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manifests/charts/istiod-remote/templates/crd-all.gen.yaml
description: Set of ports associated with the endpoint. type: object serviceAccount: description: The service account associated with the workload if a sidecar is present in the workload. type: string weight: description: The load balancing weight associated with the endpoint.
Registered: Fri Jun 14 15:00:06 UTC 2024 - Last Modified: Thu Jun 06 21:31:42 UTC 2024 - 671.7K bytes - Viewed (0) -
manifests/charts/base/crds/crd-all.gen.yaml
description: Set of ports associated with the endpoint. type: object serviceAccount: description: The service account associated with the workload if a sidecar is present in the workload. type: string weight: description: The load balancing weight associated with the endpoint.
Registered: Fri Jun 14 15:00:06 UTC 2024 - Last Modified: Thu Jun 06 21:31:42 UTC 2024 - 671.6K bytes - Viewed (0) -
api/openapi-spec/v3/apis__apps__v1_openapi.json
} ], "default": {}, "description": "A node selector term, associated with the corresponding weight." }, "weight": { "default": 0, "description": "Weight associated with matching the corresponding nodeSelectorTerm, in the range 1-100.", "format": "int32", "type": "integer" }
Registered: Sat Jun 15 01:39:40 UTC 2024 - Last Modified: Wed May 29 22:40:29 UTC 2024 - 810.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
Arg<TF_Tensor, [{Values to associate with keys.}]>:$values ); let results = (outs); TF_DerivedOperandTypeAttr Tin = TF_DerivedOperandTypeAttr<1>; TF_DerivedOperandTypeAttr Tout = TF_DerivedOperandTypeAttr<2>; } def TF_LookupTableInsertV2Op : TF_Op<"LookupTableInsertV2", []> { let summary = "Updates the table to associates keys with values."; let description = [{
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 793K bytes - Viewed (0) -
RELEASE.md
the `"mixed_float16"` policy and no loss scale for other policies. In `Model.compile`, if the model's policy had a loss scale, the optimizer would be wrapped with a `LossScaleOptimizer`. With the non-experimental `Policy`, there is no loss scale associated with the `Policy`, and `Model.compile` wraps the optimizer with a `LossScaleOptimizer` if and only if the policy is a `"mixed_float16"` policy. If you previously passed a `LossScale` to the experimental `Policy`, consider just removing it, as the...
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 730.3K bytes - Viewed (0)