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docs/multi-tenancy/README.md
This topic provides commands to set up different configurations of hosts, nodes, and drives. The examples provided here can be used as a starting point for other configurations. 1. [Standalone Deployment](#standalone-deployment) 2. [Distributed Deployment](#distributed-deployment) 3. [Cloud Scale Deployment](#cloud-scale-deployment) ## 1. Standalone Deployment
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src/main/webapp/js/login.js
Registered: Thu Oct 31 13:40:30 UTC 2024 - Last Modified: Wed Sep 12 06:47:49 UTC 2018 - 1.3K bytes - Viewed (0) -
.github/workflows/people.yml
- uses: actions/checkout@v4 # Ref: https://github.com/actions/runner/issues/2033 - name: Fix git safe.directory in container run: mkdir -p /home/runner/work/_temp/_github_home && printf "[safe]\n\tdirectory = /github/workspace" > /home/runner/work/_temp/_github_home/.gitconfig # Allow debugging with tmate - name: Setup tmate session uses: mxschmitt/action-tmate@v3
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Mon Jul 29 23:35:07 UTC 2024 - 1.2K bytes - Viewed (0) -
docs/iam/identity-management-plugin.md
If provided, the auth token parameter is sent as an authorization header. `MINIO_IDENTITY_PLUGIN_ROLE_POLICY` is a required parameter and can be list of comma separated policy names. On setting up the plugin, the MinIO server prints the Role ARN to its log. The Role ARN is generated by default based on the given plugin URL. To avoid this and use a configurable value set a unique role ID via `MINIO_IDENTITY_PLUGIN_ROLE_ID`. ## REST API call to plugin
Registered: Sun Nov 03 19:28:11 UTC 2024 - Last Modified: Fri May 27 00:58:09 UTC 2022 - 4.2K bytes - Viewed (0) -
tensorflow/c/eager/parallel_device/parallel_device.cc
return result; } // Used as an argument to TFE_NewCustomDeviceTensorHandle, indicating how // ParallelTensors wrapped in TFE_TensorHandles should be cleaned up once their // reference counts drop to zero. void ParallelTensorDeallocator(void* data) { delete reinterpret_cast<ParallelTensor*>(data); } // Used as an argument to TFE_NewCustomDeviceTensorHandle, for computing the
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src/main/webapp/js/profile.js
Registered: Thu Oct 31 13:40:30 UTC 2024 - Last Modified: Wed Sep 12 06:47:49 UTC 2018 - 1.3K bytes - Viewed (0) -
docs/tr/docs/advanced/wsgi.md
# WSGI - Flask, Django ve Daha Fazlasını FastAPI ile Kullanma WSGI uygulamalarını [Sub Applications - Mounts](sub-applications.md){.internal-link target=_blank}, [Behind a Proxy](behind-a-proxy.md){.internal-link target=_blank} bölümlerinde gördüğünüz gibi bağlayabilirsiniz. Bunun için `WSGIMiddleware` ile Flask, Django vb. WSGI uygulamanızı sarmalayabilir ve FastAPI'ya bağlayabilirsiniz. ## `WSGIMiddleware` Kullanımı `WSGIMiddleware`'ı projenize dahil edin.
Registered: Sun Nov 03 07:19:11 UTC 2024 - Last Modified: Sun Oct 06 20:36:54 UTC 2024 - 1.3K bytes - Viewed (0) -
cmd/peer-s3-client.go
} buckets := make([]BucketInfo, 0, len(bi.Value())) for _, b := range bi.Value() { if b != nil { buckets = append(buckets, *b) } } bi.Recycle() // BucketInfo has no internal pointers, so it's safe to recycle. return buckets, nil } func (client *remotePeerS3Client) HealBucket(ctx context.Context, bucket string, opts madmin.HealOpts) (madmin.HealResultItem, error) { conn := client.gridConn()
Registered: Sun Nov 03 19:28:11 UTC 2024 - Last Modified: Tue Aug 13 22:26:05 UTC 2024 - 15.4K bytes - Viewed (0) -
cmd/os-dirent_namelen_linux.go
"fmt" "syscall" "unsafe" ) func direntNamlen(dirent *syscall.Dirent) (uint64, error) { const fixedHdr = uint16(unsafe.Offsetof(syscall.Dirent{}.Name)) nameBuf := (*[unsafe.Sizeof(dirent.Name)]byte)(unsafe.Pointer(&dirent.Name[0])) const nameBufLen = uint16(len(nameBuf)) limit := dirent.Reclen - fixedHdr if limit > nameBufLen { limit = nameBufLen } // Avoid bugs in long file names
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tensorflow/c/eager/gradient_checker.h
* I.e. if y = <output of the forward model> and w = inputs[input_index], * this will calculate dy/dw numerically. * * `use_function` indicates whether to use graph mode(true) or eager(false). * * `numerical_grad` is the pointer to the AbstractTensorHandle* which will * hold the numerical gradient data at the end of the function. */ absl::Status CalcNumericalGrad(AbstractContext* ctx, Model forward,
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