Updated for new pyharp API.

app.py

@@ -1,5 +1,5 @@
 from timbre_trap.framework.modules import TimbreTrap
-from pyharp import ModelCard, build_endpoint
+from pyharp import *
 
 import gradio as gr
 import torchaudio
@@ -17,10 +17,11 @@ model = TimbreTrap(sample_rate=22050,
 model.eval()
 
 model_path_orig = os.path.join('models', 'tt-orig.pt')
+
 tt_weights_orig = torch.load(model_path_orig, map_location='cpu')
 model.load_state_dict(tt_weights_orig)
 
-card = ModelCard(
+model_card = ModelCard(
     name='Timbre-Trap',
     description='De-timbre your audio!',
     author='Frank Cwitkowitz',
@@ -28,7 +29,7 @@ card = ModelCard(
 )
 
 
-def process_fn(audio_path, de_timbre):
+def process_fn(audio_path, transcribe):
     # Load the audio with torchaudio
     audio, fs = torchaudio.load(audio_path)
     # Average channels to obtain mono-channel
@@ -41,8 +42,7 @@ def process_fn(audio_path, de_timbre):
     n_samples = audio.size(-1)
 
     # Obtain transcription or reconstructed spectral coefficients
-    coefficients = model.chunked_inference(audio, de_timbre)
-    #coefficients = model.inference(audio, de_timbre)
+    coefficients = model.chunked_inference(audio, transcribe)
 
     # Invert coefficients to produce audio
     audio = model.sliCQ.decode(coefficients)
@@ -64,32 +64,39 @@ def process_fn(audio_path, de_timbre):
     # Save the audio
     torchaudio.save(save_path, audio, fs)
 
-    return save_path
+    # No output labels
+    output_labels = LabelList()
+
+    return save_path, output_labels
 
 
 # Build Gradio endpoint
 with gr.Blocks() as demo:
-    inputs = [
-        gr.Audio(
-            label='Audio Input',
-            type='filepath'
-        ),
+    components = [
         #gr.Checkbox(
         #    value=False,
         #    label='De-Timbre'
-        #)
+        #),
         gr.Slider(
             minimum=0,
             maximum=1,
             step=1,
             value=0,
             label='De-Timbre'
-        )
+        ),
+        #gr.Number(
+        #    value=0,
+        #    label='De-Timbre'
+        #),
+        #gr.Textbox(
+        #    value='text',
+        #    label='De-Timbre'
+        #)
     ]
 
-    # Build endpoint
-    output = gr.Audio(label='Audio Output', type='filepath')
-    widgets = build_endpoint(inputs, output, process_fn, card)
+    app = build_endpoint(model_card=model_card,
+                         components=components,
+                         process_fn=process_fn)
 
 demo.queue()
 demo.launch(share=True)

requirements.txt

@@ -1,4 +1,4 @@
--e git+https://github.com/audacitorch/pyharp.git#egg=pyharp
+-e git+https://github.com/TEAMuP-dev/pyharp.git#egg=pyharp
 -e git+https://github.com/sony/timbre-trap.git@updates#egg=timbre-trap
 torchaudio
 torch