diff --git a/CHANGES.txt b/CHANGES.txt
index d0c0d4e303..47071b5d8d 100644
--- a/CHANGES.txt
+++ b/CHANGES.txt
@@ -1,7 +1,7 @@
-* v2.5.6.1
+* v2.5.7
* added 'ck_html_end_note' key to customize CK result dashboard
* fixed Pareto frontier filter
- * added "ck filter_2d math.frontier"
+ * added "ck filter_2d math.frontier" for MLPerf inference
* v2.5.6
* added --j flag to "ck install package" to update CK_HOST_CPU_NUMBER_OF_PROCESSORS env
diff --git a/README.md b/README.md
index c4d86436d1..3c2bc6dfc4 100755
--- a/README.md
+++ b/README.md
@@ -30,7 +30,7 @@ Windows: [
* [CK-powered MLPerf™ benchmark automation](https://github.com/ctuning/ck/blob/master/docs/mlperf-automation/README.md)
* [Community projects to improve and redesign CK](https://github.com/ctuning/ck/blob/master/incubator/README.md)
-* [AI/ML repository with all aggregated CK components](https://github.com/ctuning/ai)
+* [CK automation recipes for portable MLOps](https://github.com/ctuning/ck-mlops)
* [OctoML's CK-based MLOps/MLPerf repository](https://github.com/octoml/mlops)
## Overview
@@ -49,7 +49,7 @@ simplifies [MLPerf™ inference benchmark](https://github.com/ctuning/ck/blo
and supports collaborative, reproducible and reusable ML Systems research:
* [ACM TechTalk](https://www.youtube.com/watch?v=7zpeIVwICa4)
-* [AI/ML/MLPerf™ automation workflows and components from the community](https://github.com/ctuning/ai);
+* [AI/ML/MLPerf™ automation workflows and components from the community](https://github.com/ctuning/ck-mlops);
* [Reddit discussion about reproducing 150 papers](https://www.reddit.com/r/MachineLearning/comments/ioq8do/n_reproducing_150_research_papers_the_problems);
* Our reproducibility initiatives: [methodology](https://cTuning.org/ae), [checklist](https://ctuning.org/ae/submission_extra.html), [events](https://cKnowledge.io/events).
@@ -135,7 +135,7 @@ Check [CK docs](https://ck.readthedocs.io/en/latest/src/introduction.html) for f
### Portable CK workflow (with Docker)
We have prepared m CK containers with ML Systems components:
-* https://github.com/ctuning/ai/tree/main/docker
+* https://github.com/ctuning/ck-mlops/tree/main/docker
* https://github.com/octoml/mlops/tree/main/docker
You can run them as follows:
diff --git a/ck/kernel.py b/ck/kernel.py
index 67593fa3e5..462b8275fb 100755
--- a/ck/kernel.py
+++ b/ck/kernel.py
@@ -28,7 +28,7 @@
# We use 3 digits for the main (released) version and 4th digit for development revision
-__version__ = "2.5.6.1"
+__version__ = "2.5.7"
# Do not use characters (to detect outdated version)!
# Import packages that are global for the whole kernel
diff --git a/ck/repo/module/advice/module.py b/ck/repo/module/advice/module.py
index bb7681c24f..5abde2d245 100644
--- a/ck/repo/module/advice/module.py
+++ b/ck/repo/module/advice/module.py
@@ -16,16 +16,10 @@
# Local settings
hextra='\n'
-hextra+=' [ Project website ], '
-hextra+=' [ Partners ], '
-hextra+=' [ CGO\'17 test of time award for our interdisiplinary R&D ], '
-hextra+=' [ Community-driven AI R&D powered by CK ], '
-hextra+=' [ CK-Caffe ], '
-hextra+=' [ CK-TensorFlow ], '
-hextra+=' [ Wikipedia, \n'
-hextra+='paper 1, \n'
-hextra+='Paper 2, \n'
-hextra+='YouTube CK intro ] \n'
+hextra+=' [ Project website ], '
+hextra+=' [ Partners ], '
+hextra+=' [ CK automation recipes for MLOps ], '
+hextra+=' [ Wikipedia ] \n'
hextra+='\n'
hextra+='\n'
diff --git a/ck/repo/module/env/module.py b/ck/repo/module/env/module.py
index e41d0844de..1b9aaa89e2 100644
--- a/ck/repo/module/env/module.py
+++ b/ck/repo/module/env/module.py
@@ -392,7 +392,7 @@ def env_set(i):
ck.out('')
ck.out(' This is a possible bug - please report here:')
ck.out(' * https://github.com/ctuning/ck/issues')
- ck.out(' * https://github.com/ctuning/ai/issues')
+ ck.out(' * https://github.com/ctuning/ck-mlops/issues')
ck.out('')
return {'return':33, 'error':'current host or target OS ('+str(setup)+' is not matching the one in software env '+duoa}
diff --git a/ck/repo/module/experiment.bench.caffe2/module.py b/ck/repo/module/experiment.bench.caffe2/module.py
index 749f44ac64..53270166e6 100644
--- a/ck/repo/module/experiment.bench.caffe2/module.py
+++ b/ck/repo/module/experiment.bench.caffe2/module.py
@@ -24,25 +24,12 @@
form_name='wa_web_form'
onchange='document.'+form_name+'.submit();'
-#hextra='\n'
-#hextra+='This is an on-going long-term project. Please check our vision [ '
-#hextra+='IWOCL\'16, \n'
-#hextra+='CPC\'15, \n'
-#hextra+='YouTube, \n'
-#hextra+='wiki ] '
-#hextra+=' and CK-TensorFlow GitHub repo for more details!'
-#hextra+='\n'
-#hextra+='
\n'
-
hextra='\n'
-hextra+=' [ Collaborative unification of AI ], '
-hextra+=' [ CK-Caffe2 / CK-Caffe ], '
-hextra+=' [ CK-Tensorflow ], '
+hextra+=' [ Project website ], '
+hextra+=' [ CK automation recipes for portable MLOps ], '
hextra+=' [ Android app ], '
hextra+=' [ CK intro, \n'
-hextra+='vision and \n'
-hextra+='crowd-tuning; \n'
-hextra+='YouTube lecture ] \n'
+hextra+='crowd-tuning ] \n'
hextra+='\n'
hextra+='
\n'
diff --git a/ck/repo/module/experiment.bench.dnn.mobile/module.py b/ck/repo/module/experiment.bench.dnn.mobile/module.py
index 746b61bbd7..f861b5d37e 100644
--- a/ck/repo/module/experiment.bench.dnn.mobile/module.py
+++ b/ck/repo/module/experiment.bench.dnn.mobile/module.py
@@ -25,18 +25,6 @@
onchange='document.'+form_name+'.submit();'
hextra=''
-#hextra+='\n'
-#hextra+=' [ Community-driven AI R&D powered by CK ], '
-#hextra+=' [ CGO\'17 test of time award for our interdisiplinary R&D ], '
-#hextra+=' [ Android app to crowd-optimize DNN engines and models ], '
-#hextra+=' [ CK-Caffe2 GitHub / CK-Caffe GitHub ], '
-#hextra+=' [ CK-TensorFlow GitHub ], '
-#hextra+=' [ Wikipedia, \n'
-#hextra+='paper 1, \n'
-#hextra+='Paper 2, \n'
-#hextra+='YouTube CK intro ] \n'
-#hextra+='\n'
-#hextra+='
\n'
selector=[{'name':'Scenario', 'key':'crowd_uid', 'module_uoa':'65477d547a49dd2c', 'module_key':'##dict#title'},
{'name':'DNN engine', 'key':'engine'},
diff --git a/ck/repo/module/experiment.bench.dnn/module.py b/ck/repo/module/experiment.bench.dnn/module.py
index 2c26b8fa69..79b6a68bd6 100644
--- a/ck/repo/module/experiment.bench.dnn/module.py
+++ b/ck/repo/module/experiment.bench.dnn/module.py
@@ -24,25 +24,10 @@
form_name='wa_web_form'
onchange='document.'+form_name+'.submit();'
-#hextra='\n'
-#hextra+='This is an on-going long-term project. Please check our vision [ '
-#hextra+='IWOCL\'16, \n'
-#hextra+='CPC\'15, \n'
-#hextra+='YouTube, \n'
-#hextra+='wiki ] '
-#hextra+=' and CK-Caffe GitHub repo for more details!'
-#hextra+='\n'
-#hextra+='
\n'
-
hextra='\n'
-hextra+=' [ Community-driven AI R&D powered by CK ], '
-hextra+=' [ CK-Caffe2 / CK-Caffe ], '
-hextra+=' [ CK-TensorFlow ], '
-hextra+=' [ Wikipedia, \n'
-hextra+='paper 1, \n'
-hextra+='Paper 2, \n'
-hextra+='YouTube CK intro ], \n'
-hextra+=' [ CGO\'17 test of time award for our interdisiplinary R&D ]'
+hextra+=' [ CK project website ], '
+hextra+=' [ CK automation recipes for portable MLOps ], '
+hextra+=' [ Wikipedia ] \n'
hextra+='\n'
hextra+='
\n'
diff --git a/ck/repo/module/experiment.bench.tensorflow/module.py b/ck/repo/module/experiment.bench.tensorflow/module.py
index c463196905..9055e31714 100644
--- a/ck/repo/module/experiment.bench.tensorflow/module.py
+++ b/ck/repo/module/experiment.bench.tensorflow/module.py
@@ -24,25 +24,10 @@
form_name='wa_web_form'
onchange='document.'+form_name+'.submit();'
-#hextra='\n'
-#hextra+='This is an on-going long-term project. Please check our vision [ '
-#hextra+='IWOCL\'16, \n'
-#hextra+='CPC\'15, \n'
-#hextra+='YouTube, \n'
-#hextra+='wiki ] '
-#hextra+=' and CK-TensorFlow GitHub repo for more details!'
-#hextra+='\n'
-#hextra+='
\n'
-
hextra='\n'
-hextra+=' [ Collaborative unification of AI ], '
-hextra+=' [ CK-Caffe2 / CK-Caffe ], '
-hextra+=' [ CK-Tensorflow ], '
-hextra+=' [ Android app ], '
-hextra+=' [ CK intro, \n'
-hextra+='vision and \n'
-hextra+='crowd-tuning; \n'
-hextra+='YouTube lecture ] \n'
+hextra+=' [ CK project website ], '
+hextra+=' [ CK automation recipes for portable MLOps ], '
+hextra+=' [ Android app ]\n '
hextra+='\n'
hextra+='
\n'
diff --git a/ck/repo/module/model.image.classification/module.py b/ck/repo/module/model.image.classification/module.py
index fce2456c1a..577ddef3cf 100644
--- a/ck/repo/module/model.image.classification/module.py
+++ b/ck/repo/module/model.image.classification/module.py
@@ -13,14 +13,9 @@
# Local settings
hextra='\n'
-hextra+=' [ Community-driven AI R&D powered by CK ], '
-hextra+=' [ CK-Caffe ], '
-hextra+=' [ CK-Caffe2 ], '
-hextra+=' [ CK-TensorFlow ], '
-hextra+=' [ Wikipedia, \n'
-hextra+='paper 1, \n'
-hextra+='Paper 2, \n'
-hextra+='YouTube CK intro ] \n'
+hextra+=' [ CK project website ], '
+hextra+=' [ CK automation recipes for portable MLOps ], '
+hextra+=' [ Wikipedia ] \n'
hextra+='\n'
hextra+='
\n'
diff --git a/ck/repo/module/package/module.py b/ck/repo/module/package/module.py
index 6423eae41b..d6e5dacae7 100644
--- a/ck/repo/module/package/module.py
+++ b/ck/repo/module/package/module.py
@@ -2872,7 +2872,7 @@ def print_warning(i):
# x2='https://groups.google.com/forum/#!forum/collective-knowledge'
# x3='https://github.com/ctuning/ck/issues'
x2='https://github.com/ctuning/ck/issues'
- x3='https://github.com/ctuning/ai/issues'
+ x3='https://github.com/ctuning/ck-mlops/issues'
# if url2!='':
# x1='the authors'
# x2=url2
diff --git a/ck/repo/module/program.optimization/module.py b/ck/repo/module/program.optimization/module.py
index a96ec074f5..829dbe64f0 100644
--- a/ck/repo/module/program.optimization/module.py
+++ b/ck/repo/module/program.optimization/module.py
@@ -3132,21 +3132,9 @@ def links(i):
h+=' NPU ] \n'
h+='[ How to participate ] \n'
h+='[ Motivation (PPT) (PDF) ] \n'
- h+='[ Papers 1 , 2 , 3] \n'
- h+='[ Android app ] \n'
+ h+='[ Android app ] \n'
h+='[ Collective training set ] \n'
- h+='[ Unified AI ] \n'
-
-# h+='[ open research SDK ], \n'
-# h+='[ Android apps to crowdsource experiments: small kernels, apps (DNN)) ], \n'
-# h+='[ A few papers: CPC\'15, \n'
-# h+=' DATE\'16, \n'
-# h+=' TRUST@PLDI\'14, interactive,\n'
-# h+=' YouTube\n'
-# h+=' ], \n'
-# h+='[ Our reproducible initiative for ACM conferences ], \n'
-# h+='[ CGO\'17 test of time award for our interdisiplinary R&D ], '
-# h+='[ Open and unified CK API for AI ] '
+ h+='[ CK project website ] \n'
h+='\n'
h+='\n'
diff --git a/ck/repo/module/program/module.py b/ck/repo/module/program/module.py
index ba54c8386b..4d22710c04 100644
--- a/ck/repo/module/program/module.py
+++ b/ck/repo/module/program/module.py
@@ -7766,7 +7766,7 @@ def print_warning(i):
# x2='https://groups.google.com/forum/#!forum/collective-knowledge'
# x3='https://github.com/ctuning/ck/issues'
x2='https://github.com/ctuning/ck/issues'
- x3='https://github.com/ctuning/ai/issues'
+ x3='https://github.com/ctuning/ck-mlops/issues'
# if url2!='':
# x1='the authors'
# x2=url2
diff --git a/docs/mlperf-automation/README.md b/docs/mlperf-automation/README.md
index d0f39a7233..c618cdf78d 100644
--- a/docs/mlperf-automation/README.md
+++ b/docs/mlperf-automation/README.md
@@ -6,8 +6,8 @@ We also want to develop an open database for benchmarking results and provenance
compatible with [FAIR principles](https://www.go-fair.org/fair-principles).
As a starting point, we will use the open-source and technology-neutral [CK framework](https://github.com/ctuning/ck)
-with a [collection](https://github.com/ctuning/ai) of [reusable automation recipes](https://github.com/ctuning/ai/tree/main/program)
-and [plug&play packages](https://github.com/ctuning/ai/tree/main/package)
+with a [collection](https://github.com/ctuning/ck-mlops) of [reusable automation recipes](https://github.com/ctuning/ck-mlops/tree/main/program)
+and [plug&play packages](https://github.com/ctuning/ck-mlops/tree/main/package)
for ML systems. CK framework was already successfully used by several MLCommons members
to automate their MLPerf inference submissions and we want to build upon their experience.
@@ -16,7 +16,7 @@ open-source tools from the MLCommons™ Best Practices WorkGroup ([MLCube&tr
A few examples:
* [MLPerf™ object detection workflow](https://github.com/ctuning/ck/blob/master/docs/mlperf-automation/tasks/task-object-detection.md)
-* [Docker image for MLPerf™ with OpenVINO]( https://github.com/ctuning/ai/tree/main/docker/mlperf-inference-v0.7.openvino )
+* [Docker image for MLPerf™ with OpenVINO]( https://github.com/ctuning/ck-mlops/tree/main/docker/mlperf-inference-v0.7.openvino )
* [Jupyter notebook for ML DSE](https://nbviewer.jupyter.org/urls/dl.dropbox.com/s/f28u9epifr0nn09/ck-dse-demo-object-detection.ipynb)
* [Webcam test of the MLPerf object detection model with TFLite](https://cknowledge.io/solution/demo-obj-detection-coco-tf-cpu-webcam-linux-azure#test)
* [Public scoreboard with MLPerf DSE](https://cknowledge.io/result/crowd-benchmarking-mlperf-inference-classification-mobilenets-all)
diff --git a/docs/mlperf-automation/components/README.md b/docs/mlperf-automation/components/README.md
index 037b7aed48..b7b0aa2e30 100644
--- a/docs/mlperf-automation/components/README.md
+++ b/docs/mlperf-automation/components/README.md
@@ -3,7 +3,7 @@
# CK components for ML Systems (automation recipes)
Over the past few years we've collected many CK components
-and automation recipes for ML Systems in [this public repo](https://github.com/ctuning/ai)
+and automation recipes for ML Systems in [this public repo](https://github.com/ctuning/ck-mlops)
(ML models, frameworks, tools, data sets, portable workflows, autotuning scripts, etc).
We now work with the community and MLCommons to test and unify these components.
diff --git a/docs/mlperf-automation/inference/containers.md b/docs/mlperf-automation/inference/containers.md
index e02cfcbef9..6bebb97d3f 100644
--- a/docs/mlperf-automation/inference/containers.md
+++ b/docs/mlperf-automation/inference/containers.md
@@ -4,7 +4,7 @@ We would like to prepare a set of containers to run MLPerf inference benchmark o
Ongoing efforts:
* https://github.com/octoml/mlops/tree/main/docker
-* https://github.com/ctuning/ai/tree/main/docker
+* https://github.com/ctuning/ck-mlops/tree/main/docker
## Adaptive CK containers for MLPerf inference
diff --git a/docs/mlperf-automation/inference/workflow.md b/docs/mlperf-automation/inference/workflow.md
index 525a2cd38c..243a8b2831 100644
--- a/docs/mlperf-automation/inference/workflow.md
+++ b/docs/mlperf-automation/inference/workflow.md
@@ -33,7 +33,7 @@ We plan to add module:mlperf.bench.inference with the following flags:
```
-This high-level workflow will install relevant CK packages ([ctuning@ai](https://github.com/ctuning/ai/tree/main/package) / [octoml@mlops](https://github.com/octoml/mlops/tree/main/package))
+This high-level workflow will install relevant CK packages ([ctuning@ai](https://github.com/ctuning/ck-mlops/tree/main/package) / [octoml@mlops](https://github.com/octoml/mlops/tree/main/package))
and run low-level [CK program workflows for MLPerf](https://github.com/octoml/mlops/tree/main/program).
diff --git a/docs/mlperf-automation/tasks-custom/README.md b/docs/mlperf-automation/tasks-custom/README.md
index fab7341f1a..dab0809d0c 100644
--- a/docs/mlperf-automation/tasks-custom/README.md
+++ b/docs/mlperf-automation/tasks-custom/README.md
@@ -7,16 +7,16 @@ to automate design space exploration across different models, frameworks and dat
with the help of the [CK workflow framework](https://github.com/ctuning/ck).
-We collect all CK components for MLPerf and MLSystems co-design in one CK repository: https://github.com/ctuning/ai .
+We collect all CK components for MLPerf and MLSystems co-design in one CK repository: https://github.com/ctuning/ck-mlops .
We plan to test, unify and standardize them during summer 2021.
In the meantime you can have a look at [these examples](../reproduce/README.md)
and the following CK components for ML Systems benchmarking:
-* [Program workflows](https://github.com/ctuning/ai/tree/main/program)
-* [Packages with frameworks, models, data sets and quantization scripts](https://github.com/ctuning/ai/tree/main/package)
-* [SUT descriptions](https://github.com/ctuning/ai/tree/main/sut)
-* [Docker images](https://github.com/ctuning/ai/tree/main/docker)
-* [Aux scripts](https://github.com/ctuning/ai/tree/main/script)
+* [Program workflows](https://github.com/ctuning/ck-mlops/tree/main/program)
+* [Packages with frameworks, models, data sets and quantization scripts](https://github.com/ctuning/ck-mlops/tree/main/package)
+* [SUT descriptions](https://github.com/ctuning/ck-mlops/tree/main/sut)
+* [Docker images](https://github.com/ctuning/ck-mlops/tree/main/docker)
+* [Aux scripts](https://github.com/ctuning/ck-mlops/tree/main/script)
TBD:
diff --git a/docs/mlperf-automation/tasks/task-image-classification.md b/docs/mlperf-automation/tasks/task-image-classification.md
index 3a97f78978..1d87347f3e 100644
--- a/docs/mlperf-automation/tasks/task-image-classification.md
+++ b/docs/mlperf-automation/tasks/task-image-classification.md
@@ -38,7 +38,7 @@ ck activate venv:mlperf-inference
Alternatively, use the following commands if you want to use your native environment:
```
-ck pull repo:ai
+ck pull repo:ck-mlops
ck setup kernel --var.install_to_env=yes
@@ -65,7 +65,7 @@ ck show env
```
-You can explore available packages in the [CK GitHub repo](https://github.com/ctuning/ai/tree/main/package)
+You can explore available packages in the [CK GitHub repo](https://github.com/ctuning/ck-mlops/tree/main/package)
or using the [cKnowledge.io platform](https://cKnowledge.io/c/package).
## Pull CK repo with the latest MLPerf™ automations from OctoML:
@@ -88,9 +88,9 @@ ck install package --tags=imagenet,2012,val,min,non-resized
ck install package --tags=imagenet,2012,aux,from.berkeley
```
-Feel free to check the [CK JSON meta](https://github.com/ctuning/ai/blob/main/package/imagenet-2012-val-min/.cm/meta.json)
-and CK installation scripts for [Linux](https://github.com/ctuning/ai/blob/main/package/imagenet-2012-val-min/install.sh)
-and [Windows](https://github.com/ctuning/ai/blob/main/package/imagenet-2012-val-min/install.bat)
+Feel free to check the [CK JSON meta](https://github.com/ctuning/ck-mlops/blob/main/package/imagenet-2012-val-min/.cm/meta.json)
+and CK installation scripts for [Linux](https://github.com/ctuning/ck-mlops/blob/main/package/imagenet-2012-val-min/install.sh)
+and [Windows](https://github.com/ctuning/ck-mlops/blob/main/package/imagenet-2012-val-min/install.bat)
for the CK ImageNet val min package.
ImageNet 2012 validation set is no longer publicly available.
@@ -108,11 +108,11 @@ and then register in the CK using the above command.
Please check [this doc](../datasets/imagenet2012.md) to see how you can preprocess the ImageNet
in multiple ways with the help of CK.
-Feel free to check the [CK JSON meta](https://github.com/ctuning/ai/blob/main/soft/dataset.imagenet.val/.cm/meta.json)
-and [CK Python customization script](https://github.com/ctuning/ai/blob/main/soft/dataset.imagenet.val/customize.py)
+Feel free to check the [CK JSON meta](https://github.com/ctuning/ck-mlops/blob/main/soft/dataset.imagenet.val/.cm/meta.json)
+and [CK Python customization script](https://github.com/ctuning/ck-mlops/blob/main/soft/dataset.imagenet.val/customize.py)
to detect this data set on your machine.
-You can see other software detection plugins in the [CK repository](https://github.com/ctuning/ai/tree/main/soft)
+You can see other software detection plugins in the [CK repository](https://github.com/ctuning/ck-mlops/tree/main/soft)
or using the [cKnowledge.io platform](https://cKnowledge.io/c/soft).
diff --git a/docs/mlperf-automation/tasks/task-object-detection.md b/docs/mlperf-automation/tasks/task-object-detection.md
index 5569fcd521..48231751c3 100644
--- a/docs/mlperf-automation/tasks/task-object-detection.md
+++ b/docs/mlperf-automation/tasks/task-object-detection.md
@@ -43,7 +43,7 @@ ck activate venv:mlperf-inference
Alternatively, use the following commands if you want to use your native environment:
```
-ck pull repo:ai
+ck pull repo:ck-mlops
ck setup kernel --var.install_to_env=yes
@@ -70,7 +70,7 @@ ck show env
```
-You can explore available packages in the [CK GitHub repo](https://github.com/ctuning/ai/tree/main/package)
+You can explore available packages in the [CK GitHub repo](https://github.com/ctuning/ck-mlops/tree/main/package)
or using the [cKnowledge.io platform](https://cKnowledge.io/c/package).
## Pull CK repo with the latest MLPerf™ automations from OctoML:
@@ -93,19 +93,19 @@ You can install COCO 2017 val dataset as follows:
ck install package --tags=dataset,coco,val,2017,full
```
-Feel free to check the [CK JSON meta](https://github.com/ctuning/ai/tree/main/package/dataset-coco-2017-val/.cm/meta.json)
-and CK installation scripts for [Linux](https://github.com/ctuning/ai/tree/main/package/dataset-coco-2017-val/install.sh)
-and [Windows](https://github.com/ctuning/ai/tree/main/package/dataset-coco-2017-val/install.bat)
+Feel free to check the [CK JSON meta](https://github.com/ctuning/ck-mlops/tree/main/package/dataset-coco-2017-val/.cm/meta.json)
+and CK installation scripts for [Linux](https://github.com/ctuning/ck-mlops/tree/main/package/dataset-coco-2017-val/install.sh)
+and [Windows](https://github.com/ctuning/ck-mlops/tree/main/package/dataset-coco-2017-val/install.bat)
for the CK COCO2017 val dataset package.
Please check [this doc](../datasets/coco2017.md) to see how you can preprocess this data set
in multiple ways with the help of CK.
-Feel free to check the [CK JSON meta](https://github.com/ctuning/ai/tree/main/soft/dataset.coco.2017.val/.cm/meta.json)
-and [CK Python customization script](https://github.com/ctuning/ai/tree/main/soft/dataset.coco.2017.val/customize.py)
+Feel free to check the [CK JSON meta](https://github.com/ctuning/ck-mlops/tree/main/soft/dataset.coco.2017.val/.cm/meta.json)
+and [CK Python customization script](https://github.com/ctuning/ck-mlops/tree/main/soft/dataset.coco.2017.val/customize.py)
to detect this data set on your machine.
-You can see other software detection plugins in the [CK repository](https://github.com/ctuning/ai/tree/main/soft)
+You can see other software detection plugins in the [CK repository](https://github.com/ctuning/ck-mlops/tree/main/soft)
or using the [cKnowledge.io platform](https://cKnowledge.io/c/soft).
@@ -283,7 +283,7 @@ and record results in your local repository for further analysis.
Feel free to check the [CK entry](https://github.com/octoml/mlops/tree/main/docker/ck-mlperf-inference-v1.0-object-detection-native)
with this container. You can also check [adaptive CK containers shared by OctoML](https://github.com/octoml/mlops/tree/main/docker)
-and other [CK containers shared by the community](https://github.com/ctuning/ai/tree/main/docker).
+and other [CK containers shared by the community](https://github.com/ctuning/ck-mlops/tree/main/docker).
First, build a given Docker container using CK as follows:
diff --git a/docs/mlperf-automation/tbd/standardization.md b/docs/mlperf-automation/tbd/standardization.md
index 19ff8ed1a9..55a5f806c5 100644
--- a/docs/mlperf-automation/tbd/standardization.md
+++ b/docs/mlperf-automation/tbd/standardization.md
@@ -7,7 +7,7 @@
Examples of JSON meta for CK packages with ML models:
* [SSD ResNet34 1200x1200 ONNX](https://github.com/octoml/mlops/blob/main/package/ml-model-mlperf-ssd-resnet34-1200-onnx/.cm/meta.json#L6)
* [MobileNet v1.0 224x224 TensorFlow](https://github.com/octoml/mlops/blob/main/package/ml-model-mlperf-ssd-resnet34-1200-onnx/.cm/meta.json#L6)
-* [MobileNet v3.0 224x224 TFLite]( https://github.com/ctuning/ai/blob/main/package/model-tf-and-tflite-mlperf-mobilenet-v3/.cm/meta.json )
+* [MobileNet v3.0 224x224 TFLite]( https://github.com/ctuning/ck-mlops/blob/main/package/model-tf-and-tflite-mlperf-mobilenet-v3/.cm/meta.json )
## CK workflows for MLPerf
diff --git a/docs/mlperf-automation/tools/continuous-integration.md b/docs/mlperf-automation/tools/continuous-integration.md
index a31f2af913..cbf42e6685 100644
--- a/docs/mlperf-automation/tools/continuous-integration.md
+++ b/docs/mlperf-automation/tools/continuous-integration.md
@@ -41,5 +41,5 @@ Python-based CK integration with web platforms:
CMD-based CK integration with CLI platforms:
-* [Travis for Linux and MacOS (CK ML repository)](https://github.com/ctuning/ai/blob/main/.travis.yml)
-* [AppVeyor for Windows (CK ML repository)](https://github.com/ctuning/ai/blob/main/appveyor.yml)
+* [Travis for Linux and MacOS (CK ML repository)](https://github.com/ctuning/ck-mlops/blob/main/.travis.yml)
+* [AppVeyor for Windows (CK ML repository)](https://github.com/ctuning/ck-mlops/blob/main/appveyor.yml)
diff --git a/docs/src/first-steps.md b/docs/src/first-steps.md
index 7fb8582d29..15f675e85c 100644
--- a/docs/src/first-steps.md
+++ b/docs/src/first-steps.md
@@ -65,9 +65,9 @@ ck load program:image-corner-detection
ck load program:image-corner-detection --min
```
-It may be more convenient to check the structure of this entry at [GitHub](https://github.com/ctuning/ai/tree/master/program/image-corner-detection) with all the sources and meta-descriptions.
+It may be more convenient to check the structure of this entry at [GitHub](https://github.com/ctuning/ck-mlops/tree/master/program/image-corner-detection) with all the sources and meta-descriptions.
-You can also see the CK JSON meta description for this CK program entry [here](https://github.com/ctuning/ai/blob/master/program/image-corner-detection/.cm/meta.json).
+You can also see the CK JSON meta description for this CK program entry [here](https://github.com/ctuning/ck-mlops/blob/master/program/image-corner-detection/.cm/meta.json).
When you invoke automation actions in the CK module *program*, the automation code will read this meta description and perform actions for different programs accordingly.
## Invoke CK automation actions
diff --git a/docs/src/introduction.md b/docs/src/introduction.md
index e332ff6770..ff9ba46e95 100644
--- a/docs/src/introduction.md
+++ b/docs/src/introduction.md
@@ -302,20 +302,20 @@ and [ACM artifact review and badging](https://www.acm.org/publications/policies/
* ML-based autotuning project: [reproducible paper demo](https://cKnowledge.io/report/rpi3-crowd-tuning-2017-interactive), [MILEPOST]( https://github.com/ctuning/reproduce-milepost-project )
* [Quantum hackathons](https://cKnowledge.org/quantum)
* [ACM SW/HW co-design tournaments for Pareto-efficient deep learning](https://cKnowledge.org/request)
- * Portable CK workflows and components for ML Systems: https://github.com/ctuning/ai
+ * Portable CK workflows and components for ML Systems: https://github.com/ctuning/ck-mlops
* [GUI to automate ML/SW/HW benchmarking with MLPerf example (under development)](https://cKnowledge.io/test)
* [Reproduced papers]( https://cKnowledge.io/reproduced-papers )
* [Live scoreboards for reproduced papers]( https://cKnowledge.io/reproduced-results )
* Examples of CK components (automations, API, meta descriptions):
- * *program : image-classification-tflite-loadgen* [[cKnowledge.io]( https://cKnowledge.io/c/program/image-classification-tflite-loadgen )] [[GitHub]( https://github.com/ctuning/ai/tree/master/program/image-classification-tflite-loadgen )]
- * *program : image-classification-tflite* [[GitHub]( https://github.com/ctuning/ai/tree/master/program/image-classification-tflite )]
- * *soft : lib.mlperf.loadgen.static* [[GitHub]( https://github.com/ctuning/ai/tree/master/soft/lib.mlperf.loadgen.static )]
- * *package : lib-mlperf-loadgen-static* [[GitHub]( https://github.com/ctuning/ai/tree/master/package/lib-mlperf-loadgen-static )]
- * *package : model-onnx-mlperf-mobilenet* [[GitHub]( https://github.com/ctuning/ai/tree/master/package/model-onnx-mlperf-mobilenet/.cm )]
- * *package : lib-tflite* [[cKnowledge.io]( https://cKnowledge.io/c/package/lib-tflite )] [[GitHub]( https://github.com/ctuning/ai/tree/master/package/lib-tflite )]
- * *docker : ** [[GitHub]( https://github.com/ctuning/ai/tree/master/docker )]
- * *docker : speech-recognition.rnnt* [[GitHub]( https://github.com/ctuning/ai/tree/main/docker/mlperf-inference-speech-recognition-rnnt )]
- * *package : model-tf-** [[GitHub]( https://github.com/ctuning/ai/tree/master/package )]
+ * *program : image-classification-tflite-loadgen* [[cKnowledge.io]( https://cKnowledge.io/c/program/image-classification-tflite-loadgen )] [[GitHub]( https://github.com/ctuning/ck-mlops/tree/master/program/image-classification-tflite-loadgen )]
+ * *program : image-classification-tflite* [[GitHub]( https://github.com/ctuning/ck-mlops/tree/master/program/image-classification-tflite )]
+ * *soft : lib.mlperf.loadgen.static* [[GitHub]( https://github.com/ctuning/ck-mlops/tree/master/soft/lib.mlperf.loadgen.static )]
+ * *package : lib-mlperf-loadgen-static* [[GitHub]( https://github.com/ctuning/ck-mlops/tree/master/package/lib-mlperf-loadgen-static )]
+ * *package : model-onnx-mlperf-mobilenet* [[GitHub]( https://github.com/ctuning/ck-mlops/tree/master/package/model-onnx-mlperf-mobilenet/.cm )]
+ * *package : lib-tflite* [[cKnowledge.io]( https://cKnowledge.io/c/package/lib-tflite )] [[GitHub]( https://github.com/ctuning/ck-mlops/tree/master/package/lib-tflite )]
+ * *docker : ** [[GitHub]( https://github.com/ctuning/ck-mlops/tree/master/docker )]
+ * *docker : speech-recognition.rnnt* [[GitHub]( https://github.com/ctuning/ck-mlops/tree/main/docker/mlperf-inference-speech-recognition-rnnt )]
+ * *package : model-tf-** [[GitHub]( https://github.com/ctuning/ck-mlops/tree/master/package )]
* *script : mlperf-inference-v0.7.image-classification* [[cKnowledge.io]( https://cknowledge.io/c/script/mlperf-inference-v0.7.image-classification )]
* *jnotebook : object-detection* [[GitHub](https://nbviewer.jupyter.org/urls/dl.dropbox.com/s/5yqb6fy1nbywi7x/medium-object-detection.20190923.ipynb)]