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):
Schedule(
sfg,
scheduler=HybridScheduler(max_concurrent_reads=max_concurrent_reads),
)
def test_invalid_input_times(self):
sfg = ldlt_matrix_inverse(N=2)
sfg.set_latency_of_type_name(MADS.type_name(), 3)
sfg.set_latency_of_type_name(Reciprocal.type_name(), 2)
sfg.set_execution_time_of_type_name(MADS.type_name(), 1)
sfg.set_execution_time_of_type_name(Reciprocal.type_name(), 1)
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input_times = 5
with pytest.raises(
ValueError, match="Provided input_times must be a dictionary."
):
Schedule(sfg, scheduler=HybridScheduler(input_times=input_times))
input_times = "test1"
with pytest.raises(
ValueError, match="Provided input_times must be a dictionary."
):
Schedule(sfg, scheduler=HybridScheduler(input_times=input_times))
input_times = []
with pytest.raises(
ValueError, match="Provided input_times must be a dictionary."
):
Schedule(sfg, scheduler=HybridScheduler(input_times=input_times))
input_times = {3: 3}
with pytest.raises(
ValueError, match="Provided input_times keys must be strings."
):
Schedule(sfg, scheduler=HybridScheduler(input_times=input_times))
input_times = {"in0": "foo"}
with pytest.raises(
ValueError, match="Provided input_times values must be integers."
):
Schedule(sfg, scheduler=HybridScheduler(input_times=input_times))
input_times = {"in0": -1}
with pytest.raises(
ValueError, match="Provided input_times values must be non-negative."
):
Schedule(sfg, scheduler=HybridScheduler(input_times=input_times))
def test_invalid_output_delta_times(self):
sfg = ldlt_matrix_inverse(N=2)
sfg.set_latency_of_type_name(MADS.type_name(), 3)
sfg.set_latency_of_type_name(Reciprocal.type_name(), 2)
sfg.set_execution_time_of_type_name(MADS.type_name(), 1)
sfg.set_execution_time_of_type_name(Reciprocal.type_name(), 1)
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output_delta_times = 10
with pytest.raises(
ValueError, match="Provided output_delta_times must be a dictionary."
):
Schedule(
sfg, scheduler=HybridScheduler(output_delta_times=output_delta_times)
)
output_delta_times = "test2"
with pytest.raises(
ValueError, match="Provided output_delta_times must be a dictionary."
):
Schedule(
sfg, scheduler=HybridScheduler(output_delta_times=output_delta_times)
)
output_delta_times = []
with pytest.raises(
ValueError, match="Provided output_delta_times must be a dictionary."
):
Schedule(
sfg, scheduler=HybridScheduler(output_delta_times=output_delta_times)
)
output_delta_times = {4: 4}
with pytest.raises(
ValueError, match="Provided output_delta_times keys must be strings."
):
Schedule(
sfg, scheduler=HybridScheduler(output_delta_times=output_delta_times)
)
output_delta_times = {"out0": "foo"}
with pytest.raises(
ValueError, match="Provided output_delta_times values must be integers."
):
Schedule(
sfg, scheduler=HybridScheduler(output_delta_times=output_delta_times)
)
output_delta_times = {"out0": -1}
with pytest.raises(
ValueError, match="Provided output_delta_times values must be non-negative."
):
Schedule(
sfg, scheduler=HybridScheduler(output_delta_times=output_delta_times)
)
def test_resource_not_in_sfg(self):
sfg = ldlt_matrix_inverse(N=3)
sfg.set_latency_of_type_name(MADS.type_name(), 3)
sfg.set_latency_of_type_name(Reciprocal.type_name(), 2)
sfg.set_execution_time_of_type_name(MADS.type_name(), 1)
sfg.set_execution_time_of_type_name(Reciprocal.type_name(), 1)
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resources = {
MADS.type_name(): 1,
Reciprocal.type_name(): 1,
Addition.type_name(): 2,
}
with pytest.raises(
ValueError,
match="Provided max resource of type add cannot be found in the provided SFG.",
):
Schedule(sfg, scheduler=HybridScheduler(resources))
def test_input_not_in_sfg(self):
sfg = ldlt_matrix_inverse(N=2)
sfg.set_latency_of_type_name(MADS.type_name(), 3)
sfg.set_latency_of_type_name(Reciprocal.type_name(), 2)
sfg.set_execution_time_of_type_name(MADS.type_name(), 1)
sfg.set_execution_time_of_type_name(Reciprocal.type_name(), 1)
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input_times = {"in100": 4}
with pytest.raises(
ValueError,
match="Provided input time with GraphID in100 cannot be found in the provided SFG.",
):
Schedule(sfg, scheduler=HybridScheduler(input_times=input_times))
def test_output_not_in_sfg(self):
sfg = ldlt_matrix_inverse(N=2)
sfg.set_latency_of_type_name(MADS.type_name(), 3)
sfg.set_latency_of_type_name(Reciprocal.type_name(), 2)
sfg.set_execution_time_of_type_name(MADS.type_name(), 1)
sfg.set_execution_time_of_type_name(Reciprocal.type_name(), 1)
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output_delta_times = {"out90": 2}
with pytest.raises(
ValueError,
match="Provided output delta time with GraphID out90 cannot be found in the provided SFG.",
):
Schedule(
sfg, scheduler=HybridScheduler(output_delta_times=output_delta_times)
)
def test_ldlt_inverse_3x3_read_and_write_constrained(self):
sfg = ldlt_matrix_inverse(N=3)
sfg.set_latency_of_type_name(MADS.type_name(), 3)
sfg.set_latency_of_type_name(Reciprocal.type_name(), 2)
sfg.set_execution_time_of_type_name(MADS.type_name(), 1)
sfg.set_execution_time_of_type_name(Reciprocal.type_name(), 1)
resources = {MADS.type_name(): 1, Reciprocal.type_name(): 1}
schedule = Schedule(
sfg,
scheduler=HybridScheduler(
max_resources=resources,
max_concurrent_reads=3,
max_concurrent_writes=1,
),
)
direct, mem_vars = schedule.get_memory_variables().split_on_length()
assert mem_vars.read_ports_bound() == 3
assert mem_vars.write_ports_bound() == 1
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_validate_recreated_sfg_ldlt_matrix_inverse(schedule, 3)
def test_32_point_fft_custom_io_times(self):
POINTS = 32
sfg = radix_2_dif_fft(POINTS)
sfg.set_latency_of_type_name(Butterfly.type_name(), 1)
sfg.set_latency_of_type_name(ConstantMultiplication.type_name(), 3)
sfg.set_execution_time_of_type_name(Butterfly.type_name(), 1)
sfg.set_execution_time_of_type_name(ConstantMultiplication.type_name(), 1)
resources = {Butterfly.type_name(): 1, ConstantMultiplication.type_name(): 1}
input_times = {f"in{i}": i for i in range(POINTS)}
output_delta_times = {f"out{i}": i for i in range(POINTS)}
schedule = Schedule(
sfg,
scheduler=HybridScheduler(
resources,
input_times=input_times,
output_delta_times=output_delta_times,
),
)
for i in range(POINTS):
assert schedule.start_times[f"in{i}"] == i
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assert schedule.start_times[f"out{i}"] == 95 + i
# too slow for pipeline timeout
# def test_64_point_fft_custom_io_times(self):
# POINTS = 64
# sfg = radix_2_dif_fft(POINTS)
# sfg.set_latency_of_type_name(Butterfly.type_name(), 1)
# sfg.set_latency_of_type_name(ConstantMultiplication.type_name(), 3)
# sfg.set_execution_time_of_type_name(Butterfly.type_name(), 1)
# sfg.set_execution_time_of_type_name(ConstantMultiplication.type_name(), 1)
# resources = {Butterfly.type_name(): 1, ConstantMultiplication.type_name(): 1}
# input_times = {f"in{i}": i for i in range(POINTS)}
# output_delta_times = {f"out{i}": i for i in range(POINTS)}
# schedule = Schedule(
# sfg,
# scheduler=HybridScheduler(
# resources,
# input_times=input_times,
# output_delta_times=output_delta_times,
# ),
# )
# for i in range(POINTS):
# assert schedule.start_times[f"in{i}"] == i
# assert (
# schedule.start_times[f"out{i}"]
# == schedule.get_max_non_io_end_time() - 1 + i
# )
def test_32_point_fft_custom_io_times_cyclic(self):
POINTS = 32
sfg = radix_2_dif_fft(POINTS)
sfg.set_latency_of_type_name(Butterfly.type_name(), 1)
sfg.set_latency_of_type_name(ConstantMultiplication.type_name(), 3)
sfg.set_execution_time_of_type_name(Butterfly.type_name(), 1)
sfg.set_execution_time_of_type_name(ConstantMultiplication.type_name(), 1)
resources = {Butterfly.type_name(): 1, ConstantMultiplication.type_name(): 1}
input_times = {f"in{i}": i for i in range(POINTS)}
output_delta_times = {f"out{i}": i for i in range(POINTS)}
schedule = Schedule(
sfg,
scheduler=HybridScheduler(
resources,
input_times=input_times,
output_delta_times=output_delta_times,
),
schedule_time=96,
cyclic=True,
)
for i in range(POINTS):
assert schedule.start_times[f"in{i}"] == i
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if i == 0:
expected_value = 95
elif i == 1:
expected_value = 96
else:
expected_value = i - 1
assert schedule.start_times[f"out{i}"] == expected_value
def test_cyclic_scheduling(self):
sfg = radix_2_dif_fft(points=4)
sfg.set_latency_of_type_name(Butterfly.type_name(), 1)
sfg.set_latency_of_type_name(ConstantMultiplication.type_name(), 3)
sfg.set_execution_time_of_type_name(Butterfly.type_name(), 1)
sfg.set_execution_time_of_type_name(ConstantMultiplication.type_name(), 1)
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resources = {
Butterfly.type_name(): 1,
ConstantMultiplication.type_name(): 1,
}
schedule_1 = Schedule(sfg, scheduler=HybridScheduler(resources))
schedule_2 = Schedule(
sfg, scheduler=HybridScheduler(resources), schedule_time=6, cyclic=True
)
schedule_3 = Schedule(
sfg, scheduler=HybridScheduler(resources), schedule_time=5, cyclic=True
)
schedule_4 = Schedule(
sfg, scheduler=HybridScheduler(resources), schedule_time=4, cyclic=True
)
assert schedule_1.start_times == {
"in1": 0,
"in3": 1,
"bfly3": 1,
"cmul0": 2,
"in0": 2,
"in2": 3,
"bfly0": 3,
"bfly1": 4,
"bfly2": 5,
"out0": 5,
"out1": 6,
"out3": 7,
"out2": 8,
}
assert schedule_1.laps == {
"s4": 0,
"s6": 0,
"s5": 0,
"s7": 0,
"s8": 0,
"s12": 0,
"s10": 0,
"s9": 0,
"s0": 0,
"s2": 0,
"s11": 0,
"s1": 0,
"s3": 0,
}
assert schedule_1.schedule_time == 8
assert schedule_2.start_times == {
"in1": 0,
"in3": 1,
"bfly3": 1,
"cmul0": 2,
"in0": 2,
"in2": 3,
"bfly0": 3,
"bfly1": 4,
"bfly2": 5,
"out0": 5,
"out1": 6,
"out3": 1,
"out2": 2,
}
assert schedule_2.laps == {
"s4": 0,
"s6": 1,
"s5": 0,
"s7": 1,
"s8": 0,
"s12": 0,
"s10": 0,
"s9": 0,
"s0": 0,
"s2": 0,
"s11": 0,
"s1": 0,
"s3": 0,
}
assert schedule_2.schedule_time == 6
assert schedule_3.start_times == {
"in1": 0,
"in3": 1,
"bfly3": 1,
"cmul0": 2,
"in0": 2,
"in2": 3,
"bfly0": 3,
"bfly1": 4,
"bfly2": 0,
"out0": 5,
"out1": 1,
"out3": 2,
"out2": 3,
}
assert schedule_3.laps == {
"s4": 0,
"s6": 1,
"s5": 0,
"s7": 0,
"s8": 0,
"s12": 0,
"s10": 1,
"s9": 1,
"s0": 0,
"s2": 0,
"s11": 0,
"s1": 0,
"s3": 0,
}
assert schedule_3.schedule_time == 5
assert schedule_4.start_times == {
"in1": 0,
"in3": 1,
"bfly3": 1,
"cmul0": 2,
"in0": 2,
"in2": 3,
"bfly0": 3,
"bfly1": 0,
"out0": 1,
"bfly2": 2,
"out2": 2,
"out1": 3,
"out3": 4,
}
assert schedule_4.laps == {
"s4": 0,
"s6": 0,
"s5": 0,
"s7": 0,
"s8": 1,
"s12": 1,
"s10": 0,
"s9": 1,
"s0": 0,
"s2": 0,
"s11": 0,
"s1": 0,
"s3": 0,
}
assert schedule_4.schedule_time == 4
def test_resources_not_enough(self):
sfg = ldlt_matrix_inverse(N=3)
sfg.set_latency_of_type_name(MADS.type_name(), 3)
sfg.set_latency_of_type_name(Reciprocal.type_name(), 2)
sfg.set_execution_time_of_type_name(MADS.type_name(), 1)
sfg.set_execution_time_of_type_name(Reciprocal.type_name(), 1)
resources = {MADS.type_name(): 1, Reciprocal.type_name(): 1}
with pytest.raises(
ValueError,
match="Amount of resource: mads is not enough to realize schedule for scheduling time: 5.",
):
Schedule(
sfg,
scheduler=HybridScheduler(
max_resources=resources,
),
schedule_time=5,
)
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sfg = radix_2_dif_fft(points=8)
sfg.set_latency_of_type_name(Butterfly.type_name(), 1)
sfg.set_latency_of_type_name(ConstantMultiplication.type_name(), 3)
sfg.set_execution_time_of_type_name(Butterfly.type_name(), 1)
sfg.set_execution_time_of_type_name(ConstantMultiplication.type_name(), 1)
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resources = {
Butterfly.type_name(): 1,
ConstantMultiplication.type_name(): 1,
}
with pytest.raises(
ValueError,
match="Amount of resource: bfly is not enough to realize schedule for scheduling time: 6.",
):
Schedule(
sfg,
scheduler=HybridScheduler(
resources, max_concurrent_reads=2, max_concurrent_writes=2
),
schedule_time=6,
cyclic=True,
)
def test_scheduling_time_not_enough(self):
sfg = ldlt_matrix_inverse(N=3)
sfg.set_latency_of_type_name(MADS.type_name(), 3)
sfg.set_latency_of_type_name(Reciprocal.type_name(), 2)
sfg.set_execution_time_of_type_name(MADS.type_name(), 1)
sfg.set_execution_time_of_type_name(Reciprocal.type_name(), 1)
resources = {MADS.type_name(): 10, Reciprocal.type_name(): 10}
with pytest.raises(
ValueError,
match="Provided scheduling time 5 cannot be reached, try to enable the cyclic property or increase the time to at least 30.",
):
Schedule(
sfg,
scheduler=HybridScheduler(
max_resources=resources,
),
schedule_time=5,
)
def test_cyclic_scheduling_write_and_read_constrained(self):
sfg = radix_2_dif_fft(points=4)
sfg.set_latency_of_type_name(Butterfly.type_name(), 1)
sfg.set_latency_of_type_name(ConstantMultiplication.type_name(), 3)
sfg.set_execution_time_of_type_name(Butterfly.type_name(), 1)
sfg.set_execution_time_of_type_name(ConstantMultiplication.type_name(), 1)
resources = {
Butterfly.type_name(): 1,
ConstantMultiplication.type_name(): 1,
}
schedule = Schedule(
sfg,
scheduler=HybridScheduler(
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resources, max_concurrent_reads=2, max_concurrent_writes=3
),
schedule_time=6,
cyclic=True,
)
assert schedule.start_times == {
"in1": 0,
"in3": 1,
"bfly3": 1,
"cmul0": 2,
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"in0": 2,
"in2": 3,
"bfly0": 3,
"bfly1": 4,
"bfly2": 5,
"out0": 5,
"out1": 6,
"out3": 1,
"out2": 2,
}
assert schedule.laps == {
"s4": 0,
"s6": 1,
"s5": 0,
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"s7": 1,
"s8": 0,
"s12": 0,
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"s10": 0,
"s9": 0,
"s0": 0,
"s2": 0,
"s11": 0,
"s1": 0,
"s3": 0,
}
assert schedule.schedule_time == 6
_, mem_vars = schedule.get_memory_variables().split_on_length()
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assert mem_vars.read_ports_bound() <= 2
assert mem_vars.write_ports_bound() <= 3
def test_cyclic_scheduling_several_inputs_and_outputs(self):
sfg = radix_2_dif_fft(points=4)
sfg.set_latency_of_type_name(Butterfly.type_name(), 1)
sfg.set_latency_of_type_name(ConstantMultiplication.type_name(), 3)
sfg.set_execution_time_of_type_name(Butterfly.type_name(), 1)
sfg.set_execution_time_of_type_name(ConstantMultiplication.type_name(), 1)
resources = {
Butterfly.type_name(): 1,
ConstantMultiplication.type_name(): 1,
Input.type_name(): 2,
Output.type_name(): 2,
}
schedule = Schedule(
sfg, scheduler=HybridScheduler(resources), schedule_time=4, cyclic=True
)
assert schedule.schedule_time == 4
_validate_recreated_sfg_fft(schedule, points=4, delays=[0, 1, 0, 1])
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def test_invalid_output_delta_time(self):
sfg = radix_2_dif_fft(points=4)
sfg.set_latency_of_type_name(Butterfly.type_name(), 1)
sfg.set_latency_of_type_name(ConstantMultiplication.type_name(), 3)
sfg.set_execution_time_of_type_name(Butterfly.type_name(), 1)
sfg.set_execution_time_of_type_name(ConstantMultiplication.type_name(), 1)
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resources = {
Butterfly.type_name(): 1,
ConstantMultiplication.type_name(): 1,
Input.type_name(): 2,
Output.type_name(): 2,
}
output_delta_times = {"out0": 0, "out1": 1, "out2": 2, "out3": 3}
with pytest.raises(
ValueError,
match="Cannot place output out2 at time 6 for scheduling time 5. Try to relax the scheduling time, change the output delta times or enable cyclic.",
):
Schedule(
sfg,
scheduler=HybridScheduler(
resources, output_delta_times=output_delta_times
),
schedule_time=5,
)
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def test_iteration_period_bound(self):
sfg = direct_form_1_iir([1, 2, 3], [1, 2, 3])
sfg.set_latency_of_type_name(ConstantMultiplication.type_name(), 2)
sfg.set_execution_time_of_type_name(ConstantMultiplication.type_name(), 1)
sfg.set_latency_of_type_name(Addition.type_name(), 3)
sfg.set_execution_time_of_type_name(Addition.type_name(), 1)
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resources = {
Addition.type_name(): 1,
ConstantMultiplication.type_name(): 1,
}
with pytest.raises(
ValueError,
match="Provided scheduling time 5 must be larger or equal to the iteration period bound: 8.",
):
Schedule(
sfg,
scheduler=EarliestDeadlineScheduler(max_resources=resources),
schedule_time=5,
cyclic=True,
)
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def test_latency_offsets(self):
sfg = ldlt_matrix_inverse(
N=3,
mads_properties={
"latency_offsets": {"in0": 3, "in1": 0, "in2": 0, "out0": 4},
"execution_time": 1,
},
reciprocal_properties={"latency": 10, "execution_time": 1},
)
schedule = Schedule(sfg, scheduler=HybridScheduler())
assert schedule.start_times == {
"dontcare0": 49,
"dontcare1": 50,
"dontcare2": 31,
"dontcare3": 55,
"dontcare4": 14,
"dontcare5": 13,
"in0": 0,
"in1": 1,
"in2": 3,
"in3": 2,
"in4": 4,
"in5": 5,
"mads0": 10,
"mads1": 11,
"mads10": 32,
"mads11": 47,
"mads12": 16,
"mads13": 15,
"mads14": 14,
"mads2": 55,
"mads3": 51,
"mads4": 58,
"mads5": 54,
"mads6": 52,
"mads7": 50,
"mads8": 28,
"mads9": 46,
"out0": 62,
"out1": 58,
"out2": 55,
"out3": 54,
"out4": 50,
"out5": 46,
"rec0": 0,
"rec1": 18,
"rec2": 36,
}
assert all(val == 0 for val in schedule.laps.values())
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_validate_recreated_sfg_ldlt_matrix_inverse(schedule, 3)
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def test_latency_offsets_cyclic(self):
sfg = ldlt_matrix_inverse(
N=3,
mads_properties={
"latency_offsets": {"in0": 3, "in1": 0, "in2": 0, "out0": 4},
"execution_time": 1,
},
reciprocal_properties={"latency": 10, "execution_time": 1},
)
schedule = Schedule(
sfg,
scheduler=HybridScheduler(),
schedule_time=49,
cyclic=True,
)
assert schedule.schedule_time == 49
_validate_recreated_sfg_ldlt_matrix_inverse(
schedule, N=3, delays=[1, 1, 1, 1, 1, 0]
)
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def test_latency_offsets_cyclic_min_schedule_time(self):
sfg = ldlt_matrix_inverse(
N=3,
mads_properties={
"latency_offsets": {"in0": 3, "in1": 0, "in2": 0, "out0": 4},
"execution_time": 1,
},
reciprocal_properties={"latency": 10, "execution_time": 1},
)
schedule = Schedule(
sfg,
scheduler=HybridScheduler(),
schedule_time=15,
cyclic=True,
)
assert schedule.schedule_time == 15
_validate_recreated_sfg_ldlt_matrix_inverse(
schedule, N=3, delays=[4, 4, 3, 3, 3, 3]
)
class TestListScheduler:
def test_latencies_and_execution_times_not_set(self):
N = 3
Wc = 0.2
b, a = signal.butter(N, Wc, btype="lowpass", output="ba")
sfg = direct_form_1_iir(b, a)
sfg.set_latency_of_type_name(ConstantMultiplication.type_name(), 2)
resources = {
Addition.type_name(): 1,
ConstantMultiplication.type_name(): 1,
Input.type_name(): 1,
Output.type_name(): 1,
}
with pytest.raises(
ValueError,
match="Input port 0 of operation add4 has no latency-offset.",
):
Schedule(
sfg,
scheduler=ListScheduler(
sort_order=((1, True), (3, False), (4, False)),
max_resources=resources,
),
)
sfg.set_latency_offsets_of_type_name(Addition.type_name(), {"in0": 0, "in1": 0})
with pytest.raises(
ValueError,
match="Output port 0 of operation add4 has no latency-offset.",
):
Schedule(
sfg,
scheduler=ListScheduler(
sort_order=((1, True), (3, False), (4, False)),
max_resources=resources,
),
)
sfg.set_latency_of_type_name(Addition.type_name(), 3)
sfg.set_execution_time_of_type_name(ConstantMultiplication.type_name(), None)
sfg.set_execution_time_of_type_name(Addition.type_name(), None)
with pytest.raises(
ValueError,
match="All operations in the SFG must have a specified execution time. Missing operation: cmul0.",
):
Schedule(
sfg,
scheduler=ListScheduler(
sort_order=((1, True), (3, False), (4, False)),
max_resources=resources,
),
)
sfg.set_execution_time_of_type_name(ConstantMultiplication.type_name(), 1)
with pytest.raises(
ValueError,
match="All operations in the SFG must have a specified execution time. Missing operation: add0.",
):
Schedule(
sfg,
scheduler=ListScheduler(
sort_order=((1, True), (3, False), (4, False)),
max_resources=resources,
),
)
sfg.set_execution_time_of_type_name(Addition.type_name(), 1)
Schedule(
sfg,
scheduler=ListScheduler(
sort_order=((1, True), (3, False), (4, False)), max_resources=resources
),
)
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def test_cyclic_and_recursive_loops(self):
N = 3
Wc = 0.2
b, a = signal.butter(N, Wc, btype="lowpass", output="ba")
sfg = direct_form_1_iir(b, a)
sfg.set_latency_of_type_name(ConstantMultiplication.type_name(), 2)
sfg.set_execution_time_of_type_name(ConstantMultiplication.type_name(), 1)
sfg.set_latency_of_type_name(Addition.type_name(), 3)
sfg.set_execution_time_of_type_name(Addition.type_name(), 1)
resources = {
Addition.type_name(): 1,
ConstantMultiplication.type_name(): 1,
Input.type_name(): 1,
Output.type_name(): 1,
}
with pytest.raises(
ValueError,
match="ListScheduler does not support cyclic scheduling of recursive algorithms. Use RecursiveListScheduler instead.",
):
Schedule(
sfg,
scheduler=ListScheduler(
sort_order=((1, True), (3, False), (4, False)),
max_resources=resources,
),
cyclic=True,
schedule_time=sfg.iteration_period_bound(),
)
class TestRecursiveListScheduler:
def test_empty_sfg(self, sfg_empty):
with pytest.raises(
ValueError, match="Empty signal flow graph cannot be scheduled."
):
Schedule(
sfg_empty,
scheduler=RecursiveListScheduler(
sort_order=((1, True), (3, False), (4, False))
),
)
def test_direct_form_1_iir(self):
N = 3
Wc = 0.2
b, a = signal.butter(N, Wc, btype="lowpass", output="ba")
sfg = direct_form_1_iir(b, a)
sfg.set_latency_of_type_name(ConstantMultiplication.type_name(), 2)
sfg.set_execution_time_of_type_name(ConstantMultiplication.type_name(), 1)
sfg.set_latency_of_type_name(Addition.type_name(), 3)
sfg.set_execution_time_of_type_name(Addition.type_name(), 1)
resources = {
Addition.type_name(): 1,
ConstantMultiplication.type_name(): 1,
Input.type_name(): 1,
Output.type_name(): 1,
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}
schedule = Schedule(
sfg,
scheduler=RecursiveListScheduler(
sort_order=((1, True), (3, False), (4, False)), max_resources=resources
),
)
_validate_recreated_sfg_filter(sfg, schedule)
def test_direct_form_2_iir(self):
N = 3
Wc = 0.2
b, a = signal.butter(N, Wc, btype="lowpass", output="ba")
sfg = direct_form_2_iir(b, a)
sfg.set_latency_of_type_name(ConstantMultiplication.type_name(), 2)
sfg.set_execution_time_of_type_name(ConstantMultiplication.type_name(), 1)
sfg.set_latency_of_type_name(Addition.type_name(), 3)
sfg.set_execution_time_of_type_name(Addition.type_name(), 1)
resources = {
Addition.type_name(): 1,
ConstantMultiplication.type_name(): 1,
Input.type_name(): 1,
Output.type_name(): 1,
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}
schedule = Schedule(
sfg,
scheduler=RecursiveListScheduler(
sort_order=((1, True), (3, False), (4, False)), max_resources=resources
),
)
_validate_recreated_sfg_filter(sfg, schedule)
def test_large_direct_form_2_iir(self):
N = 8
Wc = 0.2
b, a = signal.butter(N, Wc, btype="lowpass", output="ba")
sfg = direct_form_2_iir(b, a)
sfg.set_latency_of_type_name(ConstantMultiplication.type_name(), 2)
sfg.set_execution_time_of_type_name(ConstantMultiplication.type_name(), 1)
sfg.set_latency_of_type_name(Addition.type_name(), 3)
sfg.set_execution_time_of_type_name(Addition.type_name(), 1)
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resources = {
Addition.type_name(): 1,
ConstantMultiplication.type_name(): 1,
Input.type_name(): 1,
Output.type_name(): 1,
}
schedule = Schedule(
sfg,
scheduler=RecursiveListScheduler(
sort_order=((1, True), (3, False), (4, False)), max_resources=resources
),
)
_validate_recreated_sfg_filter(sfg, schedule)
def test_custom_recursive_filter(self):
# Create the SFG for a digital filter (seen in an exam question from TSTE87).
x = Input()
t0 = Delay()
t1 = Delay(t0)
b = ConstantMultiplication(0.5, x)
d = ConstantMultiplication(0.5, t1)
a1 = Addition(x, d)
a = ConstantMultiplication(0.5, a1)
t2 = Delay(a1)
c = ConstantMultiplication(0.5, t2)
a2 = Addition(b, c)
a3 = Addition(a2, a)
t0.input(0).connect(a3)
y = Output(a2)
sfg = SFG([x], [y])
sfg.set_latency_of_type_name(Addition.type_name(), 1)
sfg.set_latency_of_type_name(ConstantMultiplication.type_name(), 2)
sfg.set_execution_time_of_type_name(Addition.type_name(), 1)
sfg.set_execution_time_of_type_name(ConstantMultiplication.type_name(), 1)
resources = {
Addition.type_name(): 1,
ConstantMultiplication.type_name(): 1,
Input.type_name(): 1,
Output.type_name(): 1,
}
schedule = Schedule(
sfg,
scheduler=RecursiveListScheduler(
sort_order=((1, True), (3, False), (4, False)), max_resources=resources
),
)
_validate_recreated_sfg_filter(sfg, schedule)
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def _validate_recreated_sfg_filter(sfg: SFG, schedule: Schedule) -> None:
# compare the impulse response of the original sfg and recreated one
sim1 = Simulation(sfg, [Impulse()])
sim1.run_for(1024)
sim2 = Simulation(schedule.sfg, [Impulse()])
sim2.run_for(1024)
spectrum_1 = abs(np.fft.fft(sim1.results["0"]))
spectrum_2 = abs(np.fft.fft(sim2.results["0"]))
assert np.allclose(spectrum_1, spectrum_2)
def _validate_recreated_sfg_fft(
schedule: Schedule, points: int, delays: list[int] | None = None
) -> None:
if delays is None:
delays = [0 for i in range(points)]
# impulse input -> constant output
sim = Simulation(schedule.sfg, [Constant()] + [0 for i in range(points - 1)])
sim.run_for(128)
for i in range(points):
assert np.all(np.isclose(sim.results[str(i)][delays[i] :], 1))
# constant input -> impulse (with weight=points) output
sim = Simulation(schedule.sfg, [Constant() for i in range(points)])
sim.run_for(128)
assert np.allclose(sim.results["0"], points)
for i in range(1, points):
assert np.all(np.isclose(sim.results[str(i)][delays[i] :], 0))
# sine input -> compare with numpy fft
n = np.linspace(0, 2 * np.pi, points)
waveform = np.sin(n)
input_samples = [Constant(waveform[i]) for i in range(points)]
sim = Simulation(schedule.sfg, input_samples)
sim.run_for(128)
exp_res = np.fft.fft(waveform)
res = sim.results
for i in range(points):
a = res[str(i)][delays[i] :]
b = exp_res[i]
assert np.all(np.isclose(a, b))
# multi-tone input -> compare with numpy fft
n = np.linspace(0, 2 * np.pi, points)
waveform = (
2 * np.sin(n)
+ 1.3 * np.sin(0.9 * n)
+ 0.9 * np.sin(0.6 * n)
+ 0.35 * np.sin(0.3 * n)
+ 2.4 * np.sin(0.1 * n)
)