From 8157f9fb3e13683b63b016b0cf9f54efabc6df54 Mon Sep 17 00:00:00 2001
From: Yandi <yandirzm@gmail.com>
Date: Sun, 22 Jan 2023 12:50:16 +0100
Subject: [PATCH] [Second][FFN] Simple
---
main.py | 18 ++++++++++++++----
1 file changed, 14 insertions(+), 4 deletions(-)
diff --git a/main.py b/main.py
index 9e9d6c2..1d844c5 100644
--- a/main.py
+++ b/main.py
@@ -9,6 +9,7 @@ import torch
import logging
import torch.optim
import torch.nn as nn
+import create_submission
def optimizer(cfg, model):
result = {"Adam" : torch.optim.Adam(model.parameters())}
@@ -36,7 +37,9 @@ if __name__ == "__main__":
use_cuda,
valid_ratio,
overwrite_index=True,
- max_num_samples=max_num_samples
+ max_num_samples=max_num_samples,
+ train_transform=dataloader.transform_remove_space_time(),
+ valid_transform=dataloader.transform_remove_space_time()
)
if use_cuda :
@@ -47,8 +50,13 @@ if __name__ == "__main__":
#model = model.build_model(cfg, 18)
model = nn.Sequential(
- nn.Linear(18,1,False),
- nn.ReLU()
+ nn.Linear(14,8,False),
+ nn.ReLU(),
+ nn.Linear(8, 8, True),
+ nn.ReLU(),
+ nn.Linear(8,35,True),
+ nn.ReLU(),
+ nn.Linear(35,1, True)
)
model = model.to(device)
@@ -62,14 +70,16 @@ if __name__ == "__main__":
for t in range(cfg["Training"]["Epochs"]):
+ torch.autograd.set_detect_anomaly(True)
print("Epoch {}".format(t))
train(model, train_loader, f_loss, optimizer, device)
- print(list(model.parameters())[0].grad)
+ #print(list(model.parameters())[0].grad)
val_loss = test.test(model, valid_loader, f_loss, device)
print(" Validation : Loss : {:.4f}".format(val_loss))
+ create_submission.create_submission(model)
"""
logdir = generate_unique_logpath(top_logdir, "linear")
print("Logging to {}".format(logdir))
--
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