cudnn

问题 I can't import tensorflow in pycharm, it raises the following error: ImportError: Could not find 'cudart64_90.dll'. TensorFlow requires that this DLL be installed in a directory that is named in your %PATH% environment variable. Download and install CUDA 9.0 from this URL: https://developer.nvidia.com/cuda-toolkit I checked this cudart file and its added in %PATH% It is working on CLI and python shell perfectly. I have CUDA v9.0 cuDNN v7.0.5 tensorflow-gpu v1.9 echo %PATH% C:\Program Files

问题 I've developed a NN Model with Keras, based on the LSTM Layer. In order to increase speed on Paperspace (a GPU Cloud processing infrastructure), I've switched the LSTM Layer with the new CuDNNLSTM Layer. However this is usable only on machines with GPU cuDNN support. PS: CuDNNLSTM is available only on Keras master , not in the latest release. So I've generated the weights and saved them to hdf5 format on the Cloud, and I'd like to use them locally on my MacBook. Since CuDNNLSTM layer is not

问题 When I import tensorflow in Liclipse I get the following error: Traceback (most recent call last): File "/home/user/Documents/workspace/project", line 13, in <module> import tensorflow as tf File "/usr/local/lib/python2.7/dist-packages/tensorflow/__init__.py", line 23, in <module> from tensorflow.python import * File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/__init__.py", line 45, in <module> from tensorflow.python import pywrap_tensorflow File "/usr/local/lib/python2.7/dist

问题 Please help! Using conda install tensorflow-gpu , it help me to install cuda and cudnn automatically, which is really convienience. However, the problem is that conda can only install the 7.3.1 cudnn, which is not enough for me to run the CNN in tensorflow1.13.0. Actually, I can install the newest cudnn outside easily, but it won't influence the conda environment. So how can I solve it? Thanks in advance 回答1: Try building a new conda env after you install cuda and cudnn (mind to find the

问题 Traceback (most recent call last): File "/home/alex/anaconda3/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1322, in _do_call return fn(*args) File "/home/alex/anaconda3/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1307, in _run_fn options, feed_dict, fetch_list, target_list, run_metadata) File "/home/alex/anaconda3/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1409, in

问题 I am encountering the following error: Traceback (most recent call last): File "C:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\platform\self_check.py", line 87, in preload_check ctypes.WinDLL(build_info.cudnn_dll_name) File "C:\Anaconda\envs\tensorflow\lib\ctypes\__init__.py", line 348, in __init__ self._handle = _dlopen(self._name, mode) OSError: [WinError 126] The specified module could not be found During handling of the above exception, another exception occurred:

问题 So, I've installed Bazel via Chocolatey, installed Python 3.5 and 2.7, installed CUDA v8, and cuDNN v6, and installed JDK 8.0, I'm now trying to custom-build TensorFlow on my Windows 10 device, with AVX, AVX 2 and CUDA. TensorFlow-GPU, the pre-built version, does work, I've already tested and run that successfully. I've followed the instructions of other articles, both on TensorFlows' actual site (trying to adapt some sections from the Linux/Mac installs), and on here. The furthest I've made

问题 I was trying to use TensorFlow with GPU and got the following error: I tensorflow/core/common_runtime/gpu/gpu_device.cc:838] Creating TensorFlow device (/gpu:0) -> (device: 0, name: Tesla K20m, pci bus id: 0000:02:00.0) E tensorflow/stream_executor/cuda/cuda_dnn.cc:347] Loaded runtime CuDNN library: 5005 (compatibility version 5000) but source was compiled with 5103 (compatibility version 5100). If using a binary install, upgrade your CuDNN library to match. If building from sources, make

问题 new to this may be something dumb but cant get conv2d to run windows 10 anaconda 4.2.13 python 3.5.2 C:\windows\system32>nvcc --version nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2016 NVIDIA Corporation Built on Sat_Sep__3_19:05:48_CDT_2016 Cuda compilation tools, release 8.0, V8.0.44 cudnn 5.1 TensorFlow 0.12 import numpy as np import tensorflow as tf graph1 = tf.Graph() with graph1.as_default(): f=tf.constant( np.ones(10).reshape(1,1,-1,1) ) g=tf.constant( np.ones(3).reshape(1