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Few refactorings #2

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Few refactorings #2

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5855b03
use np.dot
tosemml Aug 18, 2023
c6ad179
use numpy operations
tosemml Aug 18, 2023
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13 changes: 5 additions & 8 deletions model/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -663,9 +663,8 @@ def __init__(self, expert_dims, text_dim, use_ce, verbose, l2renorm, num_classes
self.text_GU = nn.ModuleList(gated_text_embds)
else:
print("V. simple classifier, should update....")
total_dim = 0
for mod in self.expert_dims.keys():
total_dim += self.expert_dims[mod][1] * self.repeat_temporal[mod]
total_dim = np.dot([self.expert_dims[mod][1] for mod in self.expert_dims.keys()],
[self.repeat_temporal[mod] for mod in self.expert_dims.keys()])
print(f"Total dim is {total_dim}")
self.classifier = nn.Linear(total_dim, self.num_classes)

Expand Down Expand Up @@ -767,11 +766,9 @@ def forward(self, text, experts, ind, raw_captions):

if self.use_ce in {"pairwise-star", "pairwise-star-specific",
"pairwise-star-tensor"}:
sum_all = 0
sum_ind = 0
for mod0 in experts.keys():
sum_all += (experts[mod0] * ind[mod0].float().to(dev).unsqueeze(1))
sum_ind += ind[mod0].float().to(dev).unsqueeze(1)
sum_all = np.dot([experts[mod0] for mod0 in experts.keys()],
[ind[mod0].float().to(dev).unsqueeze(1)) for mod0 in experts.keys()])
sum_ind = np.sum([ind[mod0].float().to(dev).unsqueeze(1) for mod0 in experts.keys()] )
avg_modality = sum_all / sum_ind

for ii, l in enumerate(self.video_GU):
Expand Down