Skip to content

Refactor FalconMamba: replace class-name checks with generic attribute detection #424

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Draft
Copilot wants to merge 2 commits into
base: main
Choose a base branch
from
Draft

Refactor FalconMamba: replace class-name checks with generic attribute detection #424

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
84334b9
Initial plan
Copilot Feb 23, 2026
06d3383
Refactor FalconMamba: replace class name checks with generic hasattr(…
Copilot Feb 23, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
12 changes: 6 additions & 6 deletions onnx_diagnostic/tasks/text_generation.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,7 @@

def reduce_model_config(config: Any) -> Dict[str, Any]:
"""Reduces a model size."""
# FalconMambaConfig: use_mambapy
# Mamba models (e.g. FalconMambaConfig) use use_mambapy instead of num_attention_heads
if hasattr(config, "text_config"):
# The model is probably of mixture of models used only for text.
config = config.text_config
Expand All @@ -25,7 +25,7 @@ def reduce_model_config(config: Any) -> Dict[str, Any]:
"hidden_size",
"vocab_size",
)
if config.__class__.__name__ == "FalconMambaConfig":
if hasattr(config, "use_mambapy"):
check_hasattr(config, "conv_kernel", "state_size", "intermediate_size") # 4 and 8
kwargs = dict(
num_hidden_layers=min(config.num_hidden_layers, nhl()),
Expand Down Expand Up @@ -54,7 +54,7 @@ def reduce_model_config(config: Any) -> Dict[str, Any]:
return kwargs


def _get_input_falcon_mamba(
def _get_input_mamba(
model: torch.nn.Module,
config: Optional[Any],
dummy_max_token_id: int,
Expand Down Expand Up @@ -157,8 +157,8 @@ def get_inputs(
seq_length = "seq_length" # torch.export.Dim("seq_length", min=1, max=4096)
cache_length = "cache_length" # torch.export.Dim("cache_length", min=1, max=4096)

if config is not None and config.__class__.__name__ == "FalconMambaConfig":
res = _get_input_falcon_mamba(
if config is not None and hasattr(config, "use_mambapy"):
res = _get_input_mamba(
model=model,
config=config,
dummy_max_token_id=dummy_max_token_id,
Expand Down Expand Up @@ -343,7 +343,7 @@ def random_input_kwargs(config: Any) -> Tuple[Dict[str, Any], Callable]:
("num_key_value_heads", "num_attention_heads", "use_mambapy"),
"hidden_size",
)
if config.__class__.__name__ == "FalconMambaConfig":
if hasattr(config, "use_mambapy"):
check_hasattr(config, "conv_kernel", "state_size", "intermediate_size") # 4 and 8
kwargs = dict(
batch_size=2,
Expand Down
Loading