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Version: master πŸƒ

Experiment REST API

caution

The Experiment API is in the alpha stage which is subjected to incompatible changes in future releases.

Create Experiment (Using Anonymous/Embedded Environment)​

POST /api/v1/experiment

Parameters​

Put ExperimentSpec in request body.

ExperimentSpec​

Field NameTypeDescriptionRequired
metaExperimentMetaMeta data of the experiment template.o
environmentEnvironmentSpecEnvironment of the experiment template.o
specMap<String, ExperimentTaskSpec>Spec of pods.o
codeCodeSpecExperiment codespec.x

ExperimentMeta​

Field NameTypeDescriptionRequired
nameStringExperiment name.o
namespaceStringExperiment namespace.o
frameworkStringExperiemnt framework.o
cmdStringCommand.o
envVarsMap<String, String>Environmental variables.x

EnvironmentSpec​

There are two types of environment: Anonymous and Predefined.

  • Anonymous environment: only specify dockerImage in environment spec. The container will be built on the docker image.
  • Embedded environment: specify name in environment spec. The container will be built on the existing environment (including dockerImage and kernalSpec).

See more details in environment api.

ExperimentTaskSpec​

Field NameTypeDescriptionRequired
replicasIntegerNumbers of replicas.o
resourecesStringResouces of the tasko
nameStringTask name.o
imageStringImage name.o
cmdStringCommand.x
envVarsMap<String, String>Environmental variables.x

CodeSpec​

Currently only support pulling from github. HDFS, NFS and s3 are in development

Field NameTypeDescriptionRequired
syncModeString (git|hdfs|nfs|s3)sync mode of code spec.o
urlStringurl of code spec.o

Example​

Example Request
curl -X POST -H "Content-Type: application/json" -d '
{
"meta": {
"name": "tf-mnist-json",
"namespace": "default",
"framework": "TensorFlow",
"cmd": "python /var/tf_mnist/mnist_with_summaries.py --log_dir=/train/log --learning_rate=0.01 --batch_size=150",
"envVars": {
"ENV_1": "ENV1"
}
},
"environment": {
"image": "apache/submarine:tf-mnist-with-summaries-1.0"
},
"spec": {
"Ps": {
"replicas": 1,
"resources": "cpu=1,memory=1024M"
},
"Worker": {
"replicas": 1,
"resources": "cpu=1,memory=2048M"
}
}
}
' http://127.0.0.1:32080/api/v1/experiment
Example Response
{
"status":"OK",
"code":200,
"success":true,
"message":null,
"result":{
"experimentId":"experiment-1647192232698-0001",
"uid":"b0ae271b-a01a-43ad-9877-4b8ecbc45de4",
"status":"Accepted",
"acceptedTime":"2022-03-14T16:03:10.000+08:00",
"createdTime":null,
"runningTime":null,
"finishedTime":null,
"spec":{
"meta":{
"experimentId":"experiment-1647192232698-0001",
"name":"tf-mnist-json",
"namespace":"default",
"framework":"TensorFlow",
"cmd":"python /var/tf_mnist/mnist_with_summaries.py --log_dir\u003d/train/log --learning_rate\u003d0.01 --batch_size\u003d150",
"envVars":{
"ENV_1":"ENV1"
},
"tags":[]
},
"environment":{
"name":null,
"dockerImage":null,
"kernelSpec":null,
"description":null,
"image":"apache/submarine:tf-mnist-with-summaries-1.0"
},
"spec":{
"Ps":{
"replicas":1,
"resources":"cpu\u003d1,memory\u003d1024M",
"name":null,
"image":null,
"cmd":null,
"envVars":null,
"resourceMap":{
"memory":"1024M",
"cpu":"1"
}
},
"Worker":{
"replicas":1,
"resources":"cpu\u003d1,memory\u003d2048M",
"name":null,
"image":null,
"cmd":null,
"envVars":null,
"resourceMap":{
"memory":"2048M",
"cpu":"1"
}
}
},
"code":null
}
},
"attributes":{}
}

List experiment​

GET /api/v1/experiment

Example​

Example Request
curl -X GET http://127.0.0.1:32080/api/v1/experiment
Example Response
{
"status":"OK",
"code":200,
"success":true,
"message":null,
"result":[
{
"experimentId":"experiment-1647574374688-0002",
"uid":"cf465781-6310-46d2-92b4-d20161c77d08",
"status":"Running",
"acceptedTime":"2022-03-18T15:51:04.000+08:00",
"createdTime":"2022-03-18T15:51:05.000+08:00",
"runningTime":"2022-03-18T15:51:17.000+08:00",
"finishedTime":null,
"spec":{
"meta":{
"experimentId":"experiment-1647574374688-0002",
"name":"tf-mnist-json",
"namespace":"default",
"framework":"TensorFlow",
"cmd":"python /var/tf_mnist/mnist_with_summaries.py --log_dir\u003d/train/log --learning_rate\u003d0.01 --batch_size\u003d150",
"envVars":{
"ENV_1":"ENV1"
},
"tags":[]
},
"environment":{
"name":null,
"dockerImage":null,
"kernelSpec":null,
"description":null,
"image":"apache/submarine:tf-mnist-with-summaries-1.0"
},
"spec":{
"Ps":{
"replicas":1,
"resources":"cpu\u003d1,memory\u003d1024M",
"name":null,
"image":null,
"cmd":null,
"envVars":null,
"resourceMap":{
"memory":"1024M",
"cpu":"1"
}
},
"Worker":{
"replicas":1,
"resources":"cpu\u003d1,memory\u003d2048M",
"name":null,
"image":null,
"cmd":null,
"envVars":null,
"resourceMap":{
"memory":"2048M",
"cpu":"1"
}
}
},
"code":null
}
}
],
"attributes":{}
}

Get experiment​

GET /api/v1/experiment/{id}

Parameters​

Field NameTypeInDescriptionRequired
idStringpathExperiment id.o

Example​

Example Request
curl -X GET http://127.0.0.1:32080/api/v1/experiment/experiment-1647574374688-0002
Example Response
{
"status":"OK",
"code":200,
"success":true,
"message":null,
"result":{
"experimentId":"experiment-1647574374688-0002",
"uid":"cf465781-6310-46d2-92b4-d20161c77d08",
"status":"Running",
"acceptedTime":"2022-03-18T15:51:04.000+08:00",
"createdTime":"2022-03-18T15:51:05.000+08:00",
"runningTime":"2022-03-18T15:51:17.000+08:00",
"finishedTime":null,
"spec":{
"meta":{
"experimentId":"experiment-1647574374688-0002",
"name":"tf-mnist-json",
"namespace":"default",
"framework":"TensorFlow",
"cmd":"python /var/tf_mnist/mnist_with_summaries.py --log_dir\u003d/train/log --learning_rate\u003d0.01 --batch_size\u003d150",
"envVars":{
"ENV_1":"ENV1"
},
"tags":[]
},
"environment":{
"name":null,
"dockerImage":null,
"kernelSpec":null,
"description":null,
"image":"apache/submarine:tf-mnist-with-summaries-1.0"
},
"spec":{
"Ps":{
"replicas":1,
"resources":"cpu\u003d1,memory\u003d1024M",
"name":null,
"image":null,
"cmd":null,
"envVars":null,
"resourceMap":{
"memory":"1024M",
"cpu":"1"
}
},
"Worker":{
"replicas":1,
"resources":"cpu\u003d1,memory\u003d2048M",
"name":null,
"image":null,
"cmd":null,
"envVars":null,
"resourceMap":{
"memory":"2048M",
"cpu":"1"
}
}
},
"code":null
}
},
"attributes":{}
}

Patch experiment​

PATCH /api/v1/experiment/{id}

Parameters​

Field NameTypeInDescriptionRequired
idStringpathExperiment id.o
metaExperimentMetabodyMeta data of the experiment template.o
environmentEnvironmentSpecbodyEnvironment of the experiment template.o
specMap<String, ExperimentTaskSpec>bodySpec of pods.o
codeCodeSpecbodyTODOx

Example​

Example Request
curl -X PATCH -H "Content-Type: application/json" -d '
{
"meta": {
"name": "tf-mnist-json",
"namespace": "default",
"framework": "TensorFlow",
"cmd": "python /var/tf_mnist/mnist_with_summaries.py --log_dir=/train/log --learning_rate=0.01 --batch_size=150",
"envVars": {
"ENV_1": "ENV1"
}
},
"environment": {
"image": "apache/submarine:tf-mnist-with-summaries-1.0"
},
"spec": {
"Ps": {
"replicas": 1,
"resources": "cpu=1,memory=1024M"
},
"Worker": {
"replicas": 2,
"resources": "cpu=1,memory=2048M"
}
}
}
' http://127.0.0.1:32080/api/v1/experiment/experiment-1647574374688-0002
Example Response
{
"status":"OK",
"code":200,
"success":true,
"message":null,
"result":{
"experimentId":"experiment-1647574374688-0002",
"uid":"b0ae271b-a01a-43ad-9877-4b8ecbc45de4",
"status":"Succeeded",
"acceptedTime":"2022-04-04T16:39:25.000+08:00",
"createdTime":"2022-04-04T16:39:26.000+08:00",
"runningTime":"2022-04-04T16:39:35.000+08:00",
"finishedTime":"2022-04-04T16:42:25.000+08:00",
"spec":{
"meta":{
"experimentId":"experiment-1649061491590-0002",
"name":"tf-mnist-json",
"namespace":"default",
"framework":"TensorFlow",
"cmd":"python /var/tf_mnist/mnist_with_summaries.py --log_dir\u003d/train/log --learning_rate\u003d0.01 --batch_size\u003d150",
"envVars":{
"ENV_1":"ENV1"
},
"tags":[]
},
"environment":{
"name":null,
"dockerImage":null,
"kernelSpec":null,
"description":null,
"image":"apache/submarine:tf-mnist-with-summaries-1.0"
},
"spec":{
"Ps":{
"replicas":1,
"resources":"cpu\u003d1,memory\u003d1024M",
"name":null,
"image":null,
"cmd":null,
"envVars":null,
"resourceMap":{
"memory":"1024M",
"cpu":"1"
}
},
"Worker":{
"replicas":2,
"resources":"cpu\u003d1,memory\u003d2048M",
"name":null,
"image":null,
"cmd":null,
"envVars":null,
"resourceMap":{
"memory":"2048M",
"cpu":"1"
}
}
},
"code":null
}
},
"attributes":{}
}

Delete experiment​

DELETE /api/v1/experiment/{id}

Parameters​

Field NameTypeInDescriptionRequired
idStringpathExperiment id.o

Example​

Example Request
curl -X DELETE http://127.0.0.1:32080/api/v1/experiment/experiment-1647574374688-0002
Example Response
{
"status":"OK",
"code":200,
"success":true,
"message":null,
"result":{
"experimentId":"experiment-1647574374688-0002",
"uid":"b0ae271b-a01a-43ad-9877-4b8ecbc45de4",
"status":"Deleted",
"acceptedTime":null,
"createdTime":null,
"runningTime":null,
"finishedTime":null,
"spec":{
"meta":{
"experimentId":"experiment-1647574374688-0002",
"name":"tf-mnist-json",
"namespace":"default",
"framework":"TensorFlow",
"cmd":"python /var/tf_mnist/mnist_with_summaries.py --log_dir\u003d/train/log --learning_rate\u003d0.01 --batch_size\u003d150",
"envVars":{
"ENV_1":"ENV1"
},
"tags":[]
},
"environment":{
"name":null,
"dockerImage":null,
"kernelSpec":null,
"description":null,
"image":"apache/submarine:tf-mnist-with-summaries-1.0"
},
"spec":{
"Ps":{
"replicas":1,
"resources":"cpu\u003d1,memory\u003d1024M",
"name":null,
"image":null,
"cmd":null,
"envVars":null,
"resourceMap":{
"memory":"1024M",
"cpu":"1"
}
},
"Worker":{
"replicas":2,
"resources":"cpu\u003d1,memory\u003d2048M",
"name":null,
"image":null,
"cmd":null,
"envVars":null,
"resourceMap":{
"memory":"2048M",
"cpu":"1"
}
}
},
"code":null
}
},
"attributes":{}
}

List experiment Log​

GET /api/v1/experiment/logs

Example​

Example Request
curl -X GET http://127.0.0.1:32080/api/v1/experiment/logs
Example Response
{
"status":"OK",
"code":200,
"success":true,
"message":null,
"result":[
{
"experimentId":"experiment-1647574374688-0002",
"logContent":[
{
"podName":"experiment-1647574374688-0002-ps-0",
"podLog":[]
},
{
"podName":"experiment-1647574374688-0002-worker-0",
"podLog":[

]
}
]
}
],
"attributes":{}
}

Get experiment Log​

GET /api/v1/experiment/logs/{id}

Parameters​

Field NameTypeInDescriptionRequired
idStringpathExperiment id.o

Example​

Example Request
curl -X GET http://127.0.0.1:32080/api/v1/experiment/logs/experiment-1647574374688-0002
Example Response
{
"status":"OK",
"code":200,
"success":true,
"message":null,
"result":{
"experimentId":"experiment-1647574374688-0002",
"logContent":[
{
"podName":"experiment-1647574374688-0002-ps-0",
"podLog":[
"WARNING:tensorflow:From /var/tf_mnist/mnist_with_summaries.py:39: read_data_sets (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.",
"Instructions for updating:",
"Please use alternatives such as official/mnist/dataset.py from tensorflow/models.",
"WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:260: maybe_download (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.",
"Instructions for updating:",
"Please write your own downloading logic.",
"WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/datasets/base.py:252: wrapped_fn (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.",
"Instructions for updating:",
"Please use urllib or similar directly.",
"WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:262: extract_images (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.",
"Instructions for updating:",
"Please use tf.data to implement this functionality.",
"WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:267: extract_labels (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.",
"Instructions for updating:",
"Please use tf.data to implement this functionality.",
"WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:290: __init__ (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.",
"Instructions for updating:",
"Please use alternatives such as official/mnist/dataset.py from tensorflow/models.",
"2022-03-18 07:52:07.369276: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA",
"Successfully downloaded train-images-idx3-ubyte.gz 9912422 bytes.",
"Extracting /tmp/tensorflow/mnist/input_data/train-images-idx3-ubyte.gz",
"Successfully downloaded train-labels-idx1-ubyte.gz 28881 bytes.",
"Extracting /tmp/tensorflow/mnist/input_data/train-labels-idx1-ubyte.gz",
"Successfully downloaded t10k-images-idx3-ubyte.gz 1648877 bytes.",
"Extracting /tmp/tensorflow/mnist/input_data/t10k-images-idx3-ubyte.gz",
"Successfully downloaded t10k-labels-idx1-ubyte.gz 4542 bytes.",
"Extracting /tmp/tensorflow/mnist/input_data/t10k-labels-idx1-ubyte.gz",
"Accuracy at step 0: 0.0893",
"Accuracy at step 10: 0.6851",
"Accuracy at step 20: 0.8255",
"Accuracy at step 30: 0.8969",
"Accuracy at step 40: 0.9009",
"Accuracy at step 50: 0.9185",
"Accuracy at step 60: 0.923",
"Accuracy at step 70: 0.9181",
"Accuracy at step 80: 0.9344",
"Accuracy at step 90: 0.9265",
"Adding run metadata for 99",
"Accuracy at step 100: 0.9375",
"Accuracy at step 110: 0.9414",
"Accuracy at step 120: 0.9402",
"Accuracy at step 130: 0.9466",
"Accuracy at step 140: 0.9412",
"Accuracy at step 150: 0.9497",
"Accuracy at step 160: 0.9477",
"Accuracy at step 170: 0.9465",
"Accuracy at step 180: 0.9546",
"Accuracy at step 190: 0.9485",
"Adding run metadata for 199",
"Accuracy at step 200: 0.9534",
"Accuracy at step 210: 0.9581",
"Accuracy at step 220: 0.9418",
"Accuracy at step 230: 0.9551",
"Accuracy at step 240: 0.9472",
"Accuracy at step 250: 0.9555",
"Accuracy at step 260: 0.9569",
"Accuracy at step 270: 0.9596",
"Accuracy at step 280: 0.9588",
"Accuracy at step 290: 0.9618",
"Adding run metadata for 299",
"Accuracy at step 300: 0.9589",
"Accuracy at step 310: 0.9603",
"Accuracy at step 320: 0.9632",
"Accuracy at step 330: 0.956",
"Accuracy at step 340: 0.9531",
"Accuracy at step 350: 0.9535",
"Accuracy at step 360: 0.9517",
"Accuracy at step 370: 0.9607",
"Accuracy at step 380: 0.9629",
"Accuracy at step 390: 0.9553",
"Adding run metadata for 399",
"Accuracy at step 400: 0.9623",
"Accuracy at step 410: 0.9627",
"Accuracy at step 420: 0.9614",
"Accuracy at step 430: 0.9604",
"Accuracy at step 440: 0.9663",
"Accuracy at step 450: 0.9665",
"Accuracy at step 460: 0.958",
"Accuracy at step 470: 0.9643",
"Accuracy at step 480: 0.9636",
"Accuracy at step 490: 0.9648",
"Adding run metadata for 499",
"Accuracy at step 500: 0.9638",
"Accuracy at step 510: 0.9629",
"Accuracy at step 520: 0.9661",
"Accuracy at step 530: 0.9633",
"Accuracy at step 540: 0.9669",
"Accuracy at step 550: 0.9659",
"Accuracy at step 560: 0.9652",
"Accuracy at step 570: 0.9675",
"Accuracy at step 580: 0.9602",
"Accuracy at step 590: 0.9641",
"Adding run metadata for 599",
"Accuracy at step 600: 0.9688",
"Accuracy at step 610: 0.9638",
"Accuracy at step 620: 0.9622",
"Accuracy at step 630: 0.9601",
"Accuracy at step 640: 0.9636",
"Accuracy at step 650: 0.9674",
"Accuracy at step 660: 0.9613",
"Accuracy at step 670: 0.9706",
"Accuracy at step 680: 0.9691",
"Accuracy at step 690: 0.9687",
"Adding run metadata for 699",
"Accuracy at step 700: 0.9671",
"Accuracy at step 710: 0.9659",
"Accuracy at step 720: 0.9693",
"Accuracy at step 730: 0.9698",
"Accuracy at step 740: 0.9681",
"Accuracy at step 750: 0.9678",
"Accuracy at step 760: 0.9595",
"Accuracy at step 770: 0.9697",
"Accuracy at step 780: 0.9671",
"Accuracy at step 790: 0.9658",
"Adding run metadata for 799",
"Accuracy at step 800: 0.9658",
"Accuracy at step 810: 0.9702",
"Accuracy at step 820: 0.9662",
"Accuracy at step 830: 0.9671",
"Accuracy at step 840: 0.9731",
"Accuracy at step 850: 0.9699",
"Accuracy at step 860: 0.9702",
"Accuracy at step 870: 0.9686",
"Accuracy at step 880: 0.9729",
"Accuracy at step 890: 0.968",
"Adding run metadata for 899",
"Accuracy at step 900: 0.9655",
"Accuracy at step 910: 0.9731",
"Accuracy at step 920: 0.9676",
"Accuracy at step 930: 0.9667",
"Accuracy at step 940: 0.9659",
"Accuracy at step 950: 0.9689",
"Accuracy at step 960: 0.9653",
"Accuracy at step 970: 0.9675",
"Accuracy at step 980: 0.974",
"Accuracy at step 990: 0.9723",
"Adding run metadata for 999"
]
},
{
"podName":"experiment-1647574374688-0002-worker-0",
"podLog":[
"WARNING:tensorflow:From /var/tf_mnist/mnist_with_summaries.py:39: read_data_sets (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.",
"Instructions for updating:",
"Please use alternatives such as official/mnist/dataset.py from tensorflow/models.",
"WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:260: maybe_download (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.",
"Instructions for updating:",
"Please write your own downloading logic.",
"WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/datasets/base.py:252: wrapped_fn (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.",
"Instructions for updating:",
"Please use urllib or similar directly.",
"WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:262: extract_images (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.",
"Instructions for updating:",
"Please use tf.data to implement this functionality.",
"WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:267: extract_labels (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.",
"Instructions for updating:",
"Please use tf.data to implement this functionality.",
"WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/datasets/mnist.py:290: __init__ (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.",
"Instructions for updating:",
"Please use alternatives such as official/mnist/dataset.py from tensorflow/models.",
"2022-03-18 07:52:07.369085: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA",
"Successfully downloaded train-images-idx3-ubyte.gz 9912422 bytes.",
"Extracting /tmp/tensorflow/mnist/input_data/train-images-idx3-ubyte.gz",
"Successfully downloaded train-labels-idx1-ubyte.gz 28881 bytes.",
"Extracting /tmp/tensorflow/mnist/input_data/train-labels-idx1-ubyte.gz",
"Successfully downloaded t10k-images-idx3-ubyte.gz 1648877 bytes.",
"Extracting /tmp/tensorflow/mnist/input_data/t10k-images-idx3-ubyte.gz",
"Successfully downloaded t10k-labels-idx1-ubyte.gz 4542 bytes.",
"Extracting /tmp/tensorflow/mnist/input_data/t10k-labels-idx1-ubyte.gz",
"Accuracy at step 0: 0.1348",
"Accuracy at step 10: 0.7419",
"Accuracy at step 20: 0.8574",
"Accuracy at step 30: 0.8959",
"Accuracy at step 40: 0.9135",
"Accuracy at step 50: 0.9187",
"Accuracy at step 60: 0.9276",
"Accuracy at step 70: 0.9332",
"Accuracy at step 80: 0.9399",
"Accuracy at step 90: 0.9376",
"Adding run metadata for 99",
"Accuracy at step 100: 0.9378",
"Accuracy at step 110: 0.9463",
"Accuracy at step 120: 0.9479",
"Accuracy at step 130: 0.9468",
"Accuracy at step 140: 0.9467",
"Accuracy at step 150: 0.9475",
"Accuracy at step 160: 0.947",
"Accuracy at step 170: 0.948",
"Accuracy at step 180: 0.9472",
"Accuracy at step 190: 0.954",
"Adding run metadata for 199",
"Accuracy at step 200: 0.9492",
"Accuracy at step 210: 0.9571",
"Accuracy at step 220: 0.954",
"Accuracy at step 230: 0.9557",
"Accuracy at step 240: 0.9557",
"Accuracy at step 250: 0.9591",
"Accuracy at step 260: 0.955",
"Accuracy at step 270: 0.9595",
"Accuracy at step 280: 0.9596",
"Accuracy at step 290: 0.9604",
"Adding run metadata for 299",
"Accuracy at step 300: 0.9622",
"Accuracy at step 310: 0.9529",
"Accuracy at step 320: 0.9609",
"Accuracy at step 330: 0.9613",
"Accuracy at step 340: 0.9571",
"Accuracy at step 350: 0.9599",
"Accuracy at step 360: 0.9553",
"Accuracy at step 370: 0.9546",
"Accuracy at step 380: 0.962",
"Accuracy at step 390: 0.96",
"Adding run metadata for 399",
"Accuracy at step 400: 0.9593",
"Accuracy at step 410: 0.9641",
"Accuracy at step 420: 0.9628",
"Accuracy at step 430: 0.9622",
"Accuracy at step 440: 0.9639",
"Accuracy at step 450: 0.9592",
"Accuracy at step 460: 0.9651",
"Accuracy at step 470: 0.9658",
"Accuracy at step 480: 0.9668",
"Accuracy at step 490: 0.9641",
"Adding run metadata for 499",
"Accuracy at step 500: 0.9641",
"Accuracy at step 510: 0.9561",
"Accuracy at step 520: 0.9628",
"Accuracy at step 530: 0.964",
"Accuracy at step 540: 0.9663",
"Accuracy at step 550: 0.9681",
"Accuracy at step 560: 0.968",
"Accuracy at step 570: 0.967",
"Accuracy at step 580: 0.9663",
"Accuracy at step 590: 0.9679",
"Adding run metadata for 599",
"Accuracy at step 600: 0.9666",
"Accuracy at step 610: 0.9648",
"Accuracy at step 620: 0.9682",
"Accuracy at step 630: 0.9691",
"Accuracy at step 640: 0.9683",
"Accuracy at step 650: 0.966",
"Accuracy at step 660: 0.9668",
"Accuracy at step 670: 0.9658",
"Accuracy at step 680: 0.9709",
"Accuracy at step 690: 0.9632",
"Adding run metadata for 699",
"Accuracy at step 700: 0.9697",
"Accuracy at step 710: 0.9632",
"Accuracy at step 720: 0.9641",
"Accuracy at step 730: 0.9659",
"Accuracy at step 740: 0.9654",
"Accuracy at step 750: 0.9694",
"Accuracy at step 760: 0.968",
"Accuracy at step 770: 0.9661",
"Accuracy at step 780: 0.969",
"Accuracy at step 790: 0.9663",
"Adding run metadata for 799",
"Accuracy at step 800: 0.9687",
"Accuracy at step 810: 0.9651",
"Accuracy at step 820: 0.9705",
"Accuracy at step 830: 0.9645",
"Accuracy at step 840: 0.9652",
"Accuracy at step 850: 0.9719",
"Accuracy at step 860: 0.9654",
"Accuracy at step 870: 0.964",
"Accuracy at step 880: 0.9645",
"Accuracy at step 890: 0.9615",
"Adding run metadata for 899",
"Accuracy at step 900: 0.9661",
"Accuracy at step 910: 0.9649",
"Accuracy at step 920: 0.9569",
"Accuracy at step 930: 0.9654",
"Accuracy at step 940: 0.9674",
"Accuracy at step 950: 0.971",
"Accuracy at step 960: 0.9684",
"Accuracy at step 970: 0.9648",
"Accuracy at step 980: 0.9693",
"Accuracy at step 990: 0.9627",
"Adding run metadata for 999"
]
}
]
},
"attributes":{}
}