From 7addac196916c296d2d46e73dbe6648cea919779 Mon Sep 17 00:00:00 2001
From: Schneider Leo <leo.schneider@etu.ec-lyon.fr>
Date: Tue, 30 Jan 2024 15:26:45 +0100
Subject: [PATCH] intensity model
---
.idea/misc.xml | 2 +-
requirements.txt | 3 ++-
test.py | 38 ++++++++++----------------------------
3 files changed, 13 insertions(+), 30 deletions(-)
diff --git a/.idea/misc.xml b/.idea/misc.xml
index 1b5f6f7..791742a 100644
--- a/.idea/misc.xml
+++ b/.idea/misc.xml
@@ -3,5 +3,5 @@
<component name="Black">
<option name="sdkName" value="Python 3.9 (LC-MS-RT-prediction)" />
</component>
- <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.9 (LC-MS-RT-prediction)" project-jdk-type="Python SDK" />
+ <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.10 (LC-MS-RT-prediction)" project-jdk-type="Python SDK" />
</project>
\ No newline at end of file
diff --git a/requirements.txt b/requirements.txt
index cb93452..60821c4 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -3,4 +3,5 @@ h5py~=3.10.0
pandas~=2.2.0
numpy~=1.26.2
matplotlib~=3.8.2
-wandb~=0.16.2
\ No newline at end of file
+wandb~=0.16.2
+torchmetrics~=1.3.0.post0
\ No newline at end of file
diff --git a/test.py b/test.py
index 59f1279..056bb3c 100644
--- a/test.py
+++ b/test.py
@@ -6,6 +6,7 @@ import torch
from dataloader import load_data, load_split_intensity, Intentsity_Dataset, load_intensity_from_files
from model import RT_pred_model, Intensity_pred_model_multi_head, RT_pred_model_self_attention
from config import load_args
+from loss import masked_cos_sim, masked_pearson_correlation_distance
def train(model, data_train, epoch, optimizer, criterion, cuda=False):
@@ -30,7 +31,7 @@ def train(model, data_train, epoch, optimizer, criterion, cuda=False):
distance / len(data_train))
-def eval(model, data_test, epoch, criterion=nn.MSELoss(reduction='mean'), cuda=False):
+def eval(model, data_test, epoch, criterion=masked_cos_sim, cuda=False):
losses = 0.
distance = 0.
for data, target in data_test:
@@ -57,7 +58,7 @@ def save(model, optimizer, epoch, checkpoint_name):
}, os.path.join('checkpoints', checkpoint_name))
-def run(epochs, eval_inter, save_inter, model, data_train, data_test, optimizer, criterion=nn.MSELoss(reduction='mean'),
+def run(epochs, eval_inter, save_inter, model, data_train, data_test, optimizer, criterion=masked_cos_sim,
cuda=False):
for e in range(1, epochs + 1):
train(model, data_train, e, optimizer, criterion, cuda=cuda)
@@ -68,30 +69,12 @@ def run(epochs, eval_inter, save_inter, model, data_train, data_test, optimizer,
def main(args):
+
os.environ["WANDB_API_KEY"] = 'b4a27ac6b6145e1a5d0ee7f9e2e8c20bd101dccd'
os.environ["WANDB_MODE"] = "offline"
+ os.environ["WANDB_DIR"] = os.path.abspath("./wandb_run")
- config = {
- "model": "RT prediction GRU/selfAtt+ GRU",
- "learning_rate": args.lr,
- "batch_size": args.batch_size,
- }
-
- # wdb.init(project="RT prediction", dir='wandb_run')
-
- print('Cuda : ', torch.cuda.is_available())
- data_train, data_test = load_data(args.batch_size, args.n_train, args.n_test, data_source='database/data.csv')
- print('\nData loaded')
- model = RT_pred_model_self_attention()
- if torch.cuda.is_available():
- model = model.cuda()
- optimizer = optim.Adam(model.parameters(), lr=args.lr)
- print('\nModel initialised')
- run(args.epochs, args.eval_inter, args.save_inter, model, data_train, data_test, optimizer=optimizer, cuda=True)
- # wdb.finish()
-
-
-def main2(args):
+ wdb.init(project="RT prediction", dir='./wandb_run')
print(torch.cuda.is_available())
# sources_train = ('data/intensity/sequence_train.npy',
# 'data/intensity/intensity_train.npy',
@@ -111,9 +94,7 @@ def main2(args):
'data/intensity/collision_energy_header.npy',
'data/intensity/precursor_charge_header.npy')
- data_train, data_test, data_validation = load_split_intensity(sources, (0.5, 0.25, 0.25))
- train = Intentsity_Dataset(data_train)
- test = Intentsity_Dataset(data_test)
+ data_train, data_test, data_validation = load_split_intensity(sources,32, (0.5, 0.25, 0.25))
@@ -123,10 +104,11 @@ def main2(args):
model = model.cuda()
optimizer = optim.Adam(model.parameters(), lr=0.001)
print('\nModel initialised')
- run(args.epochs, args.eval_inter, args.save_inter, model, train, test, optimizer=optimizer, cuda=True)
+ run(args.epochs, args.eval_inter, args.save_inter, model, data_train, data_test, optimizer=optimizer, cuda=True)
+ wdb.finish()
if __name__ == "__main__":
args = load_args()
print(args)
- main2(args)
+ main(args)
--
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