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update cross-training #2

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update cross-training #2

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4415f66
update cross-training
lli-rice May 23, 2022
4fc759e
update linter
lli-rice May 25, 2022
4d61c42
fix linter error
lli-rice May 25, 2022
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17 changes: 2 additions & 15 deletions src/algorithms/ETNA.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,8 +8,6 @@
# the global structure of the graph and use cross training function
# to align two embeddings

from collections import defaultdict

import algorithms.helper as helper
import networkx as nx
import numpy as np
Expand Down Expand Up @@ -570,12 +568,6 @@ def cross_training(self, seed=None):
self.emb_trainer2.emb_model.train()
orthologs = list(self.orthologs)

org1_ortholog_dict = defaultdict(int)
org2_ortholog_dict = defaultdict(int)
for i, j in orthologs:
org1_ortholog_dict[i] += 1
org2_ortholog_dict[j] += 1

if seed:
np.random.seed(seed)
np.random.shuffle(orthologs)
Expand All @@ -589,11 +581,6 @@ def cross_training(self, seed=None):
epoch_x = anchor_x[idx]
epoch_y = anchor_y[idx]

org1_weight = torch.from_numpy(
np.array([1 / org1_ortholog_dict[x] for x in epoch_x])).to(self.device)
org2_weight = torch.from_numpy(
np.array([1 / org2_ortholog_dict[x] for x in epoch_y])).to(self.device)

self.optimizer_align.zero_grad()
X1 = self.emb_trainer1.normalized_matrix[epoch_x].to(self.device)
X2 = self.emb_trainer2.normalized_matrix[epoch_y].to(self.device)
Expand All @@ -603,14 +590,14 @@ def cross_training(self, seed=None):

loss1 = F.binary_cross_entropy_with_logits(
recon1, X2, reduction='none')
loss1 = torch.mean(torch.sum(loss1, dim=1) * org1_weight)
loss1 = torch.mean(torch.sum(loss1, dim=1))

emb2 = self.emb_trainer2.emb_model.encoder(X2)
recon2 = self.emb_trainer1.emb_model.decoder(emb2)

loss2 = F.binary_cross_entropy_with_logits(
recon2, X1, reduction='none')
loss2 = torch.mean(torch.sum(loss2, dim=1) * org2_weight)
loss2 = torch.mean(torch.sum(loss2, dim=1))

loss = self.psi * (loss1 + loss2)

Expand Down
44 changes: 17 additions & 27 deletions src/demo.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,7 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -31,7 +31,7 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": 2,
"metadata": {},
"outputs": [
{
Expand Down Expand Up @@ -161,31 +161,14 @@
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<module 'algorithms.ETNA' from '/home/ETNA/src/algorithms/ETNA.py'>"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"importlib.reload(etna)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [""]
"text": [
"/Users/llc/ylab/proj-net-embed/src/algorithms/ETNA.py:101: UserWarning: nn.init.xavier_uniform is now deprecated in favor of nn.init.xavier_uniform_.\n",
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should make sure to scrub all absolute file paths from the repo

" torch.nn.init.xavier_uniform(m.weight)\n"
]
}
],
"source": [
Expand All @@ -198,14 +181,14 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.724578124149233 0.1828194242946759\n"
"0.7216661736014969 0.1817707376284373\n"
]
}
],
Expand All @@ -221,11 +204,18 @@
" test_matrix, np.ones(test_matrix.shape))\n",
"print(auroc, auprc)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
Expand All @@ -239,7 +229,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.2"
"version": "3.7.7"
}
},
"nbformat": 4,
Expand Down