their latent bottleneck is tanh it seems, constraining it to -1 to 1 for flow matching in dynamics model. please open an issue if mistakened
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@ -291,16 +291,29 @@ class SwiGLUFeedforward(Module):
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class VideoTokenizer(Module):
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class VideoTokenizer(Module):
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def __init__(
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def __init__(
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self
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self,
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dim,
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dim_latent
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):
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):
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super().__init__()
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super().__init__()
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self.encoded_to_latents = Sequential(
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LinearNoBias(dim, dim_latent),
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nn.Tanh(),
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)
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self.latents_to_decoder = LinearNoBias(dim_latent, dim)
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# dynamics model
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class DynamicsModel(Module):
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class DynamicsModel(Module):
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def __init__(
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def __init__(
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self
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self
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):
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):
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super().__init__()
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super().__init__()
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# dreamer
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class Dreamer(Module):
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class Dreamer(Module):
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def __init__(
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def __init__(
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self,
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self,
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