benchmark:replace paddleaudio.layer.feature with features in paddle

audio/tests/benchmark/log_melspectrogram.py

@@ -55,7 +55,7 @@ def enable_gpu_device():
     paddle.set_device('gpu')
 
 
-log_mel_extractor = paddleaudio.features.LogMelSpectrogram(
+log_mel_extractor = paddle.audio.features.LogMelSpectrogram(
     **mel_conf, f_min=0.0, top_db=80.0, dtype=waveform_tensor.dtype)
 
 

audio/tests/benchmark/melspectrogram.py

@@ -55,7 +55,7 @@ def enable_gpu_device():
     paddle.set_device('gpu')
 
 
-mel_extractor = paddleaudio.features.MelSpectrogram(
+mel_extractor = paddle.audio.features.MelSpectrogram(
     **mel_conf, f_min=0.0, dtype=waveform_tensor.dtype)
 
 

audio/tests/benchmark/mfcc.py

@@ -64,7 +64,7 @@ def enable_gpu_device():
     paddle.set_device('gpu')
 
 
-mfcc_extractor = paddleaudio.features.MFCC(
+mfcc_extractor = paddle.audio.features.MFCC(
     **mfcc_conf, f_min=0.0, dtype=waveform_tensor.dtype)
 
 

audio/tests/features/test_librosa.py

@@ -169,7 +169,7 @@ class TestLibrosa(FeatTest):
         # paddleaudio.features.layer
         x = paddle.to_tensor(
             self.waveform, dtype=paddle.float64).unsqueeze(0)  # Add batch dim.
-        feature_extractor = paddleaudio.features.MelSpectrogram(
+        feature_extractor = paddle.audio.features.MelSpectrogram(
             sr=self.sr,
             n_fft=self.n_fft,
             hop_length=self.hop_length,
@@ -210,7 +210,7 @@ class TestLibrosa(FeatTest):
         # paddleaudio.features.layer
         x = paddle.to_tensor(
             self.waveform, dtype=paddle.float64).unsqueeze(0)  # Add batch dim.
-        feature_extractor = paddleaudio.features.LogMelSpectrogram(
+        feature_extractor = paddle.audio.features.LogMelSpectrogram(
             sr=self.sr,
             n_fft=self.n_fft,
             hop_length=self.hop_length,
@@ -257,10 +257,10 @@ class TestLibrosa(FeatTest):
             fmin=self.fmin,
             top_db=self.top_db)
 
-        # paddleaudio.features.layer
+        # paddle.audio.features.layer
         x = paddle.to_tensor(
             self.waveform, dtype=paddle.float64).unsqueeze(0)  # Add batch dim.
-        feature_extractor = paddleaudio.features.MFCC(
+        feature_extractor = paddle.audio.features.MFCC(
             sr=self.sr,
             n_mfcc=self.n_mfcc,
             n_fft=self.n_fft,

audio/tests/features/test_spectrogram.py

@@ -31,7 +31,7 @@ class TestSpectrogram(FeatTest):
         ps_res = ps_spect(self.waveform.T).squeeze(1).T  # Magnitude
 
         x = paddle.to_tensor(self.waveform)
-        pa_spect = paddleaudio.features.Spectrogram(
+        pa_spect = paddle.audio.features.Spectrogram(
             self.n_fft, self.hop_length, power=1.0)
         pa_res = pa_spect(x).squeeze(0).numpy()