tensorflow

Why is Keras LSTM on CPU three times faster than GPU?

由 女生的网名这么多〃 提交于 2021-01-22 06:15:05
问题 I use this notebook from Kaggle to run LSTM neural network. I had started training of neural network and I saw that it is too slow. It is almost three times slower than CPU training. CPU perfomance: 8 min per epoch; GPU perfomance: 26 min per epoch. After this I decided to find answer in this question on Stackoverflow and I applied a CuDNNLSTM (which runs only on GPU) instead of LSTM . Hence, GPU perfomance became only 1 min per epoch and accuracy of model decreased on 3%. Questions: 1) Does

Why is Keras LSTM on CPU three times faster than GPU?

由 血红的双手。 提交于 2021-01-22 06:03:52
问题 I use this notebook from Kaggle to run LSTM neural network. I had started training of neural network and I saw that it is too slow. It is almost three times slower than CPU training. CPU perfomance: 8 min per epoch; GPU perfomance: 26 min per epoch. After this I decided to find answer in this question on Stackoverflow and I applied a CuDNNLSTM (which runs only on GPU) instead of LSTM . Hence, GPU perfomance became only 1 min per epoch and accuracy of model decreased on 3%. Questions: 1) Does

语义分割--(DeepLabv3+)Encoder-Decoder with Atrous Separable Convolution for Semantic

由 拈花ヽ惹草 提交于 2021-01-22 04:42:31
语义分割--(DeepLabv3+)Encoder-Decoder with Atrous Separable Convolution for Semantic .. https://blog.csdn.net/u011974639/article/details/79518175 DeepLabv3+ Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation 原文地址： DeepLabv3+ 注意本文的一作 L i a n g − C h i e h C h e n Liang-Chieh Chen L i a n g − C h i e h C h e n 参与了 DeepLab系列 ，MaskLab和 MobileNet系列 的工作。本文是在DeepLabv3的基础上将多个技术融合到一起，达到新的state-of-the-art。 论文在提出了DeepLabv3+架构。主要以DeepLabv3做encoder架构，decoder采用一个简单却有效的模块。并探索了了改进的Xception和深度分离卷积在模型中的应用，进一步提升模型在语义分割任务上的性能。 Abstract 空间金字塔模块在输入feature上应用多采样率扩张卷积、多接收野卷积或池化，探索多尺度上下文信息。

图像语义分割 —利用Deeplab v3+训练VOC2012数据集

由 孤人 提交于 2021-01-22 02:45:23
向AI转型的程序员都关注了这个号 👇👇👇 机器学习AI算法工程 公众号：datayx 前言： 配置：windows10 + Tensorflow1.6.0 + Python3.6.4（笔记本无GPU） 源码： https://github.com/tensorflow/models/tree/master/research/deeplab 权重下载地址： https://github.com/tensorflow/models/blob/master/research/deeplab/g3doc/model_zoo.md 1. 运行model_test.py 测试安装环境，如果正常，提示： Ran 5 tests in 10.758s 2. 运行build_voc2012_data.py 生成 .tfrecord数据 在VOC2012数据集中，文件夹JPEGImages存放着原始的[n*m*3] .jpg格式图片，文件夹SegmentationClass中存放Label数据，为[n*m*3]的 .png图片，首先应将这些label数据转换为[n*m*1]的单通道图片。 具体转换方法见： https://blog.csdn.net/weixin_41713230/article/details/81076292 运行成功后，会提示如下信息： 3. 运行train.py训练模型

What is meant by sequential model in Keras

由 六眼飞鱼酱① 提交于 2021-01-21 15:23:52
问题 I have recently started working Tensorflow for deep learning. I found this statement model = tf.keras.models.Sequential() bit different. I couldn't understand what is actually meant and is there any other models as well for deep learning? I worked a lot on MatconvNet (Matlab library for convolutional neural network). never saw any sequential definition in that. 回答1: There are two ways to build Keras models: sequential and functional. The sequential API allows you to create models layer-by

What is meant by sequential model in Keras

由 强颜欢笑 提交于 2021-01-21 15:15:14
问题 I have recently started working Tensorflow for deep learning. I found this statement model = tf.keras.models.Sequential() bit different. I couldn't understand what is actually meant and is there any other models as well for deep learning? I worked a lot on MatconvNet (Matlab library for convolutional neural network). never saw any sequential definition in that. 回答1: There are two ways to build Keras models: sequential and functional. The sequential API allows you to create models layer-by

What is meant by sequential model in Keras

由 给你一囗甜甜゛ 提交于 2021-01-21 15:15:06
问题 I have recently started working Tensorflow for deep learning. I found this statement model = tf.keras.models.Sequential() bit different. I couldn't understand what is actually meant and is there any other models as well for deep learning? I worked a lot on MatconvNet (Matlab library for convolutional neural network). never saw any sequential definition in that. 回答1: There are two ways to build Keras models: sequential and functional. The sequential API allows you to create models layer-by

Keras fit_generator() - How does batch for time series work?

由 戏子无情 提交于 2021-01-21 12:16:12
问题 Context: I am currently working on time series prediction using Keras with Tensorflow backend and, therefore, studied the tutorial provided here. Following this tutorial, I came to the point where the generator for the fit_generator() method is described. The output this generator generates is as follows (left sample, right target): [[[10. 15.] [20. 25.]]] => [[30. 35.]] -> Batch no. 1: 2 Samples | 1 Target --------------------------------------------- [[[20. 25.] [30. 35.]]] => [[40. 45.]] -

From audio to tensor, back to audio in tensorflow

由 十年热恋 提交于 2021-01-21 12:05:14
问题 Is there any way to directly load an audio file (wav) to a tensor in tensorflow? And then, converting the tensor into an audio file again? I saw some people transforming audio into spectograms, but I couldn't find anyone that could convert from the spectogram to audio. 回答1: TensorFlow 1.x: The tf.contrib.ffmpeg.decode_audio() op can load audio data (including in WAV format) into a tensor, and the tf.contrib.ffmpeg.encode_audio() can covert it back into audio data. input_filename = tf

From audio to tensor, back to audio in tensorflow

由 核能气质少年 提交于 2021-01-21 12:04:26
问题 Is there any way to directly load an audio file (wav) to a tensor in tensorflow? And then, converting the tensor into an audio file again? I saw some people transforming audio into spectograms, but I couldn't find anyone that could convert from the spectogram to audio. 回答1: TensorFlow 1.x: The tf.contrib.ffmpeg.decode_audio() op can load audio data (including in WAV format) into a tensor, and the tf.contrib.ffmpeg.encode_audio() can covert it back into audio data. input_filename = tf
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