Merge pull request #73 from sp-nitech/release

Next release

.github/workflows/ci.yml

@@ -20,9 +20,9 @@ jobs:
  - python: 3.8
  torch: 1.11.0
  torchaudio: 0.11.0
- - python: 3.11
- torch: 2.2.2
- torchaudio: 2.2.2
+ - python: 3.12
+ torch: 2.3.0
+ torchaudio: 2.3.0
 
  steps:
  - name: Clone

Makefile

@@ -23,61 +23,60 @@ TORCHAUDIO_VERSION := 0.11.0
 PLATFORM := cu113
 
 venv:
- test -d venv || python$(PYTHON_VERSION) -m venv venv; \
- . ./venv/bin/activate; python -m pip install pip --upgrade
- . ./venv/bin/activate; python -m pip install torch==$(TORCH_VERSION)+$(PLATFORM) torchaudio==$(TORCHAUDIO_VERSION)+$(PLATFORM) \
- -f https://download.pytorch.org/whl/$(PLATFORM)/torch_stable.html; \
- . ./venv/bin/activate; python -m pip install -e .[dev]
- . ./venv/bin/activate; python -m pip install icc-rt
+ test -d venv || python$(PYTHON_VERSION) -m venv venv
+ . ./venv/bin/activate && python -m pip install pip --upgrade
+ . ./venv/bin/activate && python -m pip install torch==$(TORCH_VERSION)+$(PLATFORM) torchaudio==$(TORCHAUDIO_VERSION)+$(PLATFORM) \
+ -f https://download.pytorch.org/whl/$(PLATFORM)/torch_stable.html
+ . ./venv/bin/activate && python -m pip install -e .[dev]
+ . ./venv/bin/activate && python -m pip install icc-rt
 
 dist:
- . ./venv/bin/activate; python -m build
- . ./venv/bin/activate; python -m twine check dist/*
+ . ./venv/bin/activate && python -m build
+ . ./venv/bin/activate && python -m twine check dist/*
 
 dist-clean:
  rm -rf dist
 
 doc:
- . ./venv/bin/activate; cd docs; make html
+ . ./venv/bin/activate && cd docs && make html
 
 doc-clean:
  @if [ -f ./venv/bin/activate ]; then \
- . ./venv/bin/activate; cd docs; make clean; \
+ . ./venv/bin/activate && cd docs && make clean; \
  fi
 
 check: tool
- . ./venv/bin/activate; python -m ruff check $(PROJECT) tests
- . ./venv/bin/activate; python -m ruff format --check $(PROJECT) tests
- . ./venv/bin/activate; python -m isort --check $(PROJECT) tests
+ . ./venv/bin/activate && python -m ruff check $(PROJECT) tests
+ . ./venv/bin/activate && python -m ruff format --check $(PROJECT) tests
+ . ./venv/bin/activate && python -m isort --check $(PROJECT) tests
  ./tools/taplo/taplo fmt --check pyproject.toml
  ./tools/yamlfmt/yamlfmt --lint *.yml .github/workflows/*.yml
 
 format: tool
- . ./venv/bin/activate; python -m ruff check --fix $(PROJECT) tests
- . ./venv/bin/activate; python -m ruff format $(PROJECT) tests
- . ./venv/bin/activate; python -m isort $(PROJECT) tests
+ . ./venv/bin/activate && python -m ruff check --fix $(PROJECT) tests
+ . ./venv/bin/activate && python -m ruff format $(PROJECT) tests
+ . ./venv/bin/activate && python -m isort $(PROJECT) tests
  ./tools/taplo/taplo fmt pyproject.toml
  ./tools/yamlfmt/yamlfmt *.yml .github/workflows/*.yml
 
 test: tool
  [ -n "$(MODULE)" ] && module=tests/test_$(MODULE).py || module=; \
- . ./venv/bin/activate; export PATH=tools/SPTK/bin:$$PATH; \
- python -m pytest -s --cov=./ --cov-report=xml $$module
+ . ./venv/bin/activate && export PATH=tools/SPTK/bin:$$PATH && python -m pytest $$module
 
 test-clean:
  rm -rf tests/__pycache__
  rm -rf *.wav
 
 tool:
- cd tools; make
+ cd tools && make
 
 tool-clean:
- cd tools; make clean
+ cd tools && make clean
 
 update: tool
- . ./venv/bin/activate; python -m pip install --upgrade pip
+ . ./venv/bin/activate && python -m pip install --upgrade pip
  @for package in $$(./tools/taplo/taplo get -f pyproject.toml project.optional-dependencies.dev); do \
- . ./venv/bin/activate; python -m pip install --upgrade $$package; \
+ . ./venv/bin/activate && python -m pip install --upgrade $$package; \
  done
 
 clean: dist-clean doc-clean test-clean tool-clean

README.md

@@ -3,10 +3,10 @@ diffsptk
 *diffsptk* is a differentiable version of [SPTK](https://github.com/sp-nitech/SPTK) based on the PyTorch framework.
 
 [![Latest Manual](https://img.shields.io/badge/docs-latest-blue.svg)](https://sp-nitech.github.io/diffsptk/latest/)
-[![Stable Manual](https://img.shields.io/badge/docs-stable-blue.svg)](https://sp-nitech.github.io/diffsptk/2.0.0/)
+[![Stable Manual](https://img.shields.io/badge/docs-stable-blue.svg)](https://sp-nitech.github.io/diffsptk/2.0.1/)
 [![Downloads](https://static.pepy.tech/badge/diffsptk)](https://pepy.tech/project/diffsptk)
 [![Python Version](https://img.shields.io/pypi/pyversions/diffsptk.svg)](https://pypi.python.org/pypi/diffsptk)
-[![PyTorch Version](https://img.shields.io/badge/pytorch-1.11.0%20%7C%202.2.2-orange.svg)](https://pypi.python.org/pypi/diffsptk)
+[![PyTorch Version](https://img.shields.io/badge/pytorch-1.11.0%20%7C%202.3.0-orange.svg)](https://pypi.python.org/pypi/diffsptk)
 [![PyPI Version](https://img.shields.io/pypi/v/diffsptk.svg)](https://pypi.python.org/pypi/diffsptk)
 [![Codecov](https://codecov.io/gh/sp-nitech/diffsptk/branch/master/graph/badge.svg)](https://app.codecov.io/gh/sp-nitech/diffsptk)
 [![License](https://img.shields.io/github/license/sp-nitech/diffsptk.svg)](https://github.com/sp-nitech/diffsptk/blob/master/LICENSE)

diffsptk/misc/utils.py

@@ -15,20 +15,22 @@
 # ------------------------------------------------------------------------ #
 
 from importlib import import_module
+import math
 
 import numpy as np
 import soundfile as sf
 import torch
+from torch import nn
 import torch.nn.functional as F
 import torchaudio
 
 UNVOICED_SYMBOL = 0
-TWO_PI = 6.283185307179586
+TWO_PI = math.tau
 
 
-class Lambda(torch.nn.Module):
+class Lambda(nn.Module):
  def __init__(self, func, **opt):
- super(Lambda, self).__init__()
+ super().__init__()
  self.func = func
  self.opt = opt
 

diffsptk/modules/acorr.py

@@ -15,7 +15,7 @@
 # ------------------------------------------------------------------------ #
 
 import torch
-import torch.nn as nn
+from torch import nn
 
 from ..misc.utils import check_size
 
@@ -41,7 +41,7 @@ class Autocorrelation(nn.Module):
  """
 
  def __init__(self, frame_length, acr_order, norm=False, estimator="none"):
- super(Autocorrelation, self).__init__()
+ super().__init__()
 
  assert 0 <= acr_order < frame_length
 
@@ -93,17 +93,17 @@ def _forward(x, acr_order, norm, const):
  @staticmethod
  def _func(x, acr_order, norm=False, estimator="none"):
  const = Autocorrelation._precompute(
- x.size(-1), acr_order, estimator, dtype=x.dtype, device=x.device
+ x.size(-1), acr_order, estimator, device=x.device
  )
  return Autocorrelation._forward(x, acr_order, norm, const)
 
  @staticmethod
- def _precompute(frame_length, acr_order, estimator, dtype=None, device=None):
- if estimator == 0 or estimator == 1 or estimator == "none":
+ def _precompute(frame_length, acr_order, estimator, device=None):
+ if estimator in (0, 1, "none"):
  return 1
- elif estimator == 2 or estimator == "biased":
+ elif estimator in (2, "biased"):
  return 1 / frame_length
- elif estimator == 3 or estimator == "unbiased":
+ elif estimator in (3, "unbiased"):
  return torch.arange(
  frame_length, frame_length - acr_order - 1, -1, device=device
  ).reciprocal()

diffsptk/modules/alaw.py

@@ -17,7 +17,7 @@
 import math
 
 import torch
-import torch.nn as nn
+from torch import nn
 
 
 class ALawCompression(nn.Module):
@@ -35,7 +35,7 @@ class ALawCompression(nn.Module):
  """
 
  def __init__(self, abs_max=1, a=87.6):
- super(ALawCompression, self).__init__()
+ super().__init__()
 
  assert 0 < abs_max
  assert 1 <= a

diffsptk/modules/ap.py

@@ -16,7 +16,7 @@
 
 import numpy as np
 import torch
-import torch.nn as nn
+from torch import nn
 import torch.nn.functional as F
 
 from ..misc.utils import UNVOICED_SYMBOL
@@ -67,7 +67,7 @@ def __init__(
  out_format="a",
  **kwargs,
  ):
- super(Aperiodicity, self).__init__()
+ super().__init__()
 
  assert 1 <= frame_period
  assert 1 <= sample_rate
@@ -79,13 +79,13 @@ def __init__(
  else:
  raise ValueError(f"algorithm {algorithm} is not supported.")
 
- if out_format == 0 or out_format == "a":
+ if out_format in (0, "a"):
  self.convert = lambda x: x
- elif out_format == 1 or out_format == "p":
+ elif out_format in (1, "p"):
  self.convert = lambda x: 1 - x
- elif out_format == 2 or out_format == "a/p":
+ elif out_format in (2, "a/p"):
  self.convert = lambda x: x / (1 - x)
- elif out_format == 3 or out_format == "p/a":
+ elif out_format in (3, "p/a"):
  self.convert = lambda x: (1 - x) / x
  else:
  raise ValueError(f"out_format {out_format} is not supported.")
@@ -149,7 +149,7 @@ def __init__(
  window_length_ms=30,
  eps=1e-5,
  ):
- super(AperiodicityExtractionByTandem, self).__init__()
+ super().__init__()
 
  assert fft_length % 2 == 0
  assert 0 <= lower_bound < upper_bound <= 1

diffsptk/modules/b2mc.py

@@ -15,7 +15,7 @@
 # ------------------------------------------------------------------------ #
 
 import torch
-import torch.nn as nn
+from torch import nn
 import torch.nn.functional as F
 
 from ..misc.utils import check_size
@@ -37,7 +37,7 @@ class MLSADigitalFilterCoefficientsToMelCepstrum(nn.Module):
  """
 
  def __init__(self, cep_order, alpha=0):
- super(MLSADigitalFilterCoefficientsToMelCepstrum, self).__init__()
+ super().__init__()
 
  assert 0 <= cep_order
  assert abs(alpha) < 1

diffsptk/modules/c2acr.py

@@ -15,7 +15,7 @@
 # ------------------------------------------------------------------------ #
 
 import torch
-import torch.nn as nn
+from torch import nn
 
 from ..misc.utils import check_size
 
@@ -38,7 +38,7 @@ class CepstrumToAutocorrelation(nn.Module):
  """
 
  def __init__(self, cep_order, acr_order, n_fft=512):
- super(CepstrumToAutocorrelation, self).__init__()
+ super().__init__()
 
  assert 0 <= cep_order
  assert 0 <= acr_order

diffsptk/modules/c2mpir.py

@@ -15,7 +15,7 @@
 # ------------------------------------------------------------------------ #
 
 import torch
-import torch.nn as nn
+from torch import nn
 
 from ..misc.utils import cexp
 from ..misc.utils import check_size
@@ -39,7 +39,7 @@ class CepstrumToMinimumPhaseImpulseResponse(nn.Module):
  """
 
  def __init__(self, cep_order, ir_length, n_fft=512):
- super(CepstrumToMinimumPhaseImpulseResponse, self).__init__()
+ super().__init__()
 
  assert 0 <= cep_order
  assert 1 <= ir_length

diffsptk/modules/c2ndps.py

@@ -15,7 +15,7 @@
 # ------------------------------------------------------------------------ #
 
 import torch
-import torch.nn as nn
+from torch import nn
 
 from ..misc.utils import check_size
 from ..misc.utils import to
@@ -36,7 +36,7 @@ class CepstrumToNegativeDerivativeOfPhaseSpectrum(nn.Module):
  """
 
  def __init__(self, cep_order, fft_length):
- super(CepstrumToNegativeDerivativeOfPhaseSpectrum, self).__init__()
+ super().__init__()
 
  assert 0 <= cep_order
  assert max(1, cep_order) <= fft_length // 2

diffsptk/modules/cdist.py

@@ -17,7 +17,7 @@
 import math
 
 import torch
-import torch.nn as nn
+from torch import nn
 
 
 class CepstralDistance(nn.Module):
@@ -38,7 +38,7 @@ class CepstralDistance(nn.Module):
  """
 
  def __init__(self, full=False, reduction="mean", eps=1e-8):
- super(CepstralDistance, self).__init__()
+ super().__init__()
 
  assert reduction in ("none", "mean", "batchmean", "sum")
  assert 0 <= eps

diffsptk/modules/cqt.py

@@ -32,7 +32,7 @@
 
 import numpy as np
 import torch
-import torch.nn as nn
+from torch import nn
 import torchaudio
 
 from ..misc.utils import Lambda
@@ -101,7 +101,7 @@ def __init__(
  scale=True,
  **kwargs,
  ):
- super(ConstantQTransform, self).__init__()
+ super().__init__()
 
  import librosa
 

diffsptk/modules/dct.py

@@ -15,7 +15,7 @@
 # ------------------------------------------------------------------------ #
 
 import torch
-import torch.nn as nn
+from torch import nn
 
 from ..misc.utils import check_size
 from ..misc.utils import to
@@ -33,7 +33,7 @@ class DiscreteCosineTransform(nn.Module):
  """
 
  def __init__(self, dct_length):
- super(DiscreteCosineTransform, self).__init__()
+ super().__init__()
 
  assert 1 <= dct_length
 

diffsptk/modules/decimate.py

@@ -15,7 +15,7 @@
 # ------------------------------------------------------------------------ #
 
 import torch
-import torch.nn as nn
+from torch import nn
 
 
 class Decimation(nn.Module):
@@ -36,7 +36,7 @@ class Decimation(nn.Module):
  """
 
  def __init__(self, period, start=0, dim=-1):
- super(Decimation, self).__init__()
+ super().__init__()
 
  assert 1 <= period
  assert 0 <= start