fix pyproject.toml

pesto/data.py

@@ -63,6 +63,7 @@ class Preprocessor(nn.Module):
         # compute CQT from input waveform, and invert dims for (time_steps, num_harmonics, freq_bins)
         # in other words, time becomes the batch dimension, enabling efficient processing for long audios.
         complex_cqt = torch.view_as_complex(self.hcqt(x, sr=sr)).permute(0, 3, 1, 2)
+        complex_cqt.squeeze_(0)
 
         # convert to dB
         return self.to_log(complex_cqt)

pesto/loader.py

@@ -24,7 +24,7 @@ def load_model(checkpoint: str,
     if os.path.exists(checkpoint):  # handle user-provided checkpoints
         model_path = checkpoint
     else:
-        model_path = os.path.join(os.path.dirname(__file__), "weights", checkpoint + ".pth")
+        model_path = os.path.join(os.path.dirname(__file__), "weights", checkpoint + ".ckpt")
         if not os.path.exists(model_path):
             raise FileNotFoundError(f"You passed an invalid checkpoint file: {checkpoint}.")
 

pyproject.toml

@@ -8,7 +8,7 @@ version = "1.0.0"
 authors = [
     {name = "Alain Riou", email = "alain.riou@sony.com"}
 ]
-description = "Efficient pitch estimation with self-supervised learning",
+description = "Efficient pitch estimation with self-supervised learning"
 readme = {file = "README.md", content-type = "text/markdown"}
 requires-python = ">=3.8"
 classifiers = [
@@ -33,13 +33,13 @@ matplotlib = ["matplotlib"]
 test = ["pytest"]
 
 [project.scripts]
-pesto = "pesto.main.py:pesto"
+pesto = "pesto.main:pesto"
 
 [project.urls]
 source = "https://github.com/SonyCSLParis/pesto"
 
-[tool.setuptools.packages.find]
-where = ["pesto"]
+[tool.pytest.ini_options]
+testpaths = "tests/"
 
 [tool.setuptools.package-data]
-weights = ["*.ckpt"]
+pesto = ["weights/*.ckpt"]