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[Typing][A-94] Add type annotations for python/paddle/signal.py #65569

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Jun 30, 2024
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[Typing][A-94] Add type annotations for python/paddle/signal.py #65569

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c1b7966
[Typing][A-94] Add type annotations for `python/paddle/signal.py`
Asthestarsfalll Jun 29, 2024
3ad2237
Add _SignalAxes
Asthestarsfalll Jun 30, 2024
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88 changes: 54 additions & 34 deletions python/paddle/signal.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,9 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import annotations

from typing import TYPE_CHECKING, Literal

import paddle
from paddle import _C_ops
Expand All @@ -21,13 +24,24 @@
from .fft import fft_c2c, fft_c2r, fft_r2c
from .tensor.attribute import is_complex

if TYPE_CHECKING:
from paddle import Tensor

_SignalAxes = Literal[0, -1]

__all__ = [
'stft',
'istft',
]


def frame(x, frame_length, hop_length, axis=-1, name=None):
def frame(
x: Tensor,
frame_length: int,
hop_length: int,
axis: _SignalAxes = -1,
name: str | None = None,
) -> Tensor:
"""
Slice the N-dimensional (where N >= 1) input into (overlapping) frames.

Expand All @@ -40,6 +54,8 @@ def frame(x, frame_length, hop_length, axis=-1, name=None):
axis (int, optional): Specify the axis to operate on the input Tensors. Its
value should be 0(the first dimension) or -1(the last dimension). If not
specified, the last axis is used by default.
name (str|None, optional): The default value is None. Normally there is no need for user
to set this property. For more information, please refer to :ref:`api_guide_Name`.

Returns:
The output frames tensor with shape `[..., frame_length, num_frames]` if `axis==-1`,
Expand Down Expand Up @@ -142,7 +158,9 @@ def frame(x, frame_length, hop_length, axis=-1, name=None):
return out


def overlap_add(x, hop_length, axis=-1, name=None):
def overlap_add(
x: Tensor, hop_length: int, axis: _SignalAxes = -1, name: str | None = None
) -> Tensor:
"""
Reconstructs a tensor consisted of overlap added sequences from input frames.

Expand All @@ -155,6 +173,8 @@ def overlap_add(x, hop_length, axis=-1, name=None):
axis (int, optional): Specify the axis to operate on the input Tensors. Its
value should be 0(the first dimension) or -1(the last dimension). If not
specified, the last axis is used by default.
name (str|None, optional): The default value is None. Normally there is no need for user
to set this property. For more information, please refer to :ref:`api_guide_Name`.

Returns:
The output frames tensor with shape `[..., seq_length]` if `axis==-1`,
Expand Down Expand Up @@ -244,17 +264,17 @@ def overlap_add(x, hop_length, axis=-1, name=None):


def stft(
x,
n_fft,
hop_length=None,
win_length=None,
window=None,
center=True,
pad_mode='reflect',
normalized=False,
onesided=True,
name=None,
):
x: Tensor,
n_fft: int,
hop_length: int | None = None,
win_length: int | None = None,
window: Tensor | None = None,
center: bool = True,
pad_mode: Literal["reflect", "constant"] = "reflect",
normalized: bool = False,
onesided: bool = True,
name: str | None = None,
) -> Tensor:
r"""

Short-time Fourier transform (STFT).
Expand All @@ -276,11 +296,11 @@ def stft(
x (Tensor): The input data which is a 1-dimensional or 2-dimensional Tensor with
shape `[..., seq_length]`. It can be a real-valued or a complex Tensor.
n_fft (int): The number of input samples to perform Fourier transform.
hop_length (int, optional): Number of steps to advance between adjacent windows
hop_length (int|None, optional): Number of steps to advance between adjacent windows
and `0 < hop_length`. Default: `None` (treated as equal to `n_fft//4`)
win_length (int, optional): The size of window. Default: `None` (treated as equal
win_length (int|None, optional): The size of window. Default: `None` (treated as equal
to `n_fft`)
window (Tensor, optional): A 1-dimensional tensor of size `win_length`. It will
window (Tensor|None, optional): A 1-dimensional tensor of size `win_length`. It will
be center padded to length `n_fft` if `win_length < n_fft`. Default: `None` (
treated as a rectangle window with value equal to 1 of size `win_length`).
center (bool, optional): Whether to pad `x` to make that the
Expand All @@ -292,7 +312,7 @@ def stft(
onesided (bool, optional): Control whether to return half of the Fourier transform
output that satisfies the conjugate symmetry condition when input is a real-valued
tensor. It can not be `True` if input is a complex tensor. Default: `True`
name (str, optional): The default value is None. Normally there is no need for user
name (str|None, optional): The default value is None. Normally there is no need for user
to set this property. For more information, please refer to :ref:`api_guide_Name`.

Returns:
Expand Down Expand Up @@ -421,18 +441,18 @@ def stft(


def istft(
x,
n_fft,
hop_length=None,
win_length=None,
window=None,
center=True,
normalized=False,
onesided=True,
length=None,
return_complex=False,
name=None,
):
x: Tensor,
n_fft: int,
hop_length: int | None = None,
win_length: int | None = None,
window: Tensor | None = None,
center: bool = True,
normalized: bool = False,
onesided: bool = True,
length: int | None = None,
return_complex: bool = False,
name: str | None = None,
) -> Tensor:
r"""
Inverse short-time Fourier transform (ISTFT).

Expand All @@ -457,12 +477,12 @@ def istft(
x (Tensor): The input data which is a 2-dimensional or 3-dimensional **complex**
Tensor with shape `[..., n_fft, num_frames]`.
n_fft (int): The size of Fourier transform.
hop_length (int, optional): Number of steps to advance between adjacent windows
hop_length (int|None, optional): Number of steps to advance between adjacent windows
from time-domain signal and `0 < hop_length < win_length`. Default: `None` (
treated as equal to `n_fft//4`)
win_length (int, optional): The size of window. Default: `None` (treated as equal
win_length (int|None, optional): The size of window. Default: `None` (treated as equal
to `n_fft`)
window (Tensor, optional): A 1-dimensional tensor of size `win_length`. It will
window (Tensor|None, optional): A 1-dimensional tensor of size `win_length`. It will
be center padded to length `n_fft` if `win_length < n_fft`. It should be a
real-valued tensor if `return_complex` is False. Default: `None`(treated as
a rectangle window with value equal to 1 of size `win_length`).
Expand All @@ -474,12 +494,12 @@ def istft(
of the conjugate symmetry STFT tensor transformed from a real-valued signal
and `istft` will return a real-valued tensor when it is set to `True`.
Default: `True`.
length (int, optional): Specify the length of time-domain signal. Default: `None`(
length (int|None, optional): Specify the length of time-domain signal. Default: `None`(
treated as the whole length of signal).
return_complex (bool, optional): It means that whether the time-domain signal is
real-valued. If `return_complex` is set to `True`, `onesided` should be set to
`False` cause the output is complex.
name (str, optional): The default value is None. Normally there is no need for user
name (str|None, optional): The default value is None. Normally there is no need for user
to set this property. For more information, please refer to :ref:`api_guide_Name`.

Returns:
Expand Down