Refactor: SDR & SI_SDR (Lightning-AI#711)

* signal_distortion_ratio
* scale_invariant_signal_distortion_ratio
* SignalDistortionRatio
* ScaleInvariantSignalDistortionRatio

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

CHANGELOG.md

@@ -64,6 +64,13 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   * `SpearmanCorrcoef` -> `SpearmanCorrCoef`
 
 
+- Renamed audio SDR metrics: ([#711](https://github.com/PyTorchLightning/metrics/pull/711))
+  * `functional.sdr` -> `functional.signal_distortion_ratio`
+  * `functional.si_sdr` -> `functional.scale_invariant_signal_distortion_ratio`
+  * `SDR` -> `SignalDistortionRatio`
+  * `SI_SDR` -> `ScaleInvariantSignalDistortionRatio`
+
+
 ### Removed
 
 - Removed `embedding_similarity` metric ([#638](https://github.com/PyTorchLightning/metrics/pull/638))

README.md

@@ -266,7 +266,7 @@ acc = torchmetrics.functional.accuracy(preds, target)
 We currently have implemented metrics within the following domains:
 
 - Audio (
-  [SI_SDR](https://torchmetrics.readthedocs.io/en/latest/references/modules.html#si-sdr),
+  [ScaleInvariantSignalDistortionRatio](https://torchmetrics.readthedocs.io/en/latest/references/modules.html#ScaleInvariantSignalDistortionRatio),
   [SI_SNR](https://torchmetrics.readthedocs.io/en/latest/references/modules.html#si-snr),
   [SNR](https://torchmetrics.readthedocs.io/en/latest/references/modules.html#snr)
   and [few more](https://torchmetrics.readthedocs.io/en/latest/references/modules.html#audio-metrics)

docs/source/references/functional.rst

@@ -24,17 +24,17 @@ pit [func]
     :noindex:
 
 
-sdr [func]
-~~~~~~~~~~
+signal_distortion_ratio [func]
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. autofunction:: torchmetrics.functional.sdr
+.. autofunction:: torchmetrics.functional.signal_distortion_ratio
     :noindex:
 
 
-si_sdr [func]
-~~~~~~~~~~~~~
+scale_invariant_signal_distortion_ratio [func]
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. autofunction:: torchmetrics.functional.si_sdr
+.. autofunction:: torchmetrics.functional.scale_invariant_signal_distortion_ratio
     :noindex:
 
 

docs/source/references/modules.rst

@@ -85,16 +85,16 @@ PIT
 .. autoclass:: torchmetrics.PIT
     :noindex:
 
-SDR
-~~~
+SignalDistortionRatio
+~~~~~~~~~~~~~~~~~~~~~
 
-.. autoclass:: torchmetrics.SDR
+.. autoclass:: torchmetrics.SignalDistortionRatio
     :noindex:
 
-SI_SDR
-~~~~~~
+ScaleInvariantSignalDistortionRatio
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. autoclass:: torchmetrics.SI_SDR
+.. autoclass:: torchmetrics.ScaleInvariantSignalDistortionRatio
     :noindex:
 
 SI_SNR

tests/audio/test_pit.py

@@ -24,7 +24,7 @@
 from tests.helpers import seed_all
 from tests.helpers.testers import BATCH_SIZE, NUM_BATCHES, MetricTester
 from torchmetrics.audio import PIT
-from torchmetrics.functional import pit, si_sdr, snr
+from torchmetrics.functional import pit, scale_invariant_signal_distortion_ratio, snr
 from torchmetrics.utilities.imports import _TORCH_GREATER_EQUAL_1_6
 
 seed_all(42)
@@ -97,16 +97,18 @@ def _average_metric(preds: Tensor, target: Tensor, metric_func: Callable) -> Ten
 
 
 snr_pit_scipy = partial(naive_implementation_pit_scipy, metric_func=snr, eval_func="max")
-si_sdr_pit_scipy = partial(naive_implementation_pit_scipy, metric_func=si_sdr, eval_func="max")
+si_sdr_pit_scipy = partial(
+    naive_implementation_pit_scipy, metric_func=scale_invariant_signal_distortion_ratio, eval_func="max"
+)
 
 
 @pytest.mark.parametrize(
     "preds, target, sk_metric, metric_func, eval_func",
     [
         (inputs1.preds, inputs1.target, snr_pit_scipy, snr, "max"),
-        (inputs1.preds, inputs1.target, si_sdr_pit_scipy, si_sdr, "max"),
+        (inputs1.preds, inputs1.target, si_sdr_pit_scipy, scale_invariant_signal_distortion_ratio, "max"),
         (inputs2.preds, inputs2.target, snr_pit_scipy, snr, "max"),
-        (inputs2.preds, inputs2.target, si_sdr_pit_scipy, si_sdr, "max"),
+        (inputs2.preds, inputs2.target, si_sdr_pit_scipy, scale_invariant_signal_distortion_ratio, "max"),
     ],
 )
 class TestPIT(MetricTester):

tests/audio/test_sdr.py

@@ -24,8 +24,8 @@
 
 from tests.helpers import seed_all
 from tests.helpers.testers import MetricTester
-from torchmetrics.audio import SDR
-from torchmetrics.functional import sdr
+from torchmetrics.audio import SignalDistortionRatio
+from torchmetrics.functional import signal_distortion_ratio
 from torchmetrics.utilities.imports import _TORCH_GREATER_EQUAL_1_6, _TORCH_GREATER_EQUAL_1_8
 
 seed_all(42)
@@ -49,7 +49,7 @@ def sdr_original_batch(preds: Tensor, target: Tensor, compute_permutation: bool
     preds = preds.detach().cpu().numpy()
     mss = []
     for b in range(preds.shape[0]):
-        sdr_val_np, sir_val_np, sar_val_np, perm = bss_eval_sources(target[b], preds[b], compute_permutation)
+        sdr_val_np, _, _, _ = bss_eval_sources(target[b], preds[b], compute_permutation)
         mss.append(sdr_val_np)
     return torch.tensor(mss)
 
@@ -83,7 +83,7 @@ def test_sdr(self, preds, target, sk_metric, ddp, dist_sync_on_step):
             ddp,
             preds,
             target,
-            SDR,
+            SignalDistortionRatio,
             sk_metric=partial(average_metric, metric_func=sk_metric),
             dist_sync_on_step=dist_sync_on_step,
             metric_args=dict(),
@@ -93,7 +93,7 @@ def test_sdr_functional(self, preds, target, sk_metric):
         self.run_functional_metric_test(
             preds,
             target,
-            sdr,
+            signal_distortion_ratio,
             sk_metric,
             metric_args=dict(),
         )
@@ -103,8 +103,8 @@ def test_sdr_differentiability(self, preds, target, sk_metric):
         self.run_differentiability_test(
             preds=preds,
             target=target,
-            metric_module=SDR,
-            metric_functional=sdr,
+            metric_module=SignalDistortionRatio,
+            metric_functional=signal_distortion_ratio,
             metric_args=dict(),
         )
 
@@ -115,8 +115,8 @@ def test_sdr_half_cpu(self, preds, target, sk_metric):
         self.run_precision_test_cpu(
             preds=preds,
             target=target,
-            metric_module=SDR,
-            metric_functional=sdr,
+            metric_module=SignalDistortionRatio,
+            metric_functional=signal_distortion_ratio,
             metric_args=dict(),
         )
 
@@ -125,13 +125,13 @@ def test_sdr_half_gpu(self, preds, target, sk_metric):
         self.run_precision_test_gpu(
             preds=preds,
             target=target,
-            metric_module=SDR,
-            metric_functional=sdr,
+            metric_module=SignalDistortionRatio,
+            metric_functional=signal_distortion_ratio,
             metric_args=dict(),
         )
 
 
-def test_error_on_different_shape(metric_class=SDR):
+def test_error_on_different_shape(metric_class=SignalDistortionRatio):
     metric = metric_class()
     with pytest.raises(RuntimeError, match="Predictions and targets are expected to have the same shape"):
         metric(torch.randn(100), torch.randn(50))
@@ -143,7 +143,7 @@ def test_on_real_audio():
     rate, ref = wavfile.read(os.path.join(current_file_dir, "examples/audio_speech.wav"))
     rate, deg = wavfile.read(os.path.join(current_file_dir, "examples/audio_speech_bab_0dB.wav"))
     assert torch.allclose(
-        sdr(torch.from_numpy(deg), torch.from_numpy(ref)).float(),
+        signal_distortion_ratio(torch.from_numpy(deg), torch.from_numpy(ref)).float(),
         torch.tensor(0.2211),
         rtol=0.0001,
         atol=1e-4,

tests/audio/test_si_sdr.py

@@ -21,8 +21,8 @@
 
 from tests.helpers import seed_all
 from tests.helpers.testers import BATCH_SIZE, NUM_BATCHES, MetricTester
-from torchmetrics.audio import SI_SDR
-from torchmetrics.functional import si_sdr
+from torchmetrics.audio import ScaleInvariantSignalDistortionRatio
+from torchmetrics.functional import scale_invariant_signal_distortion_ratio
 from torchmetrics.utilities.imports import _TORCH_GREATER_EQUAL_1_6
 
 seed_all(42)
@@ -84,7 +84,7 @@ def test_si_sdr(self, preds, target, sk_metric, zero_mean, ddp, dist_sync_on_ste
             ddp,
             preds,
             target,
-            SI_SDR,
+            ScaleInvariantSignalDistortionRatio,
             sk_metric=partial(average_metric, metric_func=sk_metric),
             dist_sync_on_step=dist_sync_on_step,
             metric_args=dict(zero_mean=zero_mean),
@@ -94,7 +94,7 @@ def test_si_sdr_functional(self, preds, target, sk_metric, zero_mean):
         self.run_functional_metric_test(
             preds,
             target,
-            si_sdr,
+            scale_invariant_signal_distortion_ratio,
             sk_metric,
             metric_args=dict(zero_mean=zero_mean),
         )
@@ -103,8 +103,8 @@ def test_si_sdr_differentiability(self, preds, target, sk_metric, zero_mean):
         self.run_differentiability_test(
             preds=preds,
             target=target,
-            metric_module=SI_SDR,
-            metric_functional=si_sdr,
+            metric_module=ScaleInvariantSignalDistortionRatio,
+            metric_functional=scale_invariant_signal_distortion_ratio,
             metric_args={"zero_mean": zero_mean},
         )
 
@@ -119,13 +119,13 @@ def test_si_sdr_half_gpu(self, preds, target, sk_metric, zero_mean):
         self.run_precision_test_gpu(
             preds=preds,
             target=target,
-            metric_module=SI_SDR,
-            metric_functional=si_sdr,
+            metric_module=ScaleInvariantSignalDistortionRatio,
+            metric_functional=scale_invariant_signal_distortion_ratio,
             metric_args={"zero_mean": zero_mean},
         )
 
 
-def test_error_on_different_shape(metric_class=SI_SDR):
+def test_error_on_different_shape(metric_class=ScaleInvariantSignalDistortionRatio):
     metric = metric_class()
     with pytest.raises(RuntimeError, match="Predictions and targets are expected to have the same shape"):
         metric(torch.randn(100), torch.randn(50))

torchmetrics/__init__.py

@@ -13,7 +13,15 @@
 
 from torchmetrics import functional  # noqa: E402
 from torchmetrics.aggregation import CatMetric, MaxMetric, MeanMetric, MinMetric, SumMetric  # noqa: E402
-from torchmetrics.audio import PIT, SDR, SI_SDR, SI_SNR, SNR  # noqa: E402
+from torchmetrics.audio import (  # noqa: E402
+    PIT,
+    SDR,
+    SI_SDR,
+    SI_SNR,
+    SNR,
+    ScaleInvariantSignalDistortionRatio,
+    SignalDistortionRatio,
+)
 from torchmetrics.classification import (  # noqa: E402, F401
     AUC,
     AUROC,
@@ -142,6 +150,8 @@
     "ROC",
     "SacreBLEUScore",
     "SDR",
+    "SignalDistortionRatio",
+    "ScaleInvariantSignalDistortionRatio",
     "SI_SDR",
     "SI_SNR",
     "SNR",

torchmetrics/audio/__init__.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 from torchmetrics.audio.pit import PIT  # noqa: F401
-from torchmetrics.audio.sdr import SDR  # noqa: F401
+from torchmetrics.audio.sdr import SDR, ScaleInvariantSignalDistortionRatio, SignalDistortionRatio  # noqa: F401
 from torchmetrics.audio.si_sdr import SI_SDR  # noqa: F401
 from torchmetrics.audio.si_snr import SI_SNR  # noqa: F401
 from torchmetrics.audio.snr import SNR  # noqa: F401