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摘要: Tensorflow Load text: This tutorial demonstrates two ways to load and preprocess text. First, you will use Keras utilities and preprocessing layers. T 阅读全文
posted @ 2024-01-06 18:18 abaelhe 阅读(14) 评论(0) 推荐(0)
摘要: Turns positive integers(indexes) into dense vectors of fixed size. e.g. [[4], [20]] -> [[0.25, 0.1], [0.6, -0.2]] This layer can only be used on posit 阅读全文
posted @ 2024-01-06 17:58 abaelhe 阅读(35) 评论(0) 推荐(0)
摘要: tf.keras.layers.Attention( View source on GitHub ) Dot-product attention layer, a.k.a. Luong-style attention. Inherits From: Layer, Module tf.keras.la 阅读全文
posted @ 2024-01-06 15:58 abaelhe 阅读(67) 评论(0) 推荐(0)
摘要: https://www.riverbankcomputing.com/static/Docs/PyQt6/ https://www.qt.io/blog/taking-qt-for-python-to-android https://github.com/shyamnathp/python-for- 阅读全文
posted @ 2024-01-05 19:51 abaelhe 阅读(341) 评论(0) 推荐(0)
摘要: Azure: https://docs.microsoft.com/python/api/overview/azure/cognitive-services https://github.com/Azure/azure-sdk-for-python https://azure.microsoft.c 阅读全文
posted @ 2024-01-04 17:23 abaelhe 阅读(78) 评论(0) 推荐(0)
摘要: Introduction to modules, layers, and models Model: To do machine learning in TensorFlow, you are likely to need to define, save, and restore a model. 阅读全文
posted @ 2024-01-02 19:03 abaelhe 阅读(26) 评论(0) 推荐(0)
摘要: Graphs are data structures that contain: a set of tf.Operation objects, which representing units of computation; and tf.Tensor objects, which represen 阅读全文
posted @ 2024-01-02 18:31 abaelhe 阅读(17) 评论(0) 推荐(0)
摘要: In this guide, you will explore ways to compute gradients with TensorFlow, especially in eager execution. Automatic Differentiation and Gradients Auto 阅读全文
posted @ 2024-01-02 16:02 abaelhe 阅读(53) 评论(0) 推荐(0)
摘要: A11 A12 A21 A22 阅读全文
posted @ 2024-01-02 10:50 abaelhe 阅读(11) 评论(0) 推荐(0)
摘要: tf.config.run_functions_eagerly(True) tf.data.experimental.enable_debug_mode() tf.debugging.set_log_device_placement(True) tf.config.set_soft_device_p 阅读全文
posted @ 2024-01-01 19:30 abaelhe 阅读(11) 评论(0) 推荐(0)
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