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SpectrogramTensorFlow

SpectrogramTensorFlow

A class for computing spectrograms using TensorFlow.

The normalization for the Fourier transform is backward by default.

Source code in src/libsegmenter/transforms/spectrogram/SpectrogramTensorFlow.py 
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class SpectrogramTensorFlow:
    """
    A class for computing spectrograms using TensorFlow.

    The normalization for the Fourier transform is `backward` by default.
    """

    def __init__(self) -> None:
        """Initializes the SpectrogramTensorFlow instance."""
        return

    def forward(self, x: tf.Tensor) -> tf.Tensor:
        """
        Converts segments into a spectrogram.

        Args:
            x (tf.Tensor): Input segments.

        Returns:
            tf.Tensor: Spectrogram representation.

        """
        s = tf.shape(x).numpy()  # pyright: ignore
        if s[-1] % 2 != 0:  # pyright: ignore
            raise ValueError(
                "Input segment size is expected to be even for a consistent definition "
                + "of the inverse real-valued FFT."
            )
        return tf.signal.rfft(x)  # pyright: ignore

    def inverse(self, y: tf.Tensor) -> tf.Tensor:
        """
        Converts spectrogram into segments.

        Args:
            y (tf.Tensor): Spectrogram from a `forward` pass.

        Returns:
            tf.Tensor: Reconstructed segments.

        """
        return tf.signal.irfft(y)  # pyright: ignore

__init__()

Initializes the SpectrogramTensorFlow instance.

Source code in src/libsegmenter/transforms/spectrogram/SpectrogramTensorFlow.py 
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def __init__(self) -> None:
    """Initializes the SpectrogramTensorFlow instance."""
    return

forward(x)

Converts segments into a spectrogram.

Parameters:

Name Type Description Default
x Tensor

Input segments.

 required

Returns:

Type Description
Tensor

tf.Tensor: Spectrogram representation.
Source code in src/libsegmenter/transforms/spectrogram/SpectrogramTensorFlow.py 
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def forward(self, x: tf.Tensor) -> tf.Tensor:
    """
    Converts segments into a spectrogram.

    Args:
        x (tf.Tensor): Input segments.

    Returns:
        tf.Tensor: Spectrogram representation.

    """
    s = tf.shape(x).numpy()  # pyright: ignore
    if s[-1] % 2 != 0:  # pyright: ignore
        raise ValueError(
            "Input segment size is expected to be even for a consistent definition "
            + "of the inverse real-valued FFT."
        )
    return tf.signal.rfft(x)  # pyright: ignore

inverse(y)

Converts spectrogram into segments.

Parameters:

Name Type Description Default
y Tensor

Spectrogram from a forward pass.

 required

Returns:

Type Description
Tensor

tf.Tensor: Reconstructed segments.
Source code in src/libsegmenter/transforms/spectrogram/SpectrogramTensorFlow.py 
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def inverse(self, y: tf.Tensor) -> tf.Tensor:
    """
    Converts spectrogram into segments.

    Args:
        y (tf.Tensor): Spectrogram from a `forward` pass.

    Returns:
        tf.Tensor: Reconstructed segments.

    """
    return tf.signal.irfft(y)  # pyright: ignore