tensorflow analysis

Abstract TensorFlow is an open-source software library designed for Deep Learning using dataflow graph computation.

readingxtra.github.io·654.9 KB

○ TensorFlow provides primitives for defining functions on tensors and automatically computing their derivatives. Page 7. But what's a Tensor? ○ ...

cs224d.stanford.edu·636.0 KB

These tools are all local analyses, for instance, mccabe focuses on the syntactic code complexity of single functions and others focus on code style issues.

yanniss.github.io·623.9 KB

It allows them to reserve and monitor resources. It also lets them run jobs in a rich web interface that supports interactive work and leading ANN environments,

acta.uni-obuda.hu·588.8 KB

ABSTRACT. We advocate that simulation based on offline profiling is a promis- ing approach to better understand and improve the complex ML systems.

henryhxu.github.io·451.9 KB

We present a list of existing tools for neural net-work analysis and summarize their shortcomings. We then introduce comgra to plug this gap in our software toolkit.

arxiv.org·445.4 KB

Detailed Fuzzing Procedure Batching and Nondeterminism TensorFlow graphs are made to take advantage of hardware-parallelism, so process batch of inputs and analyze coverage for batch of arrays each iteration

qdata.github.io·378.4 KB

This leads to A unified, powerful and easy-to-use debugging workflow Ability to do white-box testing of model behavior. Thanks also to the TensorFlow team and related teams for reviewing and guiding the design of TensorFlow Debugger. Available in open-source TensorFlow: tenorflow/python/debug

pdfs.semanticscholar.org·349.1 KB

n package designed to facilitate the implementation of deep neural networks for survival analysis. Built with compatibility for both TensorFlow/Keras and PyTorch, DeepHazard provides a customizable architecture, efficient handling of censored data, pre-defined loss function derived from the Cox mode

ceur-ws.org·334.7 KB

We describe TensorFlow-Serving, a system to serve machine learning models inside Google which is also available in the cloud and via open-source.

learningsys.org·306.7 KB

This studies endeavors to provide an in-depth comparative analysis of TensorFlow and PyTorch, two of the maximum extensively used deep getting to know frameworks.

pdfs.semanticscholar.org·248.8 KB

compared to debugging in the more conventional procedural paradigm. In this paper, we present the design of the TensorFlow Debugger (tfdbg ), a specialized debugger for ML models written in TensorFlow. tfdbg provides features to inspect runtime dataflow graphs and the state of the intermediate gra.

static.googleusercontent.com·110.6 KB

performance analysis of distributed Tensorflow using Horovod. We implemented distributed learning for AlexNet, GoogleNet, and ResNet50 using Horovod. We ...

ieeexplore.ieee.org·17.1 KB

The profiler gives information regarding what nodes that are used when training the various network models and how much time and memory is spent on each nodes.

kth.diva-portal.org

- Monitor Training: Use TensorBoard for visualization. ... As a digital resource, it bridges traditional reading with contemporary.

ftp.richmondbizsense.com