subgraph_backend, op_names):
_check_subgraph_exe1(sym, subgraph_backend, op_names)
_check_subgraph_exe2(sym, subgraph_backend, op_names)
_check_subgraph_exe3(sym, subgraph_backend, op_names)
_check_subgraph_exe4(sym, subgraph_backend, op_names)
+ _check_subgraph_exe5(sym, subgraph_backend, op_names)
+ _check_subgraph_exe6(sym, subgraph_backend, op_names)
+ _check_subgraph_exe7(sym, subgraph_backend, op_names)
+ _check_subgraph_exe8(sym, subgraph_backend, op_names)
Review comment:
Currently no subgraph property supports the excluded_ops option, so testing
now would not be helpful. We do plan to create a test for this in a follow-up
PR where we implement support for subgraph properties in libraries though.
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