GitHub
03/24/2023, 10:20 PM<https://github.com/flyteorg/flytekit/tree/master|master>
by wild-endeavor
<https://github.com/flyteorg/flytekit/commit/53f134a7c2c913c7016ac5bec9fb5cf306e491d3|53f134a7>
- Pass locally defined scopes to RemoteClientConfigStore (#1553)
flyteorg/flytekitGitHub
03/25/2023, 2:02 AMTensorFlow 2.11.1
Release 2.11.1
Note: TensorFlow 2.10 was the last TensorFlow release that supported GPU on native-Windows. Starting with TensorFlow 2.11, you will need to install TensorFlow in WSL2, or install tensorflow-cpu and, optionally, try the TensorFlow-DirectML-Plugin.
• Security vulnerability fixes will no longer be patched to this Tensorflow version. The latest Tensorflow version includes the security vulnerability fixes. You can update to the latest version (recommended) or patch security vulnerabilities yourself steps. You can refer to the release notes of the latest Tensorflow version for a list of newly fixed vulnerabilities. If you have any questions, please create a GitHub issue to let us know.
This release also introduces several vulnerability fixes:
• Fixes an FPE in TFLite in conv kernel CVE-2023-27579
• Fixes a double free in Fractional(Max/Avg)Pool CVE-2023-25801
• Fixes a null dereference on ParallelConcat with XLA CVE-2023-25676
• Fixes a segfault in Bincount with XLA CVE-2023-25675
• Fixes an NPE in RandomShuffle with XLA enable CVE-2023-25674
• Fixes an FPE in TensorListSplit with XLA CVE-2023-25673
• Fixes segmentation fault in tfg-translate CVE-2023-25671
• Fixes an NPE in QuantizedMatMulWithBiasAndDequantize CVE-2023-25670
• Fixes an FPE in AvgPoolGrad with XLA CVE-2023-25669
• Fixes a heap out-of-buffer read vulnerability in the QuantizeAndDequantize operation CVE-2023-25668
• Fixes a segfault when opening multiframe gif CVE-2023-25667
• Fixes an NPE in SparseSparseMaximum CVE-2023-25665
• Fixes an FPE in AudioSpectrogram CVE-2023-25666
• Fixes a heap-buffer-overflow in AvgPoolGrad CVE-2023-25664
• Fixes a NPE in TensorArrayConcatV2 CVE-2023-25663
• Fixes a Integer overflow in EditDistance CVE-2023-25662
• Fixes a Seg fault inCVE-2023-25660tf.raw_ops.Print
• Fixes a OOB read in DynamicStitch CVE-2023-25659
• Fixes a OOB Read in GRUBlockCellGrad CVE-2023-25658
TensorFlow 2.11.0
Release 2.11.0
Breaking Changes
• Thebase class now points to the new Keras optimizer, while the old optimizers have been moved to thetf.keras.optimizers.Optimizer
namespace.tf.keras.optimizers.legacy
If you find your workflow failing due to this change, you may be facing one of the following issues:
• Checkpoint loading failure. The new optimizer handles optimizer state differently from the old optimizer, which simplifies the logic of checkpoint saving/loading, but at the cost of breaking checkpoint backward compatibility in some cases. If you want to keep using an old checkpoint, please change your optimizer to(e.g.<http://tf.keras.optimizer.legacy.XXX|tf.keras.optimizer.legacy.XXX>
).tf.keras.optimizer.legacy.Adam
• TF1 compatibility. The new optimizer,, does not support TF1 any more, so please use the legacy optimizertf.keras.optimizers.Optimizer
. We highly recommend migrating your workflow to TF2 for stable support and new features.<http://tf.keras.optimizer.legacy.XXX|tf.keras.optimizer.legacy.XXX>
• Old optimizer API not found. The new optimizer,, has a different set of public APIs from the old optimizer. These API changes are mostly related to getting rid of slot variables and TF1 support. Please check the API documentation to find alternatives to the missing API. If you must call the deprecated API, please change your optimizer to the legacy optimizer.tf.keras.optimizers.Optimizer
• Learning rate schedule access. When using a, the new optimizer'stf.keras.optimizers.schedules.LearningRateSchedule
property returns the current learning rate value instead of alearning_rate
object as before. If you need to access theLearningRateSchedule
object, please useLearningRateSchedule
.optimizer._learning_rate
• If you implemented a custom optimizer based on the old optimizer. Please set your optimizer to subclass. If you want to migrate to the new optimizer and find it does not support your optimizer, please file an issue in the Keras GitHub repo.<http://tf.keras.optimizer.legacy.XXX|tf.keras.optimizer.legacy.XXX>
• Errors, such as. The new optimizer requires all optimizer variables to be created at the firstCannot recognize variable...
orapply_gradients()
call. If your workflow calls the optimizer to update different parts of the model in multiple stages, please callminimize()
before the training loop.optimizer.build(model.trainable_variables)
• Timeout or performance loss. We don't anticipate this to happen, but if you see such issues, please use the legacy optimizer, and file an issue in the Keras GitHub repo.
The old Keras optimizer will never be deleted, but will not see any new feature additions. New optimizers (for example,) will only be implemented based on the newtf.keras.optimizers.Adafactor
base class.tf.keras.optimizers.Optimizer
•code is a legacy copy of Keras since the TensorFlow v2.7 release, and will be deleted in the v2.12 release. Please remove any import oftensorflow/python/keras
and use the public API withtensorflow.python.keras
orfrom tensorflow import keras
.import tensorflow as tf; tf.keras
Major Features and Improvements... (truncated) Changelog Sourced from tensorflow's changelog.
Release 2.11.1
Note: TensorFlow 2.10 was the last TensorFlow release that supported GPU on native-Windows. Starting with TensorFlow 2.11, you will need to install TensorFlow in WSL2, or install tensorflow-cpu and, optionally, try the TensorFlow-DirectML-Plugin.
• Security vulnerability fixes will no longer be patched to this Tensorflow version. The latest Tensorflow version includes the security vulnerability fixes. You can update to the latest version (recommended) or patch security vulnerabilities yourself steps. You can refer to the release notes of the latest Tensorflow version for a list of newly fixed vulnerabilities. If you have any questions, please create a…flyteorg/flytelab GitHub Actions: build-and-deploy GitHub Actions: Push to GHCR GitHub Actions: Push to GHCR ✅ 2 other checks have passed 2/5 successful checks
GitHub
03/25/2023, 2:02 AMTensorFlow 2.9.3
Release 2.9.3
This release introduces several vulnerability fixes:
• Fixes an overflow in(CVE-2022-41887)tf.keras.losses.poisson
• Fixes a heap OOB failure incaused by missing validation (CVE-2022-41880)ThreadUnsafeUnigramCandidateSampler
• Fixes a segfault in(CVE-2022-41884)ndarray_tensor_bridge
• Fixes an overflow in(CVE-2022-41885)FusedResizeAndPadConv2D
• Fixes a overflow in(CVE-2022-41886)ImageProjectiveTransformV2
• Fixes an FPE inon GPU (CVE-2022-41888)tf.image.generate_bounding_box_proposals
• Fixes a segfault incaused by invalid attributes (CVE-2022-41889)pywrap_tfe_src
• Fixes afail inCHECK
(CVE-2022-41890)BCast
• Fixes a segfault in(CVE-2022-41891)TensorListConcat
• Fixes afail inCHECK_EQ
(CVE-2022-41893)TensorListResize
• Fixes an overflow inon TFLite (CVE-2022-41894)CONV_3D_TRANSPOSE
• Fixes a heap OOB in(CVE-2022-41895)MirrorPadGrad
• Fixes a crash in(CVE-2022-41896)Mfcc
• Fixes a heap OOB in(CVE-2022-41897)FractionalMaxPoolGrad
• Fixes afail inCHECK
(CVE-2022-41898)SparseFillEmptyRowsGrad
• Fixes afail inCHECK
(CVE-2022-41899)SdcaOptimizer
• Fixes a heap OOB inand `FractionalMaxPool`(CVE-2022-41900)FractionalAvgPool
• Fixes ainCHECK_EQ
(CVE-2022-41901)SparseMatrixNNZ
• Fixes an OOB write in grappler (CVE-2022-41902)
• Fixes a overflow in(CVE-2022-41907)ResizeNearestNeighborGrad
• Fixes afail inCHECK
(CVE-2022-41908)PyFunc
• Fixes a segfault in(CVE-2022-41909)CompositeTensorVariantToComponents
• Fixes a invalid char to bool conversion in printing a tensor (CVE-2022-41911)
• Fixes a heap overflow in(CVE-2022-41910)QuantizeAndDequantizeV2
• Fixes afailure inCHECK
via missing validation (CVE-2022-35935)SobolSample
• Fixes afail inCHECK
andTensorListScatter
in eager mode (CVE-2022-35935)TensorListScatterV2
TensorFlow 2.9.2
Release 2.9.2
This releases introduces several vulnerability fixes:
• Fixes afailure in tf.reshape caused by overflows (CVE-2022-35934)CHECK
• Fixes afailure inCHECK
caused by missing validation (CVE-2022-35935)SobolSample
• Fixes an OOB read inop in TF Lite (CVE-2022-35937)Gather_nd
• Fixes afailure inCHECK
caused by missing validation (CVE-2022-35960)TensorListReserve
• Fixes an OOB write inop in TF Lite (CVE-2022-35939)Scatter_nd
• Fixes an integer overflow in(CVE-2022-35940)RaggedRangeOp
• Fixes afailure inCHECK
(CVE-2022-35941)AvgPoolOp
• Fixes afailures inCHECK
(CVE-2022-35952)UnbatchGradOp
• Fixes a segfault TFLite converter on per-channel quantized transposed convolutions (CVE-2022-36027)
• Fixes afailures inCHECK
(CVE-2022-35959)AvgPool3DGrad
• Fixes afailures inCHECK
(CVE-2022-35963)FractionalAvgPoolGrad
• Fixes a segfault in(CVE-2022-35964)BlockLSTMGradV2
• Fixes a segfault in... (truncated) Changelog Sourced from tensorflow's changelog.andLowerBound
(CVE-2022-35965)UpperBound
Release 2.9.3
This release introduces several vulnerability fixes:
• Fixes an overflow in(CVE-2022-41887)tf.keras.losses.poisson
• Fixes a heap OOB failure incaused by missing validation (CVE-2022-41880)ThreadUnsafeUnigramCandidateSampler
• Fixes a segfault in(CVE-2022-41884)ndarray_tensor_bridge
• Fixes an overflow in(CVE-2022-41885)FusedResizeAndPadConv2D
• Fixes a overflow in(CVE-2022-41886)ImageProjectiveTransformV2
• Fixes an FPE inon GPU (CVE-2022-41888)tf.image.generate_bounding_box_proposals
• Fixes a segfault incaused by invalid attributes (CVE-2022-41889)pywrap_tfe_src
• Fixes afail inCHECK
(CVE-2022-41890)BCast
• Fixes a segfault in(CVE-2022-41891)TensorListConcat
• Fixes afail inCHECK_EQ
(CVE-2022-41893)TensorListResize
• Fixes an overflow inon TFLite (CVE-2022-41894)CONV_3D_TRANSPOSE
• Fixes a heap OOB in(CVE-2022-41895)MirrorPadGrad
• Fixes a crash in(CVE-2022-41896)Mfcc
• Fixes a heap OOB inflyteorg/flytelab GitHub Actions: Push to GHCR GitHub Actions: build-and-deploy ✅ 3 other checks have passed 3/5 successful checks(<https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-41897|CVE-2022-4189…FractionalMaxPoolGrad
GitHub
03/25/2023, 5:55 AM<https://github.com/flyteorg/flytekit/tree/master|master>
by samhita-alla
<https://github.com/flyteorg/flytekit/commit/ee2714f455f66474c287f49ff23d8f8215cc6ae3|ee2714f4>
- TypeTransformer for TensorFlow model (#1562)
flyteorg/flytekitGitHub
03/25/2023, 5:55 AMtf.keras.Model
as a native Flyte type.
Reference doc for serialization and deserialization of models: https://www.tensorflow.org/guide/keras/save_and_serialize
More on TypeTransfomers can be found here.
Related PR that adds PyTorch tensor and module as Flyte types: flyteorg/flytekit#1032
flyteorg/flyteGitHub
03/27/2023, 5:25 AMClientCredentialsTokenSourceProvider
and customTokenSource
, as it's not supported by underlying client credentials token source.
Type
☑︎ Bug Fix
☐ Feature
☐ Plugin
Are all requirements met?
☑︎ Code completed
☑︎ Smoke tested
☑︎ Unit tests added
☐ Code documentation added
☐ Any pending items have an associated Issue
Complete description
Previously customTokenSource
attempted to refresh near-expiration tokens; however, the underlying client credentials token source would always return the existing token, if valid.
This change drops all of the refresh logic but maintains the token cache recently added to allow tokens to be reused across token providers, consistent with the interface used for other token providers. In effect the underlying client credentials token source cache is not used (queries should always require a new token).
Tracking Issue
NA
Follow-up issue
NA
flyteorg/flyteidl
Codecov: 76.11% (-0.61%) compared to bdb7630
✅ 12 other checks have passed
12/13 successful checksGitHub
03/27/2023, 9:36 AMFlyte 404▾
GitHub
03/27/2023, 11:36 AMSdkBindingDataFactory
to create SdkBindingData
from collection or maps of other SdkBindingData
Type
☐ Bug Fix
☑︎ Feature
☐ Plugin
Are all requirements met?
☑︎ Code completed
☐ Smoke tested
☑︎ Unit tests added
☑︎ Code documentation added
☐ Any pending items have an associated Issue
Complete description
We were missing a way to construct SdkBindingData
from collections (or maps) of other `SdkBindingData`´s in the scalaś SdkBindingDataFactory
, as we have in the java one.
Tracking Issue
NA
Follow-up issue
NA
flyteorg/flytekit-java
✅ All checks have passed
3/3 successful checksGitHub
03/27/2023, 11:40 AM{
"json": {
"exec_id": "a5q5l9h95pvcfjxlkv79",
"node": "start-node"
},
"level": "error",
"msg": "Failed to read from the raw store [<s3://flyte/metadata/propeller/cadmatch-training-development-a5q5l9h95pvcfjxlkv79/start-node/data/inputs.pb>] Error: not found",
"ts": "2023-03-27T11:39:33Z"
}
Here the execution details:
[
{
"node_exec": {
"id": {
"nodeId": "start-node",
"executionId": {
"project": "cadmatch-training",
"domain": "development",
"name": "a5q5l9h95pvcfjxlkv79"
}
},
"inputUri": "<s3://flyte/metadata/propeller/cadmatch-training-development-a5q5l9h95pvcfjxlkv79/start-node/data/inputs.pb>",
"closure": {
"outputUri": "<s3://flyte/metadata/propeller/cadmatch-training-development-a5q5l9h95pvcfjxlkv79/start-node/data/0/outputs.pb>",
"phase": "SUCCEEDED",
"createdAt": "2023-03-24T14:19:33.748538643Z",
"updatedAt": "2023-03-24T14:19:33.748538643Z"
},
"metadata": {
"specNodeId": "start-node"
}
},
"outputs": {
"objectname": "purima_leitwerk_d55371396004w62001_v2",
"testset": "usecase_organized_whole_viscore9mm1000mm"
}
},
{
"node_exec": {
"id": {
"nodeId": "generatetestscenes",
"executionId": {
"project": "cadmatch-training",
"domain": "development",
"name": "a5q5l9h95pvcfjxlkv79"
}
},
"inputUri": "<s3://flyte/metadata/propeller/cadmatch-training-development-a5q5l9h95pvcfjxlkv79/generatetestscenes/data/inputs.pb>",
"closure": {
"startedAt": "2023-03-24T14:19:33.835728545Z",
"createdAt": "2023-03-24T14:19:33.783188890Z",
"updatedAt": "2023-03-26T14:19:55.235293084Z"
},
"metadata": {
"specNodeId": "generatetestscenes"
}
},
"task_execs": [
{
"id": {
"taskId": {
"resourceType": "TASK",
"project": "cadmatch-training",
"domain": "development",
"name": "generate_test_scenes",
"version": "v0.1.0-22-ge98e41d-dirty"
},
"nodeExecutionId": {
"nodeId": "generatetestscenes",
"executionId": {
"project": "cadmatch-training",
"domain": "development",
"name": "a5q5l9h95pvcfjxlkv79"
}
}
},
"inputUri": "<s3://flyte/metadata/propeller/cadmatch-training-development-a5q5l9h95pvcfjxlkv79/generatetestscenes/data/inputs.pb>",
"closure": {
"error": {
"code": "Task Aborted",
"message": "task execution timeout [24h0m0s] expired"
},
"phase": "ABORTED",
"logs": [
{
"uri": "<http://kubernetes-dashboard.k3s.roboception.de/#/log/cadmatch-training-development/a5q5l9h95pvcfjxlkv79-generatetestscenes-0/pod?namespace=cadmatch-training-development>",
"name": "Kubernetes Logs (User)",
"messageFormat": "JSON"
},
{
"uri": "<https://roboception.grafana.net/explore?left={\>"datasource\":\"grafanacloud-logs\",\"queries\":[{\"refId\":\"A\",\"datasource\":{\"type\":\"loki\",\"uid\":\"grafanacloud-logs\"},\"editorMode\":\"builder\",\"expr\":\"{namespace%3D\\\"cadmatch-training-development\\\", pod%3D\\\"a5q5l9h95pvcfjxlkv79-generatetestscenes-0\\\"} |%3D ``\",\"queryType\":\"range\"}],\"range\":{\"from\":\"1679667573000\",\"to\":\"now\"}}",
"name": "Grafana Loki (User)"
}
],
"startedAt": "2023-03-24T14:53:01.566153Z",
"duration": "84411.927456822s",
"createdAt": "2023-03-24T14:19:33.829117410Z",
"updatedAt": "2023-03-25T14:19:53.493609822Z",
"reason": "[ContainersNotReady|PodInitializing]: containers with unready status: [a5q5l9h95pvcfjxlkv79-generatetestscenes-0]|",
"taskType": "raw-container",
"metadata": {
"generatedName": "a5q5l9h95pvcfjxlkv79-generatetestscenes-0",
"pluginIdentifier": "container"
},
"eventVersion": 1
}
},
{
"id": {
"taskId": {
"resourceType": "TASK",
"project": "cadmatch-training",
"domain": "development",
"name": "generate_test_scenes",
"version": "v0.1.0-22-ge98e41d-dirty"
},
"nodeExecutionId": {
"nodeId": "generatetestscenes",
"executionId": {
"project": "cadmatch-training",
"domain": "development",
"name": "a5q5l9h95pvcfjxlkv79"
}
},
"retryAttempt": 1
},
"inputUri": "<s3://flyte/metadata/propeller/cadmatch-training-development-a5q5l9h95pvcfjxlkv79/generatetestscenes/data/inputs.pb>",
"closure": {
"error": {
"code": "Task Aborted",
"message": "node timed out"
},
"phase": "ABORTED",
"logs": [
{
"uri": "<http://kubernetes-dashboard.k3s.roboception.de/#/log/cadmatch-training-development/a5q5l9h95pvcfjxlkv79-generatetestscenes-1/pod?namespace=cadmatch-training-development>",
"name": "Kubernetes Logs (User)",
"messageFormat": "JSON"
},
{
"uri": "<https://roboception.grafana.net/explore?left={\>"datasource\":\"grafanacloud-logs\",\"queries\":[{\"refId\":\"A\",\"datasource\":{\"type\":\"loki\",\"uid\":\"grafanacloud-logs\"},\"editorMode\":\"builder\",\"expr\":\"{namespace%3D\\\"cadmatch-training-development\\\", pod%3D\\\"a5q5l9h95pvcfjxlkv79-generatetestscenes-1\\\"} |%3D ``\",\"queryType\":\"range\"}],\"range\":{\"from\":\"1679753993000\",\"to\":\"now\"}}",
"name": "Grafana Loki (User)"
}
],
"startedAt": "2023-03-25T14:20:19.382998Z",
"duration": "86375.893049005s",
"createdAt": "2023-03-25T14:19:53.566448765Z",
"updatedAt": "2023-03-26T14:19:55.276047005Z",
"reason": "[ContainersNotReady|PodInitializing]: containers with unready status: [a5q5l9h95pvcfjxlkv79-generatetestscenes-1]|",
"taskType": "raw-container",
"metadata": {
"generatedName": "a5q5l9h95pvcfjxlkv79-generatetestscenes-1",
"pluginIdentifier": "container"
},
"eventVersion": 1
}
}
],
"inputs": {
"objectname": "purima_leitwerk_d55371396004w62001_v2",
"testset": "usecase_organized_whole_viscore9mm1000mm"
}
}
]
Screenshots
flyte_console_unkown_status▾
GitHub
03/27/2023, 1:32 PMGitHub
03/27/2023, 1:47 PM<https://github.com/flyteorg/flytekit-java/tree/master|master>
by narape
<https://github.com/flyteorg/flytekit-java/commit/20f90cb3a6d839b425e0b8141fc47fb916c70f08|20f90cb3>
- fix: upgrade com.google.api.grpc:proto-google-common-protos from 2.14.1 to 2.14.2 (#215)
flyteorg/flytekit-javaGitHub
03/27/2023, 2:24 PM<https://github.com/flyteorg/flytekit-java/tree/master|master>
by narape
<https://github.com/flyteorg/flytekit-java/commit/4fe9279493c46d039f38037671febfb50d7061ab|4fe92794>
- Add binding collection/map for scala (#219)
flyteorg/flytekit-javaGitHub
03/27/2023, 2:49 PM<https://github.com/flyteorg/flyte/tree/master|master>
by kumare3
<https://github.com/flyteorg/flyte/commit/a20389c2ad02c318d1c135703a6f31d1db45363c|a20389c2>
- [auto-update-contributors] update all-contributors (#2524)
flyteorg/flyteGitHub
03/27/2023, 2:49 PMGitHub
03/27/2023, 3:26 PMGitHub
03/27/2023, 3:52 PMpyflyte --config $HOME/.flyte/config-sandbox.yaml register multi_images.py
command is resulting in AssertionError: Image Config with name mindmeld not found in the configuration
error, whereas pyflyte --config $HOME/.flyte/config-sandbox.yaml run --remote multi_images.py multi_images_wf
is working fine.
Expected behavior
The behavior of pyflyte register
should be similar to that of pyflyte run
.
Additional context to reproduce
Run the multi-images example by including images in the config file.
• pyflyte --config $HOME/.flyte/config-sandbox.yaml run --remote multi_images.py multi_images_wf
• pyflyte --config $HOME/.flyte/config-sandbox.yaml register multi_images.py
Screenshots
No response
Are you sure this issue hasn't been raised already?
☑︎ Yes
Have you read the Code of Conduct?
☑︎ Yes
flyteorg/flyteGitHub
03/27/2023, 4:00 PMGitHub
03/27/2023, 4:23 PMGitHub
03/27/2023, 4:46 PMGitHub
03/27/2023, 5:19 PMimage▾
SELECT_REJECT
to be true or false. When it's going to be reject, it should be true before SUBMIT
Tracking Issue
fixes flyteorg/flyte#3346
flyteorg/flyteconsole
Codecov: 66.61% (-0.14%) compared to 6816a5f
Codecov: 50.00% of diff hit (target 66.74%)
GitHub Actions: Build & Push FlyteConsole Image
GitHub Actions: Get Release Tag
GitHub Actions: Generate Release
✅ 6 other checks have passed
6/11 successful checksGitHub
03/27/2023, 5:43 PM<https://github.com/flyteorg/flytekit/tree/master|master>
by wild-endeavor
<https://github.com/flyteorg/flytekit/commit/6371d31f577c01e6afac4180c6a4d615ae9e6c94|6371d31f>
- Remove fsspec flytekit plugin from main Dockerfile (#1561)
flyteorg/flytekitGitHub
03/27/2023, 6:22 PM_with_override(resource=...
and @task(requests=...)
, they are injected as the node resource override in buildNodeSpec
Expected behavior
For the case of @task(requests=...)
, the resource override on the node should be empty, and the resource is injected from tasktemplate at BuildRawContainer
Additional context to reproduce
No response
Screenshots
No response
Are you sure this issue hasn't been raised already?
☑︎ Yes
Have you read the Code of Conduct?
☑︎ Yes
flyteorg/flyteGitHub
03/27/2023, 6:27 PM_with_override(resource=...
and @task(requests=...)
, they are both inject as the node resource override in buildNodeSpec
Expected behavior
For the case of @task(requests=...)
, the resource override on the node should be empty, and the resource is injected from tasktemplate at BuildRawContainer
Tracking Issue
flyteorg/flyte#3540
flyteorg/flyteplugins
Codecov: 33.33% of diff hit (target 62.75%)
Codecov: 62.65% (-0.11%) compared to 60d345d
✅ 4 other checks have passed
4/6 successful checksGitHub
03/27/2023, 6:32 PM_with_override(resource=...
and @task(requests=...)
, they are both inject as the node resource override in buildNodeSpec
Expected behavior
For the case of @task(requests=...)
, the resource override on the node should be empty, and the resource is injected from tasktemplate at BuildRawContainer
Tracking Issue
flyteorg/flyte#3540
flyteorg/flytepropeller
GitHub Actions: Goreleaser
GitHub Actions: Build & Push Flytepropeller Image
GitHub Actions: Bump Version
✅ 11 other checks have passed
11/14 successful checksGitHub
03/27/2023, 7:51 PMGitHub
03/27/2023, 8:01 PM<https://github.com/flyteorg/flyteadmin/tree/master|master>
by hamersaw
<https://github.com/flyteorg/flyteadmin/commit/cca9e1702bbc3ee774f7214b172c1e5bfff4716f|cca9e170>
- Add endpoint exposing runtime metrics (#524)
flyteorg/flyteadminGitHub
03/27/2023, 8:49 PMGitHub
03/27/2023, 9:22 PM<https://github.com/flyteorg/flyte/tree/master|master>
by wild-endeavor
<https://github.com/flyteorg/flyte/commit/507a466077883bd2c34677c928ac277be7be9c28|507a4660>
- Fix typo for enabling tensorflow plugin doc (#3539)
flyteorg/flyteGitHub
03/27/2023, 10:51 PMGitHub
03/27/2023, 11:04 PM<https://github.com/flyteorg/flyteplugins/tree/master|master>
by hamersaw
<https://github.com/flyteorg/flyteplugins/commit/18a594ecef8bf744b42d9a824df2d53635aa31d2|18a594ec>
- persisting k8s plugin phase, version, and reason (#331)
flyteorg/flyteplugins