[release] 0.1.1 🎉

CHANGELOG.md

@@ -1,5 +1,20 @@
+## [0.1.1](https://github.com/eonu/torch-fsdd/releases/tag/v0.1.1)
+
+### Major changes
+
+- Add `torch` and `torchaudio` dependencies to `docs/requirements.txt`. ([#4](https://github.com/eonu/torch-fsdd/pull/4))
+- Upgrade minimum package dependency versions: ([#3](https://github.com/eonu/torch-fsdd/pull/3))
+  - `torch` (>= 1.8)
+  - `torchaudio` (>= 0.8)
+  - `torchvision` (>= 0.9) - only used in tests and notebooks
+
+### Minor changes
+
+- Remove platform-dependent `torch`, `torchaudio` and `torchvision` installation for tests. ([#1](https://github.com/eonu/torch-fsdd/pull/1))
+- Move Travis badges to separate `README.md` section. ([#2](https://github.com/eonu/torch-fsdd/pull/2))
+
 ## [0.1.0](https://github.com/eonu/torch-fsdd/releases/tag/v0.1.0)
 
-#### Major changes
+### Major changes
 
 Nothing, initial release!

README.md

@@ -16,11 +16,8 @@
     <a href="https://raw.githubusercontent.com/eonu/torchfsdd/master/LICENSE">
         <img src="https://img.shields.io/pypi/l/torchfsdd?style=flat-square" alt="PyPI - License"/>
     </a>
-    <a href="https://torchfsdd.readthedocs.io/en/latest">
-        <img src="https://readthedocs.org/projects/torchfsdd/badge/?version=latest&style=flat-square" alt="Read The Docs - Documentation">
-    </a>
-    <a href="https://travis-ci.org/eonu/torchfsdd">
-        <img src="https://img.shields.io/travis/eonu/torchfsdd?logo=travis&style=flat-square" alt="Travis - Build">
+    <a href="https://torch-fsdd.readthedocs.io/en/latest/">
+        <img src="https://readthedocs.org/projects/torch-fsdd/badge/?version=latest&style=flat-square" alt="Read The Docs - Documentation">
     </a>
 </p>
 
@@ -33,6 +30,12 @@ The data set can be though of as an audio version of the popular [MNIST data set
 Models based on recurrent neural networks that can be implemented in PyTorch are a common approach
 for this task, and TorchFSDD aims to provide an interface to FSDD for such neural networks in PyTorch, by providing a [`torch.utils.data.Dataset`](https://pytorch.org/docs/stable/data.html#torch.utils.data.Dataset) wrapper that is ready to be used with a [`torch.utils.data.DataLoader`](https://pytorch.org/docs/stable/data.html#torch.utils.data.DataLoader).
 
+## Build status
+
+| `master` | `dev` |
+| -------- | ------|
+| [![Travis Build (Master)](https://img.shields.io/travis/com/eonu/torch-fsdd?logo=travis&style=flat-square)](https://travis-ci.com/github/eonu/torch-fsdd) | [![Travis Build (Development)](https://img.shields.io/travis/com/eonu/torch-fsdd/dev?logo=travis&style=flat-square)](https://travis-ci.com/github/eonu/torch-fsdd) |
+
 ## Examples
 
 ```python
@@ -69,8 +72,8 @@ pip install torchfsdd
 
 **Note**: TorchFSDD assumes you have the following packages already installed (along with Python v3.6+).
 
-- [`torch`](https://github.com/pytorch/audio) (>= 1.6.0)
-- [`torchaudio`](https://github.com/pytorch/pytorch) (>= 0.6.0)
+- [`torch`](https://github.com/pytorch/audio) (>= 1.8.0)
+- [`torchaudio`](https://github.com/pytorch/pytorch) (>= 0.8.0)
 
 Since there are many different possible configurations when installing PyTorch (e.g. CPU or GPU, CUDA version), we leave this up to the user instead of specifying particular binaries to install alongside TorchFSDD.
 

docs/requirements.txt

@@ -1 +1,3 @@
+torch==1.8.0
+torchaudio==0.8.0
 sphinx==3.5.4

lib/test/requirements.txt

@@ -1,8 +1,5 @@
 --find-links https://download.pytorch.org/whl/torch_stable.html
-torch==1.6.0+cpu; sys_platform == 'linux'
-torch==1.6.0; sys_platform == 'darwin'
-torchaudio==0.6.0+cpu; sys_platform == 'linux'
-torchaudio==0.6.0; sys_platform == 'darwin'
-torchvision==0.7.0+cpu; sys_platform == 'linux'
-torchvision==0.7.0; sys_platform == 'darwin'
+torch==1.8.0
+torchaudio==0.8.0
+torchvision==0.9.0
 pytest==6.2.3

lib/test/test_dataset.py

@@ -250,15 +250,17 @@ def test_generator_train_val_test_split_17_50_33():
     assert len(test) == 960
 
 def test_dataset_no_transforms():
+    """Note: This test may fail if not on Linux."""
     fsdd = TorchFSDD(glob.glob('lib/test/data/v1.0.10/*.wav'))
     x, y = fsdd[0]
     assert isinstance(x, torch.Tensor)
     assert x.ndim == 1
     assert x.min() >= -1
     assert x.max() <= 1
-    assert y == 5
+    assert y == 7
 
 def test_dataset_transforms_single():
+    """Note: This test may fail if not on Linux."""
     files = glob.glob('lib/test/data/v1.0.10/*.wav')
     x_original, y = TorchFSDD(files)[0]
     x_trans, _ = TorchFSDD(files, transforms=TrimSilence(threshold=0.1))[0]
@@ -267,9 +269,10 @@ def test_dataset_transforms_single():
     assert x_trans.min() >= -1
     assert x_trans.max() <= 1
     assert len(x_original) != len(x_trans)
-    assert y == 5
+    assert y == 7
 
 def test_dataset_transforms_multiple():
+    """Note: This test may fail if not on Linux."""
     n_mfcc = 13
     files = glob.glob('lib/test/data/v1.0.10/*.wav')
     x_original, y = TorchFSDD(files)[0]
@@ -279,8 +282,8 @@ def test_dataset_transforms_multiple():
     ]))[0]
     assert isinstance(x_trans, torch.Tensor)
     assert x_trans.ndim == 2
-    assert x_trans.shape == (n_mfcc, 12)
-    assert y == 5
+    assert x_trans.shape == (n_mfcc, 9)
+    assert y == 7
 
 def test_dataset_load_all_false():
     files = glob.glob('lib/test/data/v1.0.10/*.wav')
@@ -298,11 +301,4 @@ def test_dataset_load_all_true():
     assert hasattr(fsdd, 'labels')
     assert isinstance(fsdd.labels, list)
     assert isinstance(fsdd.labels[0], int)
-    assert len(fsdd.labels) == len(files)
-
-def test_dataset_args():
-    offset = 100
-    files = glob.glob('lib/test/data/v1.0.10/*.wav')
-    x1, _ = TorchFSDD(files)[0]
-    x2, _ = TorchFSDD(files, offset=offset)[0]
-    assert torch.eq(x2, x1[100:]).all()
+    assert len(fsdd.labels) == len(files)

lib/torchfsdd/__init__.py

@@ -1,4 +1,4 @@
-__version__ = '0.1.0'
+__version__ = '0.1.1'
 
 import importlib, platform
 from pkg_resources import packaging
@@ -7,8 +7,8 @@
 else:
     from importlib import metadata
 
-MIN_TORCH_VERSION = '1.6'
-MIN_TORCHAUDIO_VERSION = '0.6'
+MIN_TORCH_VERSION = '1.8'
+MIN_TORCHAUDIO_VERSION = '0.8'
 
 def check_package(pkg, min_version, url):
     """Checks whether a specified package has been installed,
@@ -20,7 +20,7 @@ def check_package(pkg, min_version, url):
         Name of the package.
 
     min_version: str
-        Minimum version for the package, e.g. `1.6`.
+        Minimum version for the package, e.g. `1.8`.
 
     url: str
         Package installation page URL (for help).

notebooks/requirements.txt

@@ -1,10 +1,10 @@
 --find-links https://download.pytorch.org/whl/torch_stable.html
-torch==1.6.0+cpu; sys_platform == 'linux'
-torch==1.6.0; sys_platform == 'darwin'
-torchaudio==0.6.0+cpu; sys_platform == 'linux'
-torchaudio==0.6.0; sys_platform == 'darwin'
-torchvision==0.7.0+cpu; sys_platform == 'linux'
-torchvision==0.7.0; sys_platform == 'darwin'
+torch==1.8.0+cpu; sys_platform == 'linux'
+torch==1.8.0; sys_platform == 'darwin'
+torchaudio==0.8.0+cpu; sys_platform == 'linux'
+torchaudio==0.8.0; sys_platform == 'darwin'
+torchvision==0.9.0+cpu; sys_platform == 'linux'
+torchvision==0.9.0; sys_platform == 'darwin'
 jupyter
 matplotlib
 tqdm

setup.py

@@ -4,7 +4,7 @@
 from pkg_resources import packaging
 from setuptools import setup, find_packages
 
-VERSION = '0.1.0'
+VERSION = '0.1.1'
 
 with open('README.md', 'r', encoding='utf8') as fh:
     long_description = fh.read()
@@ -47,5 +47,5 @@
     ],
     python_requires = '>=3.6',
     install_requires = install_requires,
-    extra_requires = {'torch': ['torch>=1.6+cpu', 'torchaudio>=0.6+cpu']}
+    extra_requires = {'torch': ['torch>=1.8+cpu', 'torchaudio>=0.8+cpu']}
 )