| 25 | class OPTDecoderLayer(Module): |
| 26 | |
| 27 | def __init__(self, config: PretrainedConfig, layer_idx: int): |
| 28 | super().__init__() |
| 29 | self.layer_idx = layer_idx |
| 30 | self.config = config |
| 31 | self.do_layer_norm_before = self.config.do_layer_norm_before |
| 32 | |
| 33 | hidden_size = config.hidden_size |
| 34 | dtype = config.dtype |
| 35 | tp_group = config.mapping.tp_group |
| 36 | tp_size = config.mapping.tp_size |
| 37 | |
| 38 | self.input_layernorm = LayerNorm(normalized_shape=hidden_size, |
| 39 | dtype=dtype) |
| 40 | |
| 41 | layers_range = config.mapping.pp_layers(config.num_hidden_layers) |
| 42 | local_layer_idx = layer_idx - layers_range[0] |
| 43 | self.attention = Attention( |
| 44 | local_layer_idx=local_layer_idx, |
| 45 | hidden_size=hidden_size, |
| 46 | num_attention_heads=config.num_attention_heads, |
| 47 | max_position_embeddings=config.max_position_embeddings, |
| 48 | attention_mask_type=AttentionMaskType.causal, |
| 49 | dtype=dtype, |
| 50 | tp_group=tp_group, |
| 51 | tp_size=tp_size, |
| 52 | quant_mode=config.quant_mode) |
| 53 | |
| 54 | mlp_hidden_size = hidden_size * 4 if config.intermediate_size is None else config.intermediate_size |
| 55 | |
| 56 | self.mlp = MLP(hidden_size=hidden_size, |
| 57 | ffn_hidden_size=mlp_hidden_size, |
| 58 | hidden_act=config.hidden_act, |
| 59 | dtype=dtype, |
| 60 | tp_group=tp_group, |
| 61 | tp_size=tp_size, |
| 62 | quant_mode=config.quant_mode) |
| 63 | self.post_layernorm = LayerNorm(normalized_shape=hidden_size, |
| 64 | dtype=dtype) |
| 65 | |
| 66 | def forward(self, |
| 67 | hidden_states: Tensor, |