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update previous flaky naive engine test #15651

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update previous flaky naive engine test #15651

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update precious flaky naive engine test
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88 changes: 40 additions & 48 deletions tests/python/unittest/test_profiler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -267,21 +267,23 @@ def check_sorting(debug_str, sort_by, ascending):
test_profile_event(False)
for sb in sort_by_options:
for asc in ascending_options:
debug_str = profiler.dumps(format = 'json', sort_by = sb, ascending = asc)
debug_str = profiler.dumps(format='json', sort_by=sb, ascending=asc)
check_sorting(debug_str, sb, asc)
profiler.set_state('stop')

def test_aggregate_duplication():
file_name = 'test_aggregate_duplication.json'
enable_profiler(profile_filename = file_name, run=True, continuous_dump=True, \
enable_profiler(profile_filename=file_name, run=True, continuous_dump=True, \
aggregate_stats=True)
# clear aggregate stats
profiler.dumps(reset=True)
inp = mx.nd.zeros(shape=(100, 100))
y = mx.nd.sqrt(inp)
inp = inp + 1
inp = inp + 1
mx.nd.waitall()
profiler.dump(False)
debug_str = profiler.dumps(format = 'json')
debug_str = profiler.dumps(format='json')
target_dict = json.loads(debug_str)
assert 'Time' in target_dict and 'operator' in target_dict['Time'] \
and 'sqrt' in target_dict['Time']['operator'] \
Expand All @@ -293,7 +295,7 @@ def test_aggregate_duplication():
assert target_dict['Time']['operator']['_plus_scalar']['Count'] == 2
profiler.set_state('stop')

def test_custom_operator_profiling(seed = None, file_name = None):
def test_custom_operator_profiling(seed=None, file_name=None):
class Sigmoid(mx.operator.CustomOp):
def forward(self, is_train, req, in_data, out_data, aux):
x = in_data[0].asnumpy()
Expand Down Expand Up @@ -330,25 +332,34 @@ def create_operator(self, ctx, in_shapes, in_dtypes):

if file_name is None:
file_name = 'test_custom_operator_profiling.json'
enable_profiler(profile_filename = file_name, run=True, continuous_dump=True,\
enable_profiler(profile_filename=file_name, run=True, continuous_dump=True,\
aggregate_stats=True)
# clear aggregate stats
profiler.dumps(reset=True)
x = mx.nd.array([0, 1, 2, 3])
x.attach_grad()
with mx.autograd.record():
y = mx.nd.Custom(x, op_type='MySigmoid')
y.backward()
mx.nd.waitall()
profiler.dump(False)
debug_str = profiler.dumps(format = 'json')
debug_str = profiler.dumps(format='json')
target_dict = json.loads(debug_str)
assert 'Time' in target_dict and 'Custom Operator' in target_dict['Time'] \
and 'MySigmoid::pure_python' in target_dict['Time']['Custom Operator'] \
and '_backward_MySigmoid::pure_python' in target_dict['Time']['Custom Operator'] \
and 'MySigmoid::_zeros' in target_dict['Time']['Custom Operator']
profiler.set_state('stop')

def test_custom_operator_profiling_multiple_custom_ops_imperative(seed = None, \
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why was function name changed from test_ to check_?
Gotcha

mode = 'imperative', file_name = None):
def check_custom_operator_profiling_multiple_custom_ops_output(debug_str):
target_dict = json.loads(debug_str)
assert 'Time' in target_dict and 'Custom Operator' in target_dict['Time'] \
and 'MyAdd1::pure_python' in target_dict['Time']['Custom Operator'] \
and 'MyAdd2::pure_python' in target_dict['Time']['Custom Operator'] \
and 'MyAdd1::_plus_scalar' in target_dict['Time']['Custom Operator'] \
and 'MyAdd2::_plus_scalar' in target_dict['Time']['Custom Operator']

def custom_operator_profiling_multiple_custom_ops(seed, mode, file_name):
class MyAdd(mx.operator.CustomOp):
def forward(self, is_train, req, in_data, out_data, aux):
self.assign(out_data[0], req[0], in_data[0] + 1)
Expand Down Expand Up @@ -392,65 +403,46 @@ def infer_shape(self, in_shape):
def create_operator(self, ctx, shapes, dtypes):
return MyAdd()

if file_name is None:
file_name = 'test_custom_operator_profiling_multiple_custom_ops_imperative.json'
enable_profiler(profile_filename = file_name, run=True, continuous_dump=True,\
enable_profiler(profile_filename=file_name, run=True, continuous_dump=True,\
aggregate_stats=True)
# clear aggregate stats
profiler.dumps(reset=True)
inp = mx.nd.zeros(shape=(100, 100))
if mode == 'imperative':
x = inp + 1
y = mx.nd.Custom(inp, op_type='MyAdd1')
z = mx.nd.Custom(inp, op_type='MyAdd2')
elif mode == 'symbolic':
a = mx.symbol.Variable('a')
b = a + 1
c = mx.symbol.Custom(data=a, op_type='MyAdd1')
d = mx.symbol.Custom(data=a, op_type='MyAdd2')
b.bind(mx.cpu(), {'a': inp}).forward()
c.bind(mx.cpu(), {'a': inp}).forward()
d.bind(mx.cpu(), {'a': inp}).forward()
b = mx.symbol.Custom(data=a, op_type='MyAdd1')
c = mx.symbol.Custom(data=a, op_type='MyAdd2')
y = b.bind(mx.cpu(), {'a': inp})
z = c.bind(mx.cpu(), {'a': inp})
yy = y.forward()
zz = z.forward()
mx.nd.waitall()
profiler.dump(False)
debug_str = profiler.dumps(format = 'json')
target_dict = json.loads(debug_str)
'''
We are calling _plus_scalar within MyAdd1 and MyAdd2 and outside both the custom
operators, so in aggregate stats we should have three different kinds of
_plus_scalar under domains "Custom Operator" and "operator"
'''
assert 'Time' in target_dict and 'Custom Operator' in target_dict['Time'] \
and 'MyAdd1::pure_python' in target_dict['Time']['Custom Operator'] \
and 'MyAdd2::pure_python' in target_dict['Time']['Custom Operator'] \
and 'MyAdd1::_plus_scalar' in target_dict['Time']['Custom Operator'] \
and 'MyAdd2::_plus_scalar' in target_dict['Time']['Custom Operator'] \
and '_plus_scalar' not in target_dict['Time']['Custom Operator'] \
and 'operator' in target_dict['Time'] \
and '_plus_scalar' in target_dict['Time']['operator']
debug_str = profiler.dumps(format='json')
check_custom_operator_profiling_multiple_custom_ops_output(debug_str)
profiler.set_state('stop')

@unittest.skip("Flaky test https://github.com/apache/incubator-mxnet/issues/15406")

def test_custom_operator_profiling_multiple_custom_ops_symbolic():
run_in_spawned_process(test_custom_operator_profiling_multiple_custom_ops_imperative, \
{'MXNET_EXEC_BULK_EXEC_INFERENCE' : 0, \
'MXNET_EXEC_BULK_EXEC_TRAIN' : 0}, \
'symbolic', \
custom_operator_profiling_multiple_custom_ops(None, 'symbolic', \
'test_custom_operator_profiling_multiple_custom_ops_symbolic.json')

@unittest.skip("Flaky test https://github.com/apache/incubator-mxnet/issues/15406")
def test_custom_operator_profiling_multiple_custom_ops_imperative():
custom_operator_profiling_multiple_custom_ops(None, 'imperative', \
'test_custom_operator_profiling_multiple_custom_ops_imperative.json')

def test_custom_operator_profiling_naive_engine():
# run the three tests above using Naive Engine
run_in_spawned_process(test_custom_operator_profiling, \
{'MXNET_ENGINE_TYPE' : "NaiveEngine"}, \
'test_custom_operator_profiling_naive.json')
run_in_spawned_process(test_custom_operator_profiling_multiple_custom_ops_imperative, \
{'MXNET_ENGINE_TYPE' : "NaiveEngine"}, \
'imperative', \
run_in_spawned_process(custom_operator_profiling_multiple_custom_ops, \
{'MXNET_ENGINE_TYPE' : "NaiveEngine"}, 'imperative', \
'test_custom_operator_profiling_multiple_custom_ops_imperative_naive.json')
run_in_spawned_process(test_custom_operator_profiling_multiple_custom_ops_imperative, \
{'MXNET_ENGINE_TYPE' : "NaiveEngine", \
'MXNET_EXEC_BULK_EXEC_INFERENCE' : 0, \
'MXNET_EXEC_BULK_EXEC_TRAIN' : 0}, \
'symbolic', \
run_in_spawned_process(custom_operator_profiling_multiple_custom_ops, \
{'MXNET_ENGINE_TYPE' : "NaiveEngine"}, 'symbolic', \
'test_custom_operator_profiling_multiple_custom_ops_symbolic_naive.json')

if __name__ == '__main__':
Expand Down