Computes the Short-time Fourier Transform of signals.
tf.signal.stft(
signals, frame_length, frame_step, fft_length=None,
window_fn=tf.signal.hann_window, pad_end=False, name=None
)
Used in the notebooks
Implemented with TPU/GPU-compatible ops and supports gradients.
Args |
|---|
signals
|
A [..., samples] float32/float64 Tensor of real-valued
signals.
|
frame_length
|
An integer scalar Tensor. The window length in samples.
|
frame_step
|
An integer scalar Tensor. The number of samples to step.
|
fft_length
|
An integer scalar Tensor. The size of the FFT to apply.
If not provided, uses the smallest power of 2 enclosing frame_length.
|
window_fn
|
A callable that takes a window length and a dtype keyword
argument and returns a [window_length] Tensor of samples in the
provided datatype. If set to None, no windowing is used.
|
pad_end
|
Whether to pad the end of signals with zeros when the provided
frame length and step produces a frame that lies partially past its end.
|
name
|
An optional name for the operation.
|
Returns |
|---|
A [..., frames, fft_unique_bins] Tensor of complex64/complex128
STFT values where fft_unique_bins is fft_length // 2 + 1 (the unique
components of the FFT).
|
Raises |
|---|
ValueError
|
If signals is not at least rank 1, frame_length is
not scalar, or frame_step is not scalar.
|
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TensorFlow 1 version
View source on GitHub