Set and tweak global matplotlib configuration in tutorials (#3515)

Summary:
- Set global matplotlib rc params
- Fix style check
- Fix and updates FA tutorial plots
- Add av-asr index cars

Pull Request resolved: https://github.com/pytorch/audio/pull/3515

Reviewed By: huangruizhe

Differential Revision: D47894156

Pulled By: mthrok

fbshipit-source-id: b40d8d31f12ffc2b337e35e632afc216e9d59a6e

examples/tutorials/streamreader_advanced_tutorial.py

@@ -355,13 +355,14 @@ chunks = next(streamer.stream())
 
 def _display(i):
     print("filter_desc:", streamer.get_out_stream_info(i).filter_description)
-    _, axs = plt.subplots(2, 1)
+    fig, axs = plt.subplots(2, 1)
     waveform = chunks[i][:, 0]
     axs[0].plot(waveform)
     axs[0].grid(True)
     axs[0].set_ylim([-1, 1])
     plt.setp(axs[0].get_xticklabels(), visible=False)
     axs[1].specgram(waveform, Fs=sample_rate)
+    fig.tight_layout()
     return IPython.display.Audio(chunks[i].T, rate=sample_rate)
 
 
@@ -440,7 +441,6 @@ def _display(i):
         axs[j].imshow(chunk[10 * j + 1].permute(1, 2, 0))
         axs[j].set_axis_off()
     plt.tight_layout()
-    plt.show(block=False)
 
 
 ######################################################################

examples/tutorials/streamreader_basic_tutorial.py

@@ -592,7 +592,6 @@ for i, vid in enumerate(vids2):
         if i == 0 and j == 0:
             ax.set_ylabel("Stream 2")
 plt.tight_layout()
-plt.show(block=False)
 
 ######################################################################
 #

examples/tutorials/tacotron2_pipeline_tutorial.py

@@ -7,10 +7,6 @@ Text-to-Speech with Tacotron2
 
 """
 
-import IPython
-import matplotlib
-import matplotlib.pyplot as plt
-
 ######################################################################
 # Overview
 # --------
@@ -65,8 +61,6 @@ import matplotlib.pyplot as plt
 import torch
 import torchaudio
 
-matplotlib.rcParams["figure.figsize"] = [16.0, 4.8]
-
 torch.random.manual_seed(0)
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
@@ -75,6 +69,13 @@ print(torchaudio.__version__)
 print(device)
 
 
+######################################################################
+#
+
+import IPython
+import matplotlib.pyplot as plt
+
+
 ######################################################################
 # Text Processing
 # ---------------
@@ -226,13 +227,17 @@ _ = plt.imshow(spec[0].cpu().detach(), origin="lower", aspect="auto")
 # therefor, the process of generating the spectrogram incurs randomness.
 #
 
-fig, ax = plt.subplots(3, 1, figsize=(16, 4.3 * 3))
-for i in range(3):
+
+def plot():
+    fig, ax = plt.subplots(3, 1)
+    for i in range(3):
         with torch.inference_mode():
             spec, spec_lengths, _ = tacotron2.infer(processed, lengths)
         print(spec[0].shape)
         ax[i].imshow(spec[0].cpu().detach(), origin="lower", aspect="auto")
-plt.show()
+
+
+plot()
 
 
 ######################################################################
@@ -270,11 +275,22 @@ with torch.inference_mode():
     spec, spec_lengths, _ = tacotron2.infer(processed, lengths)
     waveforms, lengths = vocoder(spec, spec_lengths)
 
-fig, [ax1, ax2] = plt.subplots(2, 1, figsize=(16, 9))
-ax1.imshow(spec[0].cpu().detach(), origin="lower", aspect="auto")
-ax2.plot(waveforms[0].cpu().detach())
+######################################################################
+#
+
+
+def plot(waveforms, spec, sample_rate):
+    waveforms = waveforms.cpu().detach()
 
-IPython.display.Audio(waveforms[0:1].cpu(), rate=vocoder.sample_rate)
+    fig, [ax1, ax2] = plt.subplots(2, 1)
+    ax1.plot(waveforms[0])
+    ax1.set_xlim(0, waveforms.size(-1))
+    ax1.grid(True)
+    ax2.imshow(spec[0].cpu().detach(), origin="lower", aspect="auto")
+    return IPython.display.Audio(waveforms[0:1], rate=sample_rate)
+
+
+plot(waveforms, spec, vocoder.sample_rate)
 
 
 ######################################################################
@@ -300,11 +316,10 @@ with torch.inference_mode():
     spec, spec_lengths, _ = tacotron2.infer(processed, lengths)
 waveforms, lengths = vocoder(spec, spec_lengths)
 
-fig, [ax1, ax2] = plt.subplots(2, 1, figsize=(16, 9))
-ax1.imshow(spec[0].cpu().detach(), origin="lower", aspect="auto")
-ax2.plot(waveforms[0].cpu().detach())
+######################################################################
+#
 
-IPython.display.Audio(waveforms[0:1].cpu(), rate=vocoder.sample_rate)
+plot(waveforms, spec, vocoder.sample_rate)
 
 
 ######################################################################
@@ -339,8 +354,7 @@ waveglow.eval()
 with torch.no_grad():
     waveforms = waveglow.infer(spec)
 
-fig, [ax1, ax2] = plt.subplots(2, 1, figsize=(16, 9))
-ax1.imshow(spec[0].cpu().detach(), origin="lower", aspect="auto")
-ax2.plot(waveforms[0].cpu().detach())
+######################################################################
+#
 
-IPython.display.Audio(waveforms[0:1].cpu(), rate=22050)
+plot(waveforms, spec, 22050)