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# Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class DFT(Base):
@staticmethod
def export_opset19() -> None:
node = onnx.helper.make_node("DFT", inputs=["x"], outputs=["y"], axis=1)
x = np.arange(0, 100).reshape(10, 10).astype(np.float32)
y = np.fft.fft(x, axis=0)
x = x.reshape(1, 10, 10, 1)
y = np.stack((y.real, y.imag), axis=2).astype(np.float32).reshape(1, 10, 10, 2)
expect(
node,
inputs=[x],
outputs=[y],
name="test_dft_opset19",
opset_imports=[onnx.helper.make_opsetid("", 19)],
)
node = onnx.helper.make_node("DFT", inputs=["x"], outputs=["y"], axis=2)
x = np.arange(0, 100).reshape(10, 10).astype(np.float32)
y = np.fft.fft(x, axis=1)
x = x.reshape(1, 10, 10, 1)
y = np.stack((y.real, y.imag), axis=2).astype(np.float32).reshape(1, 10, 10, 2)
expect(
node,
inputs=[x],
outputs=[y],
name="test_dft_axis_opset19",
opset_imports=[onnx.helper.make_opsetid("", 19)],
)
node = onnx.helper.make_node(
"DFT", inputs=["x"], outputs=["y"], inverse=1, axis=1
)
x = np.arange(0, 100, dtype=np.complex64).reshape(
10,
10,
)
y = np.fft.ifft(x, axis=0)
x = np.stack((x.real, x.imag), axis=2).astype(np.float32).reshape(1, 10, 10, 2)
y = np.stack((y.real, y.imag), axis=2).astype(np.float32).reshape(1, 10, 10, 2)
expect(
node,
inputs=[x],
outputs=[y],
name="test_dft_inverse_opset19",
opset_imports=[onnx.helper.make_opsetid("", 19)],
)
@staticmethod
def export() -> None:
node = onnx.helper.make_node("DFT", inputs=["x", "", "axis"], outputs=["y"])
x = np.arange(0, 100).reshape(10, 10).astype(np.float32)
axis = np.array(1, dtype=np.int64)
y = np.fft.fft(x, axis=0)
x = x.reshape(1, 10, 10, 1)
y = np.stack((y.real, y.imag), axis=2).astype(np.float32).reshape(1, 10, 10, 2)
expect(node, inputs=[x, axis], outputs=[y], name="test_dft")
node = onnx.helper.make_node("DFT", inputs=["x", "", "axis"], outputs=["y"])
x = np.arange(0, 100).reshape(10, 10).astype(np.float32)
axis = np.array(2, dtype=np.int64)
y = np.fft.fft(x, axis=1)
x = x.reshape(1, 10, 10, 1)
y = np.stack((y.real, y.imag), axis=2).astype(np.float32).reshape(1, 10, 10, 2)
expect(node, inputs=[x, axis], outputs=[y], name="test_dft_axis")
node = onnx.helper.make_node(
"DFT", inputs=["x", "", "axis"], outputs=["y"], inverse=1
)
x = np.arange(0, 100, dtype=np.complex64).reshape(10, 10)
axis = np.array(1, dtype=np.int64)
y = np.fft.ifft(x, axis=0)
x = np.stack((x.real, x.imag), axis=2).astype(np.float32).reshape(1, 10, 10, 2)
y = np.stack((y.real, y.imag), axis=2).astype(np.float32).reshape(1, 10, 10, 2)
expect(node, inputs=[x, axis], outputs=[y], name="test_dft_inverse")
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