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gguf : style fixes in simple conversion script

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This commit is contained in:
M. Yusuf Sarıgöz 2023-08-17 19:05:43 +03:00
parent 2f8fc92d86
commit 22c61c5b45
1 changed files with 11 additions and 3 deletions
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14
convert-llama-h5-to-gguf.py
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@ -23,6 +23,7 @@ NDArray: 'TypeAlias' = 'np.ndarray[Any, Any]'
def reverse_hf_permute(weights: NDArray, n_head: int, n_kv_head: Optional[int] = None) -> NDArray:
if n_kv_head is not None and n_head != n_kv_head:
n_head //= n_kv_head
return (weights.reshape(n_head, 2, weights.shape[0] // n_head // 2, *weights.shape[1:])
.swapaxes(1, 2)
.reshape(weights.shape))
@ -30,12 +31,14 @@ def reverse_hf_permute(weights: NDArray, n_head: int, n_kv_head: Optional[int] =
def count_model_parts(dir_model: str) -> int:
num_parts = 0
for filename in os.listdir(dir_model):
if filename.startswith("pytorch_model-"):
num_parts += 1
if num_parts > 0:
print("gguf: found " + str(num_parts) + " model parts")
return num_parts
@ -43,6 +46,7 @@ if len(sys.argv) < 3:
print("Usage: convert-h5-to-ggml.py dir-model ftype\n")
print(" ftype == 0 -> float32")
print(" ftype == 1 -> float16")
sys.exit(1)
@ -54,7 +58,8 @@ last_dir = os.path.basename(os.path.normpath(dir_model))
# possible tensor data types
# ftype == 0 -> float32
# ftype == 1 -> float16
#
# map from ftype to string
ftype_str = ["f32", "f16"]
@ -63,6 +68,7 @@ if len(sys.argv) > 2:
ftype = int(sys.argv[2])
if ftype < 0 or ftype > 1:
print("Invalid ftype: " + str(ftype))
sys.exit(1)
fname_out = sys.argv[1] + "/ggml-model-" + ftype_str[ftype] + ".gguf"
@ -74,12 +80,13 @@ with open(dir_model + "/config.json", "r", encoding="utf-8") as f:
if hparams["architectures"][0] != "LlamaForCausalLM":
print("Model architecture not supported: " + hparams["architectures"][0])
sys.exit()
# get number of model parts
num_parts = count_model_parts(dir_model)
gguf_writer = gguf.GGUFWriter(fname_out, architecture="llama")
gguf_writer = gguf.GGUFWriter(fname_out, arch="llama")
print("gguf: get model metadata")
@ -103,12 +110,12 @@ elif "max_position_embeddings" in hparams:
ctx_length = hparams["max_position_embeddings"]
else:
print("gguf: can not find ctx length parameter.")
sys.exit()
gguf_writer.add_architecture()
gguf_writer.add_name(last_dir)
gguf_writer.add_file_type("All tensors F32" if ftype == 0 else "Most tensors F16, some F32")
gguf_writer.add_source_hf_repo(hf_repo)
gguf_writer.add_tensor_data_layout("Meta AI original pth")
gguf_writer.add_context_length(ctx_length)
@ -247,6 +254,7 @@ for part_name in part_names:
name = tensor_map[name[:-5]] + ".bias"
else:
print("Can not map tensor '" + name + "'")
sys.exit()
n_dims = len(data.shape)