Adam O. adamoudad
adamoudad
/ python-statements-7.py
Created
October 16, 2022 19:17
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| def myfunc(a: int = 1, b: str = "", c: list = []): | |
| pass |
adamoudad
/ python-statements-6.py
Created
October 16, 2022 19:10
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| def myfunc(a, b, c): | |
| pass | |
| config = { | |
| "a": 1, | |
| "b": 2, | |
| "c": 5 | |
| } | |
| myfunc(**config) |
adamoudad
/ python-statements-5.py
Created
October 16, 2022 19:09
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| def myfunc(a, b, c, d, e, f): | |
| # Do stuff | |
| pass | |
| myfunc(a=1, b="foo", c=42, d=100, f="bar") |
adamoudad
/ python-statements-4.py
Created
October 16, 2022 19:08
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| class EmptyClass: | |
| pass | |
| def some_function(): | |
| pass |
adamoudad
/ python-statements-3.py
Created
October 16, 2022 19:07
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| for i in range(n): | |
| # Do stuff... | |
| if condition_is_met: | |
| break | |
| else: | |
| # This will be executed only if break is never read. |
adamoudad
/ python-statements-2.py
Created
October 16, 2022 19:06
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| for i in range(n): | |
| # Do stuff... | |
| if condition_is_met: | |
| break |
adamoudad
/ python-statements-1.py
Created
October 16, 2022 19:05
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| for i in range(n): | |
| try: | |
| data = next(dataiter) | |
| except ValueError: | |
| continue | |
| # The code here is ignored if ValueError is raised in the "try" block | |
| # Otherwise, run the rest of the loop here ... |
adamoudad
/ imdb_evaluate_epoch_end_pytorch.py
Created
March 20, 2021 21:40
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| epoch_history["loss"].append(sum(batch_history["loss"]) / len(batch_history["loss"])) | |
| epoch_history["accuracy"].append(sum(batch_history["accuracy"]) / len(batch_history["accuracy"])) | |
| model.eval() | |
| print("Validation...") | |
| val_loss, val_accuracy = validate(model, valid_loader) | |
| epoch_history["val_loss"].append(val_loss) | |
| epoch_history["val_accuracy"].append(val_accuracy) | |
| print(f"{epoch_history=}") |
adamoudad
/ imdb_pytorch_training.py
Created
March 20, 2021 21:35
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| from tqdm import tqdm, trange | |
| for i in trange(epochs, unit="epoch", desc="Train"): | |
| model.train() | |
| with tqdm(train_loader, desc="Train") as tbatch: | |
| for i, (samples, targets) in enumerate(tbatch): | |
| model.train() | |
| samples = samples.to(device).long() | |
| targets = targets.to(device) | |
| model.zero_grad() | |
| predictions, _ = model(samples.transpose(0, 1)) |
adamoudad
/ initialize_training_imdb_pytorch.py
Created
March 20, 2021 21:32
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| model = BiLSTM(input_dim, embedding_dim, hidden_dim) | |
| device = torch.device("cuda" if torch.cuda.is_available() else "cpu") | |
| criterion = nn.BCELoss().to(device) | |
| optimizer = torch.optim.Adam(model.parameters()) | |
| model.to(device) | |
| batch_history = { | |
| "loss": [], | |
| "accuracy": [] | |
| } | |
| epoch_history = { |
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