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InternLM
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fix some info

pull/478/head
YWMditto 2023-11-09 16:58:27 +08:00
parent 18bd6429f5
commit 8f8fe84c03
2 changed files with 1 additions and 4 deletions
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2
internlm/apis/inference.py
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@ -407,12 +407,10 @@ def _streaming_no_beam_search_generate(
bos_pos = torch.where(bos_sum.eq(bos_sum[:, -1:]), 0, 1) bos_pos = torch.where(bos_sum.eq(bos_sum[:, -1:]), 0, 1)
to_atten_x = bos_pos[:, :, None] to_atten_x = bos_pos[:, :, None]
to_atten_y = bos_pos[:, None, :] to_atten_y = bos_pos[:, None, :]
# attention_mask = torch.einsum('bno,bom->bnm', to_atten_x, to_atten_y).eq(1)
else: else:
bos_pos = torch.where(token_ids.eq(bos_token_id), 1, 0) bos_pos = torch.where(token_ids.eq(bos_token_id), 1, 0)
to_atten_x = bos_pos[:, :, None] to_atten_x = bos_pos[:, :, None]
to_atten_y = bos_pos[:, None, :] to_atten_y = bos_pos[:, None, :]
# attention_mask = torch.einsum('bno,bom->bnm', to_atten_x, to_atten_y).eq(1)
attention_mask = torch.logical_or(to_atten_x, to_atten_y).eq(1) attention_mask = torch.logical_or(to_atten_x, to_atten_y).eq(1)
inference_params.attention_mask = attention_mask inference_params.attention_mask = attention_mask
scores = decoder(**{"input_ids": token_ids[:, -1:], "inference_params": inference_params}) scores = decoder(**{"input_ids": token_ids[:, -1:], "inference_params": inference_params})

3
tools/load_internlm_model.py
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@ -134,8 +134,7 @@ def initialize_internlm_model(
"""Initialize internlm model. """Initialize internlm model.
Args: Args:
model_type (str): The types of models supported by train_internlm, such as "LLAMA" or "INTERNLM". Note that model_type (str): The types of models supported by train_internlm, such as "INTERNLM".
when loading these models, ``model_type`` can only be "LLAMA".
ckpt_dir (str): Directory where model checkpoints are stored. Its format needs to be like this: ckpt_dir (str): Directory where model checkpoints are stored. Its format needs to be like this:
(a) local path, such as: "local:{your local path}"; (a) local path, such as: "local:{your local path}";
(b) boto3 path, such as: "boto3:s3://{bucket name}.{ip}/{your ceph path}". (b) boto3 path, such as: "boto3:s3://{bucket name}.{ip}/{your ceph path}".