Spaces:
Running
Running
import jax | |
import flax.linen as nn | |
from transformers.models.bart.modeling_flax_bart import ( | |
FlaxBartModule, | |
FlaxBartForConditionalGenerationModule, | |
FlaxBartForConditionalGeneration, | |
FlaxBartEncoder, | |
FlaxBartDecoder, | |
) | |
from transformers import BartConfig | |
class CustomFlaxBartModule(FlaxBartModule): | |
def setup(self): | |
# we keep shared to easily load pre-trained weights | |
self.shared = nn.Embed( | |
self.config.vocab_size, | |
self.config.d_model, | |
embedding_init=jax.nn.initializers.normal(self.config.init_std), | |
) | |
# a separate embedding is used for the decoder | |
self.decoder_embed = nn.Embed( | |
self.config.image_vocab_size + 1, | |
self.config.d_model, | |
embedding_init=jax.nn.initializers.normal(self.config.init_std), | |
) | |
self.encoder = FlaxBartEncoder( | |
self.config, dtype=self.dtype, embed_tokens=self.shared | |
) | |
# the decoder has a different config | |
# TODO: should not be needed once we have custom config/module | |
decoder_config = BartConfig(self.config.to_dict()) | |
decoder_config.max_position_embeddings = ( | |
self.config.image_length + 1 # image tokens + BOS | |
) | |
decoder_config.vocab_size = self.config.image_vocab_size + 1 | |
self.decoder = FlaxBartDecoder( | |
decoder_config, dtype=self.dtype, embed_tokens=self.decoder_embed | |
) | |
class CustomFlaxBartForConditionalGenerationModule( | |
FlaxBartForConditionalGenerationModule | |
): | |
def setup(self): | |
self.model = CustomFlaxBartModule(config=self.config, dtype=self.dtype) | |
self.lm_head = nn.Dense( | |
self.config.image_vocab_size + 1, # encoded image token space + 1 for bos | |
use_bias=False, | |
kernel_init=jax.nn.initializers.normal(self.config.init_std), | |
) | |
self.final_logits_bias = self.param( | |
"final_logits_bias", self.bias_init, (1, self.config.image_vocab_size + 1) | |
) | |
class CustomFlaxBartForConditionalGeneration(FlaxBartForConditionalGeneration): | |
module_class = CustomFlaxBartForConditionalGenerationModule | |