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開始行:
[[ノート>ノート/ノート]]
*TensorflowCaffeのTutorialを試してみる (2016-03-28〜 ) [#m8f810c5]
[[Download and Setup:https://www.tensorflow.org/versions/r0.7/get_started/os_setup.html#test-the-tensorflow-installation]]
**インストール [#b7282b02]
Pip installで済ませる。CUDAやcuDNNはインストール済み
cuDNNのインストールは、まず登録してlinux用のtgzファイルをダウンロード。/usr/local/cuda/の下へ追加する形でdynamic libraryファイルやinclude headerファイルを置いただけ。
Run a TensorFlow demo modelを試してみる
$ python -c 'import os; import inspect; import tensorflow; print(os.path.dirname(inspect.getfile(tensorflow)))'
MNISTデータを試してみる。（convolutionらしい）
python /usr/local/anaconda/lib/python2.7/site-pack
ages/tensorflow/models/image/mnist/convolutional.py
結果は、
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcublas.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcudnn.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcufft.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcurand.so locally
Successfully downloaded train-images-idx3-ubyte.gz 9912422 bytes.
Successfully downloaded train-labels-idx1-ubyte.gz 28881 bytes.
Successfully downloaded t10k-images-idx3-ubyte.gz 1648877 bytes.
Successfully downloaded t10k-labels-idx1-ubyte.gz 4542 bytes.
Extracting data/train-images-idx3-ubyte.gz
Extracting data/train-labels-idx1-ubyte.gz
Extracting data/t10k-images-idx3-ubyte.gz
Extracting data/t10k-labels-idx1-ubyte.gz
I tensorflow/core/common_runtime/gpu/gpu_init.cc:102] Found device 0 with properties:
name: GeForce GTX TITAN X
major: 5 minor: 2 memoryClockRate (GHz) 1.076
pciBusID 0000:03:00.0
Total memory: 12.00GiB
Free memory: 11.74GiB
I tensorflow/core/common_runtime/gpu/gpu_init.cc:126] DMA: 0
I tensorflow/core/common_runtime/gpu/gpu_init.cc:136] 0: Y
I tensorflow/core/common_runtime/gpu/gpu_device.cc:717] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX TITAN X, pci bus id: 0000:03:00.0)
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 1.0KiB
（中略）
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 16.00GiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:73] Allocating 11.16GiB bytes.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:83] GPU 0 memory begins at 0x2306c80000 extends to 0x25d0c7eb34
Initialized!
Step 0 (epoch 0.00), 16.2 ms
Minibatch loss: 12.054, learning rate: 0.010000
Minibatch error: 90.6%
Validation error: 84.6%
Step 100 (epoch 0.12), 13.9 ms
Minibatch loss: 3.283, learning rate: 0.010000
Minibatch error: 6.2%
Validation error: 7.0%
（中略）
Step 8400 (epoch 9.77), 13.4 ms
Minibatch loss: 1.595, learning rate: 0.006302
Minibatch error: 0.0%
Validation error: 0.7%
Step 8500 (epoch 9.89), 13.3 ms
Minibatch loss: 1.605, learning rate: 0.006302
Minibatch error: 0.0%
Validation error: 1.0%
Test error: 0.8%
終了行:
[[ノート>ノート/ノート]]
*TensorflowCaffeのTutorialを試してみる (2016-03-28〜 ) [#m8f810c5]
[[Download and Setup:https://www.tensorflow.org/versions/r0.7/get_started/os_setup.html#test-the-tensorflow-installation]]
**インストール [#b7282b02]
Pip installで済ませる。CUDAやcuDNNはインストール済み
cuDNNのインストールは、まず登録してlinux用のtgzファイルをダウンロード。/usr/local/cuda/の下へ追加する形でdynamic libraryファイルやinclude headerファイルを置いただけ。
Run a TensorFlow demo modelを試してみる
$ python -c 'import os; import inspect; import tensorflow; print(os.path.dirname(inspect.getfile(tensorflow)))'
MNISTデータを試してみる。（convolutionらしい）
python /usr/local/anaconda/lib/python2.7/site-pack
ages/tensorflow/models/image/mnist/convolutional.py
結果は、
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcublas.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcudnn.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcufft.so locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcurand.so locally
Successfully downloaded train-images-idx3-ubyte.gz 9912422 bytes.
Successfully downloaded train-labels-idx1-ubyte.gz 28881 bytes.
Successfully downloaded t10k-images-idx3-ubyte.gz 1648877 bytes.
Successfully downloaded t10k-labels-idx1-ubyte.gz 4542 bytes.
Extracting data/train-images-idx3-ubyte.gz
Extracting data/train-labels-idx1-ubyte.gz
Extracting data/t10k-images-idx3-ubyte.gz
Extracting data/t10k-labels-idx1-ubyte.gz
I tensorflow/core/common_runtime/gpu/gpu_init.cc:102] Found device 0 with properties:
name: GeForce GTX TITAN X
major: 5 minor: 2 memoryClockRate (GHz) 1.076
pciBusID 0000:03:00.0
Total memory: 12.00GiB
Free memory: 11.74GiB
I tensorflow/core/common_runtime/gpu/gpu_init.cc:126] DMA: 0
I tensorflow/core/common_runtime/gpu/gpu_init.cc:136] 0: Y
I tensorflow/core/common_runtime/gpu/gpu_device.cc:717] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX TITAN X, pci bus id: 0000:03:00.0)
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 1.0KiB
（中略）
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:51] Creating bin of max chunk size 16.00GiB
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:73] Allocating 11.16GiB bytes.
I tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:83] GPU 0 memory begins at 0x2306c80000 extends to 0x25d0c7eb34
Initialized!
Step 0 (epoch 0.00), 16.2 ms
Minibatch loss: 12.054, learning rate: 0.010000
Minibatch error: 90.6%
Validation error: 84.6%
Step 100 (epoch 0.12), 13.9 ms
Minibatch loss: 3.283, learning rate: 0.010000
Minibatch error: 6.2%
Validation error: 7.0%
（中略）
Step 8400 (epoch 9.77), 13.4 ms
Minibatch loss: 1.595, learning rate: 0.006302
Minibatch error: 0.0%
Validation error: 0.7%
Step 8500 (epoch 9.89), 13.3 ms
Minibatch loss: 1.605, learning rate: 0.006302
Minibatch error: 0.0%
Validation error: 1.0%
Test error: 0.8%
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