tensorflow | 易学教程

Why does loading tensorflow on Mac lead to “Process finished with exit code 132 (interrupted by signal 4: SIGILL)”?

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问题 I am using a MacBook Pro with M1 processor, macOS version 11.0.1, Python 3.8 in PyCharm, Tensorflow version 2.4.0rc4 (also tried 2.3.0, 2.3.1, 2.4.0rc0). I am trying to run the following code: import tensorflow This causes the error message: Process finished with exit code 132 (interrupted by signal 4: SIGILL) The code runs fine on my Windows and Linux machines. What does the error message mean and how can I fix it? 回答1: Seems that this problem happens when you have multiple python

Illegal hardware instruction when trying to import tensorflow

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问题 I just installed tensorflow using the instructions for the virtualenv method. The installation process went smoothly, so I don't think there was any problem there. After installation I proceeded to try and import it to validate that everything is ok, and I got the following message: [1] 4492 illegal hardware instruction (core dumped) python This happened after I use the following command using th python interactive console: import tensorflow as tf I tried using the link with pip to reinstall

Illegal hardware instruction when trying to import tensorflow

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Illegal hardware instruction when trying to import tensorflow

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机器学习&深度学习&人工智能资料

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一、机器学习书籍吴恩达深度学习课程：神经网络和深度学习链接： https://pan.baidu.com/s/1H1_fB924YcWkIKZI9rP6Cg 提取码：mjej 机器学习_周志华：链接： https://pan.baidu.com/s/1j55DqrkCNEzLfdWoIOjwDQ 提取码：m0es 机器学习训练秘籍（完整中文版）链接： https://pan.baidu.com/s/1mcseYd3JvQ7jizXJGmyQsQ 提取码：dfmo Python机器学习经典实例：链接： https://pan.baidu.com/s/1hHKP4iw_MXHe_aij8lmxdw 提取码：p8dq 《深度学习之TensorFlow：入门、原理与进阶实战》链接： https://pan.baidu.com/s/1frVnbD5lilYqWHeWaBkV4g 提取码：c3bs tnesorflow书籍中的代码：链接： https://pan.baidu.com/s/1o-xMzQoH-Qfci-lZZR2J_w 提取码：drlp 机器学习实践中文版链接： https://pan.baidu.com/s/12FYjosFEYH1JUK9cJsSHXQ 提取码：v91n Machine Learning in Action (机器学习实战-中文版) 链接：

Faulty TensorFlow C install on MacOS?: dyld errors “Library not loaded: @rpath/libtensorflow.1.dylib” and “Symbol not found: __cg_DGifCloseFile”

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问题 Question How should I install the TensorFlow C library on MacOS or otherwise address the errors: dyld: Library not loaded: @rpath/libtensorflow.1.dylib Referenced from: /Users/Me/./hello_tf Reason: image not found Abort trap: 6 and dyld: Symbol not found: __cg_DGifCloseFile Referenced from: /System/Library/Frameworks/ImageIO.framework/Versions/A/ImageIO Expected in: /usr/local/lib/libGIF.dylib in /System/Library/Frameworks/ImageIO.framework/Versions/A/ImageIO Abort trap: 6 Context I followed

How to create a variable that persists over tf.estimator.train_and_evaluate evaluation steps?

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问题 TLDR: How to create a variable that holds the confusion matrix used for computing custom metrics, accumulating the values across all of the evaluation steps? I have implemented custom metrics to use in the tf.estimator.train_and_evaluation pipeline, with a confusion matrix as the crux for them all. My goal is to make this confusion matrix persist over multiple evaluation steps in order to track the learning progress. Using get_variable in the variable scope did not work, since it does not

How does the Tensorflow's TripletSemiHardLoss and TripletHardLoss and how to use with Siamese Network?

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问题 As much as I know that Triplet Loss is a Loss Function which decrease the distance between anchor and positive but decrease between anchor and negative. Also, there is a margin added to it. So for EXAMPLE LEt us Suppose: a Siamese Network , which gives embeddings: anchor_output = [1,2,3,4,5...] # embedding given by the CNN model positive_output = [1,2,3,4,4...] negative_output= [53,43,33,23,13...] And I think I can get the triplet loss such as: (I think I have to make it as loss using Lambda

ValueError: Error when checking input: expected embedding_1_input to have shape (32,) but got array with shape (1,)

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问题 model.fit throws an error ValueError: Error when checking input: expected embedding_1_input to have shape (32,) but got array with shape (1,) , but there are no arrays of shape (1,) passed to model.fit . def create_model(vocabulary_size, input_word_count, embedding_dims=50): model = Sequential() model.add(Embedding(vocabulary_size, embedding_dims, input_length=input_word_count)) model.add(GlobalAveragePooling1D()) model.add(Dense(1, activation="sigmoid")) model.compile(loss="binary

TensorFlow: Is there a way to locate the filenames of images encoded into TFRecord files?

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问题 I am wondering if the filename information of the image encoded could be encoded into a TFRecord file while creating the tfrecord files, and if so, how could this information be decoded back? When decoded, is the filename a Tensor object? 回答1: Just like fabrizioM said, you have to store the sources in the tfrecords file if you want to use them. Here is an example: #!/usr/bin/env python """Example for reading and writing tfrecords.""" import tensorflow as tf from PIL import Image import numpy