Update to latest working version
This commit is contained in:
Christoph Schranz
parent
676da22290
commit
0256b04f04
@ -27,7 +27,7 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Tue Mar 10 17:55:25 2020 \n",
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"Wed Mar 11 07:16:17 2020 \n",
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"+-----------------------------------------------------------------------------+\n",
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"| NVIDIA-SMI 440.48.02 Driver Version: 440.48.02 CUDA Version: 10.2 |\n",
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"|-------------------------------+----------------------+----------------------+\n",
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@ -35,7 +35,7 @@
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"| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n",
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"|===============================+======================+======================|\n",
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"| 0 GeForce RTX 207... Off | 00000000:01:00.0 Off | N/A |\n",
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"| 0% 41C P8 1W / 215W | 215MiB / 7974MiB | 0% Default |\n",
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"| 0% 42C P8 1W / 215W | 1788MiB / 7974MiB | 0% Default |\n",
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"+-------------------------------+----------------------+----------------------+\n",
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" \n",
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"+-----------------------------------------------------------------------------+\n",
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@ -80,13 +80,16 @@
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"WARNING:tensorflow:From <ipython-input-3-d1bfbb527297>:3: is_gpu_available (from tensorflow.python.framework.test_util) is deprecated and will be removed in a future version.\n",
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"Instructions for updating:\n",
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"Use `tf.config.list_physical_devices('GPU')` instead.\n",
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"True\n"
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]
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},
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@ -98,34 +101,34 @@
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" memory_limit: 268435456\n",
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" locality {\n",
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" }\n",
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" incarnation: 933763008911863935,\n",
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" incarnation: 8034786465358909470,\n",
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" name: \"/device:XLA_CPU:0\"\n",
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" device_type: \"XLA_CPU\"\n",
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" memory_limit: 17179869184\n",
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" locality {\n",
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" }\n",
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" incarnation: 12790964875098705008\n",
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" incarnation: 13772661904993777233\n",
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" physical_device_desc: \"device: XLA_CPU device\",\n",
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" name: \"/device:GPU:0\"\n",
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" device_type: \"GPU\"\n",
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" memory_limit: 6940531098\n",
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" memory_limit: 5480775680\n",
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" locality {\n",
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" bus_id: 1\n",
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" links {\n",
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" }\n",
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" }\n",
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" incarnation: 4940791198162309705\n",
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" incarnation: 8336380964433791501\n",
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" physical_device_desc: \"device: 0, name: GeForce RTX 2070 SUPER, pci bus id: 0000:01:00.0, compute capability: 7.5\",\n",
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" name: \"/device:XLA_GPU:0\"\n",
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" device_type: \"XLA_GPU\"\n",
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" memory_limit: 17179869184\n",
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" locality {\n",
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" }\n",
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" incarnation: 6996862811697216940\n",
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" incarnation: 4817022749254415174\n",
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" physical_device_desc: \"device: XLA_GPU device\"]"
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]
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},
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"execution_count": 7,
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -139,20 +142,20 @@
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"tensor([[0.8519, 0.7682, 0.3258],\n",
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" [0.1957, 0.4073, 0.6085],\n",
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" [0.9164, 0.8401, 0.4548],\n",
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" [0.9011, 0.8838, 0.9559],\n",
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" [0.4692, 0.3993, 0.4313]])"
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"tensor([[0.1091, 0.0178, 0.2500],\n",
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" [0.1409, 0.9612, 0.0325],\n",
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" [0.8944, 0.3869, 0.9657],\n",
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" [0.8131, 0.5454, 0.2587],\n",
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" [0.6570, 0.0147, 0.1361]])"
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]
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},
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"execution_count": 8,
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -183,7 +186,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -192,14 +195,14 @@
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"362 ms ± 86.4 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
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"248 ms ± 174 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
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]
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}
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],
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@ -217,7 +220,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"execution_count": 7,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -226,14 +229,14 @@
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"135 ms ± 3.48 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
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"78.2 ms ± 250 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
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]
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}
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],
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@ -252,36 +255,23 @@
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"execution_count": 9,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"tensor([[0.2812, 0.3255, 0.5715, 0.1665, 0.6951],\n",
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" [0.5562, 0.9592, 0.0911, 0.9672, 0.3311],\n",
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" [0.6711, 0.0422, 0.5091, 0.6653, 0.9234],\n",
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" [0.1029, 0.1447, 0.8385, 0.7580, 0.7998],\n",
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" [0.7787, 0.0114, 0.4865, 0.4171, 0.7066]], device='cuda:0')\n",
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"tensor([[0.2812, 0.3255, 0.5715, 0.1665, 0.6951],\n",
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" [0.5562, 0.9592, 0.0911, 0.9672, 0.3311],\n",
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" [0.6711, 0.0422, 0.5091, 0.6653, 0.9234],\n",
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" [0.1029, 0.1447, 0.8385, 0.7580, 0.7998],\n",
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" [0.7787, 0.0114, 0.4865, 0.4171, 0.7066]], dtype=torch.float64)\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/opt/conda/lib/python3.7/site-packages/torch/cuda/__init__.py:134: UserWarning: \n",
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" Found GPU0 GeForce RTX 2070 SUPER which requires CUDA_VERSION >= 10000 to\n",
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" work properly, but your PyTorch was compiled\n",
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" with CUDA_VERSION 9000. Please install the correct PyTorch binary\n",
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" using instructions from https://pytorch.org\n",
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" \n",
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" warnings.warn(incorrect_binary_warn % (d, name, 10000, CUDA_VERSION))\n"
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"tensor([[0.0962, 0.3125, 0.7327, 0.5982, 0.4624],\n",
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" [0.4655, 0.4890, 0.9603, 0.4339, 0.0524],\n",
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" [0.9294, 0.9639, 0.6312, 0.1752, 0.7721],\n",
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" [0.5533, 0.3656, 0.9329, 0.8796, 0.9513],\n",
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" [0.4949, 0.0972, 0.2892, 0.7570, 0.2847]], device='cuda:0')\n",
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"tensor([[0.0962, 0.3125, 0.7327, 0.5982, 0.4624],\n",
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" [0.4655, 0.4890, 0.9603, 0.4339, 0.0524],\n",
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" [0.9294, 0.9639, 0.6312, 0.1752, 0.7721],\n",
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" [0.5533, 0.3656, 0.9329, 0.8796, 0.9513],\n",
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" [0.4949, 0.0972, 0.2892, 0.7570, 0.2847]], dtype=torch.float64)\n"
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]
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}
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],
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@ -298,14 +288,14 @@
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"12.8 ms ± 564 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
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"11.4 ms ± 60.2 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
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]
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}
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],
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@ -330,7 +320,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"execution_count": 11,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -344,18 +334,18 @@
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"execution_count": 12,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"tensor([[0.6760, 0.8890, 0.7271, 0.4208, 0.1131],\n",
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" [0.4036, 0.8012, 0.3448, 0.4120, 0.2439],\n",
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" [0.6088, 0.4356, 0.9391, 0.1366, 0.4379],\n",
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" [0.4540, 0.5981, 0.3885, 0.2473, 0.5938],\n",
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" [0.2976, 0.8384, 0.6107, 0.6882, 0.9593]], device='cuda:0')\n"
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"tensor([[0.4303, 0.7364, 0.1235, 0.7786, 0.7036],\n",
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" [0.3256, 0.4515, 0.7994, 0.9814, 0.7705],\n",
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" [0.2292, 0.5194, 0.4354, 0.3964, 0.5804],\n",
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" [0.8855, 0.5156, 0.9321, 0.9555, 0.4150],\n",
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" [0.0640, 0.0665, 0.1170, 0.9547, 0.2668]], device='cuda:0')\n"
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]
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}
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],
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@ -367,7 +357,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"execution_count": 13,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -379,18 +369,18 @@
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"execution_count": 14,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"tensor([[ 1.1191e-03, 1.6152e-04, -2.1592e-04, 1.4253e-04, -4.0365e-04],\n",
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" [ 1.6151e-04, 5.5901e-04, 2.6872e-04, -3.1842e-06, 2.8985e-04],\n",
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" [-2.1592e-04, 2.6872e-04, 1.0728e-03, -3.5968e-05, 5.5613e-04],\n",
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" [ 1.4253e-04, -3.1840e-06, -3.5968e-05, 6.5156e-04, -3.1820e-04],\n",
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" [-4.0365e-04, 2.8985e-04, 5.5613e-04, -3.1820e-04, 1.4067e-03]],\n",
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"tensor([[1.0966e-03, 3.5866e-04, 4.0044e-04, 3.2466e-04, 2.3044e-04],\n",
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" [3.5866e-04, 9.7424e-04, 2.8649e-04, 8.2904e-04, 2.0482e-04],\n",
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" [4.0044e-04, 2.8649e-04, 5.4179e-04, 1.2729e-04, 9.4659e-05],\n",
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" [3.2466e-04, 8.2904e-04, 1.2729e-04, 1.3005e-03, 6.6951e-06],\n",
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" [2.3044e-04, 2.0482e-04, 9.4659e-05, 6.6950e-06, 1.3420e-03]],\n",
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" device='cuda:0')\n"
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]
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}
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@ -402,18 +392,18 @@
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"execution_count": 15,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"tensor([[ 1.1191e-03, 1.6152e-04, -2.1592e-04, 1.4253e-04, -4.0365e-04],\n",
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" [ 1.6151e-04, 5.5901e-04, 2.6872e-04, -3.1842e-06, 2.8985e-04],\n",
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" [-2.1592e-04, 2.6872e-04, 1.0728e-03, -3.5968e-05, 5.5613e-04],\n",
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" [ 1.4253e-04, -3.1840e-06, -3.5968e-05, 6.5156e-04, -3.1820e-04],\n",
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" [-4.0365e-04, 2.8985e-04, 5.5613e-04, -3.1820e-04, 1.4067e-03]],\n",
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"tensor([[1.0966e-03, 3.5866e-04, 4.0044e-04, 3.2466e-04, 2.3044e-04],\n",
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" [3.5866e-04, 9.7424e-04, 2.8649e-04, 8.2904e-04, 2.0482e-04],\n",
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" [4.0044e-04, 2.8649e-04, 5.4179e-04, 1.2729e-04, 9.4659e-05],\n",
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" [3.2466e-04, 8.2904e-04, 1.2729e-04, 1.3005e-03, 6.6951e-06],\n",
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" [2.3044e-04, 2.0482e-04, 9.4659e-05, 6.6950e-06, 1.3420e-03]],\n",
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" dtype=torch.float64)\n"
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]
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}
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