riaz.somc/transformers
1
0
Fork 0
mirror of https://github.com/huggingface/transformers.git synced 2025-08-01 02:31:11 +06:00
Code Issues Actions 3 Packages Projects Releases Wiki Activity

Add inputs_embeds support when generating with GPT-J (#21575)

Browse Source
This commit is contained in:
Dzmitry Pletnikau 2023-02-13 08:11:40 -07:00 committed by GitHub
parent dcb5e01197
commit 93ed89bf40
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 19 additions and 9 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

28
src/transformers/models/gptj/modeling_gptj.py
View File

@ -771,7 +771,7 @@ class GPTJForCausalLM(GPTJPreTrainedModel):
def set_output_embeddings(self, new_embeddings): def set_output_embeddings(self, new_embeddings):
self.lm_head = new_embeddings self.lm_head = new_embeddings
def prepare_inputs_for_generation(self, input_ids, past_key_values=None, **kwargs): def prepare_inputs_for_generation(self, input_ids, past_key_values=None, inputs_embeds=None, **kwargs):
token_type_ids = kwargs.get("token_type_ids", None) token_type_ids = kwargs.get("token_type_ids", None)
# only last token for inputs_ids if past is defined in kwargs # only last token for inputs_ids if past is defined in kwargs
if past_key_values: if past_key_values:
@ -790,14 +790,24 @@ class GPTJForCausalLM(GPTJPreTrainedModel):
position_ids = position_ids[:, -1].unsqueeze(-1) position_ids = position_ids[:, -1].unsqueeze(-1)
else: else:
position_ids = None position_ids = None
return {
"input_ids": input_ids, # if `inputs_embeds` are passed, we only want to use them in the 1st generation step
"past_key_values": past_key_values, if inputs_embeds is not None and past_key_values is None:
"use_cache": kwargs.get("use_cache"), model_inputs = {"inputs_embeds": inputs_embeds}
"position_ids": position_ids, else:
"attention_mask": attention_mask, model_inputs = {"input_ids": input_ids}
"token_type_ids": token_type_ids,
} model_inputs.update(
{
"past_key_values": past_key_values,
"use_cache": kwargs.get("use_cache"),
"position_ids": position_ids,
"attention_mask": attention_mask,
"token_type_ids": token_type_ids,
}
)
return model_inputs
@add_start_docstrings_to_model_forward(GPTJ_INPUTS_DOCSTRING.format("batch_size, sequence_length")) @add_start_docstrings_to_model_forward(GPTJ_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings( @add_code_sample_docstrings(