mlflow--mlflow
wehub-resource-sync
38 行
1.9 KiB
Protocol Buffer
38 行
1.9 KiB
Protocol Buffer
// Ported from //api-base/proto/exception_with_details.proto in the universe
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// repo. Only the `DatabricksServiceExceptionWithDetailsProto` message is kept.
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//
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// Differences from the universe source (both wire-safe and intentional):
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// - `error_code` is `optional string` instead of `.api.ErrorCode` because the
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// REST/JSON wire format carries error codes as string names; this avoids
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// pulling in `error_code_enum.proto` (~931 lines) and its transitive
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// `linter.proto` extension dep.
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// - The `details` field (tag 4, `repeated google.protobuf.Any` in universe)
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// is intentionally omitted. Our Python client never reads it, and keeping
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// it would force `google.protobuf.json_format.ParseDict` to resolve every
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// detail entry's `@type` URL against our type pool — universe servers emit
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// details under internal package names we don't register, which would
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// crash error handling with a cryptic `Can not find message descriptor`
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// error at exactly the wrong time. With the field missing from the proto,
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// MLflow's `parse_dict` (called with `ignore_unknown_fields=True`) simply
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// skips the `details` key. No loss because we don't consume it.
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syntax = "proto2";
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package databricks.api;
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import "scalapb/scalapb.proto";
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option java_generate_equals_and_hash = true;
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option java_multiple_files = true;
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option java_outer_classname = "ExceptionWithDetailsProto";
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option java_package = "com.databricks.api.proto.databricks.jproto";
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option (scalapb.options).flat_package = true;
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option (scalapb.options).package_name = "com.databricks.api.proto.databricks";
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// Databricks Error that is returned by all Databricks APIs. Field tags 1–3
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// match the universe definition so wire format stays compatible.
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message DatabricksServiceExceptionWithDetailsProto {
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optional string error_code = 1;
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optional string message = 2;
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optional string stack_trace = 3;
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}
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