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new model

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This commit is contained in:
adamnsandle
2020-12-22 12:14:54 +00:00
parent dee92fb847
commit b23720e3ca
4 changed files with 10 additions and 10 deletions
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16
utils.py
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@@ -52,7 +52,7 @@ def init_jit_model(model_path: str,
def get_speech_ts(wav: torch.Tensor,
model,
trig_sum: float = 0.25,
neg_trig_sum: float = 0.02,
neg_trig_sum: float = 0.1,
num_steps: int = 8,
batch_size: int = 200,
run_function=validate):
@@ -70,13 +70,13 @@ def get_speech_ts(wav: torch.Tensor,
to_concat.append(chunk.unsqueeze(0))
if len(to_concat) >= batch_size:
chunks = torch.Tensor(torch.cat(to_concat, dim=0))
out = run_function(model, chunks)[-2]
out = run_function(model, chunks)
outs.append(out)
to_concat = []
if to_concat:
chunks = torch.Tensor(torch.cat(to_concat, dim=0))
out = run_function(model, chunks)[-2]
out = run_function(model, chunks)
outs.append(out)
outs = torch.cat(outs, dim=0)
@@ -107,7 +107,7 @@ def get_speech_ts(wav: torch.Tensor,
class VADiterator:
def __init__(self,
trig_sum: float = 0.26,
neg_trig_sum: float = 0.02,
neg_trig_sum: float = 0.1,
num_steps: int = 8):
self.num_samples = 4000
self.num_steps = num_steps
@@ -168,7 +168,7 @@ def state_generator(model,
audios: List[str],
onnx: bool = False,
trig_sum: float = 0.26,
neg_trig_sum: float = 0.02,
neg_trig_sum: float = 0.1,
num_steps: int = 8,
audios_in_stream: int = 2,
run_function=validate):
@@ -178,7 +178,7 @@ def state_generator(model,
batch = torch.cat(for_batch)
outs = run_function(model, batch)
vad_outs = torch.split(outs[-2], num_steps)
vad_outs = torch.split(outs, num_steps)
states = []
for x, y in zip(VADiters, vad_outs):
@@ -227,7 +227,7 @@ def single_audio_stream(model,
audio: str,
onnx: bool = False,
trig_sum: float = 0.26,
neg_trig_sum: float = 0.02,
neg_trig_sum: float = 0.1,
num_steps: int = 8,
run_function=validate):
num_samples = 4000
@@ -238,7 +238,7 @@ def single_audio_stream(model,
batch = VADiter.prepare_batch(chunk)
outs = run_function(model, batch)
vad_outs = outs[-2] # this is very misleading
vad_outs = outs # this is very misleading
states = []
state = VADiter.state(vad_outs)