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Discy Latest Questions

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This is the sample MNIST code I am running: from tensorflow.examples.tutorials.mnist import input_data mnist = input_data.read_data_sets('MNIST_data', one_hot=True) import tensorflow as tf sess = tf.InteractiveSession() x = tf.placeholder(tf.float32, shape=[None, 784]) y_ = tf.placeholder(tf.float32, shape=[None, 10]) W = tf.Variable(tf.zeros([784,10])) b = tf.Variable(tf.zeros([10])) y = tf.nn.softmax(tf.matmul(x,W) + b) def weight_variable(shape): ...

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I am installing tensorflow from source (documentation). Cuda driver version: nvcc: NVIDIA (R) Cuda compiler driver Cuda compilation tools, release 7.5, V7.5.17 When I ran the following command : bazel-bin/tensorflow/cc/tutorials_example_trainer --use_gpu it gave me the following error : I tensorflow/stream_executor/dso_loader.cc:108] successfully opened ...

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I can list gpu devices sing the following tensorflow code: import tensorflow as tf from tensorflow.python.client import device_lib print device_lib.list_local_devices() The result is: [name: "/device:CPU:0" device_type: "CPU" memory_limit: 268435456 locality { } incarnation: 17897160860519880862, name: "/device:XLA_GPU:0" device_type: "XLA_GPU" memory_limit: 17179869184 locality { } ...

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UPDATE: Fixed in Tensorflow 1.14.0 (maybe earlier, didn’t check) UPDATE: Still occurring in Tensorflow 1.7.0 UPDATE: I wrote a collab notebook that reproduces this bug on google’s gpu hardware: https://drive.google.com/file/d/13V87kSTyyFVMM7NoJNk9QTsCYS7FRbyz/view?usp=sharing UPDATE: After wrongly accusing tf.gather in the first ...

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