李理 fancyerii
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| import tensorflow as tf | |
| import random as rand | |
| import numpy as np | |
| data=np.reshape(np.random.uniform(0,1, 1000),(1000,1)) | |
| label = 2*data+1 | |
| # Setting configurations | |
| n_nodes_hl1 = 3 # nodes in hidden layer 1 | |
| n_nodes_hl2 = 5 # nodes in hidden layer 2 |
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| package com.easemob.ai.robotapi.test.tensorflow; | |
| import org.tensorflow.SavedModelBundle; | |
| import org.tensorflow.Session; | |
| import org.tensorflow.Tensor; | |
| public class ImportModelTest { | |
| public static void main(String[] args) { | |
| try (SavedModelBundle b = SavedModelBundle.load("/home/mc/data/test-tensorflow/model", "serve")) { |
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| java -Xmx4G -Dorg.bytedeco.javacpp.maxbytes=8G -Dorg.bytedeco.javacpp.maxphysicalbytes=8G -cp target/dl4j-examples-0.9.1-bin.jar org.deeplearning4j.examples.recurrent.video.VideoClassificationExample | |
| o.n.n.Nd4jBlas - Number of threads used for BLAS: 0 | |
| Exception in thread "main" java.lang.OutOfMemoryError: Cannot allocate new FloatPointer(1): totalBytes = 513, physicalBytes = 8G | |
| at org.bytedeco.javacpp.FloatPointer.<init>(FloatPointer.java:76) | |
| at org.bytedeco.javacpp.FloatPointer.<init>(FloatPointer.java:41) | |
| at org.nd4j.linalg.jcublas.blas.JcublasLevel3.sgemm(JcublasLevel3.java:107) | |
| at org.nd4j.linalg.api.blas.impl.BaseLevel3.gemm(BaseLevel3.java:57) | |
| at org.nd4j.linalg.api.ndarray.BaseNDArray.mmuli(BaseNDArray.java:3011) |
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| Machine 2, Ubuntu 14.04, no gpu, 16 core, 32GB RAM(but free memory is about 16GB for dl4j) | |
| java -Xmx2G -Dorg.bytedeco.javacpp.maxbytes=4G -Dorg.bytedeco.javacpp.maxphysicalbytes=4G -cp target/dl4j-examples-0.9.1-bin.jar org.deeplearning4j.examples.recurrent.video.VideoClassificationExample | |
| Starting data generation... | |
| Data generation complete | |
| o.n.l.f.Nd4jBackend - Loaded [CpuBackend] backend | |
| o.n.n.NativeOpsHolder - Number of threads used for NativeOps: 16 | |
| o.n.n.Nd4jBlas - Number of threads used for BLAS: 16 | |
| o.n.l.a.o.e.DefaultOpExecutioner - Backend used: [CPU]; OS: [Linux] | |
| o.n.l.a.o.e.DefaultOpExecutioner - Cores: [16]; Memory: [1.8GB]; |
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| $objdump -tTC bazel-bin/native_client/libctc_decoder_with_kenlm.so | grep UND | |
| 0000000000000000 F *UND* 0000000000000000 tensorflow::OpDef::~OpDef() | |
| 0000000000000000 F *UND* 0000000000000000 std::basic_istream<char, std::char_traits<char> >& std::getline<char, std::char_traits<char>, std::allocator<char> >(std::basic_istream<char, std::char_traits<char> >&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >&, char)@@GLIBCXX_3.4.21 | |
| 0000000000000000 F *UND* 0000000000000000 tensorflow::Status::Status(tensorflow::error::Code, tensorflow::StringPiece) | |
| 0000000000000000 F *UND* 0000000000000000 tensorflow::TensorShapeBase<tensorflow::TensorShape>::dim_size(int) const | |
| 0000000000000000 F *UND* 0000000000000000 std::basic_ifstream<char, std::char_traits<char> >::~basic_ifstream()@@GLIBCXX_3.4 | |
| 0000000000000000 F *UND* 0000000000000000 std::__throw_out_of_range_fmt(char const*, .. |
fancyerii
/ gist:9cfdfe08b46c6126f5362020da95544f
Created
March 16, 2018 09:47
libtensorflow_framework
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| /home/lili/env-deepspeech/lib/python2.7/site-packages/tensorflow/libtensorflow_framework.so： 文件格式 elf64-x86-64 | |
| SYMBOL TABLE: | |
| 0000000000000200 l d .note.gnu.build-id 0000000000000000 .note.gnu.build-id | |
| 0000000000000220 l d .gnu.hash 0000000000000000 .gnu.hash | |
| 0000000000030358 l d .dynsym 0000000000000000 .dynsym | |
| 00000000000c44e0 l d .dynstr 0000000000000000 .dynstr | |
| 000000000028dea0 l d .gnu.version 0000000000000000 .gnu.version | |
| 000000000029a418 l d .gnu.version_r 0000000000000000 .gnu.version_r |
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| import torch | |
| import torch.nn as nn | |
| import numpy as np | |
| from torch.autograd import Variable | |
| class LinearRegression(nn.Module): | |
| def __init__(self, input_size, output_size): | |
| super(LinearRegression, self).__init__() | |
| self.linear = nn.Linear(input_size, output_size) |
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| == cat /etc/issue =============================================== | |
| Linux lili-Precision-7720 4.15.0-30-generic #32~16.04.1-Ubuntu SMP Thu Jul 26 20:25:39 UTC 2018 x86_64 x86_64 x86_64 GNU/Linux | |
| VERSION="16.04.4 LTS (Xenial Xerus)" | |
| VERSION_ID="16.04" | |
| VERSION_CODENAME=xenial | |
| == are we in docker ============================================= | |
| No |
fancyerii
/ boosted_tree.py
Created
December 3, 2019 07:08
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| from __future__ import absolute_import, division, print_function, unicode_literals | |
| import numpy as np | |
| import pandas as pd | |
| from matplotlib import pyplot as plt | |
| # Load dataset. | |
| dftrain = pd.read_csv('https://storage.googleapis.com/tf-datasets/titanic/train.csv') | |
| dfeval = pd.read_csv('https://storage.googleapis.com/tf-datasets/titanic/eval.csv') | |
| y_train = dftrain.pop('survived') |
fancyerii
/ error info
Created
December 3, 2019 07:09
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| /home/lili/env-torch13/bin/python /home/lili/codes/huggface-transformer/test/boosted_trees.py | |
| 2.0.0 | |
| WARNING:tensorflow:Using temporary folder as model directory: /tmp/tmp47on6eju | |
| WARNING:tensorflow:From /home/lili/env-torch13/lib/python3.6/site-packages/tensorflow_core/python/ops/resource_variable_ops.py:1630: calling BaseResourceVariable.__init__ (from tensorflow.python.ops.resource_variable_ops) with constraint is deprecated and will be removed in a future version. | |
| Instructions for updating: | |
| If using Keras pass *_constraint arguments to layers. | |
| WARNING:tensorflow:From /home/lili/env-torch13/lib/python3.6/site-packages/tensorflow_core/python/training/training_util.py:236: Variable.initialized_value (from tensorflow.python.ops.variables) is deprecated and will be removed in a future version. | |
| Instructions for updating: | |
| Use Variable.read_value. Variables in 2.X are initialized automatically both in eager and graph (inside tf.defun) contexts. | |
| 2019-12-03 15:09:35.636006: I tensorflow/stream_executor/platform/defa |