tf.keras.ops.irfft
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Inverse real-valued Fast Fourier transform along the last axis.
tf.keras.ops.irfft(
x, fft_length=None
)
Computes the inverse 1D Discrete Fourier Transform of a real-valued signal
over the inner-most dimension of input.
The inner-most dimension of the input is assumed to be the result of RFFT:
the fft_length / 2 + 1 unique components of the DFT of a real-valued
signal. If fft_length is not provided, it is computed from the size of the
inner-most dimension of the input (fft_length = 2 * (inner - 1)). If the
FFT length used to compute is odd, it should be provided since it cannot
be inferred properly.
Along the axis IRFFT is computed on, if fft_length / 2 + 1 is smaller than
the corresponding dimension of the input, the dimension is cropped. If it is
larger, the dimension is padded with zeros.
Args |
|---|
x
|
Tuple of the real and imaginary parts of the input tensor. Both
tensors in the tuple should be of floating type.
|
fft_length
|
An integer representing the number of the fft length. If not
specified, it is inferred from the length of the last axis of x.
Defaults to None.
|
Returns |
|---|
A tensor containing the inverse real-valued Fast Fourier Transform
along the last axis of x.
|
Examples:
real = keras.ops.convert_to_tensor([0.0, 1.0, 2.0, 3.0, 4.0])
imag = keras.ops.convert_to_tensor([0.0, 1.0, 2.0, 3.0, 4.0])
irfft((real, imag))
array([0.66666667, -0.9106836, 0.24401694])
irfft(rfft(real, 5), 5)
array([0.0, 1.0, 2.0, 3.0, 4.0])
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Last updated 2024-06-07 UTC.
[null,null,["Last updated 2024-06-07 UTC."],[],[],null,["# tf.keras.ops.irfft\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/keras-team/keras/tree/v3.3.3/keras/src/ops/math.py#L569-L610) |\n\nInverse real-valued Fast Fourier transform along the last axis. \n\n tf.keras.ops.irfft(\n x, fft_length=None\n )\n\nComputes the inverse 1D Discrete Fourier Transform of a real-valued signal\nover the inner-most dimension of input.\n\nThe inner-most dimension of the input is assumed to be the result of RFFT:\nthe `fft_length / 2 + 1` unique components of the DFT of a real-valued\nsignal. If `fft_length` is not provided, it is computed from the size of the\ninner-most dimension of the input `(fft_length = 2 * (inner - 1))`. If the\nFFT length used to compute is odd, it should be provided since it cannot\nbe inferred properly.\n\nAlong the axis IRFFT is computed on, if `fft_length / 2 + 1` is smaller than\nthe corresponding dimension of the input, the dimension is cropped. If it is\nlarger, the dimension is padded with zeros.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|--------------|-----------------------------------------------------------------------------------------------------------------------------------------------------|\n| `x` | Tuple of the real and imaginary parts of the input tensor. Both tensors in the tuple should be of floating type. |\n| `fft_length` | An integer representing the number of the fft length. If not specified, it is inferred from the length of the last axis of `x`. Defaults to `None`. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A tensor containing the inverse real-valued Fast Fourier Transform along the last axis of `x`. ||\n\n\u003cbr /\u003e\n\n#### Examples:\n\n real = keras.ops.convert_to_tensor([0.0, 1.0, 2.0, 3.0, 4.0])\n imag = keras.ops.convert_to_tensor([0.0, 1.0, 2.0, 3.0, 4.0])\n irfft((real, imag))\n array([0.66666667, -0.9106836, 0.24401694])\n\n irfft(rfft(real, 5), 5)\n array([0.0, 1.0, 2.0, 3.0, 4.0])"]]
View source on GitHub