| 797 | """ |
| 798 | |
| 799 | def __init__(self, config: ChatGLMConfig): |
| 800 | super().__init__(config) |
| 801 | |
| 802 | # recording parameters |
| 803 | self.max_sequence_length = config.max_sequence_length |
| 804 | self.hidden_size = config.hidden_size |
| 805 | self.params_dtype = torch.half |
| 806 | self.num_attention_heads = config.num_attention_heads |
| 807 | self.vocab_size = config.vocab_size |
| 808 | self.num_layers = config.num_layers |
| 809 | self.layernorm_epsilon = config.layernorm_epsilon |
| 810 | self.inner_hidden_size = config.inner_hidden_size |
| 811 | self.hidden_size_per_attention_head = self.hidden_size // self.num_attention_heads |
| 812 | self.position_encoding_2d = config.position_encoding_2d |
| 813 | self.model_parallel = True |
| 814 | |
| 815 | self.word_embeddings = skip_init( |
| 816 | torch.nn.Embedding, |
| 817 | num_embeddings=self.vocab_size, embedding_dim=self.hidden_size, |
| 818 | dtype=self.params_dtype |
| 819 | ) |
| 820 | |
| 821 | def get_layer(layer_id): |
| 822 | return GLMBlock( |
| 823 | self.hidden_size, |
| 824 | self.num_attention_heads, |
| 825 | self.layernorm_epsilon, |
| 826 | layer_id, |
| 827 | inner_hidden_size=self.inner_hidden_size, |
| 828 | hidden_size_per_attention_head=self.hidden_size_per_attention_head, |
| 829 | layernorm=LayerNorm, |
| 830 | use_bias=True, |
| 831 | params_dtype=self.params_dtype, |
| 832 | position_encoding_2d=self.position_encoding_2d, |
| 833 | ) |
| 834 | |
| 835 | self.layers = torch.nn.ModuleList( |
| 836 | [get_layer(layer_id) for layer_id in range(self.num_layers)] |
| 837 | ) |
| 838 | |
| 839 | # Final layer norm before output. |
| 840 | self.final_layernorm = LayerNorm(self.hidden_size, eps=self.layernorm_epsilon) |
| 841 | |
| 842 | def get_input_embeddings(self): |
| 843 | return self.word_embeddings |