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PyTorchStepByStep - Chapter 5: Convolutions

摘要： single = np.array( [[[[5, 0, 8, 7, 8, 1], [1, 9, 5, 0, 7, 7], [6, 0, 2, 4, 6, 6], [9, 7, 6, 6, 8, 4], [8, 3, 8, 5, 1, 3], [7, 2, 7, 0, 1, 0]]]] ) sing 阅读全文

posted @ 2024-10-17 22:03 ZhangZhihuiAAA 阅读(4) 评论(0) 推荐(0) 编辑

PyTorchStepByStep - Bonus Chapter: Feature Space

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posted @ 2024-10-17 21:03 ZhangZhihuiAAA 阅读(2) 评论(0) 推荐(0) 编辑

PyTorchStepByStep - Chapter 4: Classifying Images

摘要： images, labels = generate_dataset(img_size=5, n_images=300, binary=True, seed=13) And then let’s visualize the first 30 images: image_r = np.zeros((5, 阅读全文

posted @ 2024-10-15 22:38 ZhangZhihuiAAA 阅读(8) 评论(0) 推荐(0) 编辑

Numpy - np.c_

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posted @ 2024-10-15 09:19 ZhangZhihuiAAA 阅读(4) 评论(0) 推荐(0) 编辑

VSCode - Error loading webview: Error: Could not register service workers: InvalidStateError: Failed to register a ServiceWorker: The document is in an invalid state..

摘要： Fixed with restarting VSCode. 阅读全文

posted @ 2024-10-14 12:00 ZhangZhihuiAAA 阅读(22) 评论(0) 推荐(0) 编辑

PyTorchStepByStep - Chapter 3: A Simple Classification Problem

摘要： from sklearn.datasets import make_moons from sklearn.model_selection import train_test_split X, y = make_moons(n_samples=100, noise=.3, random_state=0 阅读全文

posted @ 2024-10-14 09:20 ZhangZhihuiAAA 阅读(2) 评论(0) 推荐(0) 编辑

PyTorchStepByStep - Chapter 2.1: Going Classy

摘要： class StepByStep(): def __init__(self, model, loss_fn, optimizer): self.device = 'cuda' if torch.cuda.is_available() else 'cpu' self.model = model.to( 阅读全文

posted @ 2024-10-13 17:48 ZhangZhihuiAAA 阅读(2) 评论(0) 推荐(0) 编辑

VSCode - TensorBoard Extention

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posted @ 2024-10-13 09:50 ZhangZhihuiAAA 阅读(7) 评论(0) 推荐(0) 编辑

PyTorchStepByStep - Chapter 2: Rethinking the Training Loop

摘要： def make_train_step_fn(model, loss_fn, optimizer): def perform_train_step_fn(x, y): # Set model to TRAIN mode model.train() # Step 1 - Compute model's 阅读全文

posted @ 2024-10-12 21:32 ZhangZhihuiAAA 阅读(16) 评论(0) 推荐(0) 编辑

Jupyter - Magic Function Usage

摘要： %%writefile data_preparation/v0.py device = 'cuda' if torch.cuda.is_available() else 'cpu' # Our data was in Numpy arrays, but we need to transform th 阅读全文

posted @ 2024-10-05 20:17 ZhangZhihuiAAA 阅读(8) 评论(0) 推荐(0) 编辑

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