facebookresearch--audiocraft
Alexandre Défossez (autodoc)
307 行
20 KiB
HTML
307 行
20 KiB
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and provide easy access to the generation API.">
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<main>
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<article id="content">
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<header>
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<h1 class="title">Module <code>audiocraft.models.audiogen</code></h1>
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</header>
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<section id="section-intro">
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<p>Main model for using AudioGen. This will combine all the required components
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and provide easy access to the generation API.</p>
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</section>
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<section>
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</section>
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<section>
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</section>
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<section>
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</section>
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<section>
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<h2 class="section-title" id="header-classes">Classes</h2>
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<dl>
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<dt id="audiocraft.models.audiogen.AudioGen"><code class="flex name class">
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<span>class <span class="ident">AudioGen</span></span>
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<span>(</span><span>name: str,<br>compression_model: <a title="audiocraft.models.encodec.CompressionModel" href="encodec.html#audiocraft.models.encodec.CompressionModel">CompressionModel</a>,<br>lm: <a title="audiocraft.models.lm.LMModel" href="lm.html#audiocraft.models.lm.LMModel">LMModel</a>,<br>max_duration: float | None = None)</span>
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</code></dt>
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<dd>
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<details class="source">
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<summary>
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<span>Expand source code</span>
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</summary>
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<pre><code class="python">class AudioGen(BaseGenModel):
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"""AudioGen main model with convenient generation API.
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Args:
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name (str): name of the model.
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compression_model (CompressionModel): Compression model
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used to map audio to invertible discrete representations.
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lm (LMModel): Language model over discrete representations.
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max_duration (float, optional): maximum duration the model can produce,
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otherwise, inferred from the training params.
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"""
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def __init__(self, name: str, compression_model: CompressionModel, lm: LMModel,
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max_duration: tp.Optional[float] = None):
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super().__init__(name, compression_model, lm, max_duration)
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self.set_generation_params(duration=5) # default duration
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@staticmethod
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def get_pretrained(name: str = 'facebook/audiogen-medium', device=None):
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"""Return pretrained model, we provide a single model for now:
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- facebook/audiogen-medium (1.5B), text to sound,
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# see: https://huggingface.co/facebook/audiogen-medium
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"""
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if device is None:
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if torch.cuda.device_count():
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device = 'cuda'
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else:
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device = 'cpu'
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if name == 'debug':
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# used only for unit tests
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compression_model = get_debug_compression_model(device, sample_rate=16000)
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lm = get_debug_lm_model(device)
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return AudioGen(name, compression_model, lm, max_duration=10)
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compression_model = load_compression_model(name, device=device)
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lm = load_lm_model(name, device=device)
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assert 'self_wav' not in lm.condition_provider.conditioners, \
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"AudioGen do not support waveform conditioning for now"
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return AudioGen(name, compression_model, lm)
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def set_generation_params(self, use_sampling: bool = True, top_k: int = 250,
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top_p: float = 0.0, temperature: float = 1.0,
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duration: float = 10.0, cfg_coef: float = 3.0,
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two_step_cfg: bool = False, extend_stride: float = 2):
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"""Set the generation parameters for AudioGen.
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Args:
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use_sampling (bool, optional): Use sampling if True, else do argmax decoding. Defaults to True.
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top_k (int, optional): top_k used for sampling. Defaults to 250.
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top_p (float, optional): top_p used for sampling, when set to 0 top_k is used. Defaults to 0.0.
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temperature (float, optional): Softmax temperature parameter. Defaults to 1.0.
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duration (float, optional): Duration of the generated waveform. Defaults to 10.0.
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cfg_coef (float, optional): Coefficient used for classifier free guidance. Defaults to 3.0.
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two_step_cfg (bool, optional): If True, performs 2 forward for Classifier Free Guidance,
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instead of batching together the two. This has some impact on how things
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are padded but seems to have little impact in practice.
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extend_stride: when doing extended generation (i.e. more than 10 seconds), by how much
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should we extend the audio each time. Larger values will mean less context is
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preserved, and shorter value will require extra computations.
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"""
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assert extend_stride < self.max_duration, "Cannot stride by more than max generation duration."
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self.extend_stride = extend_stride
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self.duration = duration
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self.generation_params = {
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'use_sampling': use_sampling,
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'temp': temperature,
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'top_k': top_k,
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'top_p': top_p,
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'cfg_coef': cfg_coef,
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'two_step_cfg': two_step_cfg,
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}</code></pre>
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</details>
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<div class="desc"><p>AudioGen main model with convenient generation API.</p>
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<h2 id="args">Args</h2>
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<dl>
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<dt><strong><code>name</code></strong> : <code>str</code></dt>
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<dd>name of the model.</dd>
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<dt><strong><code>compression_model</code></strong> : <code>CompressionModel</code></dt>
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<dd>Compression model
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used to map audio to invertible discrete representations.</dd>
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<dt><strong><code>lm</code></strong> : <code>LMModel</code></dt>
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<dd>Language model over discrete representations.</dd>
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||
<dt><strong><code>max_duration</code></strong> : <code>float</code>, optional</dt>
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<dd>maximum duration the model can produce,
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otherwise, inferred from the training params.</dd>
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</dl></div>
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<h3>Ancestors</h3>
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<ul class="hlist">
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<li><a title="audiocraft.models.genmodel.BaseGenModel" href="genmodel.html#audiocraft.models.genmodel.BaseGenModel">BaseGenModel</a></li>
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<li>abc.ABC</li>
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</ul>
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<h3>Static methods</h3>
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<dl>
|
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<dt id="audiocraft.models.audiogen.AudioGen.get_pretrained"><code class="name flex">
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<span>def <span class="ident">get_pretrained</span></span>(<span>name: str = 'facebook/audiogen-medium', device=None)</span>
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||
</code></dt>
|
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<dd>
|
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<details class="source">
|
||
<summary>
|
||
<span>Expand source code</span>
|
||
</summary>
|
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<pre><code class="python">@staticmethod
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def get_pretrained(name: str = 'facebook/audiogen-medium', device=None):
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"""Return pretrained model, we provide a single model for now:
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- facebook/audiogen-medium (1.5B), text to sound,
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# see: https://huggingface.co/facebook/audiogen-medium
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"""
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if device is None:
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if torch.cuda.device_count():
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device = 'cuda'
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else:
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device = 'cpu'
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||
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if name == 'debug':
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# used only for unit tests
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compression_model = get_debug_compression_model(device, sample_rate=16000)
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lm = get_debug_lm_model(device)
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return AudioGen(name, compression_model, lm, max_duration=10)
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compression_model = load_compression_model(name, device=device)
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lm = load_lm_model(name, device=device)
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assert 'self_wav' not in lm.condition_provider.conditioners, \
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"AudioGen do not support waveform conditioning for now"
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return AudioGen(name, compression_model, lm)</code></pre>
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</details>
|
||
<div class="desc"><p>Return pretrained model, we provide a single model for now:
|
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- facebook/audiogen-medium (1.5B), text to sound,
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# see: <a href="https://huggingface.co/facebook/audiogen-medium">https://huggingface.co/facebook/audiogen-medium</a></p></div>
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</dd>
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</dl>
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<h3>Methods</h3>
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<dl>
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<dt id="audiocraft.models.audiogen.AudioGen.set_generation_params"><code class="name flex">
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<span>def <span class="ident">set_generation_params</span></span>(<span>self,<br>use_sampling: bool = True,<br>top_k: int = 250,<br>top_p: float = 0.0,<br>temperature: float = 1.0,<br>duration: float = 10.0,<br>cfg_coef: float = 3.0,<br>two_step_cfg: bool = False,<br>extend_stride: float = 2)</span>
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</code></dt>
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<dd>
|
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<details class="source">
|
||
<summary>
|
||
<span>Expand source code</span>
|
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</summary>
|
||
<pre><code class="python">def set_generation_params(self, use_sampling: bool = True, top_k: int = 250,
|
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top_p: float = 0.0, temperature: float = 1.0,
|
||
duration: float = 10.0, cfg_coef: float = 3.0,
|
||
two_step_cfg: bool = False, extend_stride: float = 2):
|
||
"""Set the generation parameters for AudioGen.
|
||
|
||
Args:
|
||
use_sampling (bool, optional): Use sampling if True, else do argmax decoding. Defaults to True.
|
||
top_k (int, optional): top_k used for sampling. Defaults to 250.
|
||
top_p (float, optional): top_p used for sampling, when set to 0 top_k is used. Defaults to 0.0.
|
||
temperature (float, optional): Softmax temperature parameter. Defaults to 1.0.
|
||
duration (float, optional): Duration of the generated waveform. Defaults to 10.0.
|
||
cfg_coef (float, optional): Coefficient used for classifier free guidance. Defaults to 3.0.
|
||
two_step_cfg (bool, optional): If True, performs 2 forward for Classifier Free Guidance,
|
||
instead of batching together the two. This has some impact on how things
|
||
are padded but seems to have little impact in practice.
|
||
extend_stride: when doing extended generation (i.e. more than 10 seconds), by how much
|
||
should we extend the audio each time. Larger values will mean less context is
|
||
preserved, and shorter value will require extra computations.
|
||
"""
|
||
assert extend_stride < self.max_duration, "Cannot stride by more than max generation duration."
|
||
self.extend_stride = extend_stride
|
||
self.duration = duration
|
||
self.generation_params = {
|
||
'use_sampling': use_sampling,
|
||
'temp': temperature,
|
||
'top_k': top_k,
|
||
'top_p': top_p,
|
||
'cfg_coef': cfg_coef,
|
||
'two_step_cfg': two_step_cfg,
|
||
}</code></pre>
|
||
</details>
|
||
<div class="desc"><p>Set the generation parameters for AudioGen.</p>
|
||
<h2 id="args">Args</h2>
|
||
<dl>
|
||
<dt><strong><code>use_sampling</code></strong> : <code>bool</code>, optional</dt>
|
||
<dd>Use sampling if True, else do argmax decoding. Defaults to True.</dd>
|
||
<dt><strong><code>top_k</code></strong> : <code>int</code>, optional</dt>
|
||
<dd>top_k used for sampling. Defaults to 250.</dd>
|
||
<dt><strong><code>top_p</code></strong> : <code>float</code>, optional</dt>
|
||
<dd>top_p used for sampling, when set to 0 top_k is used. Defaults to 0.0.</dd>
|
||
<dt><strong><code>temperature</code></strong> : <code>float</code>, optional</dt>
|
||
<dd>Softmax temperature parameter. Defaults to 1.0.</dd>
|
||
<dt><strong><code>duration</code></strong> : <code>float</code>, optional</dt>
|
||
<dd>Duration of the generated waveform. Defaults to 10.0.</dd>
|
||
<dt><strong><code>cfg_coef</code></strong> : <code>float</code>, optional</dt>
|
||
<dd>Coefficient used for classifier free guidance. Defaults to 3.0.</dd>
|
||
<dt><strong><code>two_step_cfg</code></strong> : <code>bool</code>, optional</dt>
|
||
<dd>If True, performs 2 forward for Classifier Free Guidance,
|
||
instead of batching together the two. This has some impact on how things
|
||
are padded but seems to have little impact in practice.</dd>
|
||
<dt><strong><code>extend_stride</code></strong></dt>
|
||
<dd>when doing extended generation (i.e. more than 10 seconds), by how much
|
||
should we extend the audio each time. Larger values will mean less context is
|
||
preserved, and shorter value will require extra computations.</dd>
|
||
</dl></div>
|
||
</dd>
|
||
</dl>
|
||
<h3>Inherited members</h3>
|
||
<ul class="hlist">
|
||
<li><code><b><a title="audiocraft.models.genmodel.BaseGenModel" href="genmodel.html#audiocraft.models.genmodel.BaseGenModel">BaseGenModel</a></b></code>:
|
||
<ul class="hlist">
|
||
<li><code><a title="audiocraft.models.genmodel.BaseGenModel.audio_channels" href="genmodel.html#audiocraft.models.genmodel.BaseGenModel.audio_channels">audio_channels</a></code></li>
|
||
<li><code><a title="audiocraft.models.genmodel.BaseGenModel.frame_rate" href="genmodel.html#audiocraft.models.genmodel.BaseGenModel.frame_rate">frame_rate</a></code></li>
|
||
<li><code><a title="audiocraft.models.genmodel.BaseGenModel.generate" href="genmodel.html#audiocraft.models.genmodel.BaseGenModel.generate">generate</a></code></li>
|
||
<li><code><a title="audiocraft.models.genmodel.BaseGenModel.generate_audio" href="genmodel.html#audiocraft.models.genmodel.BaseGenModel.generate_audio">generate_audio</a></code></li>
|
||
<li><code><a title="audiocraft.models.genmodel.BaseGenModel.generate_continuation" href="genmodel.html#audiocraft.models.genmodel.BaseGenModel.generate_continuation">generate_continuation</a></code></li>
|
||
<li><code><a title="audiocraft.models.genmodel.BaseGenModel.generate_unconditional" href="genmodel.html#audiocraft.models.genmodel.BaseGenModel.generate_unconditional">generate_unconditional</a></code></li>
|
||
<li><code><a title="audiocraft.models.genmodel.BaseGenModel.sample_rate" href="genmodel.html#audiocraft.models.genmodel.BaseGenModel.sample_rate">sample_rate</a></code></li>
|
||
<li><code><a title="audiocraft.models.genmodel.BaseGenModel.set_custom_progress_callback" href="genmodel.html#audiocraft.models.genmodel.BaseGenModel.set_custom_progress_callback">set_custom_progress_callback</a></code></li>
|
||
</ul>
|
||
</li>
|
||
</ul>
|
||
</dd>
|
||
</dl>
|
||
</section>
|
||
</article>
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<li><h3>Super-module</h3>
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<li><code><a title="audiocraft.models" href="index.html">audiocraft.models</a></code></li>
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<li><h3><a href="#header-classes">Classes</a></h3>
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<h4><code><a title="audiocraft.models.audiogen.AudioGen" href="#audiocraft.models.audiogen.AudioGen">AudioGen</a></code></h4>
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<li><code><a title="audiocraft.models.audiogen.AudioGen.get_pretrained" href="#audiocraft.models.audiogen.AudioGen.get_pretrained">get_pretrained</a></code></li>
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<li><code><a title="audiocraft.models.audiogen.AudioGen.set_generation_params" href="#audiocraft.models.audiogen.AudioGen.set_generation_params">set_generation_params</a></code></li>
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