Update TimeStretch doc and tutorial (#3694)

examples/tutorials/audio_feature_augmentation_tutorial.py

@@ -25,6 +25,7 @@ print(torchaudio.__version__)
 
 import librosa
 import matplotlib.pyplot as plt
+from IPython.display import Audio
 from torchaudio.utils import download_asset
 
 ######################################################################
@@ -69,11 +70,6 @@ def get_spectrogram(
     return spectrogram(waveform)
 
 
-def plot_spec(ax, spec, title, ylabel="freq_bin"):
-    ax.set_title(title)
-    ax.imshow(librosa.power_to_db(spec), origin="lower", aspect="auto")
-
-
 ######################################################################
 # SpecAugment
 # -----------
@@ -98,11 +94,15 @@ stretch = T.TimeStretch()
 spec_12 = stretch(spec, overriding_rate=1.2)
 spec_09 = stretch(spec, overriding_rate=0.9)
 
-######################################################################
-#
-
 
+######################################################################
+# Visualization
+# ~~~~~~~~~~~~~
 def plot():
+    def plot_spec(ax, spec, title):
+        ax.set_title(title)
+        ax.imshow(librosa.amplitude_to_db(spec), origin="lower", aspect="auto")
+
     fig, axes = plt.subplots(3, 1, sharex=True, sharey=True)
     plot_spec(axes[0], torch.abs(spec_12[0]), title="Stretched x1.2")
     plot_spec(axes[1], torch.abs(spec[0]), title="Original")
@@ -112,6 +112,30 @@ def plot():
 
 plot()
 
+
+######################################################################
+# Audio Samples
+# ~~~~~~~~~~~~~
+def preview(spec, rate=16000):
+    ispec = T.InverseSpectrogram()
+    waveform = ispec(spec)
+
+    return Audio(waveform[0].numpy().T, rate=rate)
+
+
+preview(spec)
+
+
+######################################################################
+#
+preview(spec_12)
+
+
+######################################################################
+#
+preview(spec_09)
+
+
 ######################################################################
 # Time and Frequency Masking
 # --------------------------
@@ -131,6 +155,10 @@ freq_masked = freq_masking(spec)
 
 
 def plot():
+    def plot_spec(ax, spec, title):
+        ax.set_title(title)
+        ax.imshow(librosa.power_to_db(spec), origin="lower", aspect="auto")
+
     fig, axes = plt.subplots(3, 1, sharex=True, sharey=True)
     plot_spec(axes[0], spec[0], title="Original")
     plot_spec(axes[1], time_masked[0], title="Masked along time axis")

src/torchaudio/transforms/_transforms.py

@@ -1020,31 +1020,27 @@ class TimeStretch(torch.nn.Module):
     Proposed in *SpecAugment* :cite:`specaugment`.
 
     Args:
-        hop_length (int or None, optional): Length of hop between STFT windows. (Default: ``win_length // 2``)
+        hop_length (int or None, optional): Length of hop between STFT windows.
+            (Default: ``n_fft // 2``, where ``n_fft == (n_freq - 1) * 2``)
         n_freq (int, optional): number of filter banks from stft. (Default: ``201``)
         fixed_rate (float or None, optional): rate to speed up or slow down by.
             If None is provided, rate must be passed to the forward method. (Default: ``None``)
 
+    .. note::
+
+       The expected input is raw, complex-valued spectrogram.
+
     Example
-        >>> spectrogram = torchaudio.transforms.Spectrogram()
+        >>> spectrogram = torchaudio.transforms.Spectrogram(power=None)
         >>> stretch = torchaudio.transforms.TimeStretch()
         >>>
         >>> original = spectrogram(waveform)
-        >>> streched_1_2 = stretch(original, 1.2)
-        >>> streched_0_9 = stretch(original, 0.9)
-
-        .. image:: https://download.pytorch.org/torchaudio/doc-assets/specaugment_time_stretch_1.png
-           :width: 600
-           :alt: Spectrogram streched by 1.2
+        >>> stretched_1_2 = stretch(original, 1.2)
+        >>> stretched_0_9 = stretch(original, 0.9)
 
-        .. image:: https://download.pytorch.org/torchaudio/doc-assets/specaugment_time_stretch_2.png
+        .. image:: https://download.pytorch.org/torchaudio/doc-assets/specaugment_time_stretch.png
            :width: 600
-           :alt: The original spectrogram
-
-        .. image:: https://download.pytorch.org/torchaudio/doc-assets/specaugment_time_stretch_3.png
-           :width: 600
-           :alt: Spectrogram streched by 0.9
-
+           :alt: The visualization of stretched spectrograms.
     """
     __constants__ = ["fixed_rate"]
 
@@ -1067,8 +1063,8 @@ class TimeStretch(torch.nn.Module):
 
         Returns:
             Tensor:
-                Stretched spectrogram. The resulting tensor is of the same dtype as the input
-                spectrogram, but the number of frames is changed to ``ceil(num_frame / rate)``.
+                Stretched spectrogram. The resulting tensor is of the corresponding complex dtype
+                as the input spectrogram, and the number of frames is changed to ``ceil(num_frame / rate)``.
         """
         if overriding_rate is None:
             if self.fixed_rate is None: