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7 changes: 6 additions & 1 deletion tests/module_tree/test_subset.py
Original file line number Diff line number Diff line change
Expand Up @@ -573,7 +573,12 @@ def test_qwen3_5_moe_subset_early_stop_follows_module_tree_execution_order():
num_attention_heads=4,
num_key_value_heads=4,
num_experts=4,
num_experts_per_tok=2,
# Route all experts: with top-k < num_experts the executed expert set
# (and therefore the forward-hook order asserted below) depends on the
# random router weights, which shift with prior RNG consumption in
# other test files. Routing every expert keeps the subset execution
# order fully deterministic.
num_experts_per_tok=4,
vocab_size=128,
pad_token_id=0,
bos_token_id=1,
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12 changes: 12 additions & 0 deletions tests/test_calibration_data_device.py
Original file line number Diff line number Diff line change
Expand Up @@ -241,6 +241,10 @@ def shell_module_materialize(self, target_submodule, device, **kwargs):
def get_base_modules(self, model):
return []

@classmethod
def get_modules_with_direct_meta_tensors(cls, model):
return []

def pre_quantize_generate_hook_start(self):
pass

Expand Down Expand Up @@ -387,6 +391,10 @@ def shell_module_materialize(self, target_submodule, device, **kwargs):
def get_base_modules(self, model):
return []

@classmethod
def get_modules_with_direct_meta_tensors(cls, model):
return []

def pre_quantize_generate_hook_start(self):
pass

Expand Down Expand Up @@ -542,6 +550,10 @@ def shell_module_materialize(self, target_submodule, device, **kwargs):
def get_base_modules(self, model):
return []

@classmethod
def get_modules_with_direct_meta_tensors(cls, model):
return []

def pre_quantize_generate_hook_start(self):
pass

Expand Down