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updated changelog details (#48042)
* Update CHANGELOG.md * Update CHANGELOG.md * Update CHANGELOG for version 1.34.1 Updated CHANGELOG.md with bug fixes and version date change. * Fix datastore create and BatchEndpoint serialization bugs Fixed issues with datastore creation and BatchEndpoint serialization.
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sdk/ml/azure-ai-ml/CHANGELOG.md

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### Other Changes
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## 1.34.1 (unreleased)
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## 1.34.1 (2026-07-15)
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### Bugs Fixed
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### Bugs Fixed
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- Fixed `datastore create` failing with `TypeError: Object of type Datastore is not JSON serializable`. The datastore operation was migrated to the TypeSpec client while the datastore entity still produced a legacy msrest model; the request body is now serialized to its wire form before being sent, keeping the on-the-wire request unchanged.
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- Fixed `BatchEndpoint` defaults serialization regression where `deployment_name` was sent to the service as snake_case instead of camelCase (`deploymentName`), causing `begin_create_or_update` to fail with "Could not find member 'deployment_name' on object of type 'BatchEndpointDefaults'". Serialization now emits the correct camelCase wire format, while `BatchEndpoint.defaults` returned from `get()` continues to expose an object that supports attribute access (e.g. `endpoint.defaults.deployment_name`), preserving backward compatibility with existing code and samples.
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## 1.34.0 (2026-06-11)
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### Bugs Fixed
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- Fixed `datastore create` failing with `TypeError: Object of type Datastore is not JSON serializable`. The datastore operation was migrated to the TypeSpec client while the datastore entity still produced a legacy msrest model; the request body is now serialized to its wire form before being sent, keeping the on-the-wire request unchanged.
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- Fixed cross-tenant registry endpoint resolution for deployment template operations by using the registry discovery API instead of ARM calls.
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- Fixed deployment template update failing with immutable field errors by ensuring `allowedInstanceType` and `allowedEnvironmentVariableOverrides` are properly round-tripped during serialization.
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