s478839/ium_478839
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Zaktualizuj 'ml_pytroch_sacred.py'

Browse Source
This commit is contained in:
Sebastian Wałęsa 2022-05-08 20:38:37 +02:00
parent 7445be7014
commit 023b0756a0
1 changed files with 9 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

14
ml_pytroch_sacred.py
View File

@ -100,12 +100,6 @@ def fit(epochs, lr, model, train_loader, val_loader, opt_func=torch.optim.SGD):
history.append(result) history.append(result)
return history return history
input_size = len(input_cols)
output_size = len(output_cols)
model=Model_xPosition()
lr = 1e-5
learning_proccess = fit(epochs, lr, model, train_loader, val_loader)
def predict_single(input, target, model): def predict_single(input, target, model):
inputs = input.unsqueeze(0) inputs = input.unsqueeze(0)
predictions = model(inputs) predictions = model(inputs)
@ -113,8 +107,16 @@ def predict_single(input, target, model):
return "Target: "+str(target)+" Predicted: "+str(prediction)+"\n" return "Target: "+str(target)+" Predicted: "+str(prediction)+"\n"
input_size = len(input_cols)
output_size = len(output_cols)
model=Model_xPosition()
lr = 1e-5
@ex.automain @ex.automain
def my_main(epochs): def my_main(epochs):
learning_proccess = fit(epochs, lr, model, train_loader, val_loader)
for i in random.sample(range(0, len(val_ds)), 10): for i in random.sample(range(0, len(val_ds)), 10):
input_, target = val_ds[i] input_, target = val_ds[i]
print(predict_single(input_, target, model),end="") print(predict_single(input_, target, model),end="")