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mirror of https://github.com/osmarks/nanogpt-experiments.git synced 2024-11-10 20:09:58 +00:00

fix bug with loading GPT-2 parameters, assert gets incorrectly tripped due to .bias missing since it is now optionally present depending on flash or not

This commit is contained in:
Andrej Karpathy 2023-02-01 02:05:34 +00:00
parent 038ce89438
commit d995c22128

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@ -229,18 +229,22 @@ class GPT(nn.Module):
config = GPTConfig(block_size=1024, bias=True, **config_args) # note: force bias=True, as in gpt2 models
model = GPT(config)
sd = model.state_dict()
sd_keys = sd.keys()
sd_keys = [k for k in sd_keys if not k.endswith('.attn.bias')] # discard this mask / buffer, not a param
# init a huggingface/transformers model
model_hf = GPT2LMHeadModel.from_pretrained(model_type)
sd_hf = model_hf.state_dict()
# copy while ensuring all of the parameters are aligned and match in names and shapes
keys = [k for k in sd_hf if not k.endswith('attn.masked_bias')] # ignore these
sd_keys_hf = sd_hf.keys()
sd_keys_hf = [k for k in sd_keys_hf if not k.endswith('.attn.masked_bias')] # ignore these, just a buffer
sd_keys_hf = [k for k in sd_keys_hf if not k.endswith('.attn.bias')] # same, just the mask (buffer)
transposed = ['attn.c_attn.weight', 'attn.c_proj.weight', 'mlp.c_fc.weight', 'mlp.c_proj.weight']
# basically the openai checkpoints use a "Conv1D" module, but we only want to use a vanilla Linear
# this means that we have to transpose these weights when we import them
assert len(keys) == len(sd)
for k in keys:
assert len(sd_keys_hf) == len(sd_keys), f"mismatched keys: {len(sd_keys_hf)} != {len(sd_keys)}"
for k in sd_keys_hf:
if any(k.endswith(w) for w in transposed):
# special treatment for the Conv1D weights we need to transpose
assert sd_hf[k].shape[::-1] == sd[k].shape