change to AudioGen
Browse files- handler.py +16 -21
- requirements.txt +1 -1
handler.py
CHANGED
@@ -1,13 +1,19 @@
|
|
1 |
from typing import Dict, List, Any
|
2 |
-
from transformers import AutoProcessor, MusicgenForConditionalGeneration
|
3 |
-
import torch
|
|
|
|
|
|
|
|
|
4 |
|
5 |
class EndpointHandler:
|
6 |
def __init__(self, path=""):
|
7 |
# load model and processor from path
|
8 |
-
path = "jamesdon/audiogen-medium-endpoint"
|
9 |
-
self.processor = AutoProcessor.from_pretrained(path)
|
10 |
-
self.model = MusicgenForConditionalGeneration.from_pretrained(path).to("cuda")
|
|
|
|
|
11 |
|
12 |
def __call__(self, data: Dict[str, Any]) -> Dict[str, str]:
|
13 |
"""
|
@@ -16,22 +22,11 @@ class EndpointHandler:
|
|
16 |
The payload with the text prompt and generation parameters.
|
17 |
"""
|
18 |
# process input
|
19 |
-
inputs = data.pop("inputs", data)
|
20 |
-
|
21 |
-
|
22 |
-
|
23 |
-
|
24 |
-
text=[inputs],
|
25 |
-
padding=True,
|
26 |
-
return_tensors="pt",).to("cuda")
|
27 |
-
|
28 |
-
# pass inputs with all kwargs in data
|
29 |
-
if parameters is not None:
|
30 |
-
outputs = self.model.generate(**inputs, **parameters)
|
31 |
-
else:
|
32 |
-
outputs = self.model.generate(**inputs)
|
33 |
-
|
34 |
-
# postprocess the prediction
|
35 |
prediction = outputs[0].cpu().numpy()
|
36 |
|
37 |
return [{"generated_audio": prediction}]
|
|
|
1 |
from typing import Dict, List, Any
|
2 |
+
# from transformers import AutoProcessor, MusicgenForConditionalGeneration
|
3 |
+
# import torch
|
4 |
+
|
5 |
+
# import torchaudio
|
6 |
+
from audiocraft.models import AudioGen
|
7 |
+
from audiocraft.data.audio import audio_write
|
8 |
|
9 |
class EndpointHandler:
|
10 |
def __init__(self, path=""):
|
11 |
# load model and processor from path
|
12 |
+
# path = "jamesdon/audiogen-medium-endpoint"
|
13 |
+
# self.processor = AutoProcessor.from_pretrained(path)
|
14 |
+
# self.model = MusicgenForConditionalGeneration.from_pretrained(path).to("cuda")
|
15 |
+
self.model = AudioGen.get_pretrained(path)
|
16 |
+
|
17 |
|
18 |
def __call__(self, data: Dict[str, Any]) -> Dict[str, str]:
|
19 |
"""
|
|
|
22 |
The payload with the text prompt and generation parameters.
|
23 |
"""
|
24 |
# process input
|
25 |
+
inputs = data.pop("inputs", data) # list of string
|
26 |
+
duration = data.pop("duration", 5) # seconds to generate
|
27 |
+
|
28 |
+
self.model.set_generation_params(duration=duration)
|
29 |
+
outputs = self.model.generate(inputs)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
30 |
prediction = outputs[0].cpu().numpy()
|
31 |
|
32 |
return [{"generated_audio": prediction}]
|
requirements.txt
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
transformers==4.31.0
|
2 |
accelerate>=0.20.3
|
3 |
-
|
|
|
1 |
transformers==4.31.0
|
2 |
accelerate>=0.20.3
|
3 |
+
audiocraft
|