deduce share_decoder_embeddings from HF tie_word_embeddings flag (#123)

eole/bin/convert/convert_HF.py

@@ -577,6 +577,8 @@ def run(cls, args):
  quant_layers = []
  params = ["weight", "bias"]
 
+ share_decoder_embeddings = config.get("tie_word_embeddings", False)
+
  add_qkvbias = False
  add_ffnbias = False
  shared_layer_norm = False
@@ -589,7 +591,6 @@ def run(cls, args):
  optional_eos = []
  mapped_tokens = []
  gpt2_pretok = False
- share_decoder_embeddings = False
  generator_bias = False
 
  # ALL THESE IF SHOULD BE HANDLED IN MAPPINGS
@@ -689,6 +690,8 @@ def get_weight(checkpoint, tensor_name):
  "encoder.layer_norm.bias",
  "generator.weight",
  ]
+ if share_decoder_embeddings:
+ targetlist.remove("generator.weight")
  for target in targetlist:
  if target in key_maps[arch].keys():
  source = key_maps[arch][target]
@@ -701,19 +704,10 @@ def get_weight(checkpoint, tensor_name):
  w = get_weight(checkpoint, source)
  if w is not None:
  eole_safetensor[target] = w
- elif target == "generator.weight":
- # lm_head is not in HF safetensors -> share from embeddings matrix
- share_decoder_embeddings = True
 
  if target == "generator.bias":
  generator_bias = True
 
- if torch.equal(
- eole_safetensor.get("generator.weight", None),
- eole_safetensor["tgt_emb.embeddings.weight"],
- ):
- share_decoder_embeddings = True
-
  if wmap_path:
  weightmap = wmap["weight_map"]
  ckpt_list = []