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71 lines
2.3 KiB
Python
71 lines
2.3 KiB
Python
# Copyright (c) ONNX Project Contributors
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#
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# SPDX-License-Identifier: Apache-2.0
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from __future__ import annotations
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import numpy as np
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import onnx
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from onnx.backend.test.case.base import Base
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from onnx.backend.test.case.node import expect
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class STFT(Base):
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@staticmethod
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def export() -> None:
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signal = np.arange(0, 128, dtype=np.float32).reshape(1, 128, 1)
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length = np.array(16).astype(np.int64)
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onesided_length = (length >> 1) + 1
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step = np.array(8).astype(np.int64)
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no_window = "" # optional input, not supplied
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node = onnx.helper.make_node(
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"STFT",
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inputs=["signal", "frame_step", no_window, "frame_length"],
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outputs=["output"],
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)
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nstfts = ((signal.shape[1] - length) // step) + 1
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# [batch_size][frames][frame_length][2]
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output = np.empty([1, nstfts, onesided_length, 2], dtype=np.float32)
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for i in range(nstfts):
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start = i * step
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stop = i * step + length
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complex_out = np.fft.fft(signal[0, start:stop, 0])[0:onesided_length]
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output[0, i] = np.stack((complex_out.real, complex_out.imag), axis=1)
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output = output.astype(signal.dtype)
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expect(node, inputs=[signal, step, length], outputs=[output], name="test_stft")
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node = onnx.helper.make_node(
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"STFT",
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inputs=["signal", "frame_step", "window"],
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outputs=["output"],
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)
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# Test with window
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a0 = 0.5
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a1 = 0.5
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window = a0 + a1 * np.cos(
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2 * np.pi * np.arange(0, length, 1, dtype=np.float32) / length
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)
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nstfts = 1 + (signal.shape[1] - window.shape[0]) // step
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# [batch_size][frames][frame_length][2]
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output = np.empty([1, nstfts, onesided_length, 2], dtype=np.float32)
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for i in range(nstfts):
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start = i * step
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stop = i * step + length
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complex_out = np.fft.fft(signal[0, start:stop, 0] * window)[
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0:onesided_length
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]
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output[0, i] = np.stack((complex_out.real, complex_out.imag), axis=1)
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window = window.astype(signal.dtype)
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output = output.astype(signal.dtype)
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expect(
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node,
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inputs=[signal, step, window],
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outputs=[output],
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name="test_stft_with_window",
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)
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