Défi : Préparer le Jeu de Données Iris
Tâche
Swipe to start coding
- Créez un
TensorDataset. - Enveloppez le
TensorDatasetdans unDataLoaderavec une taille de lot de32et un mélange activé.
Solution
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import torch
from torch.utils.data import TensorDataset, DataLoader
import pandas as pd
torch.manual_seed(42)
iris_df = pd.read_csv('https://content-media-cdn.codefinity.com/courses/1dd2b0f6-6ec0-40e6-a570-ed0ac2209666/section_2/iris.csv')
features = iris_df.drop(columns='species').values
target = iris_df['species'].values
# Convert features and target into PyTorch tensors
features_tensor = torch.tensor(features, dtype=torch.float32)
target_tensor = torch.tensor(target, dtype=torch.long)
# Create a TensorDataset
iris_dataset = TensorDataset(features_tensor, target_tensor)
# Wrap the dataset in a DataLoader
iris_loader = DataLoader(iris_dataset, batch_size=32, shuffle=True)
# Display the DataLoader in action
for batch_idx, (batch_features, batch_targets) in enumerate(iris_loader):
print(f"Batch {batch_idx + 1}:")
print("Features:\n", batch_features)
print("Targets:\n", batch_targets)
break # Display only the first batch
Tout était clair ?
Merci pour vos commentaires !
Section 2. Chapitre 6
single
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import torch
from torch.utils.data import TensorDataset, DataLoader
import pandas as pd
torch.manual_seed(42)
iris_df = pd.read_csv('https://content-media-cdn.codefinity.com/courses/1dd2b0f6-6ec0-40e6-a570-ed0ac2209666/section_2/iris.csv')
features = iris_df.drop(columns='species').values
target = iris_df['species'].values
# Convert features and target into PyTorch tensors
features_tensor = torch.tensor(features, dtype=torch.float32)
target_tensor = torch.tensor(target, dtype=torch.long)
# Create a TensorDataset
iris_dataset = ___
# Wrap the dataset in a DataLoader
iris_loader = ___
# Display the DataLoader in action
for batch_idx, (batch_features, batch_targets) in enumerate(iris_loader):
print(f"Batch {batch_idx + 1}:")
print("Features:\n", batch_features)
print("Targets:\n", batch_targets)
break
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