@@ -15,20 +15,18 @@ pip install audio-diffusion-pytorch
1515## Usage
1616
1717``` py
18-
1918model = AudioDiffusionModel()
2019
2120# Train model with audio sources [batch, channels, samples]
2221x = torch.randn(2 , 1 , 2 ** 18 )
2322loss = net(x)
2423loss.backward()
2524
26-
2725# Sample given start noise
2826noise = torch.randn(2 , 1 , 2 ** 18 )
2927sampled = net.sample(
3028 noise = noise,
31- num_steps = 5 # Range 1-100
29+ num_steps = 5 # Suggested range: 1-100
3230) # [2, 1, 2**18]
3331```
3432
@@ -88,7 +86,7 @@ from audio_diffusion_pytorch import DiffusionSampler, KerrasSchedule
8886
8987sampler = DiffusionSampler(
9088 diffusion,
91- num_steps = 5 , # Range 1-100, higher better quality but takes longer
89+ num_steps = 5 , # Suggested range 1-100, higher better quality but takes longer
9290 sampler = ADPM2Sampler(rho = 1 ),
9391 sigma_schedule = KarrasSchedule(
9492 sigma_min = 0.002 ,
@@ -108,8 +106,8 @@ from audio_diffusion_pytorch import DiffusionInpainter, KerrasSchedule
108106
109107inpainter = DiffusionInpainter(
110108 diffusion,
111- num_steps = 50 , # Range 32-1000, higher for better quality
112- num_resamples = 5 , # Range 1-10, higher for better quality
109+ num_steps = 50 , # Suggested range 32-1000, higher for better quality
110+ num_resamples = 5 , # Suggested range 1-10, higher for better quality
113111 sigma_schedule = KerrasSchedule(
114112 sigma_min = 0.002 ,
115113 sigma_max = 1
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