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Tag: tensorflow

How to calculate factorial in tensorflow?

I am new to tensorflow, I am trying to find a function that calculates the n!. I saw that one can use the gamma function, which was possible with theano, but did not work for tensorflow. I am using a for loop to multiply number from n to 1, but I assume there is an easier and faster way. I

Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2

I have recently installed tensorflow (Windows CPU version) and received the following message: Successfully installed tensorflow-1.4.0 tensorflow-tensorboard-0.4.0rc2 Then when I tried to run (which I found through https://github.com/tensorflow/tensorflow) I received the following message: 2017-11-02 01:56:21.698935: I C:tf_jenkinshomeworkspacerel-winMwindowsPY36tensorflowcoreplatformcpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2 But when I ran it ran as it

Tensorflow import error: No module named ‘tensorflow’

I installed TensorFlow on my Windows Python 3.5 Anaconda environment The validation was successful (with a warning) Python 3.5.3 |Intel Corporation| (default, Apr 27 2017, 17:03:30) [MSC v.1900 64 bit (AMD64)] on win32 Type “help”, “copyright”, “credits” or “license” for more information. Intel(R) Distribution for Python is brought to you by Intel Corporation. Please check out: https://software.intel.com/en-us/python-distribution 2017-10-04 11:06:13.569696: W

tensorflow – how to add an if statement?

This is a simplified version of what I am trying to do: Yet when trying to run this I get: How to fix this? EDIT: results in a: : Tensor(“cond/Merge:0”, shape=(?, 128), dtype=float32) Answer tensorflow objects can’t be used with regular python objects and functions. That’s how tensorflow is designed. if/else blocks, for, while and other python stuff should be

Mixture usage of CPU and GPU in Keras

I am building a neural network on Keras, including multiple layers of LSTM, Permute and Dense. It seems LSTM is GPU-unfriendly. So I did research and use But based on my understanding about with, with is try…finally block to ensure that clean-up code is executed. I don’t know whether the following CPU/GPU mixture usage code works or not? Will they

Can not use both bias and batch normalization in convolution layers

I use slim framework for tensorflow, because of its simplicity. But I want to have convolutional layer with both biases and batch normalization. In vanilla tensorflow, I have: and I rewrote it to slim by this: But this code does not add bias to conv layer. That is because of https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/layers/python/layers/layers.py#L1025 where is in the construction of layer, which results

Standalone Protocol buffer file in tensorflow and its usage?

I have a .pb file alone created using freeze_graph.py. Other than the standalone .pb file i don’t have any files in the folder. Till now i have figured out a way to visualize the model using tensor board and to fetch the tensors involved in the Net. Also the .pb was a model created using ResNet architecture. 1.How do i

load weights require h5py

Im trying to run a keras model,trying to use pre-trained VGGnet- When i run this Command base_model = applications.VGG16(weights=’imagenet’, include_top=False, input_shape=(img_rows, img_cols, img_channel)) I get this error: I went through some github issues page where a relevant question was asked,but no solutions were given. Any suggestions? Answer Install h5py: Or if using conda:

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