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Fix: Window functions generate incorrect shape for with symmetric attribute #4256

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merged 5 commits into from
Jun 8, 2022
Merged

Fix: Window functions generate incorrect shape for with symmetric attribute #4256

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365556a
fix symmetric function definition, and add shape inference test
smk2007 Jun 7, 2022
a04a377
whitespace...
smk2007 Jun 7, 2022
635c7a2
whitespace...
smk2007 Jun 7, 2022
267af02
flake8 whitespace error
smk2007 Jun 7, 2022
c1c1a0f
fix stft test
smk2007 Jun 7, 2022
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4 changes: 2 additions & 2 deletions docs/Operators.md
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Original file line number Diff line number Diff line change
Expand Up @@ -19263,8 +19263,8 @@ nstfts = ((signal.shape[1] - length) // step) + 1
output = np.empty([1, nstfts, onesided_length, 2], dtype=np.float32)
for i in range(nstfts):
start = i * step
stop = i * step + onesided_length
complex_out = np.fft.fft(signal[0, start:stop, 0])
stop = i * step + length
complex_out = np.fft.fft(signal[0, start:stop, 0])[0:onesided_length]
output[0, i] = np.stack((complex_out.real, complex_out.imag), axis=1)

expect(node, inputs=[signal, step, length], outputs=[output],
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4 changes: 2 additions & 2 deletions docs/TestCoverage.md
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Expand Up @@ -12138,8 +12138,8 @@ nstfts = ((signal.shape[1] - length) // step) + 1
output = np.empty([1, nstfts, onesided_length, 2], dtype=np.float32)
for i in range(nstfts):
start = i * step
stop = i * step + onesided_length
complex_out = np.fft.fft(signal[0, start:stop, 0])
stop = i * step + length
complex_out = np.fft.fft(signal[0, start:stop, 0])[0:onesided_length]
output[0, i] = np.stack((complex_out.real, complex_out.imag), axis=1)

expect(node, inputs=[signal, step, length], outputs=[output],
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4 changes: 2 additions & 2 deletions onnx/backend/test/case/node/stft.py
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Expand Up @@ -29,8 +29,8 @@ def export() -> None:
output = np.empty([1, nstfts, onesided_length, 2], dtype=np.float32)
for i in range(nstfts):
start = i * step
stop = i * step + onesided_length
complex_out = np.fft.fft(signal[0, start:stop, 0])
stop = i * step + length
complex_out = np.fft.fft(signal[0, start:stop, 0])[0:onesided_length]
output[0, i] = np.stack((complex_out.real, complex_out.imag), axis=1)

expect(node, inputs=[signal, step, length], outputs=[output],
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Binary file modified onnx/backend/test/data/node/test_blackmanwindow_expanded/model.onnx
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Binary file modified onnx/backend/test/data/node/test_hammingwindow_expanded/model.onnx
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6 changes: 3 additions & 3 deletions onnx/defs/math/defs.cc
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Expand Up @@ -2918,7 +2918,7 @@ ONNX_OPERATOR_SET_SCHEMA(
Symmetric_Component = Mul(Symmetric_Size_FP, IsSymmetric_FP)
Size_FP = Add(Periodic_Component, Symmetric_Component)
AngularIncrement = Div (Tau, Size_FP)
Range = Range (Zero, Size_FP, One)
Range = Range (Zero, Periodic_Size_FP, One)
RangeAngular = Mul (Range, AngularIncrement)
TwoRangeAngular = Mul (RangeAngular, Two)
CosTwoRangeAngular = Cos (TwoRangeAngular)
Expand Down Expand Up @@ -2956,7 +2956,7 @@ ONNX_OPERATOR_SET_SCHEMA(
Symmetric_Component = Mul(Symmetric_Size_FP, IsSymmetric_FP)
Size_FP = Add(Periodic_Component, Symmetric_Component)
AngularIncrement = Div (Tau, Size_FP)
Range = Range (Zero, Size_FP, One)
Range = Range (Zero, Periodic_Size_FP, One)
RangeAngular = Mul (Range, AngularIncrement)
TwoRangeAngular = Mul (RangeAngular, Two)
CosTwoRangeAngular = Cos (TwoRangeAngular)
Expand Down Expand Up @@ -2994,7 +2994,7 @@ ONNX_OPERATOR_SET_SCHEMA(
Symmetric_Component = Mul(Symmetric_Size_FP, IsSymmetric_FP)
Size_FP = Add(Periodic_Component, Symmetric_Component)
AngularIncrement = Div (Tau, Size_FP)
Range = Range (Zero, Size_FP, One)
Range = Range (Zero, Periodic_Size_FP, One)
RangeAngular = Mul (Range, AngularIncrement)
TwoRangeAngular = Mul (RangeAngular, Two)
CosTwoRangeAngular = Cos (TwoRangeAngular)
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27 changes: 27 additions & 0 deletions onnx/test/shape_inference_test.py
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Expand Up @@ -4202,6 +4202,15 @@ def test_hammingwindow(self): # type: () -> None
[make_tensor_value_info('shape', TensorProto.INT64, ()),
make_tensor_value_info('y', TensorProto.FLOAT, (10,))]) # type: ignore

graph = self._make_graph([],
[make_node("Constant", [], ['shape'],
value=make_tensor('shape', TensorProto.INT64, (), (10,))),
make_node("HammingWindow", ['shape'], ['y'], periodic=0)],
[])
self._assert_inferred(graph,
[make_tensor_value_info('shape', TensorProto.INT64, ()),
make_tensor_value_info('y', TensorProto.FLOAT, (10,))]) # type: ignore

def test_hannwindow(self): # type: () -> None
graph = self._make_graph([],
[make_node("Constant", [], ['shape'],
Expand All @@ -4212,6 +4221,15 @@ def test_hannwindow(self): # type: () -> None
[make_tensor_value_info('shape', TensorProto.INT64, ()),
make_tensor_value_info('y', TensorProto.FLOAT, (10,))]) # type: ignore

graph = self._make_graph([],
[make_node("Constant", [], ['shape'],
value=make_tensor('shape', TensorProto.INT64, (), (10,))),
make_node("HannWindow", ['shape'], ['y'], periodic=0)],
[])
self._assert_inferred(graph,
[make_tensor_value_info('shape', TensorProto.INT64, ()),
make_tensor_value_info('y', TensorProto.FLOAT, (10,))]) # type: ignore

def test_blackmanwindow(self): # type: () -> None
graph = self._make_graph([],
[make_node("Constant", [], ['shape'],
Expand All @@ -4222,6 +4240,15 @@ def test_blackmanwindow(self): # type: () -> None
[make_tensor_value_info('shape', TensorProto.INT64, ()),
make_tensor_value_info('y', TensorProto.FLOAT, (10,))]) # type: ignore

graph = self._make_graph([],
[make_node("Constant", [], ['shape'],
value=make_tensor('shape', TensorProto.INT64, (), (10,))),
make_node("BlackmanWindow", ['shape'], ['y'], periodic=0)],
[])
self._assert_inferred(graph,
[make_tensor_value_info('shape', TensorProto.INT64, ()),
make_tensor_value_info('y', TensorProto.FLOAT, (10,))]) # type: ignore

def test_dft_reals(self): # type: () -> None
graph = self._make_graph([],
[make_node("Constant", [], ['input'],
Expand Down