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emb_size = 64 |
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self.transformer = SimpleTransformer( |
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x_self_size=encoder_input_size, |
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entities_sizes=[4], # hard coded, 4 obs per entity |
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x_self_size=64, |
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entities_sizes=[64], # hard coded, 4 obs per entity |
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# self.self_embedding = LinearEncoder(6, 2, 64) |
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# self.obs_embeding = LinearEncoder(4, 2, 64) |
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self.self_embedding = LinearEncoder(6, 2, 64) |
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self.obs_embeding = LinearEncoder(4, 2, 64) |
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emb_size + encoder_input_size, network_settings.num_layers, self.h_size |
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64 + 64, network_settings.num_layers, self.h_size |
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) |
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if self.use_lstm: |
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inputs = torch.cat(encodes, dim=-1) |
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x_self = processed_vec.reshape(-1, processed_vec.shape[1]) |
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x_self = self.self_embedding(x_self) |
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var_len_input = self.obs_embeding(var_len_input) |
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output = self.transformer(x_self, [var_len_input]) |
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# # TODO : This is a Hack |
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vincentpierre