From 13d9d2cb5d75a04fad83ea827b7772fa03344c7e Mon Sep 17 00:00:00 2001
From: Schneider Leo <leo.schneider@etu.ec-lyon.fr>
Date: Mon, 21 Oct 2024 09:06:51 +0200
Subject: [PATCH] datasets
---
main_custom.py | 2 --
model_custom.py | 2 ++
2 files changed, 2 insertions(+), 2 deletions(-)
diff --git a/main_custom.py b/main_custom.py
index 8ddbdea..7c7421b 100644
--- a/main_custom.py
+++ b/main_custom.py
@@ -26,7 +26,6 @@ def train(model, data_train, epoch, optimizer, criterion_rt, criterion_intensity
param.requires_grad = True
if forward == 'both':
for seq, charge, rt, intensity in data_train:
- print(seq, charge, rt, intensity )
rt, intensity = rt.float(), intensity.float()
if torch.cuda.is_available():
seq, charge, rt, intensity = seq.cuda(), charge.cuda(), rt.cuda(), intensity.cuda()
@@ -288,7 +287,6 @@ def get_n_params(model):
for s in list(p.size()):
nn = nn * s
- print(n, nn)
pp += nn
return pp
diff --git a/model_custom.py b/model_custom.py
index eddc158..6745da3 100644
--- a/model_custom.py
+++ b/model_custom.py
@@ -102,6 +102,8 @@ class Model_Common_Transformer(nn.Module):
def forward(self, seq, charge):
meta_ohe = torch.nn.functional.one_hot(charge - 1, self.charge_max).float()
seq_emb = torch.nn.functional.one_hot(seq, self.nb_aa).float()
+ print(seq_emb.shape())
+ print(self.nb_aa, self.embedding_dim)
emb = self.pos_embedding(self.emb(seq_emb))
meta_enc = self.meta_enc(meta_ohe)
--
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