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removing swish in favor of silu
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@@ -44,10 +44,6 @@ else:
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from .configuration_vla_jepa import VLAJEPAConfig
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from .configuration_vla_jepa import VLAJEPAConfig
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def swish(x: torch.Tensor) -> torch.Tensor:
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return x * torch.sigmoid(x)
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class SinusoidalPositionalEncoding(nn.Module):
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class SinusoidalPositionalEncoding(nn.Module):
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def __init__(self, embedding_dim: int):
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def __init__(self, embedding_dim: int):
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super().__init__()
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super().__init__()
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@@ -78,7 +74,7 @@ class ActionEncoder(nn.Module):
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timesteps = timesteps.unsqueeze(1).expand(-1, seq_len)
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timesteps = timesteps.unsqueeze(1).expand(-1, seq_len)
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action_emb = self.layer1(actions)
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action_emb = self.layer1(actions)
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time_emb = self.pos_encoding(timesteps).to(dtype=action_emb.dtype)
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time_emb = self.pos_encoding(timesteps).to(dtype=action_emb.dtype)
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return self.layer3(swish(self.layer2(torch.cat([action_emb, time_emb], dim=-1))))
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return self.layer3(F.silu(self.layer2(torch.cat([action_emb, time_emb], dim=-1))))
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class TimestepEncoder(nn.Module):
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class TimestepEncoder(nn.Module):
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