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import os
import sys
import torch
sys.path.append(os.path.join(os.path.dirname(__file__), "..", "src"))
from gliomasam3_moe.models.gliomasam3_moe import GliomaSAM3_MoE
def test_model_shapes():
model = GliomaSAM3_MoE(
patch_size=16,
token_dim=64,
depth=2,
heads=4,
slice_attn_k=4,
spectral_bins=8,
spectral_q=3,
moe_experts=5,
moe_topk=2,
decoder_hidden=32,
prompt_mlp_hidden=64,
)
x = torch.randn(2, 4, 16, 128, 128)
logits, aux = model(x)
assert logits.shape == (2, 3, 16, 128, 128)
assert "pi_et" in aux
assert "moe_gamma" in aux
assert "spectral_stats" in aux
assert "et_prob_gated" in aux
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