| |
| |
|
|
| """ CodeT5+ embedding model configuration""" |
| from transformers.configuration_utils import PretrainedConfig |
| from transformers.utils import logging |
|
|
| logger = logging.get_logger(__name__) |
|
|
|
|
| class CodeT5pEmbeddingConfig(PretrainedConfig): |
| model_type = "codet5p_embedding" |
| keys_to_ignore_at_inference = ["past_key_values"] |
| attribute_map = {"hidden_size": "d_model", "num_attention_heads": "num_heads", "num_hidden_layers": "num_layers"} |
|
|
| def __init__( |
| self, |
| vocab_size=32103, |
| d_model=768, |
| embed_dim=256, |
| d_kv=64, |
| d_ff=3072, |
| num_layers=12, |
| num_heads=12, |
| relative_attention_num_buckets=32, |
| relative_attention_max_distance=128, |
| dropout_rate=0.1, |
| layer_norm_epsilon=1e-6, |
| initializer_factor=1.0, |
| feed_forward_proj="relu", |
| is_encoder_decoder=False, |
| use_cache=True, |
| pad_token_id=0, |
| eos_token_id=2, |
| **kwargs |
| ): |
| self.vocab_size = vocab_size |
| self.d_model = d_model |
| self.embed_dim = embed_dim |
| self.d_kv = d_kv |
| self.d_ff = d_ff |
| self.num_layers = num_layers |
| self.num_heads = num_heads |
| self.relative_attention_num_buckets = relative_attention_num_buckets |
| self.relative_attention_max_distance = relative_attention_max_distance |
| self.dropout_rate = dropout_rate |
| self.layer_norm_epsilon = layer_norm_epsilon |
| self.initializer_factor = initializer_factor |
| self.feed_forward_proj = feed_forward_proj |
| self.use_cache = use_cache |
|
|
| act_info = self.feed_forward_proj.split("-") |
| self.dense_act_fn = act_info[-1] |
| self.is_gated_act = act_info[0] == "gated" |
|
|
| if len(act_info) > 1 and act_info[0] != "gated" or len(act_info) > 2: |
| raise ValueError( |
| f"`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer." |
| "Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. " |
| "'gated-gelu' or 'relu'" |
| ) |
|
|
| |
| if feed_forward_proj == "gated-gelu": |
| self.dense_act_fn = "gelu_new" |
|
|
| super().__init__( |
| pad_token_id=pad_token_id, |
| eos_token_id=eos_token_id, |
| is_encoder_decoder=is_encoder_decoder, |
| **kwargs, |
| ) |
|
|
