From 094a3cb47bde381f8ac2a0931d26a27f9f97f384 Mon Sep 17 00:00:00 2001 From: DCL Team Date: Fri, 5 Aug 2022 09:43:32 -0700 Subject: [PATCH] Automated DCL import. - 573cf0cdebedc3d250e0d74b5c67457cd39f9ee3 Automatic import from cloud_mmv2_dcl_20220805_0931_RC00 by DCL Team GitOrigin-RevId: 573cf0cdebedc3d250e0d74b5c67457cd39f9ee3 --- dcl/strings.go | 61 ++++++++++++------- python/proto/vertexai/alpha/endpoint.proto | 9 ++- python/proto/vertexai/beta/endpoint.proto | 9 ++- python/proto/vertexai/endpoint.proto | 5 +- python/services/vertexai/alpha/endpoint.py | 9 --- .../vertexai/alpha/endpoint_server.go | 26 ++++---- python/services/vertexai/beta/endpoint.py | 9 --- .../services/vertexai/beta/endpoint_server.go | 26 ++++---- python/services/vertexai/endpoint.py | 9 --- python/services/vertexai/endpoint_server.go | 22 +++---- services/google/vertexai/alpha/endpoint.go | 29 ++++----- services/google/vertexai/alpha/endpoint.yaml | 9 --- .../alpha/endpoint_alpha_yaml_embed.go | 6 +- .../vertexai/alpha/endpoint_internal.go | 19 ------ .../google/vertexai/alpha/endpoint_schema.go | 6 -- services/google/vertexai/beta/endpoint.go | 29 ++++----- services/google/vertexai/beta/endpoint.yaml | 9 --- .../vertexai/beta/endpoint_beta_yaml_embed.go | 6 +- .../google/vertexai/beta/endpoint_internal.go | 19 ------ .../google/vertexai/beta/endpoint_schema.go | 6 -- services/google/vertexai/endpoint.go | 25 ++++---- services/google/vertexai/endpoint.yaml | 9 --- services/google/vertexai/endpoint_internal.go | 19 ------ services/google/vertexai/endpoint_schema.go | 6 -- .../google/vertexai/endpoint_yaml_embed.go | 6 +- .../google/vertexai/alpha/endpoint.go | 10 --- unstructured/google/vertexai/beta/endpoint.go | 10 --- unstructured/google/vertexai/endpoint.go | 10 --- 28 files changed, 129 insertions(+), 289 deletions(-) diff --git a/dcl/strings.go b/dcl/strings.go index 1d04debb18..c472cd94a3 100755 --- a/dcl/strings.go +++ b/dcl/strings.go @@ -94,34 +94,51 @@ func TitleToCamelCasePath(s string) string { // go protoc special rules: convert to camel case, except when // the character following the underscore is a digit; e.g., // foo_bar_2 -> FooBar_2. +// From: http://google3/net/goa/codegen/names.go;l=14;rcl=294425921 func ProtoCamelCase(s string) string { - var result string + // Invariant: if the next letter is lower case, it must be converted + // to upper case. + // That is, we process a word at a time, where words are marked by _ or + // upper case letter. Digits are treated as words. + var b []byte for i := 0; i < len(s); i++ { c := s[i] - if i == 0 { - result += strings.ToUpper(string(c)) - continue - } - if c == '_' { - // Current character is underscore. - continue - } - p := s[i-1] - if p == '_' { - // Previous character was underscore. - if '0' <= c && c <= '9' { - // Current character is digit following an underscore. - result += "_" + switch { + case c == '.' && i+1 < len(s) && isASCIILower(s[i+1]): + // Skip over '.' in ".{{lowercase}}". + case c == '.': + b = append(b, '_') // convert '.' to '_' + case c == '_' && (i == 0 || s[i-1] == '.'): + // Convert initial '_' to ensure we start with a capital letter. + // Do the same for '_' after '.' to match historic behavior. + b = append(b, 'X') // convert '_' to 'X' + case c == '_' && i+1 < len(s) && isASCIILower(s[i+1]): + // Skip over '_' in "_{{lowercase}}". + case isASCIIDigit(c): + b = append(b, c) + default: + // Assume we have a letter now - if not, it's a bogus identifier. + // The next word is a sequence of characters that must start upper case. + if isASCIILower(c) { + c -= 'a' - 'A' // convert lowercase to uppercase + } + b = append(b, c) + + // Accept lower case sequence that follows. + for ; i+1 < len(s) && isASCIILower(s[i+1]); i++ { + b = append(b, s[i+1]) } - result += strings.ToUpper(string(c)) - } else if '0' <= p && p <= '9' { - // Previous character was digit. - result += strings.ToUpper(string(c)) - } else { - result += string(c) } } - return result + return string(b) +} + +func isASCIILower(c byte) bool { + return 'a' <= c && c <= 'z' +} + +func isASCIIDigit(c byte) bool { + return '0' <= c && c <= '9' } // TitleToSnakeCase takes in a TitleCase string and returns a snake_case string. diff --git a/python/proto/vertexai/alpha/endpoint.proto b/python/proto/vertexai/alpha/endpoint.proto index de75fb85ad..b250a317b7 100755 --- a/python/proto/vertexai/alpha/endpoint.proto +++ b/python/proto/vertexai/alpha/endpoint.proto @@ -59,11 +59,10 @@ message VertexaiAlphaEndpointDeployedModels { string display_name = 6; string create_time = 7; string service_account = 8; - bool disable_container_logging = 9; - bool enable_access_logging = 10; - VertexaiAlphaEndpointDeployedModelsPrivateEndpoints private_endpoints = 11; - string shared_resources = 12; - bool enable_container_logging = 13; + bool enable_access_logging = 9; + VertexaiAlphaEndpointDeployedModelsPrivateEndpoints private_endpoints = 10; + string shared_resources = 11; + bool enable_container_logging = 12; } message VertexaiAlphaEndpointDeployedModelsDedicatedResources { diff --git a/python/proto/vertexai/beta/endpoint.proto b/python/proto/vertexai/beta/endpoint.proto index 6980908b8d..5b636f8b3e 100755 --- a/python/proto/vertexai/beta/endpoint.proto +++ b/python/proto/vertexai/beta/endpoint.proto @@ -59,11 +59,10 @@ message VertexaiBetaEndpointDeployedModels { string display_name = 6; string create_time = 7; string service_account = 8; - bool disable_container_logging = 9; - bool enable_access_logging = 10; - VertexaiBetaEndpointDeployedModelsPrivateEndpoints private_endpoints = 11; - string shared_resources = 12; - bool enable_container_logging = 13; + bool enable_access_logging = 9; + VertexaiBetaEndpointDeployedModelsPrivateEndpoints private_endpoints = 10; + string shared_resources = 11; + bool enable_container_logging = 12; } message VertexaiBetaEndpointDeployedModelsDedicatedResources { diff --git a/python/proto/vertexai/endpoint.proto b/python/proto/vertexai/endpoint.proto index b96a12be4b..a0a87412e8 100755 --- a/python/proto/vertexai/endpoint.proto +++ b/python/proto/vertexai/endpoint.proto @@ -59,9 +59,8 @@ message VertexaiEndpointDeployedModels { string display_name = 6; string create_time = 7; string service_account = 8; - bool disable_container_logging = 9; - bool enable_access_logging = 10; - VertexaiEndpointDeployedModelsPrivateEndpoints private_endpoints = 11; + bool enable_access_logging = 9; + VertexaiEndpointDeployedModelsPrivateEndpoints private_endpoints = 10; } message VertexaiEndpointDeployedModelsDedicatedResources { diff --git a/python/services/vertexai/alpha/endpoint.py b/python/services/vertexai/alpha/endpoint.py index 2324af2702..9fc1d5f904 100755 --- a/python/services/vertexai/alpha/endpoint.py +++ b/python/services/vertexai/alpha/endpoint.py @@ -181,7 +181,6 @@ def __init__( display_name: str = None, create_time: str = None, service_account: str = None, - disable_container_logging: bool = None, enable_access_logging: bool = None, private_endpoints: dict = None, shared_resources: str = None, @@ -195,7 +194,6 @@ def __init__( self.display_name = display_name self.create_time = create_time self.service_account = service_account - self.disable_container_logging = disable_container_logging self.enable_access_logging = enable_access_logging self.private_endpoints = private_endpoints self.shared_resources = shared_resources @@ -239,10 +237,6 @@ def to_proto(self, resource): res.create_time = Primitive.to_proto(resource.create_time) if Primitive.to_proto(resource.service_account): res.service_account = Primitive.to_proto(resource.service_account) - if Primitive.to_proto(resource.disable_container_logging): - res.disable_container_logging = Primitive.to_proto( - resource.disable_container_logging - ) if Primitive.to_proto(resource.enable_access_logging): res.enable_access_logging = Primitive.to_proto( resource.enable_access_logging @@ -281,9 +275,6 @@ def from_proto(self, resource): display_name=Primitive.from_proto(resource.display_name), create_time=Primitive.from_proto(resource.create_time), service_account=Primitive.from_proto(resource.service_account), - disable_container_logging=Primitive.from_proto( - resource.disable_container_logging - ), enable_access_logging=Primitive.from_proto(resource.enable_access_logging), private_endpoints=EndpointDeployedModelsPrivateEndpoints.from_proto( resource.private_endpoints diff --git a/python/services/vertexai/alpha/endpoint_server.go b/python/services/vertexai/alpha/endpoint_server.go index 0d20f6cc0a..e9ce8f7426 100755 --- a/python/services/vertexai/alpha/endpoint_server.go +++ b/python/services/vertexai/alpha/endpoint_server.go @@ -42,19 +42,18 @@ func ProtoToVertexaiAlphaEndpointDeployedModels(p *alphapb.VertexaiAlphaEndpoint return nil } obj := &alpha.EndpointDeployedModels{ - DedicatedResources: ProtoToVertexaiAlphaEndpointDeployedModelsDedicatedResources(p.GetDedicatedResources()), - AutomaticResources: ProtoToVertexaiAlphaEndpointDeployedModelsAutomaticResources(p.GetAutomaticResources()), - Id: dcl.StringOrNil(p.GetId()), - Model: dcl.StringOrNil(p.GetModel()), - ModelVersionId: dcl.StringOrNil(p.GetModelVersionId()), - DisplayName: dcl.StringOrNil(p.GetDisplayName()), - CreateTime: dcl.StringOrNil(p.GetCreateTime()), - ServiceAccount: dcl.StringOrNil(p.GetServiceAccount()), - DisableContainerLogging: dcl.Bool(p.GetDisableContainerLogging()), - EnableAccessLogging: dcl.Bool(p.GetEnableAccessLogging()), - PrivateEndpoints: ProtoToVertexaiAlphaEndpointDeployedModelsPrivateEndpoints(p.GetPrivateEndpoints()), - SharedResources: dcl.StringOrNil(p.GetSharedResources()), - EnableContainerLogging: dcl.Bool(p.GetEnableContainerLogging()), + DedicatedResources: ProtoToVertexaiAlphaEndpointDeployedModelsDedicatedResources(p.GetDedicatedResources()), + AutomaticResources: ProtoToVertexaiAlphaEndpointDeployedModelsAutomaticResources(p.GetAutomaticResources()), + Id: dcl.StringOrNil(p.GetId()), + Model: dcl.StringOrNil(p.GetModel()), + ModelVersionId: dcl.StringOrNil(p.GetModelVersionId()), + DisplayName: dcl.StringOrNil(p.GetDisplayName()), + CreateTime: dcl.StringOrNil(p.GetCreateTime()), + ServiceAccount: dcl.StringOrNil(p.GetServiceAccount()), + EnableAccessLogging: dcl.Bool(p.GetEnableAccessLogging()), + PrivateEndpoints: ProtoToVertexaiAlphaEndpointDeployedModelsPrivateEndpoints(p.GetPrivateEndpoints()), + SharedResources: dcl.StringOrNil(p.GetSharedResources()), + EnableContainerLogging: dcl.Bool(p.GetEnableContainerLogging()), } return obj } @@ -183,7 +182,6 @@ func VertexaiAlphaEndpointDeployedModelsToProto(o *alpha.EndpointDeployedModels) p.SetDisplayName(dcl.ValueOrEmptyString(o.DisplayName)) p.SetCreateTime(dcl.ValueOrEmptyString(o.CreateTime)) p.SetServiceAccount(dcl.ValueOrEmptyString(o.ServiceAccount)) - p.SetDisableContainerLogging(dcl.ValueOrEmptyBool(o.DisableContainerLogging)) p.SetEnableAccessLogging(dcl.ValueOrEmptyBool(o.EnableAccessLogging)) p.SetPrivateEndpoints(VertexaiAlphaEndpointDeployedModelsPrivateEndpointsToProto(o.PrivateEndpoints)) p.SetSharedResources(dcl.ValueOrEmptyString(o.SharedResources)) diff --git a/python/services/vertexai/beta/endpoint.py b/python/services/vertexai/beta/endpoint.py index b59b804353..5493253757 100755 --- a/python/services/vertexai/beta/endpoint.py +++ b/python/services/vertexai/beta/endpoint.py @@ -181,7 +181,6 @@ def __init__( display_name: str = None, create_time: str = None, service_account: str = None, - disable_container_logging: bool = None, enable_access_logging: bool = None, private_endpoints: dict = None, shared_resources: str = None, @@ -195,7 +194,6 @@ def __init__( self.display_name = display_name self.create_time = create_time self.service_account = service_account - self.disable_container_logging = disable_container_logging self.enable_access_logging = enable_access_logging self.private_endpoints = private_endpoints self.shared_resources = shared_resources @@ -239,10 +237,6 @@ def to_proto(self, resource): res.create_time = Primitive.to_proto(resource.create_time) if Primitive.to_proto(resource.service_account): res.service_account = Primitive.to_proto(resource.service_account) - if Primitive.to_proto(resource.disable_container_logging): - res.disable_container_logging = Primitive.to_proto( - resource.disable_container_logging - ) if Primitive.to_proto(resource.enable_access_logging): res.enable_access_logging = Primitive.to_proto( resource.enable_access_logging @@ -281,9 +275,6 @@ def from_proto(self, resource): display_name=Primitive.from_proto(resource.display_name), create_time=Primitive.from_proto(resource.create_time), service_account=Primitive.from_proto(resource.service_account), - disable_container_logging=Primitive.from_proto( - resource.disable_container_logging - ), enable_access_logging=Primitive.from_proto(resource.enable_access_logging), private_endpoints=EndpointDeployedModelsPrivateEndpoints.from_proto( resource.private_endpoints diff --git a/python/services/vertexai/beta/endpoint_server.go b/python/services/vertexai/beta/endpoint_server.go index b75b4d3f6f..4ab787ce60 100755 --- a/python/services/vertexai/beta/endpoint_server.go +++ b/python/services/vertexai/beta/endpoint_server.go @@ -42,19 +42,18 @@ func ProtoToVertexaiBetaEndpointDeployedModels(p *betapb.VertexaiBetaEndpointDep return nil } obj := &beta.EndpointDeployedModels{ - DedicatedResources: ProtoToVertexaiBetaEndpointDeployedModelsDedicatedResources(p.GetDedicatedResources()), - AutomaticResources: ProtoToVertexaiBetaEndpointDeployedModelsAutomaticResources(p.GetAutomaticResources()), - Id: dcl.StringOrNil(p.GetId()), - Model: dcl.StringOrNil(p.GetModel()), - ModelVersionId: dcl.StringOrNil(p.GetModelVersionId()), - DisplayName: dcl.StringOrNil(p.GetDisplayName()), - CreateTime: dcl.StringOrNil(p.GetCreateTime()), - ServiceAccount: dcl.StringOrNil(p.GetServiceAccount()), - DisableContainerLogging: dcl.Bool(p.GetDisableContainerLogging()), - EnableAccessLogging: dcl.Bool(p.GetEnableAccessLogging()), - PrivateEndpoints: ProtoToVertexaiBetaEndpointDeployedModelsPrivateEndpoints(p.GetPrivateEndpoints()), - SharedResources: dcl.StringOrNil(p.GetSharedResources()), - EnableContainerLogging: dcl.Bool(p.GetEnableContainerLogging()), + DedicatedResources: ProtoToVertexaiBetaEndpointDeployedModelsDedicatedResources(p.GetDedicatedResources()), + AutomaticResources: ProtoToVertexaiBetaEndpointDeployedModelsAutomaticResources(p.GetAutomaticResources()), + Id: dcl.StringOrNil(p.GetId()), + Model: dcl.StringOrNil(p.GetModel()), + ModelVersionId: dcl.StringOrNil(p.GetModelVersionId()), + DisplayName: dcl.StringOrNil(p.GetDisplayName()), + CreateTime: dcl.StringOrNil(p.GetCreateTime()), + ServiceAccount: dcl.StringOrNil(p.GetServiceAccount()), + EnableAccessLogging: dcl.Bool(p.GetEnableAccessLogging()), + PrivateEndpoints: ProtoToVertexaiBetaEndpointDeployedModelsPrivateEndpoints(p.GetPrivateEndpoints()), + SharedResources: dcl.StringOrNil(p.GetSharedResources()), + EnableContainerLogging: dcl.Bool(p.GetEnableContainerLogging()), } return obj } @@ -183,7 +182,6 @@ func VertexaiBetaEndpointDeployedModelsToProto(o *beta.EndpointDeployedModels) * p.SetDisplayName(dcl.ValueOrEmptyString(o.DisplayName)) p.SetCreateTime(dcl.ValueOrEmptyString(o.CreateTime)) p.SetServiceAccount(dcl.ValueOrEmptyString(o.ServiceAccount)) - p.SetDisableContainerLogging(dcl.ValueOrEmptyBool(o.DisableContainerLogging)) p.SetEnableAccessLogging(dcl.ValueOrEmptyBool(o.EnableAccessLogging)) p.SetPrivateEndpoints(VertexaiBetaEndpointDeployedModelsPrivateEndpointsToProto(o.PrivateEndpoints)) p.SetSharedResources(dcl.ValueOrEmptyString(o.SharedResources)) diff --git a/python/services/vertexai/endpoint.py b/python/services/vertexai/endpoint.py index 7d7e129467..5402e82334 100755 --- a/python/services/vertexai/endpoint.py +++ b/python/services/vertexai/endpoint.py @@ -181,7 +181,6 @@ def __init__( display_name: str = None, create_time: str = None, service_account: str = None, - disable_container_logging: bool = None, enable_access_logging: bool = None, private_endpoints: dict = None, ): @@ -193,7 +192,6 @@ def __init__( self.display_name = display_name self.create_time = create_time self.service_account = service_account - self.disable_container_logging = disable_container_logging self.enable_access_logging = enable_access_logging self.private_endpoints = private_endpoints @@ -235,10 +233,6 @@ def to_proto(self, resource): res.create_time = Primitive.to_proto(resource.create_time) if Primitive.to_proto(resource.service_account): res.service_account = Primitive.to_proto(resource.service_account) - if Primitive.to_proto(resource.disable_container_logging): - res.disable_container_logging = Primitive.to_proto( - resource.disable_container_logging - ) if Primitive.to_proto(resource.enable_access_logging): res.enable_access_logging = Primitive.to_proto( resource.enable_access_logging @@ -271,9 +265,6 @@ def from_proto(self, resource): display_name=Primitive.from_proto(resource.display_name), create_time=Primitive.from_proto(resource.create_time), service_account=Primitive.from_proto(resource.service_account), - disable_container_logging=Primitive.from_proto( - resource.disable_container_logging - ), enable_access_logging=Primitive.from_proto(resource.enable_access_logging), private_endpoints=EndpointDeployedModelsPrivateEndpoints.from_proto( resource.private_endpoints diff --git a/python/services/vertexai/endpoint_server.go b/python/services/vertexai/endpoint_server.go index 202017cb6d..626df89460 100755 --- a/python/services/vertexai/endpoint_server.go +++ b/python/services/vertexai/endpoint_server.go @@ -42,17 +42,16 @@ func ProtoToVertexaiEndpointDeployedModels(p *vertexaipb.VertexaiEndpointDeploye return nil } obj := &vertexai.EndpointDeployedModels{ - DedicatedResources: ProtoToVertexaiEndpointDeployedModelsDedicatedResources(p.GetDedicatedResources()), - AutomaticResources: ProtoToVertexaiEndpointDeployedModelsAutomaticResources(p.GetAutomaticResources()), - Id: dcl.StringOrNil(p.GetId()), - Model: dcl.StringOrNil(p.GetModel()), - ModelVersionId: dcl.StringOrNil(p.GetModelVersionId()), - DisplayName: dcl.StringOrNil(p.GetDisplayName()), - CreateTime: dcl.StringOrNil(p.GetCreateTime()), - ServiceAccount: dcl.StringOrNil(p.GetServiceAccount()), - DisableContainerLogging: dcl.Bool(p.GetDisableContainerLogging()), - EnableAccessLogging: dcl.Bool(p.GetEnableAccessLogging()), - PrivateEndpoints: ProtoToVertexaiEndpointDeployedModelsPrivateEndpoints(p.GetPrivateEndpoints()), + DedicatedResources: ProtoToVertexaiEndpointDeployedModelsDedicatedResources(p.GetDedicatedResources()), + AutomaticResources: ProtoToVertexaiEndpointDeployedModelsAutomaticResources(p.GetAutomaticResources()), + Id: dcl.StringOrNil(p.GetId()), + Model: dcl.StringOrNil(p.GetModel()), + ModelVersionId: dcl.StringOrNil(p.GetModelVersionId()), + DisplayName: dcl.StringOrNil(p.GetDisplayName()), + CreateTime: dcl.StringOrNil(p.GetCreateTime()), + ServiceAccount: dcl.StringOrNil(p.GetServiceAccount()), + EnableAccessLogging: dcl.Bool(p.GetEnableAccessLogging()), + PrivateEndpoints: ProtoToVertexaiEndpointDeployedModelsPrivateEndpoints(p.GetPrivateEndpoints()), } return obj } @@ -181,7 +180,6 @@ func VertexaiEndpointDeployedModelsToProto(o *vertexai.EndpointDeployedModels) * p.SetDisplayName(dcl.ValueOrEmptyString(o.DisplayName)) p.SetCreateTime(dcl.ValueOrEmptyString(o.CreateTime)) p.SetServiceAccount(dcl.ValueOrEmptyString(o.ServiceAccount)) - p.SetDisableContainerLogging(dcl.ValueOrEmptyBool(o.DisableContainerLogging)) p.SetEnableAccessLogging(dcl.ValueOrEmptyBool(o.EnableAccessLogging)) p.SetPrivateEndpoints(VertexaiEndpointDeployedModelsPrivateEndpointsToProto(o.PrivateEndpoints)) return p diff --git a/services/google/vertexai/alpha/endpoint.go b/services/google/vertexai/alpha/endpoint.go index ae2bdb2214..89ac3f1982 100755 --- a/services/google/vertexai/alpha/endpoint.go +++ b/services/google/vertexai/alpha/endpoint.go @@ -72,20 +72,19 @@ func (v EndpointDeployedModelsDedicatedResourcesMachineSpecAcceleratorTypeEnum) } type EndpointDeployedModels struct { - empty bool `json:"-"` - DedicatedResources *EndpointDeployedModelsDedicatedResources `json:"dedicatedResources"` - AutomaticResources *EndpointDeployedModelsAutomaticResources `json:"automaticResources"` - Id *string `json:"id"` - Model *string `json:"model"` - ModelVersionId *string `json:"modelVersionId"` - DisplayName *string `json:"displayName"` - CreateTime *string `json:"createTime"` - ServiceAccount *string `json:"serviceAccount"` - DisableContainerLogging *bool `json:"disableContainerLogging"` - EnableAccessLogging *bool `json:"enableAccessLogging"` - PrivateEndpoints *EndpointDeployedModelsPrivateEndpoints `json:"privateEndpoints"` - SharedResources *string `json:"sharedResources"` - EnableContainerLogging *bool `json:"enableContainerLogging"` + empty bool `json:"-"` + DedicatedResources *EndpointDeployedModelsDedicatedResources `json:"dedicatedResources"` + AutomaticResources *EndpointDeployedModelsAutomaticResources `json:"automaticResources"` + Id *string `json:"id"` + Model *string `json:"model"` + ModelVersionId *string `json:"modelVersionId"` + DisplayName *string `json:"displayName"` + CreateTime *string `json:"createTime"` + ServiceAccount *string `json:"serviceAccount"` + EnableAccessLogging *bool `json:"enableAccessLogging"` + PrivateEndpoints *EndpointDeployedModelsPrivateEndpoints `json:"privateEndpoints"` + SharedResources *string `json:"sharedResources"` + EnableContainerLogging *bool `json:"enableContainerLogging"` } type jsonEndpointDeployedModels EndpointDeployedModels @@ -119,8 +118,6 @@ func (r *EndpointDeployedModels) UnmarshalJSON(data []byte) error { r.ServiceAccount = res.ServiceAccount - r.DisableContainerLogging = res.DisableContainerLogging - r.EnableAccessLogging = res.EnableAccessLogging r.PrivateEndpoints = res.PrivateEndpoints diff --git a/services/google/vertexai/alpha/endpoint.yaml b/services/google/vertexai/alpha/endpoint.yaml index 52f7884f20..3424935524 100755 --- a/services/google/vertexai/alpha/endpoint.yaml +++ b/services/google/vertexai/alpha/endpoint.yaml @@ -263,15 +263,6 @@ components: it may dynamically be deployed onto more replicas, and as traffic decreases, some of these extra replicas may be freed. x-kubernetes-immutable: true - disableContainerLogging: - type: boolean - x-dcl-go-name: DisableContainerLogging - description: For custom-trained Models and AutoML Tabular Models, - the container of the DeployedModel instances will send `stderr` - and `stdout` streams to Stackdriver Logging by default. Please note - that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/stackdriver/pricing). - User can disable container logging by setting this flag to true. - x-kubernetes-immutable: true displayName: type: string x-dcl-go-name: DisplayName diff --git a/services/google/vertexai/alpha/endpoint_alpha_yaml_embed.go b/services/google/vertexai/alpha/endpoint_alpha_yaml_embed.go index c487b9036b..23035c70ce 100755 --- a/services/google/vertexai/alpha/endpoint_alpha_yaml_embed.go +++ b/services/google/vertexai/alpha/endpoint_alpha_yaml_embed.go @@ -17,7 +17,7 @@ package alpha // blaze-out/k8-fastbuild/genfiles/cloud/graphite/mmv2/services/google/vertexai/alpha/endpoint.yaml -var YAML_endpoint = []byte("info:\n title: VertexAI/Endpoint\n description: The VertexAI Endpoint resource\n x-dcl-struct-name: Endpoint\n x-dcl-has-iam: false\npaths:\n get:\n description: The function used to get information about a Endpoint\n parameters:\n - name: Endpoint\n required: true\n description: A full instance of a Endpoint\n apply:\n description: The function used to apply information about a Endpoint\n parameters:\n - name: Endpoint\n required: true\n description: A full instance of a Endpoint\n delete:\n description: The function used to delete a Endpoint\n parameters:\n - name: Endpoint\n required: true\n description: A full instance of a Endpoint\n deleteAll:\n description: The function used to delete all Endpoint\n parameters:\n - name: project\n required: true\n schema:\n type: string\n - name: location\n required: true\n schema:\n type: string\n list:\n description: The function used to list information about many Endpoint\n parameters:\n - name: project\n required: true\n schema:\n type: string\n - name: location\n required: true\n schema:\n type: string\ncomponents:\n schemas:\n Endpoint:\n title: Endpoint\n x-dcl-id: projects/{{project}}/locations/{{location}}/endpoints/{{name}}\n x-dcl-parent-container: project\n x-dcl-labels: labels\n x-dcl-has-create: true\n x-dcl-has-iam: false\n x-dcl-read-timeout: 0\n x-dcl-apply-timeout: 0\n x-dcl-delete-timeout: 0\n type: object\n required:\n - displayName\n - project\n - location\n properties:\n createTime:\n type: string\n format: date-time\n x-dcl-go-name: CreateTime\n readOnly: true\n description: Output only. Timestamp when this Endpoint was created.\n x-kubernetes-immutable: true\n deployedModels:\n type: array\n x-dcl-go-name: DeployedModels\n readOnly: true\n description: Output only. The models deployed in this Endpoint. To add or\n remove DeployedModels use EndpointService.DeployModel and EndpointService.UndeployModel\n respectively.\n x-kubernetes-immutable: true\n x-dcl-list-type: list\n items:\n type: object\n x-dcl-go-type: EndpointDeployedModels\n properties:\n automaticResources:\n type: object\n x-dcl-go-name: AutomaticResources\n x-dcl-go-type: EndpointDeployedModelsAutomaticResources\n description: A description of resources that to large degree are decided\n by Vertex AI, and require only a modest additional configuration.\n x-kubernetes-immutable: true\n x-dcl-conflicts:\n - dedicatedResources\n properties:\n maxReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MaxReplicaCount\n description: The maximum number of replicas this DeployedModel\n may be deployed on when the traffic against it increases. If\n the requested value is too large, the deployment will error,\n but if deployment succeeds then the ability to scale the model\n to that many replicas is guaranteed (barring service outages).\n If traffic against the DeployedModel increases beyond what its\n replicas at maximum may handle, a portion of the traffic will\n be dropped. If this value is not provided, a no upper bound\n for scaling under heavy traffic will be assume, though Vertex\n AI may be unable to scale beyond certain replica number.\n x-kubernetes-immutable: true\n minReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MinReplicaCount\n description: The minimum number of replicas this DeployedModel\n will be always deployed on. If traffic against it increases,\n it may dynamically be deployed onto more replicas up to max_replica_count,\n and as traffic decreases, some of these extra replicas may be\n freed. If the requested value is too large, the deployment will\n error.\n x-kubernetes-immutable: true\n createTime:\n type: string\n format: date-time\n x-dcl-go-name: CreateTime\n readOnly: true\n description: Output only. Timestamp when the DeployedModel was created.\n x-kubernetes-immutable: true\n dedicatedResources:\n type: object\n x-dcl-go-name: DedicatedResources\n x-dcl-go-type: EndpointDeployedModelsDedicatedResources\n description: A description of resources that are dedicated to the\n DeployedModel, and that need a higher degree of manual configuration.\n x-kubernetes-immutable: true\n x-dcl-conflicts:\n - automaticResources\n properties:\n autoscalingMetricSpecs:\n type: array\n x-dcl-go-name: AutoscalingMetricSpecs\n description: The metric specifications that overrides a resource\n utilization metric (CPU utilization, accelerator's duty cycle,\n and so on) target value (default to 60 if not set). At most\n one entry is allowed per metric. If machine_spec.accelerator_count\n is above 0, the autoscaling will be based on both CPU utilization\n and accelerator's duty cycle metrics and scale up when either\n metrics exceeds its target value while scale down if both metrics\n are under their target value. The default target value is 60\n for both metrics. If machine_spec.accelerator_count is 0, the\n autoscaling will be based on CPU utilization metric only with\n default target value 60 if not explicitly set. For example,\n in the case of Online Prediction, if you want to override target\n CPU utilization to 80, you should set autoscaling_metric_specs.metric_name\n to `aiplatform.googleapis.com/prediction/online/cpu/utilization`\n and autoscaling_metric_specs.target to `80`.\n x-kubernetes-immutable: true\n x-dcl-send-empty: true\n x-dcl-list-type: list\n items:\n type: object\n x-dcl-go-type: EndpointDeployedModelsDedicatedResourcesAutoscalingMetricSpecs\n properties:\n metricName:\n type: string\n x-dcl-go-name: MetricName\n description: 'The resource metric name. Supported metrics:\n * For Online Prediction: * `aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle`\n * `aiplatform.googleapis.com/prediction/online/cpu/utilization`'\n x-kubernetes-immutable: true\n target:\n type: integer\n format: int64\n x-dcl-go-name: Target\n description: The target resource utilization in percentage\n (1% - 100%) for the given metric; once the real usage\n deviates from the target by a certain percentage, the\n machine replicas change. The default value is 60 (representing\n 60%) if not provided.\n x-kubernetes-immutable: true\n machineSpec:\n type: object\n x-dcl-go-name: MachineSpec\n x-dcl-go-type: EndpointDeployedModelsDedicatedResourcesMachineSpec\n description: The specification of a single machine used by the\n prediction.\n x-kubernetes-immutable: true\n properties:\n acceleratorCount:\n type: integer\n format: int64\n x-dcl-go-name: AcceleratorCount\n description: The number of accelerators to attach to the machine.\n x-kubernetes-immutable: true\n acceleratorType:\n type: string\n x-dcl-go-name: AcceleratorType\n x-dcl-go-type: EndpointDeployedModelsDedicatedResourcesMachineSpecAcceleratorTypeEnum\n description: 'The type of accelerator(s) that may be attached\n to the machine as per accelerator_count. Possible values:\n ACCELERATOR_TYPE_UNSPECIFIED, NVIDIA_TESLA_K80, NVIDIA_TESLA_P100,\n NVIDIA_TESLA_V100, NVIDIA_TESLA_P4, NVIDIA_TESLA_T4, NVIDIA_TESLA_A100,\n TPU_V2, TPU_V3'\n x-kubernetes-immutable: true\n enum:\n - ACCELERATOR_TYPE_UNSPECIFIED\n - NVIDIA_TESLA_K80\n - NVIDIA_TESLA_P100\n - NVIDIA_TESLA_V100\n - NVIDIA_TESLA_P4\n - NVIDIA_TESLA_T4\n - NVIDIA_TESLA_A100\n - TPU_V2\n - TPU_V3\n machineType:\n type: string\n x-dcl-go-name: MachineType\n description: 'The type of the machine. See the [list of machine\n types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types)\n See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types).\n For DeployedModel this field is optional, and the default\n value is `n1-standard-2`. For BatchPredictionJob or as part\n of WorkerPoolSpec this field is required. TODO(rsurowka):\n Try to better unify the required vs optional.'\n x-kubernetes-immutable: true\n maxReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MaxReplicaCount\n description: The maximum number of replicas this DeployedModel\n may be deployed on when the traffic against it increases. If\n the requested value is too large, the deployment will error,\n but if deployment succeeds then the ability to scale the model\n to that many replicas is guaranteed (barring service outages).\n If traffic against the DeployedModel increases beyond what its\n replicas at maximum may handle, a portion of the traffic will\n be dropped. If this value is not provided, will use min_replica_count\n as the default value. The value of this field impacts the charge\n against Vertex CPU and GPU quotas. Specifically, you will be\n charged for max_replica_count * number of cores in the selected\n machine type) and (max_replica_count * number of GPUs per replica\n in the selected machine type).\n x-kubernetes-immutable: true\n minReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MinReplicaCount\n description: The minimum number of machine replicas this DeployedModel\n will be always deployed on. This value must be greater than\n or equal to 1. If traffic against the DeployedModel increases,\n it may dynamically be deployed onto more replicas, and as traffic\n decreases, some of these extra replicas may be freed.\n x-kubernetes-immutable: true\n disableContainerLogging:\n type: boolean\n x-dcl-go-name: DisableContainerLogging\n description: For custom-trained Models and AutoML Tabular Models,\n the container of the DeployedModel instances will send `stderr`\n and `stdout` streams to Stackdriver Logging by default. Please note\n that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/stackdriver/pricing).\n User can disable container logging by setting this flag to true.\n x-kubernetes-immutable: true\n displayName:\n type: string\n x-dcl-go-name: DisplayName\n description: The display name of the DeployedModel. If not provided\n upon creation, the Model's display_name is used.\n x-kubernetes-immutable: true\n enableAccessLogging:\n type: boolean\n x-dcl-go-name: EnableAccessLogging\n description: These logs are like standard server access logs, containing\n information like timestamp and latency for each prediction request.\n Note that Stackdriver logs may incur a cost, especially if your\n project receives prediction requests at a high queries per second\n rate (QPS). Estimate your costs before enabling this option.\n x-kubernetes-immutable: true\n enableContainerLogging:\n type: boolean\n x-dcl-go-name: EnableContainerLogging\n description: If true, the container of the DeployedModel instances\n will send `stderr` and `stdout` streams to Stackdriver Logging.\n Only supported for custom-trained Models and AutoML Tabular Models.\n x-kubernetes-immutable: true\n id:\n type: string\n x-dcl-go-name: Id\n description: The ID of the DeployedModel. If not provided upon deployment,\n Vertex AI will generate a value for this ID. This value should be\n 1-10 characters, and valid characters are /[0-9]/.\n x-kubernetes-immutable: true\n model:\n type: string\n x-dcl-go-name: Model\n description: The name of the Model that this is the deployment of.\n Note that the Model may be in a different location than the DeployedModel's\n Endpoint.\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Aiplatform/Model\n field: selfLink\n modelVersionId:\n type: string\n x-dcl-go-name: ModelVersionId\n readOnly: true\n description: Output only. The version ID of the model that is deployed.\n x-kubernetes-immutable: true\n privateEndpoints:\n type: object\n x-dcl-go-name: PrivateEndpoints\n x-dcl-go-type: EndpointDeployedModelsPrivateEndpoints\n readOnly: true\n description: Output only. Provide paths for users to send predict/explain/health\n requests directly to the deployed model services running on Cloud\n via private services access. This field is populated if network\n is configured.\n x-kubernetes-immutable: true\n properties:\n explainHttpUri:\n type: string\n x-dcl-go-name: ExplainHttpUri\n readOnly: true\n description: Output only. Http(s) path to send explain requests.\n x-kubernetes-immutable: true\n healthHttpUri:\n type: string\n x-dcl-go-name: HealthHttpUri\n readOnly: true\n description: Output only. Http(s) path to send health check requests.\n x-kubernetes-immutable: true\n predictHttpUri:\n type: string\n x-dcl-go-name: PredictHttpUri\n readOnly: true\n description: Output only. Http(s) path to send prediction requests.\n x-kubernetes-immutable: true\n serviceAttachment:\n type: string\n x-dcl-go-name: ServiceAttachment\n readOnly: true\n description: Output only. The name of the service attachment resource.\n Populated if private service connect is enabled.\n x-kubernetes-immutable: true\n serviceAccount:\n type: string\n x-dcl-go-name: ServiceAccount\n description: The service account that the DeployedModel's container\n runs as. Specify the email address of the service account. If this\n service account is not specified, the container runs as a service\n account that doesn't have access to the resource project. Users\n deploying the Model must have the `iam.serviceAccounts.actAs` permission\n on this service account.\n x-kubernetes-immutable: true\n sharedResources:\n type: string\n x-dcl-go-name: SharedResources\n description: 'The resource name of the shared DeploymentResourcePool\n to deploy on. Format: projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}'\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Aiplatform/DeploymentResourcePool\n field: selfLink\n description:\n type: string\n x-dcl-go-name: Description\n description: The description of the Endpoint.\n displayName:\n type: string\n x-dcl-go-name: DisplayName\n description: Required. The display name of the Endpoint. The name can be\n up to 128 characters long and can be consist of any UTF-8 characters.\n encryptionSpec:\n type: object\n x-dcl-go-name: EncryptionSpec\n x-dcl-go-type: EndpointEncryptionSpec\n description: Customer-managed encryption key spec for an Endpoint. If set,\n this Endpoint and all sub-resources of this Endpoint will be secured by\n this key.\n x-kubernetes-immutable: true\n required:\n - kmsKeyName\n properties:\n kmsKeyName:\n type: string\n x-dcl-go-name: KmsKeyName\n description: 'Required. The Cloud KMS resource identifier of the customer\n managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`.\n The key needs to be in the same region as where the compute resource\n is created.'\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Cloudkms/CryptoKey\n field: name\n etag:\n type: string\n x-dcl-go-name: Etag\n readOnly: true\n description: Used to perform consistent read-modify-write updates. If not\n set, a blind \"overwrite\" update happens.\n x-kubernetes-immutable: true\n labels:\n type: object\n additionalProperties:\n type: string\n x-dcl-go-name: Labels\n description: The labels with user-defined metadata to organize your Endpoints.\n Label keys and values can be no longer than 64 characters (Unicode codepoints),\n can only contain lowercase letters, numeric characters, underscores and\n dashes. International characters are allowed. See https://goo.gl/xmQnxf\n for more information and examples of labels.\n location:\n type: string\n x-dcl-go-name: Location\n description: The location for the resource\n x-kubernetes-immutable: true\n modelDeploymentMonitoringJob:\n type: string\n x-dcl-go-name: ModelDeploymentMonitoringJob\n readOnly: true\n description: 'Output only. Resource name of the Model Monitoring job associated\n with this Endpoint if monitoring is enabled by CreateModelDeploymentMonitoringJob.\n Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`'\n x-kubernetes-immutable: true\n name:\n type: string\n x-dcl-go-name: Name\n description: Output only. The resource name of the Endpoint.\n x-kubernetes-immutable: true\n x-dcl-server-generated-parameter: true\n network:\n type: string\n x-dcl-go-name: Network\n description: 'The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)\n to which the Endpoint should be peered. Private services access must already\n be configured for the network. If left unspecified, the Endpoint is not\n peered with any network. Only one of the fields, network or enable_private_service_connect,\n can be set. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert):\n `projects/{project}/global/networks/{network}`. Where `{project}` is a\n project number, as in `12345`, and `{network}` is network name.'\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Compute/Network\n field: selfLink\n project:\n type: string\n x-dcl-go-name: Project\n description: The project for the resource\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Cloudresourcemanager/Project\n field: name\n parent: true\n updateTime:\n type: string\n format: date-time\n x-dcl-go-name: UpdateTime\n readOnly: true\n description: Output only. Timestamp when this Endpoint was last updated.\n x-kubernetes-immutable: true\n") +var YAML_endpoint = []byte("info:\n title: VertexAI/Endpoint\n description: The VertexAI Endpoint resource\n x-dcl-struct-name: Endpoint\n x-dcl-has-iam: false\npaths:\n get:\n description: The function used to get information about a Endpoint\n parameters:\n - name: Endpoint\n required: true\n description: A full instance of a Endpoint\n apply:\n description: The function used to apply information about a Endpoint\n parameters:\n - name: Endpoint\n required: true\n description: A full instance of a Endpoint\n delete:\n description: The function used to delete a Endpoint\n parameters:\n - name: Endpoint\n required: true\n description: A full instance of a Endpoint\n deleteAll:\n description: The function used to delete all Endpoint\n parameters:\n - name: project\n required: true\n schema:\n type: string\n - name: location\n required: true\n schema:\n type: string\n list:\n description: The function used to list information about many Endpoint\n parameters:\n - name: project\n required: true\n schema:\n type: string\n - name: location\n required: true\n schema:\n type: string\ncomponents:\n schemas:\n Endpoint:\n title: Endpoint\n x-dcl-id: projects/{{project}}/locations/{{location}}/endpoints/{{name}}\n x-dcl-parent-container: project\n x-dcl-labels: labels\n x-dcl-has-create: true\n x-dcl-has-iam: false\n x-dcl-read-timeout: 0\n x-dcl-apply-timeout: 0\n x-dcl-delete-timeout: 0\n type: object\n required:\n - displayName\n - project\n - location\n properties:\n createTime:\n type: string\n format: date-time\n x-dcl-go-name: CreateTime\n readOnly: true\n description: Output only. Timestamp when this Endpoint was created.\n x-kubernetes-immutable: true\n deployedModels:\n type: array\n x-dcl-go-name: DeployedModels\n readOnly: true\n description: Output only. The models deployed in this Endpoint. To add or\n remove DeployedModels use EndpointService.DeployModel and EndpointService.UndeployModel\n respectively.\n x-kubernetes-immutable: true\n x-dcl-list-type: list\n items:\n type: object\n x-dcl-go-type: EndpointDeployedModels\n properties:\n automaticResources:\n type: object\n x-dcl-go-name: AutomaticResources\n x-dcl-go-type: EndpointDeployedModelsAutomaticResources\n description: A description of resources that to large degree are decided\n by Vertex AI, and require only a modest additional configuration.\n x-kubernetes-immutable: true\n x-dcl-conflicts:\n - dedicatedResources\n properties:\n maxReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MaxReplicaCount\n description: The maximum number of replicas this DeployedModel\n may be deployed on when the traffic against it increases. If\n the requested value is too large, the deployment will error,\n but if deployment succeeds then the ability to scale the model\n to that many replicas is guaranteed (barring service outages).\n If traffic against the DeployedModel increases beyond what its\n replicas at maximum may handle, a portion of the traffic will\n be dropped. If this value is not provided, a no upper bound\n for scaling under heavy traffic will be assume, though Vertex\n AI may be unable to scale beyond certain replica number.\n x-kubernetes-immutable: true\n minReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MinReplicaCount\n description: The minimum number of replicas this DeployedModel\n will be always deployed on. If traffic against it increases,\n it may dynamically be deployed onto more replicas up to max_replica_count,\n and as traffic decreases, some of these extra replicas may be\n freed. If the requested value is too large, the deployment will\n error.\n x-kubernetes-immutable: true\n createTime:\n type: string\n format: date-time\n x-dcl-go-name: CreateTime\n readOnly: true\n description: Output only. Timestamp when the DeployedModel was created.\n x-kubernetes-immutable: true\n dedicatedResources:\n type: object\n x-dcl-go-name: DedicatedResources\n x-dcl-go-type: EndpointDeployedModelsDedicatedResources\n description: A description of resources that are dedicated to the\n DeployedModel, and that need a higher degree of manual configuration.\n x-kubernetes-immutable: true\n x-dcl-conflicts:\n - automaticResources\n properties:\n autoscalingMetricSpecs:\n type: array\n x-dcl-go-name: AutoscalingMetricSpecs\n description: The metric specifications that overrides a resource\n utilization metric (CPU utilization, accelerator's duty cycle,\n and so on) target value (default to 60 if not set). At most\n one entry is allowed per metric. If machine_spec.accelerator_count\n is above 0, the autoscaling will be based on both CPU utilization\n and accelerator's duty cycle metrics and scale up when either\n metrics exceeds its target value while scale down if both metrics\n are under their target value. The default target value is 60\n for both metrics. If machine_spec.accelerator_count is 0, the\n autoscaling will be based on CPU utilization metric only with\n default target value 60 if not explicitly set. For example,\n in the case of Online Prediction, if you want to override target\n CPU utilization to 80, you should set autoscaling_metric_specs.metric_name\n to `aiplatform.googleapis.com/prediction/online/cpu/utilization`\n and autoscaling_metric_specs.target to `80`.\n x-kubernetes-immutable: true\n x-dcl-send-empty: true\n x-dcl-list-type: list\n items:\n type: object\n x-dcl-go-type: EndpointDeployedModelsDedicatedResourcesAutoscalingMetricSpecs\n properties:\n metricName:\n type: string\n x-dcl-go-name: MetricName\n description: 'The resource metric name. Supported metrics:\n * For Online Prediction: * `aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle`\n * `aiplatform.googleapis.com/prediction/online/cpu/utilization`'\n x-kubernetes-immutable: true\n target:\n type: integer\n format: int64\n x-dcl-go-name: Target\n description: The target resource utilization in percentage\n (1% - 100%) for the given metric; once the real usage\n deviates from the target by a certain percentage, the\n machine replicas change. The default value is 60 (representing\n 60%) if not provided.\n x-kubernetes-immutable: true\n machineSpec:\n type: object\n x-dcl-go-name: MachineSpec\n x-dcl-go-type: EndpointDeployedModelsDedicatedResourcesMachineSpec\n description: The specification of a single machine used by the\n prediction.\n x-kubernetes-immutable: true\n properties:\n acceleratorCount:\n type: integer\n format: int64\n x-dcl-go-name: AcceleratorCount\n description: The number of accelerators to attach to the machine.\n x-kubernetes-immutable: true\n acceleratorType:\n type: string\n x-dcl-go-name: AcceleratorType\n x-dcl-go-type: EndpointDeployedModelsDedicatedResourcesMachineSpecAcceleratorTypeEnum\n description: 'The type of accelerator(s) that may be attached\n to the machine as per accelerator_count. Possible values:\n ACCELERATOR_TYPE_UNSPECIFIED, NVIDIA_TESLA_K80, NVIDIA_TESLA_P100,\n NVIDIA_TESLA_V100, NVIDIA_TESLA_P4, NVIDIA_TESLA_T4, NVIDIA_TESLA_A100,\n TPU_V2, TPU_V3'\n x-kubernetes-immutable: true\n enum:\n - ACCELERATOR_TYPE_UNSPECIFIED\n - NVIDIA_TESLA_K80\n - NVIDIA_TESLA_P100\n - NVIDIA_TESLA_V100\n - NVIDIA_TESLA_P4\n - NVIDIA_TESLA_T4\n - NVIDIA_TESLA_A100\n - TPU_V2\n - TPU_V3\n machineType:\n type: string\n x-dcl-go-name: MachineType\n description: 'The type of the machine. See the [list of machine\n types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types)\n See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types).\n For DeployedModel this field is optional, and the default\n value is `n1-standard-2`. For BatchPredictionJob or as part\n of WorkerPoolSpec this field is required. TODO(rsurowka):\n Try to better unify the required vs optional.'\n x-kubernetes-immutable: true\n maxReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MaxReplicaCount\n description: The maximum number of replicas this DeployedModel\n may be deployed on when the traffic against it increases. If\n the requested value is too large, the deployment will error,\n but if deployment succeeds then the ability to scale the model\n to that many replicas is guaranteed (barring service outages).\n If traffic against the DeployedModel increases beyond what its\n replicas at maximum may handle, a portion of the traffic will\n be dropped. If this value is not provided, will use min_replica_count\n as the default value. The value of this field impacts the charge\n against Vertex CPU and GPU quotas. Specifically, you will be\n charged for max_replica_count * number of cores in the selected\n machine type) and (max_replica_count * number of GPUs per replica\n in the selected machine type).\n x-kubernetes-immutable: true\n minReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MinReplicaCount\n description: The minimum number of machine replicas this DeployedModel\n will be always deployed on. This value must be greater than\n or equal to 1. If traffic against the DeployedModel increases,\n it may dynamically be deployed onto more replicas, and as traffic\n decreases, some of these extra replicas may be freed.\n x-kubernetes-immutable: true\n displayName:\n type: string\n x-dcl-go-name: DisplayName\n description: The display name of the DeployedModel. If not provided\n upon creation, the Model's display_name is used.\n x-kubernetes-immutable: true\n enableAccessLogging:\n type: boolean\n x-dcl-go-name: EnableAccessLogging\n description: These logs are like standard server access logs, containing\n information like timestamp and latency for each prediction request.\n Note that Stackdriver logs may incur a cost, especially if your\n project receives prediction requests at a high queries per second\n rate (QPS). Estimate your costs before enabling this option.\n x-kubernetes-immutable: true\n enableContainerLogging:\n type: boolean\n x-dcl-go-name: EnableContainerLogging\n description: If true, the container of the DeployedModel instances\n will send `stderr` and `stdout` streams to Stackdriver Logging.\n Only supported for custom-trained Models and AutoML Tabular Models.\n x-kubernetes-immutable: true\n id:\n type: string\n x-dcl-go-name: Id\n description: The ID of the DeployedModel. If not provided upon deployment,\n Vertex AI will generate a value for this ID. This value should be\n 1-10 characters, and valid characters are /[0-9]/.\n x-kubernetes-immutable: true\n model:\n type: string\n x-dcl-go-name: Model\n description: The name of the Model that this is the deployment of.\n Note that the Model may be in a different location than the DeployedModel's\n Endpoint.\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Aiplatform/Model\n field: selfLink\n modelVersionId:\n type: string\n x-dcl-go-name: ModelVersionId\n readOnly: true\n description: Output only. The version ID of the model that is deployed.\n x-kubernetes-immutable: true\n privateEndpoints:\n type: object\n x-dcl-go-name: PrivateEndpoints\n x-dcl-go-type: EndpointDeployedModelsPrivateEndpoints\n readOnly: true\n description: Output only. Provide paths for users to send predict/explain/health\n requests directly to the deployed model services running on Cloud\n via private services access. This field is populated if network\n is configured.\n x-kubernetes-immutable: true\n properties:\n explainHttpUri:\n type: string\n x-dcl-go-name: ExplainHttpUri\n readOnly: true\n description: Output only. Http(s) path to send explain requests.\n x-kubernetes-immutable: true\n healthHttpUri:\n type: string\n x-dcl-go-name: HealthHttpUri\n readOnly: true\n description: Output only. Http(s) path to send health check requests.\n x-kubernetes-immutable: true\n predictHttpUri:\n type: string\n x-dcl-go-name: PredictHttpUri\n readOnly: true\n description: Output only. Http(s) path to send prediction requests.\n x-kubernetes-immutable: true\n serviceAttachment:\n type: string\n x-dcl-go-name: ServiceAttachment\n readOnly: true\n description: Output only. The name of the service attachment resource.\n Populated if private service connect is enabled.\n x-kubernetes-immutable: true\n serviceAccount:\n type: string\n x-dcl-go-name: ServiceAccount\n description: The service account that the DeployedModel's container\n runs as. Specify the email address of the service account. If this\n service account is not specified, the container runs as a service\n account that doesn't have access to the resource project. Users\n deploying the Model must have the `iam.serviceAccounts.actAs` permission\n on this service account.\n x-kubernetes-immutable: true\n sharedResources:\n type: string\n x-dcl-go-name: SharedResources\n description: 'The resource name of the shared DeploymentResourcePool\n to deploy on. Format: projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}'\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Aiplatform/DeploymentResourcePool\n field: selfLink\n description:\n type: string\n x-dcl-go-name: Description\n description: The description of the Endpoint.\n displayName:\n type: string\n x-dcl-go-name: DisplayName\n description: Required. The display name of the Endpoint. The name can be\n up to 128 characters long and can be consist of any UTF-8 characters.\n encryptionSpec:\n type: object\n x-dcl-go-name: EncryptionSpec\n x-dcl-go-type: EndpointEncryptionSpec\n description: Customer-managed encryption key spec for an Endpoint. If set,\n this Endpoint and all sub-resources of this Endpoint will be secured by\n this key.\n x-kubernetes-immutable: true\n required:\n - kmsKeyName\n properties:\n kmsKeyName:\n type: string\n x-dcl-go-name: KmsKeyName\n description: 'Required. The Cloud KMS resource identifier of the customer\n managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`.\n The key needs to be in the same region as where the compute resource\n is created.'\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Cloudkms/CryptoKey\n field: name\n etag:\n type: string\n x-dcl-go-name: Etag\n readOnly: true\n description: Used to perform consistent read-modify-write updates. If not\n set, a blind \"overwrite\" update happens.\n x-kubernetes-immutable: true\n labels:\n type: object\n additionalProperties:\n type: string\n x-dcl-go-name: Labels\n description: The labels with user-defined metadata to organize your Endpoints.\n Label keys and values can be no longer than 64 characters (Unicode codepoints),\n can only contain lowercase letters, numeric characters, underscores and\n dashes. International characters are allowed. See https://goo.gl/xmQnxf\n for more information and examples of labels.\n location:\n type: string\n x-dcl-go-name: Location\n description: The location for the resource\n x-kubernetes-immutable: true\n modelDeploymentMonitoringJob:\n type: string\n x-dcl-go-name: ModelDeploymentMonitoringJob\n readOnly: true\n description: 'Output only. Resource name of the Model Monitoring job associated\n with this Endpoint if monitoring is enabled by CreateModelDeploymentMonitoringJob.\n Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`'\n x-kubernetes-immutable: true\n name:\n type: string\n x-dcl-go-name: Name\n description: Output only. The resource name of the Endpoint.\n x-kubernetes-immutable: true\n x-dcl-server-generated-parameter: true\n network:\n type: string\n x-dcl-go-name: Network\n description: 'The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)\n to which the Endpoint should be peered. Private services access must already\n be configured for the network. If left unspecified, the Endpoint is not\n peered with any network. Only one of the fields, network or enable_private_service_connect,\n can be set. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert):\n `projects/{project}/global/networks/{network}`. Where `{project}` is a\n project number, as in `12345`, and `{network}` is network name.'\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Compute/Network\n field: selfLink\n project:\n type: string\n x-dcl-go-name: Project\n description: The project for the resource\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Cloudresourcemanager/Project\n field: name\n parent: true\n updateTime:\n type: string\n format: date-time\n x-dcl-go-name: UpdateTime\n readOnly: true\n description: Output only. Timestamp when this Endpoint was last updated.\n x-kubernetes-immutable: true\n") -// 23326 bytes -// MD5: f2d199a3c33262380fcf26e97f9ba8ae +// 22688 bytes +// MD5: 9e881ec31f7d4004ab9b72923b135488 diff --git a/services/google/vertexai/alpha/endpoint_internal.go b/services/google/vertexai/alpha/endpoint_internal.go index 3187ecb218..636156a4b4 100755 --- a/services/google/vertexai/alpha/endpoint_internal.go +++ b/services/google/vertexai/alpha/endpoint_internal.go @@ -692,11 +692,6 @@ func canonicalizeEndpointDeployedModels(des, initial *EndpointDeployedModels, op } else { cDes.ServiceAccount = des.ServiceAccount } - if dcl.BoolCanonicalize(des.DisableContainerLogging, initial.DisableContainerLogging) || dcl.IsZeroValue(des.DisableContainerLogging) { - cDes.DisableContainerLogging = initial.DisableContainerLogging - } else { - cDes.DisableContainerLogging = des.DisableContainerLogging - } if dcl.BoolCanonicalize(des.EnableAccessLogging, initial.EnableAccessLogging) || dcl.IsZeroValue(des.EnableAccessLogging) { cDes.EnableAccessLogging = initial.EnableAccessLogging } else { @@ -773,9 +768,6 @@ func canonicalizeNewEndpointDeployedModels(c *Client, des, nw *EndpointDeployedM if dcl.StringCanonicalize(des.ServiceAccount, nw.ServiceAccount) { nw.ServiceAccount = des.ServiceAccount } - if dcl.BoolCanonicalize(des.DisableContainerLogging, nw.DisableContainerLogging) { - nw.DisableContainerLogging = des.DisableContainerLogging - } if dcl.BoolCanonicalize(des.EnableAccessLogging, nw.EnableAccessLogging) { nw.EnableAccessLogging = des.EnableAccessLogging } @@ -1736,13 +1728,6 @@ func compareEndpointDeployedModelsNewStyle(d, a interface{}, fn dcl.FieldName) ( diffs = append(diffs, ds...) } - if ds, err := dcl.Diff(desired.DisableContainerLogging, actual.DisableContainerLogging, dcl.DiffInfo{OperationSelector: dcl.RequiresRecreate()}, fn.AddNest("DisableContainerLogging")); len(ds) != 0 || err != nil { - if err != nil { - return nil, err - } - diffs = append(diffs, ds...) - } - if ds, err := dcl.Diff(desired.EnableAccessLogging, actual.EnableAccessLogging, dcl.DiffInfo{OperationSelector: dcl.RequiresRecreate()}, fn.AddNest("EnableAccessLogging")); len(ds) != 0 || err != nil { if err != nil { return nil, err @@ -2261,9 +2246,6 @@ func expandEndpointDeployedModels(c *Client, f *EndpointDeployedModels, res *End if v := f.ServiceAccount; !dcl.IsEmptyValueIndirect(v) { m["serviceAccount"] = v } - if v := f.DisableContainerLogging; !dcl.IsEmptyValueIndirect(v) { - m["disableContainerLogging"] = v - } if v := f.EnableAccessLogging; !dcl.IsEmptyValueIndirect(v) { m["enableAccessLogging"] = v } @@ -2298,7 +2280,6 @@ func flattenEndpointDeployedModels(c *Client, i interface{}, res *Endpoint) *End r.DisplayName = dcl.FlattenString(m["displayName"]) r.CreateTime = dcl.FlattenString(m["createTime"]) r.ServiceAccount = dcl.FlattenString(m["serviceAccount"]) - r.DisableContainerLogging = dcl.FlattenBool(m["disableContainerLogging"]) r.EnableAccessLogging = dcl.FlattenBool(m["enableAccessLogging"]) r.PrivateEndpoints = flattenEndpointDeployedModelsPrivateEndpoints(c, m["privateEndpoints"], res) r.SharedResources = dcl.FlattenString(m["sharedResources"]) diff --git a/services/google/vertexai/alpha/endpoint_schema.go b/services/google/vertexai/alpha/endpoint_schema.go index c5ec5236be..18ecb5b443 100755 --- a/services/google/vertexai/alpha/endpoint_schema.go +++ b/services/google/vertexai/alpha/endpoint_schema.go @@ -256,12 +256,6 @@ func DCLEndpointSchema() *dcl.Schema { }, }, }, - "disableContainerLogging": &dcl.Property{ - Type: "boolean", - GoName: "DisableContainerLogging", - Description: "For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Stackdriver Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/stackdriver/pricing). User can disable container logging by setting this flag to true.", - Immutable: true, - }, "displayName": &dcl.Property{ Type: "string", GoName: "DisplayName", diff --git a/services/google/vertexai/beta/endpoint.go b/services/google/vertexai/beta/endpoint.go index 9736cfff9e..5b24572ef5 100755 --- a/services/google/vertexai/beta/endpoint.go +++ b/services/google/vertexai/beta/endpoint.go @@ -72,20 +72,19 @@ func (v EndpointDeployedModelsDedicatedResourcesMachineSpecAcceleratorTypeEnum) } type EndpointDeployedModels struct { - empty bool `json:"-"` - DedicatedResources *EndpointDeployedModelsDedicatedResources `json:"dedicatedResources"` - AutomaticResources *EndpointDeployedModelsAutomaticResources `json:"automaticResources"` - Id *string `json:"id"` - Model *string `json:"model"` - ModelVersionId *string `json:"modelVersionId"` - DisplayName *string `json:"displayName"` - CreateTime *string `json:"createTime"` - ServiceAccount *string `json:"serviceAccount"` - DisableContainerLogging *bool `json:"disableContainerLogging"` - EnableAccessLogging *bool `json:"enableAccessLogging"` - PrivateEndpoints *EndpointDeployedModelsPrivateEndpoints `json:"privateEndpoints"` - SharedResources *string `json:"sharedResources"` - EnableContainerLogging *bool `json:"enableContainerLogging"` + empty bool `json:"-"` + DedicatedResources *EndpointDeployedModelsDedicatedResources `json:"dedicatedResources"` + AutomaticResources *EndpointDeployedModelsAutomaticResources `json:"automaticResources"` + Id *string `json:"id"` + Model *string `json:"model"` + ModelVersionId *string `json:"modelVersionId"` + DisplayName *string `json:"displayName"` + CreateTime *string `json:"createTime"` + ServiceAccount *string `json:"serviceAccount"` + EnableAccessLogging *bool `json:"enableAccessLogging"` + PrivateEndpoints *EndpointDeployedModelsPrivateEndpoints `json:"privateEndpoints"` + SharedResources *string `json:"sharedResources"` + EnableContainerLogging *bool `json:"enableContainerLogging"` } type jsonEndpointDeployedModels EndpointDeployedModels @@ -119,8 +118,6 @@ func (r *EndpointDeployedModels) UnmarshalJSON(data []byte) error { r.ServiceAccount = res.ServiceAccount - r.DisableContainerLogging = res.DisableContainerLogging - r.EnableAccessLogging = res.EnableAccessLogging r.PrivateEndpoints = res.PrivateEndpoints diff --git a/services/google/vertexai/beta/endpoint.yaml b/services/google/vertexai/beta/endpoint.yaml index 52f7884f20..3424935524 100755 --- a/services/google/vertexai/beta/endpoint.yaml +++ b/services/google/vertexai/beta/endpoint.yaml @@ -263,15 +263,6 @@ components: it may dynamically be deployed onto more replicas, and as traffic decreases, some of these extra replicas may be freed. x-kubernetes-immutable: true - disableContainerLogging: - type: boolean - x-dcl-go-name: DisableContainerLogging - description: For custom-trained Models and AutoML Tabular Models, - the container of the DeployedModel instances will send `stderr` - and `stdout` streams to Stackdriver Logging by default. Please note - that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/stackdriver/pricing). - User can disable container logging by setting this flag to true. - x-kubernetes-immutable: true displayName: type: string x-dcl-go-name: DisplayName diff --git a/services/google/vertexai/beta/endpoint_beta_yaml_embed.go b/services/google/vertexai/beta/endpoint_beta_yaml_embed.go index 118a2da3cd..378461c27c 100755 --- a/services/google/vertexai/beta/endpoint_beta_yaml_embed.go +++ b/services/google/vertexai/beta/endpoint_beta_yaml_embed.go @@ -17,7 +17,7 @@ package beta // blaze-out/k8-fastbuild/genfiles/cloud/graphite/mmv2/services/google/vertexai/beta/endpoint.yaml -var YAML_endpoint = []byte("info:\n title: VertexAI/Endpoint\n description: The VertexAI Endpoint resource\n x-dcl-struct-name: Endpoint\n x-dcl-has-iam: false\npaths:\n get:\n description: The function used to get information about a Endpoint\n parameters:\n - name: Endpoint\n required: true\n description: A full instance of a Endpoint\n apply:\n description: The function used to apply information about a Endpoint\n parameters:\n - name: Endpoint\n required: true\n description: A full instance of a Endpoint\n delete:\n description: The function used to delete a Endpoint\n parameters:\n - name: Endpoint\n required: true\n description: A full instance of a Endpoint\n deleteAll:\n description: The function used to delete all Endpoint\n parameters:\n - name: project\n required: true\n schema:\n type: string\n - name: location\n required: true\n schema:\n type: string\n list:\n description: The function used to list information about many Endpoint\n parameters:\n - name: project\n required: true\n schema:\n type: string\n - name: location\n required: true\n schema:\n type: string\ncomponents:\n schemas:\n Endpoint:\n title: Endpoint\n x-dcl-id: projects/{{project}}/locations/{{location}}/endpoints/{{name}}\n x-dcl-parent-container: project\n x-dcl-labels: labels\n x-dcl-has-create: true\n x-dcl-has-iam: false\n x-dcl-read-timeout: 0\n x-dcl-apply-timeout: 0\n x-dcl-delete-timeout: 0\n type: object\n required:\n - displayName\n - project\n - location\n properties:\n createTime:\n type: string\n format: date-time\n x-dcl-go-name: CreateTime\n readOnly: true\n description: Output only. Timestamp when this Endpoint was created.\n x-kubernetes-immutable: true\n deployedModels:\n type: array\n x-dcl-go-name: DeployedModels\n readOnly: true\n description: Output only. The models deployed in this Endpoint. To add or\n remove DeployedModels use EndpointService.DeployModel and EndpointService.UndeployModel\n respectively.\n x-kubernetes-immutable: true\n x-dcl-list-type: list\n items:\n type: object\n x-dcl-go-type: EndpointDeployedModels\n properties:\n automaticResources:\n type: object\n x-dcl-go-name: AutomaticResources\n x-dcl-go-type: EndpointDeployedModelsAutomaticResources\n description: A description of resources that to large degree are decided\n by Vertex AI, and require only a modest additional configuration.\n x-kubernetes-immutable: true\n x-dcl-conflicts:\n - dedicatedResources\n properties:\n maxReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MaxReplicaCount\n description: The maximum number of replicas this DeployedModel\n may be deployed on when the traffic against it increases. If\n the requested value is too large, the deployment will error,\n but if deployment succeeds then the ability to scale the model\n to that many replicas is guaranteed (barring service outages).\n If traffic against the DeployedModel increases beyond what its\n replicas at maximum may handle, a portion of the traffic will\n be dropped. If this value is not provided, a no upper bound\n for scaling under heavy traffic will be assume, though Vertex\n AI may be unable to scale beyond certain replica number.\n x-kubernetes-immutable: true\n minReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MinReplicaCount\n description: The minimum number of replicas this DeployedModel\n will be always deployed on. If traffic against it increases,\n it may dynamically be deployed onto more replicas up to max_replica_count,\n and as traffic decreases, some of these extra replicas may be\n freed. If the requested value is too large, the deployment will\n error.\n x-kubernetes-immutable: true\n createTime:\n type: string\n format: date-time\n x-dcl-go-name: CreateTime\n readOnly: true\n description: Output only. Timestamp when the DeployedModel was created.\n x-kubernetes-immutable: true\n dedicatedResources:\n type: object\n x-dcl-go-name: DedicatedResources\n x-dcl-go-type: EndpointDeployedModelsDedicatedResources\n description: A description of resources that are dedicated to the\n DeployedModel, and that need a higher degree of manual configuration.\n x-kubernetes-immutable: true\n x-dcl-conflicts:\n - automaticResources\n properties:\n autoscalingMetricSpecs:\n type: array\n x-dcl-go-name: AutoscalingMetricSpecs\n description: The metric specifications that overrides a resource\n utilization metric (CPU utilization, accelerator's duty cycle,\n and so on) target value (default to 60 if not set). At most\n one entry is allowed per metric. If machine_spec.accelerator_count\n is above 0, the autoscaling will be based on both CPU utilization\n and accelerator's duty cycle metrics and scale up when either\n metrics exceeds its target value while scale down if both metrics\n are under their target value. The default target value is 60\n for both metrics. If machine_spec.accelerator_count is 0, the\n autoscaling will be based on CPU utilization metric only with\n default target value 60 if not explicitly set. For example,\n in the case of Online Prediction, if you want to override target\n CPU utilization to 80, you should set autoscaling_metric_specs.metric_name\n to `aiplatform.googleapis.com/prediction/online/cpu/utilization`\n and autoscaling_metric_specs.target to `80`.\n x-kubernetes-immutable: true\n x-dcl-send-empty: true\n x-dcl-list-type: list\n items:\n type: object\n x-dcl-go-type: EndpointDeployedModelsDedicatedResourcesAutoscalingMetricSpecs\n properties:\n metricName:\n type: string\n x-dcl-go-name: MetricName\n description: 'The resource metric name. Supported metrics:\n * For Online Prediction: * `aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle`\n * `aiplatform.googleapis.com/prediction/online/cpu/utilization`'\n x-kubernetes-immutable: true\n target:\n type: integer\n format: int64\n x-dcl-go-name: Target\n description: The target resource utilization in percentage\n (1% - 100%) for the given metric; once the real usage\n deviates from the target by a certain percentage, the\n machine replicas change. The default value is 60 (representing\n 60%) if not provided.\n x-kubernetes-immutable: true\n machineSpec:\n type: object\n x-dcl-go-name: MachineSpec\n x-dcl-go-type: EndpointDeployedModelsDedicatedResourcesMachineSpec\n description: The specification of a single machine used by the\n prediction.\n x-kubernetes-immutable: true\n properties:\n acceleratorCount:\n type: integer\n format: int64\n x-dcl-go-name: AcceleratorCount\n description: The number of accelerators to attach to the machine.\n x-kubernetes-immutable: true\n acceleratorType:\n type: string\n x-dcl-go-name: AcceleratorType\n x-dcl-go-type: EndpointDeployedModelsDedicatedResourcesMachineSpecAcceleratorTypeEnum\n description: 'The type of accelerator(s) that may be attached\n to the machine as per accelerator_count. Possible values:\n ACCELERATOR_TYPE_UNSPECIFIED, NVIDIA_TESLA_K80, NVIDIA_TESLA_P100,\n NVIDIA_TESLA_V100, NVIDIA_TESLA_P4, NVIDIA_TESLA_T4, NVIDIA_TESLA_A100,\n TPU_V2, TPU_V3'\n x-kubernetes-immutable: true\n enum:\n - ACCELERATOR_TYPE_UNSPECIFIED\n - NVIDIA_TESLA_K80\n - NVIDIA_TESLA_P100\n - NVIDIA_TESLA_V100\n - NVIDIA_TESLA_P4\n - NVIDIA_TESLA_T4\n - NVIDIA_TESLA_A100\n - TPU_V2\n - TPU_V3\n machineType:\n type: string\n x-dcl-go-name: MachineType\n description: 'The type of the machine. See the [list of machine\n types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types)\n See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types).\n For DeployedModel this field is optional, and the default\n value is `n1-standard-2`. For BatchPredictionJob or as part\n of WorkerPoolSpec this field is required. TODO(rsurowka):\n Try to better unify the required vs optional.'\n x-kubernetes-immutable: true\n maxReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MaxReplicaCount\n description: The maximum number of replicas this DeployedModel\n may be deployed on when the traffic against it increases. If\n the requested value is too large, the deployment will error,\n but if deployment succeeds then the ability to scale the model\n to that many replicas is guaranteed (barring service outages).\n If traffic against the DeployedModel increases beyond what its\n replicas at maximum may handle, a portion of the traffic will\n be dropped. If this value is not provided, will use min_replica_count\n as the default value. The value of this field impacts the charge\n against Vertex CPU and GPU quotas. Specifically, you will be\n charged for max_replica_count * number of cores in the selected\n machine type) and (max_replica_count * number of GPUs per replica\n in the selected machine type).\n x-kubernetes-immutable: true\n minReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MinReplicaCount\n description: The minimum number of machine replicas this DeployedModel\n will be always deployed on. This value must be greater than\n or equal to 1. If traffic against the DeployedModel increases,\n it may dynamically be deployed onto more replicas, and as traffic\n decreases, some of these extra replicas may be freed.\n x-kubernetes-immutable: true\n disableContainerLogging:\n type: boolean\n x-dcl-go-name: DisableContainerLogging\n description: For custom-trained Models and AutoML Tabular Models,\n the container of the DeployedModel instances will send `stderr`\n and `stdout` streams to Stackdriver Logging by default. Please note\n that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/stackdriver/pricing).\n User can disable container logging by setting this flag to true.\n x-kubernetes-immutable: true\n displayName:\n type: string\n x-dcl-go-name: DisplayName\n description: The display name of the DeployedModel. If not provided\n upon creation, the Model's display_name is used.\n x-kubernetes-immutable: true\n enableAccessLogging:\n type: boolean\n x-dcl-go-name: EnableAccessLogging\n description: These logs are like standard server access logs, containing\n information like timestamp and latency for each prediction request.\n Note that Stackdriver logs may incur a cost, especially if your\n project receives prediction requests at a high queries per second\n rate (QPS). Estimate your costs before enabling this option.\n x-kubernetes-immutable: true\n enableContainerLogging:\n type: boolean\n x-dcl-go-name: EnableContainerLogging\n description: If true, the container of the DeployedModel instances\n will send `stderr` and `stdout` streams to Stackdriver Logging.\n Only supported for custom-trained Models and AutoML Tabular Models.\n x-kubernetes-immutable: true\n id:\n type: string\n x-dcl-go-name: Id\n description: The ID of the DeployedModel. If not provided upon deployment,\n Vertex AI will generate a value for this ID. This value should be\n 1-10 characters, and valid characters are /[0-9]/.\n x-kubernetes-immutable: true\n model:\n type: string\n x-dcl-go-name: Model\n description: The name of the Model that this is the deployment of.\n Note that the Model may be in a different location than the DeployedModel's\n Endpoint.\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Aiplatform/Model\n field: selfLink\n modelVersionId:\n type: string\n x-dcl-go-name: ModelVersionId\n readOnly: true\n description: Output only. The version ID of the model that is deployed.\n x-kubernetes-immutable: true\n privateEndpoints:\n type: object\n x-dcl-go-name: PrivateEndpoints\n x-dcl-go-type: EndpointDeployedModelsPrivateEndpoints\n readOnly: true\n description: Output only. Provide paths for users to send predict/explain/health\n requests directly to the deployed model services running on Cloud\n via private services access. This field is populated if network\n is configured.\n x-kubernetes-immutable: true\n properties:\n explainHttpUri:\n type: string\n x-dcl-go-name: ExplainHttpUri\n readOnly: true\n description: Output only. Http(s) path to send explain requests.\n x-kubernetes-immutable: true\n healthHttpUri:\n type: string\n x-dcl-go-name: HealthHttpUri\n readOnly: true\n description: Output only. Http(s) path to send health check requests.\n x-kubernetes-immutable: true\n predictHttpUri:\n type: string\n x-dcl-go-name: PredictHttpUri\n readOnly: true\n description: Output only. Http(s) path to send prediction requests.\n x-kubernetes-immutable: true\n serviceAttachment:\n type: string\n x-dcl-go-name: ServiceAttachment\n readOnly: true\n description: Output only. The name of the service attachment resource.\n Populated if private service connect is enabled.\n x-kubernetes-immutable: true\n serviceAccount:\n type: string\n x-dcl-go-name: ServiceAccount\n description: The service account that the DeployedModel's container\n runs as. Specify the email address of the service account. If this\n service account is not specified, the container runs as a service\n account that doesn't have access to the resource project. Users\n deploying the Model must have the `iam.serviceAccounts.actAs` permission\n on this service account.\n x-kubernetes-immutable: true\n sharedResources:\n type: string\n x-dcl-go-name: SharedResources\n description: 'The resource name of the shared DeploymentResourcePool\n to deploy on. Format: projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}'\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Aiplatform/DeploymentResourcePool\n field: selfLink\n description:\n type: string\n x-dcl-go-name: Description\n description: The description of the Endpoint.\n displayName:\n type: string\n x-dcl-go-name: DisplayName\n description: Required. The display name of the Endpoint. The name can be\n up to 128 characters long and can be consist of any UTF-8 characters.\n encryptionSpec:\n type: object\n x-dcl-go-name: EncryptionSpec\n x-dcl-go-type: EndpointEncryptionSpec\n description: Customer-managed encryption key spec for an Endpoint. If set,\n this Endpoint and all sub-resources of this Endpoint will be secured by\n this key.\n x-kubernetes-immutable: true\n required:\n - kmsKeyName\n properties:\n kmsKeyName:\n type: string\n x-dcl-go-name: KmsKeyName\n description: 'Required. The Cloud KMS resource identifier of the customer\n managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`.\n The key needs to be in the same region as where the compute resource\n is created.'\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Cloudkms/CryptoKey\n field: name\n etag:\n type: string\n x-dcl-go-name: Etag\n readOnly: true\n description: Used to perform consistent read-modify-write updates. If not\n set, a blind \"overwrite\" update happens.\n x-kubernetes-immutable: true\n labels:\n type: object\n additionalProperties:\n type: string\n x-dcl-go-name: Labels\n description: The labels with user-defined metadata to organize your Endpoints.\n Label keys and values can be no longer than 64 characters (Unicode codepoints),\n can only contain lowercase letters, numeric characters, underscores and\n dashes. International characters are allowed. See https://goo.gl/xmQnxf\n for more information and examples of labels.\n location:\n type: string\n x-dcl-go-name: Location\n description: The location for the resource\n x-kubernetes-immutable: true\n modelDeploymentMonitoringJob:\n type: string\n x-dcl-go-name: ModelDeploymentMonitoringJob\n readOnly: true\n description: 'Output only. Resource name of the Model Monitoring job associated\n with this Endpoint if monitoring is enabled by CreateModelDeploymentMonitoringJob.\n Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`'\n x-kubernetes-immutable: true\n name:\n type: string\n x-dcl-go-name: Name\n description: Output only. The resource name of the Endpoint.\n x-kubernetes-immutable: true\n x-dcl-server-generated-parameter: true\n network:\n type: string\n x-dcl-go-name: Network\n description: 'The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)\n to which the Endpoint should be peered. Private services access must already\n be configured for the network. If left unspecified, the Endpoint is not\n peered with any network. Only one of the fields, network or enable_private_service_connect,\n can be set. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert):\n `projects/{project}/global/networks/{network}`. Where `{project}` is a\n project number, as in `12345`, and `{network}` is network name.'\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Compute/Network\n field: selfLink\n project:\n type: string\n x-dcl-go-name: Project\n description: The project for the resource\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Cloudresourcemanager/Project\n field: name\n parent: true\n updateTime:\n type: string\n format: date-time\n x-dcl-go-name: UpdateTime\n readOnly: true\n description: Output only. Timestamp when this Endpoint was last updated.\n x-kubernetes-immutable: true\n") +var YAML_endpoint = []byte("info:\n title: VertexAI/Endpoint\n description: The VertexAI Endpoint resource\n x-dcl-struct-name: Endpoint\n x-dcl-has-iam: false\npaths:\n get:\n description: The function used to get information about a Endpoint\n parameters:\n - name: Endpoint\n required: true\n description: A full instance of a Endpoint\n apply:\n description: The function used to apply information about a Endpoint\n parameters:\n - name: Endpoint\n required: true\n description: A full instance of a Endpoint\n delete:\n description: The function used to delete a Endpoint\n parameters:\n - name: Endpoint\n required: true\n description: A full instance of a Endpoint\n deleteAll:\n description: The function used to delete all Endpoint\n parameters:\n - name: project\n required: true\n schema:\n type: string\n - name: location\n required: true\n schema:\n type: string\n list:\n description: The function used to list information about many Endpoint\n parameters:\n - name: project\n required: true\n schema:\n type: string\n - name: location\n required: true\n schema:\n type: string\ncomponents:\n schemas:\n Endpoint:\n title: Endpoint\n x-dcl-id: projects/{{project}}/locations/{{location}}/endpoints/{{name}}\n x-dcl-parent-container: project\n x-dcl-labels: labels\n x-dcl-has-create: true\n x-dcl-has-iam: false\n x-dcl-read-timeout: 0\n x-dcl-apply-timeout: 0\n x-dcl-delete-timeout: 0\n type: object\n required:\n - displayName\n - project\n - location\n properties:\n createTime:\n type: string\n format: date-time\n x-dcl-go-name: CreateTime\n readOnly: true\n description: Output only. Timestamp when this Endpoint was created.\n x-kubernetes-immutable: true\n deployedModels:\n type: array\n x-dcl-go-name: DeployedModels\n readOnly: true\n description: Output only. The models deployed in this Endpoint. To add or\n remove DeployedModels use EndpointService.DeployModel and EndpointService.UndeployModel\n respectively.\n x-kubernetes-immutable: true\n x-dcl-list-type: list\n items:\n type: object\n x-dcl-go-type: EndpointDeployedModels\n properties:\n automaticResources:\n type: object\n x-dcl-go-name: AutomaticResources\n x-dcl-go-type: EndpointDeployedModelsAutomaticResources\n description: A description of resources that to large degree are decided\n by Vertex AI, and require only a modest additional configuration.\n x-kubernetes-immutable: true\n x-dcl-conflicts:\n - dedicatedResources\n properties:\n maxReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MaxReplicaCount\n description: The maximum number of replicas this DeployedModel\n may be deployed on when the traffic against it increases. If\n the requested value is too large, the deployment will error,\n but if deployment succeeds then the ability to scale the model\n to that many replicas is guaranteed (barring service outages).\n If traffic against the DeployedModel increases beyond what its\n replicas at maximum may handle, a portion of the traffic will\n be dropped. If this value is not provided, a no upper bound\n for scaling under heavy traffic will be assume, though Vertex\n AI may be unable to scale beyond certain replica number.\n x-kubernetes-immutable: true\n minReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MinReplicaCount\n description: The minimum number of replicas this DeployedModel\n will be always deployed on. If traffic against it increases,\n it may dynamically be deployed onto more replicas up to max_replica_count,\n and as traffic decreases, some of these extra replicas may be\n freed. If the requested value is too large, the deployment will\n error.\n x-kubernetes-immutable: true\n createTime:\n type: string\n format: date-time\n x-dcl-go-name: CreateTime\n readOnly: true\n description: Output only. Timestamp when the DeployedModel was created.\n x-kubernetes-immutable: true\n dedicatedResources:\n type: object\n x-dcl-go-name: DedicatedResources\n x-dcl-go-type: EndpointDeployedModelsDedicatedResources\n description: A description of resources that are dedicated to the\n DeployedModel, and that need a higher degree of manual configuration.\n x-kubernetes-immutable: true\n x-dcl-conflicts:\n - automaticResources\n properties:\n autoscalingMetricSpecs:\n type: array\n x-dcl-go-name: AutoscalingMetricSpecs\n description: The metric specifications that overrides a resource\n utilization metric (CPU utilization, accelerator's duty cycle,\n and so on) target value (default to 60 if not set). At most\n one entry is allowed per metric. If machine_spec.accelerator_count\n is above 0, the autoscaling will be based on both CPU utilization\n and accelerator's duty cycle metrics and scale up when either\n metrics exceeds its target value while scale down if both metrics\n are under their target value. The default target value is 60\n for both metrics. If machine_spec.accelerator_count is 0, the\n autoscaling will be based on CPU utilization metric only with\n default target value 60 if not explicitly set. For example,\n in the case of Online Prediction, if you want to override target\n CPU utilization to 80, you should set autoscaling_metric_specs.metric_name\n to `aiplatform.googleapis.com/prediction/online/cpu/utilization`\n and autoscaling_metric_specs.target to `80`.\n x-kubernetes-immutable: true\n x-dcl-send-empty: true\n x-dcl-list-type: list\n items:\n type: object\n x-dcl-go-type: EndpointDeployedModelsDedicatedResourcesAutoscalingMetricSpecs\n properties:\n metricName:\n type: string\n x-dcl-go-name: MetricName\n description: 'The resource metric name. Supported metrics:\n * For Online Prediction: * `aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle`\n * `aiplatform.googleapis.com/prediction/online/cpu/utilization`'\n x-kubernetes-immutable: true\n target:\n type: integer\n format: int64\n x-dcl-go-name: Target\n description: The target resource utilization in percentage\n (1% - 100%) for the given metric; once the real usage\n deviates from the target by a certain percentage, the\n machine replicas change. The default value is 60 (representing\n 60%) if not provided.\n x-kubernetes-immutable: true\n machineSpec:\n type: object\n x-dcl-go-name: MachineSpec\n x-dcl-go-type: EndpointDeployedModelsDedicatedResourcesMachineSpec\n description: The specification of a single machine used by the\n prediction.\n x-kubernetes-immutable: true\n properties:\n acceleratorCount:\n type: integer\n format: int64\n x-dcl-go-name: AcceleratorCount\n description: The number of accelerators to attach to the machine.\n x-kubernetes-immutable: true\n acceleratorType:\n type: string\n x-dcl-go-name: AcceleratorType\n x-dcl-go-type: EndpointDeployedModelsDedicatedResourcesMachineSpecAcceleratorTypeEnum\n description: 'The type of accelerator(s) that may be attached\n to the machine as per accelerator_count. Possible values:\n ACCELERATOR_TYPE_UNSPECIFIED, NVIDIA_TESLA_K80, NVIDIA_TESLA_P100,\n NVIDIA_TESLA_V100, NVIDIA_TESLA_P4, NVIDIA_TESLA_T4, NVIDIA_TESLA_A100,\n TPU_V2, TPU_V3'\n x-kubernetes-immutable: true\n enum:\n - ACCELERATOR_TYPE_UNSPECIFIED\n - NVIDIA_TESLA_K80\n - NVIDIA_TESLA_P100\n - NVIDIA_TESLA_V100\n - NVIDIA_TESLA_P4\n - NVIDIA_TESLA_T4\n - NVIDIA_TESLA_A100\n - TPU_V2\n - TPU_V3\n machineType:\n type: string\n x-dcl-go-name: MachineType\n description: 'The type of the machine. See the [list of machine\n types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types)\n See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types).\n For DeployedModel this field is optional, and the default\n value is `n1-standard-2`. For BatchPredictionJob or as part\n of WorkerPoolSpec this field is required. TODO(rsurowka):\n Try to better unify the required vs optional.'\n x-kubernetes-immutable: true\n maxReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MaxReplicaCount\n description: The maximum number of replicas this DeployedModel\n may be deployed on when the traffic against it increases. If\n the requested value is too large, the deployment will error,\n but if deployment succeeds then the ability to scale the model\n to that many replicas is guaranteed (barring service outages).\n If traffic against the DeployedModel increases beyond what its\n replicas at maximum may handle, a portion of the traffic will\n be dropped. If this value is not provided, will use min_replica_count\n as the default value. The value of this field impacts the charge\n against Vertex CPU and GPU quotas. Specifically, you will be\n charged for max_replica_count * number of cores in the selected\n machine type) and (max_replica_count * number of GPUs per replica\n in the selected machine type).\n x-kubernetes-immutable: true\n minReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MinReplicaCount\n description: The minimum number of machine replicas this DeployedModel\n will be always deployed on. This value must be greater than\n or equal to 1. If traffic against the DeployedModel increases,\n it may dynamically be deployed onto more replicas, and as traffic\n decreases, some of these extra replicas may be freed.\n x-kubernetes-immutable: true\n displayName:\n type: string\n x-dcl-go-name: DisplayName\n description: The display name of the DeployedModel. If not provided\n upon creation, the Model's display_name is used.\n x-kubernetes-immutable: true\n enableAccessLogging:\n type: boolean\n x-dcl-go-name: EnableAccessLogging\n description: These logs are like standard server access logs, containing\n information like timestamp and latency for each prediction request.\n Note that Stackdriver logs may incur a cost, especially if your\n project receives prediction requests at a high queries per second\n rate (QPS). Estimate your costs before enabling this option.\n x-kubernetes-immutable: true\n enableContainerLogging:\n type: boolean\n x-dcl-go-name: EnableContainerLogging\n description: If true, the container of the DeployedModel instances\n will send `stderr` and `stdout` streams to Stackdriver Logging.\n Only supported for custom-trained Models and AutoML Tabular Models.\n x-kubernetes-immutable: true\n id:\n type: string\n x-dcl-go-name: Id\n description: The ID of the DeployedModel. If not provided upon deployment,\n Vertex AI will generate a value for this ID. This value should be\n 1-10 characters, and valid characters are /[0-9]/.\n x-kubernetes-immutable: true\n model:\n type: string\n x-dcl-go-name: Model\n description: The name of the Model that this is the deployment of.\n Note that the Model may be in a different location than the DeployedModel's\n Endpoint.\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Aiplatform/Model\n field: selfLink\n modelVersionId:\n type: string\n x-dcl-go-name: ModelVersionId\n readOnly: true\n description: Output only. The version ID of the model that is deployed.\n x-kubernetes-immutable: true\n privateEndpoints:\n type: object\n x-dcl-go-name: PrivateEndpoints\n x-dcl-go-type: EndpointDeployedModelsPrivateEndpoints\n readOnly: true\n description: Output only. Provide paths for users to send predict/explain/health\n requests directly to the deployed model services running on Cloud\n via private services access. This field is populated if network\n is configured.\n x-kubernetes-immutable: true\n properties:\n explainHttpUri:\n type: string\n x-dcl-go-name: ExplainHttpUri\n readOnly: true\n description: Output only. Http(s) path to send explain requests.\n x-kubernetes-immutable: true\n healthHttpUri:\n type: string\n x-dcl-go-name: HealthHttpUri\n readOnly: true\n description: Output only. Http(s) path to send health check requests.\n x-kubernetes-immutable: true\n predictHttpUri:\n type: string\n x-dcl-go-name: PredictHttpUri\n readOnly: true\n description: Output only. Http(s) path to send prediction requests.\n x-kubernetes-immutable: true\n serviceAttachment:\n type: string\n x-dcl-go-name: ServiceAttachment\n readOnly: true\n description: Output only. The name of the service attachment resource.\n Populated if private service connect is enabled.\n x-kubernetes-immutable: true\n serviceAccount:\n type: string\n x-dcl-go-name: ServiceAccount\n description: The service account that the DeployedModel's container\n runs as. Specify the email address of the service account. If this\n service account is not specified, the container runs as a service\n account that doesn't have access to the resource project. Users\n deploying the Model must have the `iam.serviceAccounts.actAs` permission\n on this service account.\n x-kubernetes-immutable: true\n sharedResources:\n type: string\n x-dcl-go-name: SharedResources\n description: 'The resource name of the shared DeploymentResourcePool\n to deploy on. Format: projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}'\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Aiplatform/DeploymentResourcePool\n field: selfLink\n description:\n type: string\n x-dcl-go-name: Description\n description: The description of the Endpoint.\n displayName:\n type: string\n x-dcl-go-name: DisplayName\n description: Required. The display name of the Endpoint. The name can be\n up to 128 characters long and can be consist of any UTF-8 characters.\n encryptionSpec:\n type: object\n x-dcl-go-name: EncryptionSpec\n x-dcl-go-type: EndpointEncryptionSpec\n description: Customer-managed encryption key spec for an Endpoint. If set,\n this Endpoint and all sub-resources of this Endpoint will be secured by\n this key.\n x-kubernetes-immutable: true\n required:\n - kmsKeyName\n properties:\n kmsKeyName:\n type: string\n x-dcl-go-name: KmsKeyName\n description: 'Required. The Cloud KMS resource identifier of the customer\n managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`.\n The key needs to be in the same region as where the compute resource\n is created.'\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Cloudkms/CryptoKey\n field: name\n etag:\n type: string\n x-dcl-go-name: Etag\n readOnly: true\n description: Used to perform consistent read-modify-write updates. If not\n set, a blind \"overwrite\" update happens.\n x-kubernetes-immutable: true\n labels:\n type: object\n additionalProperties:\n type: string\n x-dcl-go-name: Labels\n description: The labels with user-defined metadata to organize your Endpoints.\n Label keys and values can be no longer than 64 characters (Unicode codepoints),\n can only contain lowercase letters, numeric characters, underscores and\n dashes. International characters are allowed. See https://goo.gl/xmQnxf\n for more information and examples of labels.\n location:\n type: string\n x-dcl-go-name: Location\n description: The location for the resource\n x-kubernetes-immutable: true\n modelDeploymentMonitoringJob:\n type: string\n x-dcl-go-name: ModelDeploymentMonitoringJob\n readOnly: true\n description: 'Output only. Resource name of the Model Monitoring job associated\n with this Endpoint if monitoring is enabled by CreateModelDeploymentMonitoringJob.\n Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`'\n x-kubernetes-immutable: true\n name:\n type: string\n x-dcl-go-name: Name\n description: Output only. The resource name of the Endpoint.\n x-kubernetes-immutable: true\n x-dcl-server-generated-parameter: true\n network:\n type: string\n x-dcl-go-name: Network\n description: 'The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)\n to which the Endpoint should be peered. Private services access must already\n be configured for the network. If left unspecified, the Endpoint is not\n peered with any network. Only one of the fields, network or enable_private_service_connect,\n can be set. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert):\n `projects/{project}/global/networks/{network}`. Where `{project}` is a\n project number, as in `12345`, and `{network}` is network name.'\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Compute/Network\n field: selfLink\n project:\n type: string\n x-dcl-go-name: Project\n description: The project for the resource\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Cloudresourcemanager/Project\n field: name\n parent: true\n updateTime:\n type: string\n format: date-time\n x-dcl-go-name: UpdateTime\n readOnly: true\n description: Output only. Timestamp when this Endpoint was last updated.\n x-kubernetes-immutable: true\n") -// 23326 bytes -// MD5: f2d199a3c33262380fcf26e97f9ba8ae +// 22688 bytes +// MD5: 9e881ec31f7d4004ab9b72923b135488 diff --git a/services/google/vertexai/beta/endpoint_internal.go b/services/google/vertexai/beta/endpoint_internal.go index 475ed748fb..6c492327f7 100755 --- a/services/google/vertexai/beta/endpoint_internal.go +++ b/services/google/vertexai/beta/endpoint_internal.go @@ -692,11 +692,6 @@ func canonicalizeEndpointDeployedModels(des, initial *EndpointDeployedModels, op } else { cDes.ServiceAccount = des.ServiceAccount } - if dcl.BoolCanonicalize(des.DisableContainerLogging, initial.DisableContainerLogging) || dcl.IsZeroValue(des.DisableContainerLogging) { - cDes.DisableContainerLogging = initial.DisableContainerLogging - } else { - cDes.DisableContainerLogging = des.DisableContainerLogging - } if dcl.BoolCanonicalize(des.EnableAccessLogging, initial.EnableAccessLogging) || dcl.IsZeroValue(des.EnableAccessLogging) { cDes.EnableAccessLogging = initial.EnableAccessLogging } else { @@ -773,9 +768,6 @@ func canonicalizeNewEndpointDeployedModels(c *Client, des, nw *EndpointDeployedM if dcl.StringCanonicalize(des.ServiceAccount, nw.ServiceAccount) { nw.ServiceAccount = des.ServiceAccount } - if dcl.BoolCanonicalize(des.DisableContainerLogging, nw.DisableContainerLogging) { - nw.DisableContainerLogging = des.DisableContainerLogging - } if dcl.BoolCanonicalize(des.EnableAccessLogging, nw.EnableAccessLogging) { nw.EnableAccessLogging = des.EnableAccessLogging } @@ -1736,13 +1728,6 @@ func compareEndpointDeployedModelsNewStyle(d, a interface{}, fn dcl.FieldName) ( diffs = append(diffs, ds...) } - if ds, err := dcl.Diff(desired.DisableContainerLogging, actual.DisableContainerLogging, dcl.DiffInfo{OperationSelector: dcl.RequiresRecreate()}, fn.AddNest("DisableContainerLogging")); len(ds) != 0 || err != nil { - if err != nil { - return nil, err - } - diffs = append(diffs, ds...) - } - if ds, err := dcl.Diff(desired.EnableAccessLogging, actual.EnableAccessLogging, dcl.DiffInfo{OperationSelector: dcl.RequiresRecreate()}, fn.AddNest("EnableAccessLogging")); len(ds) != 0 || err != nil { if err != nil { return nil, err @@ -2261,9 +2246,6 @@ func expandEndpointDeployedModels(c *Client, f *EndpointDeployedModels, res *End if v := f.ServiceAccount; !dcl.IsEmptyValueIndirect(v) { m["serviceAccount"] = v } - if v := f.DisableContainerLogging; !dcl.IsEmptyValueIndirect(v) { - m["disableContainerLogging"] = v - } if v := f.EnableAccessLogging; !dcl.IsEmptyValueIndirect(v) { m["enableAccessLogging"] = v } @@ -2298,7 +2280,6 @@ func flattenEndpointDeployedModels(c *Client, i interface{}, res *Endpoint) *End r.DisplayName = dcl.FlattenString(m["displayName"]) r.CreateTime = dcl.FlattenString(m["createTime"]) r.ServiceAccount = dcl.FlattenString(m["serviceAccount"]) - r.DisableContainerLogging = dcl.FlattenBool(m["disableContainerLogging"]) r.EnableAccessLogging = dcl.FlattenBool(m["enableAccessLogging"]) r.PrivateEndpoints = flattenEndpointDeployedModelsPrivateEndpoints(c, m["privateEndpoints"], res) r.SharedResources = dcl.FlattenString(m["sharedResources"]) diff --git a/services/google/vertexai/beta/endpoint_schema.go b/services/google/vertexai/beta/endpoint_schema.go index 4c54872be7..0dcafda4a0 100755 --- a/services/google/vertexai/beta/endpoint_schema.go +++ b/services/google/vertexai/beta/endpoint_schema.go @@ -256,12 +256,6 @@ func DCLEndpointSchema() *dcl.Schema { }, }, }, - "disableContainerLogging": &dcl.Property{ - Type: "boolean", - GoName: "DisableContainerLogging", - Description: "For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Stackdriver Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/stackdriver/pricing). User can disable container logging by setting this flag to true.", - Immutable: true, - }, "displayName": &dcl.Property{ Type: "string", GoName: "DisplayName", diff --git a/services/google/vertexai/endpoint.go b/services/google/vertexai/endpoint.go index 021a48fa31..59b0447c57 100755 --- a/services/google/vertexai/endpoint.go +++ b/services/google/vertexai/endpoint.go @@ -72,18 +72,17 @@ func (v EndpointDeployedModelsDedicatedResourcesMachineSpecAcceleratorTypeEnum) } type EndpointDeployedModels struct { - empty bool `json:"-"` - DedicatedResources *EndpointDeployedModelsDedicatedResources `json:"dedicatedResources"` - AutomaticResources *EndpointDeployedModelsAutomaticResources `json:"automaticResources"` - Id *string `json:"id"` - Model *string `json:"model"` - ModelVersionId *string `json:"modelVersionId"` - DisplayName *string `json:"displayName"` - CreateTime *string `json:"createTime"` - ServiceAccount *string `json:"serviceAccount"` - DisableContainerLogging *bool `json:"disableContainerLogging"` - EnableAccessLogging *bool `json:"enableAccessLogging"` - PrivateEndpoints *EndpointDeployedModelsPrivateEndpoints `json:"privateEndpoints"` + empty bool `json:"-"` + DedicatedResources *EndpointDeployedModelsDedicatedResources `json:"dedicatedResources"` + AutomaticResources *EndpointDeployedModelsAutomaticResources `json:"automaticResources"` + Id *string `json:"id"` + Model *string `json:"model"` + ModelVersionId *string `json:"modelVersionId"` + DisplayName *string `json:"displayName"` + CreateTime *string `json:"createTime"` + ServiceAccount *string `json:"serviceAccount"` + EnableAccessLogging *bool `json:"enableAccessLogging"` + PrivateEndpoints *EndpointDeployedModelsPrivateEndpoints `json:"privateEndpoints"` } type jsonEndpointDeployedModels EndpointDeployedModels @@ -117,8 +116,6 @@ func (r *EndpointDeployedModels) UnmarshalJSON(data []byte) error { r.ServiceAccount = res.ServiceAccount - r.DisableContainerLogging = res.DisableContainerLogging - r.EnableAccessLogging = res.EnableAccessLogging r.PrivateEndpoints = res.PrivateEndpoints diff --git a/services/google/vertexai/endpoint.yaml b/services/google/vertexai/endpoint.yaml index 00400ec202..b5a0bcf9b0 100755 --- a/services/google/vertexai/endpoint.yaml +++ b/services/google/vertexai/endpoint.yaml @@ -263,15 +263,6 @@ components: it may dynamically be deployed onto more replicas, and as traffic decreases, some of these extra replicas may be freed. x-kubernetes-immutable: true - disableContainerLogging: - type: boolean - x-dcl-go-name: DisableContainerLogging - description: For custom-trained Models and AutoML Tabular Models, - the container of the DeployedModel instances will send `stderr` - and `stdout` streams to Stackdriver Logging by default. Please note - that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/stackdriver/pricing). - User can disable container logging by setting this flag to true. - x-kubernetes-immutable: true displayName: type: string x-dcl-go-name: DisplayName diff --git a/services/google/vertexai/endpoint_internal.go b/services/google/vertexai/endpoint_internal.go index 5f3f83683b..7fbd646c86 100755 --- a/services/google/vertexai/endpoint_internal.go +++ b/services/google/vertexai/endpoint_internal.go @@ -692,11 +692,6 @@ func canonicalizeEndpointDeployedModels(des, initial *EndpointDeployedModels, op } else { cDes.ServiceAccount = des.ServiceAccount } - if dcl.BoolCanonicalize(des.DisableContainerLogging, initial.DisableContainerLogging) || dcl.IsZeroValue(des.DisableContainerLogging) { - cDes.DisableContainerLogging = initial.DisableContainerLogging - } else { - cDes.DisableContainerLogging = des.DisableContainerLogging - } if dcl.BoolCanonicalize(des.EnableAccessLogging, initial.EnableAccessLogging) || dcl.IsZeroValue(des.EnableAccessLogging) { cDes.EnableAccessLogging = initial.EnableAccessLogging } else { @@ -762,9 +757,6 @@ func canonicalizeNewEndpointDeployedModels(c *Client, des, nw *EndpointDeployedM if dcl.StringCanonicalize(des.ServiceAccount, nw.ServiceAccount) { nw.ServiceAccount = des.ServiceAccount } - if dcl.BoolCanonicalize(des.DisableContainerLogging, nw.DisableContainerLogging) { - nw.DisableContainerLogging = des.DisableContainerLogging - } if dcl.BoolCanonicalize(des.EnableAccessLogging, nw.EnableAccessLogging) { nw.EnableAccessLogging = des.EnableAccessLogging } @@ -1722,13 +1714,6 @@ func compareEndpointDeployedModelsNewStyle(d, a interface{}, fn dcl.FieldName) ( diffs = append(diffs, ds...) } - if ds, err := dcl.Diff(desired.DisableContainerLogging, actual.DisableContainerLogging, dcl.DiffInfo{OperationSelector: dcl.RequiresRecreate()}, fn.AddNest("DisableContainerLogging")); len(ds) != 0 || err != nil { - if err != nil { - return nil, err - } - diffs = append(diffs, ds...) - } - if ds, err := dcl.Diff(desired.EnableAccessLogging, actual.EnableAccessLogging, dcl.DiffInfo{OperationSelector: dcl.RequiresRecreate()}, fn.AddNest("EnableAccessLogging")); len(ds) != 0 || err != nil { if err != nil { return nil, err @@ -2233,9 +2218,6 @@ func expandEndpointDeployedModels(c *Client, f *EndpointDeployedModels, res *End if v := f.ServiceAccount; !dcl.IsEmptyValueIndirect(v) { m["serviceAccount"] = v } - if v := f.DisableContainerLogging; !dcl.IsEmptyValueIndirect(v) { - m["disableContainerLogging"] = v - } if v := f.EnableAccessLogging; !dcl.IsEmptyValueIndirect(v) { m["enableAccessLogging"] = v } @@ -2264,7 +2246,6 @@ func flattenEndpointDeployedModels(c *Client, i interface{}, res *Endpoint) *End r.DisplayName = dcl.FlattenString(m["displayName"]) r.CreateTime = dcl.FlattenString(m["createTime"]) r.ServiceAccount = dcl.FlattenString(m["serviceAccount"]) - r.DisableContainerLogging = dcl.FlattenBool(m["disableContainerLogging"]) r.EnableAccessLogging = dcl.FlattenBool(m["enableAccessLogging"]) r.PrivateEndpoints = flattenEndpointDeployedModelsPrivateEndpoints(c, m["privateEndpoints"], res) diff --git a/services/google/vertexai/endpoint_schema.go b/services/google/vertexai/endpoint_schema.go index 6d949ba889..cbafb77539 100755 --- a/services/google/vertexai/endpoint_schema.go +++ b/services/google/vertexai/endpoint_schema.go @@ -256,12 +256,6 @@ func DCLEndpointSchema() *dcl.Schema { }, }, }, - "disableContainerLogging": &dcl.Property{ - Type: "boolean", - GoName: "DisableContainerLogging", - Description: "For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Stackdriver Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/stackdriver/pricing). User can disable container logging by setting this flag to true.", - Immutable: true, - }, "displayName": &dcl.Property{ Type: "string", GoName: "DisplayName", diff --git a/services/google/vertexai/endpoint_yaml_embed.go b/services/google/vertexai/endpoint_yaml_embed.go index def891dfab..7e69567a41 100755 --- a/services/google/vertexai/endpoint_yaml_embed.go +++ b/services/google/vertexai/endpoint_yaml_embed.go @@ -17,7 +17,7 @@ package vertexai // blaze-out/k8-fastbuild/genfiles/cloud/graphite/mmv2/services/google/vertexai/endpoint.yaml -var YAML_endpoint = []byte("info:\n title: VertexAI/Endpoint\n description: The VertexAI Endpoint resource\n x-dcl-struct-name: Endpoint\n x-dcl-has-iam: false\npaths:\n get:\n description: The function used to get information about a Endpoint\n parameters:\n - name: Endpoint\n required: true\n description: A full instance of a Endpoint\n apply:\n description: The function used to apply information about a Endpoint\n parameters:\n - name: Endpoint\n required: true\n description: A full instance of a Endpoint\n delete:\n description: The function used to delete a Endpoint\n parameters:\n - name: Endpoint\n required: true\n description: A full instance of a Endpoint\n deleteAll:\n description: The function used to delete all Endpoint\n parameters:\n - name: project\n required: true\n schema:\n type: string\n - name: location\n required: true\n schema:\n type: string\n list:\n description: The function used to list information about many Endpoint\n parameters:\n - name: project\n required: true\n schema:\n type: string\n - name: location\n required: true\n schema:\n type: string\ncomponents:\n schemas:\n Endpoint:\n title: Endpoint\n x-dcl-id: projects/{{project}}/locations/{{location}}/endpoints/{{name}}\n x-dcl-parent-container: project\n x-dcl-labels: labels\n x-dcl-has-create: true\n x-dcl-has-iam: false\n x-dcl-read-timeout: 0\n x-dcl-apply-timeout: 0\n x-dcl-delete-timeout: 0\n type: object\n required:\n - displayName\n - project\n - location\n properties:\n createTime:\n type: string\n format: date-time\n x-dcl-go-name: CreateTime\n readOnly: true\n description: Output only. Timestamp when this Endpoint was created.\n x-kubernetes-immutable: true\n deployedModels:\n type: array\n x-dcl-go-name: DeployedModels\n readOnly: true\n description: Output only. The models deployed in this Endpoint. To add or\n remove DeployedModels use EndpointService.DeployModel and EndpointService.UndeployModel\n respectively.\n x-kubernetes-immutable: true\n x-dcl-list-type: list\n items:\n type: object\n x-dcl-go-type: EndpointDeployedModels\n properties:\n automaticResources:\n type: object\n x-dcl-go-name: AutomaticResources\n x-dcl-go-type: EndpointDeployedModelsAutomaticResources\n description: A description of resources that to large degree are decided\n by Vertex AI, and require only a modest additional configuration.\n x-kubernetes-immutable: true\n x-dcl-conflicts:\n - dedicatedResources\n properties:\n maxReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MaxReplicaCount\n description: The maximum number of replicas this DeployedModel\n may be deployed on when the traffic against it increases. If\n the requested value is too large, the deployment will error,\n but if deployment succeeds then the ability to scale the model\n to that many replicas is guaranteed (barring service outages).\n If traffic against the DeployedModel increases beyond what its\n replicas at maximum may handle, a portion of the traffic will\n be dropped. If this value is not provided, a no upper bound\n for scaling under heavy traffic will be assume, though Vertex\n AI may be unable to scale beyond certain replica number.\n x-kubernetes-immutable: true\n minReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MinReplicaCount\n description: The minimum number of replicas this DeployedModel\n will be always deployed on. If traffic against it increases,\n it may dynamically be deployed onto more replicas up to max_replica_count,\n and as traffic decreases, some of these extra replicas may be\n freed. If the requested value is too large, the deployment will\n error.\n x-kubernetes-immutable: true\n createTime:\n type: string\n format: date-time\n x-dcl-go-name: CreateTime\n readOnly: true\n description: Output only. Timestamp when the DeployedModel was created.\n x-kubernetes-immutable: true\n dedicatedResources:\n type: object\n x-dcl-go-name: DedicatedResources\n x-dcl-go-type: EndpointDeployedModelsDedicatedResources\n description: A description of resources that are dedicated to the\n DeployedModel, and that need a higher degree of manual configuration.\n x-kubernetes-immutable: true\n x-dcl-conflicts:\n - automaticResources\n properties:\n autoscalingMetricSpecs:\n type: array\n x-dcl-go-name: AutoscalingMetricSpecs\n description: The metric specifications that overrides a resource\n utilization metric (CPU utilization, accelerator's duty cycle,\n and so on) target value (default to 60 if not set). At most\n one entry is allowed per metric. If machine_spec.accelerator_count\n is above 0, the autoscaling will be based on both CPU utilization\n and accelerator's duty cycle metrics and scale up when either\n metrics exceeds its target value while scale down if both metrics\n are under their target value. The default target value is 60\n for both metrics. If machine_spec.accelerator_count is 0, the\n autoscaling will be based on CPU utilization metric only with\n default target value 60 if not explicitly set. For example,\n in the case of Online Prediction, if you want to override target\n CPU utilization to 80, you should set autoscaling_metric_specs.metric_name\n to `aiplatform.googleapis.com/prediction/online/cpu/utilization`\n and autoscaling_metric_specs.target to `80`.\n x-kubernetes-immutable: true\n x-dcl-send-empty: true\n x-dcl-list-type: list\n items:\n type: object\n x-dcl-go-type: EndpointDeployedModelsDedicatedResourcesAutoscalingMetricSpecs\n properties:\n metricName:\n type: string\n x-dcl-go-name: MetricName\n description: 'The resource metric name. Supported metrics:\n * For Online Prediction: * `aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle`\n * `aiplatform.googleapis.com/prediction/online/cpu/utilization`'\n x-kubernetes-immutable: true\n target:\n type: integer\n format: int64\n x-dcl-go-name: Target\n description: The target resource utilization in percentage\n (1% - 100%) for the given metric; once the real usage\n deviates from the target by a certain percentage, the\n machine replicas change. The default value is 60 (representing\n 60%) if not provided.\n x-kubernetes-immutable: true\n machineSpec:\n type: object\n x-dcl-go-name: MachineSpec\n x-dcl-go-type: EndpointDeployedModelsDedicatedResourcesMachineSpec\n description: The specification of a single machine used by the\n prediction.\n x-kubernetes-immutable: true\n properties:\n acceleratorCount:\n type: integer\n format: int64\n x-dcl-go-name: AcceleratorCount\n description: The number of accelerators to attach to the machine.\n x-kubernetes-immutable: true\n acceleratorType:\n type: string\n x-dcl-go-name: AcceleratorType\n x-dcl-go-type: EndpointDeployedModelsDedicatedResourcesMachineSpecAcceleratorTypeEnum\n description: 'The type of accelerator(s) that may be attached\n to the machine as per accelerator_count. Possible values:\n ACCELERATOR_TYPE_UNSPECIFIED, NVIDIA_TESLA_K80, NVIDIA_TESLA_P100,\n NVIDIA_TESLA_V100, NVIDIA_TESLA_P4, NVIDIA_TESLA_T4, NVIDIA_TESLA_A100,\n TPU_V2, TPU_V3'\n x-kubernetes-immutable: true\n enum:\n - ACCELERATOR_TYPE_UNSPECIFIED\n - NVIDIA_TESLA_K80\n - NVIDIA_TESLA_P100\n - NVIDIA_TESLA_V100\n - NVIDIA_TESLA_P4\n - NVIDIA_TESLA_T4\n - NVIDIA_TESLA_A100\n - TPU_V2\n - TPU_V3\n machineType:\n type: string\n x-dcl-go-name: MachineType\n description: 'The type of the machine. See the [list of machine\n types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types)\n See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types).\n For DeployedModel this field is optional, and the default\n value is `n1-standard-2`. For BatchPredictionJob or as part\n of WorkerPoolSpec this field is required. TODO(rsurowka):\n Try to better unify the required vs optional.'\n x-kubernetes-immutable: true\n maxReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MaxReplicaCount\n description: The maximum number of replicas this DeployedModel\n may be deployed on when the traffic against it increases. If\n the requested value is too large, the deployment will error,\n but if deployment succeeds then the ability to scale the model\n to that many replicas is guaranteed (barring service outages).\n If traffic against the DeployedModel increases beyond what its\n replicas at maximum may handle, a portion of the traffic will\n be dropped. If this value is not provided, will use min_replica_count\n as the default value. The value of this field impacts the charge\n against Vertex CPU and GPU quotas. Specifically, you will be\n charged for max_replica_count * number of cores in the selected\n machine type) and (max_replica_count * number of GPUs per replica\n in the selected machine type).\n x-kubernetes-immutable: true\n minReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MinReplicaCount\n description: The minimum number of machine replicas this DeployedModel\n will be always deployed on. This value must be greater than\n or equal to 1. If traffic against the DeployedModel increases,\n it may dynamically be deployed onto more replicas, and as traffic\n decreases, some of these extra replicas may be freed.\n x-kubernetes-immutable: true\n disableContainerLogging:\n type: boolean\n x-dcl-go-name: DisableContainerLogging\n description: For custom-trained Models and AutoML Tabular Models,\n the container of the DeployedModel instances will send `stderr`\n and `stdout` streams to Stackdriver Logging by default. Please note\n that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/stackdriver/pricing).\n User can disable container logging by setting this flag to true.\n x-kubernetes-immutable: true\n displayName:\n type: string\n x-dcl-go-name: DisplayName\n description: The display name of the DeployedModel. If not provided\n upon creation, the Model's display_name is used.\n x-kubernetes-immutable: true\n enableAccessLogging:\n type: boolean\n x-dcl-go-name: EnableAccessLogging\n description: These logs are like standard server access logs, containing\n information like timestamp and latency for each prediction request.\n Note that Stackdriver logs may incur a cost, especially if your\n project receives prediction requests at a high queries per second\n rate (QPS). Estimate your costs before enabling this option.\n x-kubernetes-immutable: true\n id:\n type: string\n x-dcl-go-name: Id\n description: The ID of the DeployedModel. If not provided upon deployment,\n Vertex AI will generate a value for this ID. This value should be\n 1-10 characters, and valid characters are /[0-9]/.\n x-kubernetes-immutable: true\n model:\n type: string\n x-dcl-go-name: Model\n description: The name of the Model that this is the deployment of.\n Note that the Model may be in a different location than the DeployedModel's\n Endpoint.\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Aiplatform/Model\n field: selfLink\n modelVersionId:\n type: string\n x-dcl-go-name: ModelVersionId\n readOnly: true\n description: Output only. The version ID of the model that is deployed.\n x-kubernetes-immutable: true\n privateEndpoints:\n type: object\n x-dcl-go-name: PrivateEndpoints\n x-dcl-go-type: EndpointDeployedModelsPrivateEndpoints\n readOnly: true\n description: Output only. Provide paths for users to send predict/explain/health\n requests directly to the deployed model services running on Cloud\n via private services access. This field is populated if network\n is configured.\n x-kubernetes-immutable: true\n properties:\n explainHttpUri:\n type: string\n x-dcl-go-name: ExplainHttpUri\n readOnly: true\n description: Output only. Http(s) path to send explain requests.\n x-kubernetes-immutable: true\n healthHttpUri:\n type: string\n x-dcl-go-name: HealthHttpUri\n readOnly: true\n description: Output only. Http(s) path to send health check requests.\n x-kubernetes-immutable: true\n predictHttpUri:\n type: string\n x-dcl-go-name: PredictHttpUri\n readOnly: true\n description: Output only. Http(s) path to send prediction requests.\n x-kubernetes-immutable: true\n serviceAttachment:\n type: string\n x-dcl-go-name: ServiceAttachment\n readOnly: true\n description: Output only. The name of the service attachment resource.\n Populated if private service connect is enabled.\n x-kubernetes-immutable: true\n serviceAccount:\n type: string\n x-dcl-go-name: ServiceAccount\n description: The service account that the DeployedModel's container\n runs as. Specify the email address of the service account. If this\n service account is not specified, the container runs as a service\n account that doesn't have access to the resource project. Users\n deploying the Model must have the `iam.serviceAccounts.actAs` permission\n on this service account.\n x-kubernetes-immutable: true\n description:\n type: string\n x-dcl-go-name: Description\n description: The description of the Endpoint.\n displayName:\n type: string\n x-dcl-go-name: DisplayName\n description: Required. The display name of the Endpoint. The name can be\n up to 128 characters long and can be consist of any UTF-8 characters.\n encryptionSpec:\n type: object\n x-dcl-go-name: EncryptionSpec\n x-dcl-go-type: EndpointEncryptionSpec\n description: Customer-managed encryption key spec for an Endpoint. If set,\n this Endpoint and all sub-resources of this Endpoint will be secured by\n this key.\n x-kubernetes-immutable: true\n required:\n - kmsKeyName\n properties:\n kmsKeyName:\n type: string\n x-dcl-go-name: KmsKeyName\n description: 'Required. The Cloud KMS resource identifier of the customer\n managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`.\n The key needs to be in the same region as where the compute resource\n is created.'\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Cloudkms/CryptoKey\n field: name\n etag:\n type: string\n x-dcl-go-name: Etag\n readOnly: true\n description: Used to perform consistent read-modify-write updates. If not\n set, a blind \"overwrite\" update happens.\n x-kubernetes-immutable: true\n labels:\n type: object\n additionalProperties:\n type: string\n x-dcl-go-name: Labels\n description: The labels with user-defined metadata to organize your Endpoints.\n Label keys and values can be no longer than 64 characters (Unicode codepoints),\n can only contain lowercase letters, numeric characters, underscores and\n dashes. International characters are allowed. See https://goo.gl/xmQnxf\n for more information and examples of labels.\n location:\n type: string\n x-dcl-go-name: Location\n description: The location for the resource\n x-kubernetes-immutable: true\n modelDeploymentMonitoringJob:\n type: string\n x-dcl-go-name: ModelDeploymentMonitoringJob\n readOnly: true\n description: 'Output only. Resource name of the Model Monitoring job associated\n with this Endpoint if monitoring is enabled by CreateModelDeploymentMonitoringJob.\n Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`'\n x-kubernetes-immutable: true\n name:\n type: string\n x-dcl-go-name: Name\n description: Output only. The resource name of the Endpoint.\n x-kubernetes-immutable: true\n x-dcl-server-generated-parameter: true\n network:\n type: string\n x-dcl-go-name: Network\n description: 'The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)\n to which the Endpoint should be peered. Private services access must already\n be configured for the network. If left unspecified, the Endpoint is not\n peered with any network. Only one of the fields, network or enable_private_service_connect,\n can be set. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert):\n `projects/{project}/global/networks/{network}`. Where `{project}` is a\n project number, as in `12345`, and `{network}` is network name.'\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Compute/Network\n field: selfLink\n project:\n type: string\n x-dcl-go-name: Project\n description: The project for the resource\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Cloudresourcemanager/Project\n field: name\n parent: true\n updateTime:\n type: string\n format: date-time\n x-dcl-go-name: UpdateTime\n readOnly: true\n description: Output only. Timestamp when this Endpoint was last updated.\n x-kubernetes-immutable: true\n") +var YAML_endpoint = []byte("info:\n title: VertexAI/Endpoint\n description: The VertexAI Endpoint resource\n x-dcl-struct-name: Endpoint\n x-dcl-has-iam: false\npaths:\n get:\n description: The function used to get information about a Endpoint\n parameters:\n - name: Endpoint\n required: true\n description: A full instance of a Endpoint\n apply:\n description: The function used to apply information about a Endpoint\n parameters:\n - name: Endpoint\n required: true\n description: A full instance of a Endpoint\n delete:\n description: The function used to delete a Endpoint\n parameters:\n - name: Endpoint\n required: true\n description: A full instance of a Endpoint\n deleteAll:\n description: The function used to delete all Endpoint\n parameters:\n - name: project\n required: true\n schema:\n type: string\n - name: location\n required: true\n schema:\n type: string\n list:\n description: The function used to list information about many Endpoint\n parameters:\n - name: project\n required: true\n schema:\n type: string\n - name: location\n required: true\n schema:\n type: string\ncomponents:\n schemas:\n Endpoint:\n title: Endpoint\n x-dcl-id: projects/{{project}}/locations/{{location}}/endpoints/{{name}}\n x-dcl-parent-container: project\n x-dcl-labels: labels\n x-dcl-has-create: true\n x-dcl-has-iam: false\n x-dcl-read-timeout: 0\n x-dcl-apply-timeout: 0\n x-dcl-delete-timeout: 0\n type: object\n required:\n - displayName\n - project\n - location\n properties:\n createTime:\n type: string\n format: date-time\n x-dcl-go-name: CreateTime\n readOnly: true\n description: Output only. Timestamp when this Endpoint was created.\n x-kubernetes-immutable: true\n deployedModels:\n type: array\n x-dcl-go-name: DeployedModels\n readOnly: true\n description: Output only. The models deployed in this Endpoint. To add or\n remove DeployedModels use EndpointService.DeployModel and EndpointService.UndeployModel\n respectively.\n x-kubernetes-immutable: true\n x-dcl-list-type: list\n items:\n type: object\n x-dcl-go-type: EndpointDeployedModels\n properties:\n automaticResources:\n type: object\n x-dcl-go-name: AutomaticResources\n x-dcl-go-type: EndpointDeployedModelsAutomaticResources\n description: A description of resources that to large degree are decided\n by Vertex AI, and require only a modest additional configuration.\n x-kubernetes-immutable: true\n x-dcl-conflicts:\n - dedicatedResources\n properties:\n maxReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MaxReplicaCount\n description: The maximum number of replicas this DeployedModel\n may be deployed on when the traffic against it increases. If\n the requested value is too large, the deployment will error,\n but if deployment succeeds then the ability to scale the model\n to that many replicas is guaranteed (barring service outages).\n If traffic against the DeployedModel increases beyond what its\n replicas at maximum may handle, a portion of the traffic will\n be dropped. If this value is not provided, a no upper bound\n for scaling under heavy traffic will be assume, though Vertex\n AI may be unable to scale beyond certain replica number.\n x-kubernetes-immutable: true\n minReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MinReplicaCount\n description: The minimum number of replicas this DeployedModel\n will be always deployed on. If traffic against it increases,\n it may dynamically be deployed onto more replicas up to max_replica_count,\n and as traffic decreases, some of these extra replicas may be\n freed. If the requested value is too large, the deployment will\n error.\n x-kubernetes-immutable: true\n createTime:\n type: string\n format: date-time\n x-dcl-go-name: CreateTime\n readOnly: true\n description: Output only. Timestamp when the DeployedModel was created.\n x-kubernetes-immutable: true\n dedicatedResources:\n type: object\n x-dcl-go-name: DedicatedResources\n x-dcl-go-type: EndpointDeployedModelsDedicatedResources\n description: A description of resources that are dedicated to the\n DeployedModel, and that need a higher degree of manual configuration.\n x-kubernetes-immutable: true\n x-dcl-conflicts:\n - automaticResources\n properties:\n autoscalingMetricSpecs:\n type: array\n x-dcl-go-name: AutoscalingMetricSpecs\n description: The metric specifications that overrides a resource\n utilization metric (CPU utilization, accelerator's duty cycle,\n and so on) target value (default to 60 if not set). At most\n one entry is allowed per metric. If machine_spec.accelerator_count\n is above 0, the autoscaling will be based on both CPU utilization\n and accelerator's duty cycle metrics and scale up when either\n metrics exceeds its target value while scale down if both metrics\n are under their target value. The default target value is 60\n for both metrics. If machine_spec.accelerator_count is 0, the\n autoscaling will be based on CPU utilization metric only with\n default target value 60 if not explicitly set. For example,\n in the case of Online Prediction, if you want to override target\n CPU utilization to 80, you should set autoscaling_metric_specs.metric_name\n to `aiplatform.googleapis.com/prediction/online/cpu/utilization`\n and autoscaling_metric_specs.target to `80`.\n x-kubernetes-immutable: true\n x-dcl-send-empty: true\n x-dcl-list-type: list\n items:\n type: object\n x-dcl-go-type: EndpointDeployedModelsDedicatedResourcesAutoscalingMetricSpecs\n properties:\n metricName:\n type: string\n x-dcl-go-name: MetricName\n description: 'The resource metric name. Supported metrics:\n * For Online Prediction: * `aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle`\n * `aiplatform.googleapis.com/prediction/online/cpu/utilization`'\n x-kubernetes-immutable: true\n target:\n type: integer\n format: int64\n x-dcl-go-name: Target\n description: The target resource utilization in percentage\n (1% - 100%) for the given metric; once the real usage\n deviates from the target by a certain percentage, the\n machine replicas change. The default value is 60 (representing\n 60%) if not provided.\n x-kubernetes-immutable: true\n machineSpec:\n type: object\n x-dcl-go-name: MachineSpec\n x-dcl-go-type: EndpointDeployedModelsDedicatedResourcesMachineSpec\n description: The specification of a single machine used by the\n prediction.\n x-kubernetes-immutable: true\n properties:\n acceleratorCount:\n type: integer\n format: int64\n x-dcl-go-name: AcceleratorCount\n description: The number of accelerators to attach to the machine.\n x-kubernetes-immutable: true\n acceleratorType:\n type: string\n x-dcl-go-name: AcceleratorType\n x-dcl-go-type: EndpointDeployedModelsDedicatedResourcesMachineSpecAcceleratorTypeEnum\n description: 'The type of accelerator(s) that may be attached\n to the machine as per accelerator_count. Possible values:\n ACCELERATOR_TYPE_UNSPECIFIED, NVIDIA_TESLA_K80, NVIDIA_TESLA_P100,\n NVIDIA_TESLA_V100, NVIDIA_TESLA_P4, NVIDIA_TESLA_T4, NVIDIA_TESLA_A100,\n TPU_V2, TPU_V3'\n x-kubernetes-immutable: true\n enum:\n - ACCELERATOR_TYPE_UNSPECIFIED\n - NVIDIA_TESLA_K80\n - NVIDIA_TESLA_P100\n - NVIDIA_TESLA_V100\n - NVIDIA_TESLA_P4\n - NVIDIA_TESLA_T4\n - NVIDIA_TESLA_A100\n - TPU_V2\n - TPU_V3\n machineType:\n type: string\n x-dcl-go-name: MachineType\n description: 'The type of the machine. See the [list of machine\n types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types)\n See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types).\n For DeployedModel this field is optional, and the default\n value is `n1-standard-2`. For BatchPredictionJob or as part\n of WorkerPoolSpec this field is required. TODO(rsurowka):\n Try to better unify the required vs optional.'\n x-kubernetes-immutable: true\n maxReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MaxReplicaCount\n description: The maximum number of replicas this DeployedModel\n may be deployed on when the traffic against it increases. If\n the requested value is too large, the deployment will error,\n but if deployment succeeds then the ability to scale the model\n to that many replicas is guaranteed (barring service outages).\n If traffic against the DeployedModel increases beyond what its\n replicas at maximum may handle, a portion of the traffic will\n be dropped. If this value is not provided, will use min_replica_count\n as the default value. The value of this field impacts the charge\n against Vertex CPU and GPU quotas. Specifically, you will be\n charged for max_replica_count * number of cores in the selected\n machine type) and (max_replica_count * number of GPUs per replica\n in the selected machine type).\n x-kubernetes-immutable: true\n minReplicaCount:\n type: integer\n format: int64\n x-dcl-go-name: MinReplicaCount\n description: The minimum number of machine replicas this DeployedModel\n will be always deployed on. This value must be greater than\n or equal to 1. If traffic against the DeployedModel increases,\n it may dynamically be deployed onto more replicas, and as traffic\n decreases, some of these extra replicas may be freed.\n x-kubernetes-immutable: true\n displayName:\n type: string\n x-dcl-go-name: DisplayName\n description: The display name of the DeployedModel. If not provided\n upon creation, the Model's display_name is used.\n x-kubernetes-immutable: true\n enableAccessLogging:\n type: boolean\n x-dcl-go-name: EnableAccessLogging\n description: These logs are like standard server access logs, containing\n information like timestamp and latency for each prediction request.\n Note that Stackdriver logs may incur a cost, especially if your\n project receives prediction requests at a high queries per second\n rate (QPS). Estimate your costs before enabling this option.\n x-kubernetes-immutable: true\n id:\n type: string\n x-dcl-go-name: Id\n description: The ID of the DeployedModel. If not provided upon deployment,\n Vertex AI will generate a value for this ID. This value should be\n 1-10 characters, and valid characters are /[0-9]/.\n x-kubernetes-immutable: true\n model:\n type: string\n x-dcl-go-name: Model\n description: The name of the Model that this is the deployment of.\n Note that the Model may be in a different location than the DeployedModel's\n Endpoint.\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Aiplatform/Model\n field: selfLink\n modelVersionId:\n type: string\n x-dcl-go-name: ModelVersionId\n readOnly: true\n description: Output only. The version ID of the model that is deployed.\n x-kubernetes-immutable: true\n privateEndpoints:\n type: object\n x-dcl-go-name: PrivateEndpoints\n x-dcl-go-type: EndpointDeployedModelsPrivateEndpoints\n readOnly: true\n description: Output only. Provide paths for users to send predict/explain/health\n requests directly to the deployed model services running on Cloud\n via private services access. This field is populated if network\n is configured.\n x-kubernetes-immutable: true\n properties:\n explainHttpUri:\n type: string\n x-dcl-go-name: ExplainHttpUri\n readOnly: true\n description: Output only. Http(s) path to send explain requests.\n x-kubernetes-immutable: true\n healthHttpUri:\n type: string\n x-dcl-go-name: HealthHttpUri\n readOnly: true\n description: Output only. Http(s) path to send health check requests.\n x-kubernetes-immutable: true\n predictHttpUri:\n type: string\n x-dcl-go-name: PredictHttpUri\n readOnly: true\n description: Output only. Http(s) path to send prediction requests.\n x-kubernetes-immutable: true\n serviceAttachment:\n type: string\n x-dcl-go-name: ServiceAttachment\n readOnly: true\n description: Output only. The name of the service attachment resource.\n Populated if private service connect is enabled.\n x-kubernetes-immutable: true\n serviceAccount:\n type: string\n x-dcl-go-name: ServiceAccount\n description: The service account that the DeployedModel's container\n runs as. Specify the email address of the service account. If this\n service account is not specified, the container runs as a service\n account that doesn't have access to the resource project. Users\n deploying the Model must have the `iam.serviceAccounts.actAs` permission\n on this service account.\n x-kubernetes-immutable: true\n description:\n type: string\n x-dcl-go-name: Description\n description: The description of the Endpoint.\n displayName:\n type: string\n x-dcl-go-name: DisplayName\n description: Required. The display name of the Endpoint. The name can be\n up to 128 characters long and can be consist of any UTF-8 characters.\n encryptionSpec:\n type: object\n x-dcl-go-name: EncryptionSpec\n x-dcl-go-type: EndpointEncryptionSpec\n description: Customer-managed encryption key spec for an Endpoint. If set,\n this Endpoint and all sub-resources of this Endpoint will be secured by\n this key.\n x-kubernetes-immutable: true\n required:\n - kmsKeyName\n properties:\n kmsKeyName:\n type: string\n x-dcl-go-name: KmsKeyName\n description: 'Required. The Cloud KMS resource identifier of the customer\n managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key`.\n The key needs to be in the same region as where the compute resource\n is created.'\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Cloudkms/CryptoKey\n field: name\n etag:\n type: string\n x-dcl-go-name: Etag\n readOnly: true\n description: Used to perform consistent read-modify-write updates. If not\n set, a blind \"overwrite\" update happens.\n x-kubernetes-immutable: true\n labels:\n type: object\n additionalProperties:\n type: string\n x-dcl-go-name: Labels\n description: The labels with user-defined metadata to organize your Endpoints.\n Label keys and values can be no longer than 64 characters (Unicode codepoints),\n can only contain lowercase letters, numeric characters, underscores and\n dashes. International characters are allowed. See https://goo.gl/xmQnxf\n for more information and examples of labels.\n location:\n type: string\n x-dcl-go-name: Location\n description: The location for the resource\n x-kubernetes-immutable: true\n modelDeploymentMonitoringJob:\n type: string\n x-dcl-go-name: ModelDeploymentMonitoringJob\n readOnly: true\n description: 'Output only. Resource name of the Model Monitoring job associated\n with this Endpoint if monitoring is enabled by CreateModelDeploymentMonitoringJob.\n Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`'\n x-kubernetes-immutable: true\n name:\n type: string\n x-dcl-go-name: Name\n description: Output only. The resource name of the Endpoint.\n x-kubernetes-immutable: true\n x-dcl-server-generated-parameter: true\n network:\n type: string\n x-dcl-go-name: Network\n description: 'The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks)\n to which the Endpoint should be peered. Private services access must already\n be configured for the network. If left unspecified, the Endpoint is not\n peered with any network. Only one of the fields, network or enable_private_service_connect,\n can be set. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert):\n `projects/{project}/global/networks/{network}`. Where `{project}` is a\n project number, as in `12345`, and `{network}` is network name.'\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Compute/Network\n field: selfLink\n project:\n type: string\n x-dcl-go-name: Project\n description: The project for the resource\n x-kubernetes-immutable: true\n x-dcl-references:\n - resource: Cloudresourcemanager/Project\n field: name\n parent: true\n updateTime:\n type: string\n format: date-time\n x-dcl-go-name: UpdateTime\n readOnly: true\n description: Output only. Timestamp when this Endpoint was last updated.\n x-kubernetes-immutable: true\n") -// 22409 bytes -// MD5: 3f2408707643a9528a4b2c52bfdc1177 +// 21771 bytes +// MD5: c7c7328b69f8a0abd274b65d23131cef diff --git a/unstructured/google/vertexai/alpha/endpoint.go b/unstructured/google/vertexai/alpha/endpoint.go index a04cffb63d..16326bac85 100755 --- a/unstructured/google/vertexai/alpha/endpoint.go +++ b/unstructured/google/vertexai/alpha/endpoint.go @@ -86,9 +86,6 @@ func EndpointToUnstructured(r *dclService.Endpoint) *unstructured.Resource { } rDeployedModelsObject["dedicatedResources"] = rDeployedModelsValDedicatedResources } - if rDeployedModelsVal.DisableContainerLogging != nil { - rDeployedModelsObject["disableContainerLogging"] = *rDeployedModelsVal.DisableContainerLogging - } if rDeployedModelsVal.DisplayName != nil { rDeployedModelsObject["displayName"] = *rDeployedModelsVal.DisplayName } @@ -293,13 +290,6 @@ func UnstructuredToEndpoint(u *unstructured.Resource) (*dclService.Endpoint, err return nil, fmt.Errorf("rDeployedModels.DedicatedResources: expected map[string]interface{}") } } - if _, ok := objval["disableContainerLogging"]; ok { - if b, ok := objval["disableContainerLogging"].(bool); ok { - rDeployedModels.DisableContainerLogging = dcl.Bool(b) - } else { - return nil, fmt.Errorf("rDeployedModels.DisableContainerLogging: expected bool") - } - } if _, ok := objval["displayName"]; ok { if s, ok := objval["displayName"].(string); ok { rDeployedModels.DisplayName = dcl.String(s) diff --git a/unstructured/google/vertexai/beta/endpoint.go b/unstructured/google/vertexai/beta/endpoint.go index c5dcae0091..81552d78e2 100755 --- a/unstructured/google/vertexai/beta/endpoint.go +++ b/unstructured/google/vertexai/beta/endpoint.go @@ -86,9 +86,6 @@ func EndpointToUnstructured(r *dclService.Endpoint) *unstructured.Resource { } rDeployedModelsObject["dedicatedResources"] = rDeployedModelsValDedicatedResources } - if rDeployedModelsVal.DisableContainerLogging != nil { - rDeployedModelsObject["disableContainerLogging"] = *rDeployedModelsVal.DisableContainerLogging - } if rDeployedModelsVal.DisplayName != nil { rDeployedModelsObject["displayName"] = *rDeployedModelsVal.DisplayName } @@ -293,13 +290,6 @@ func UnstructuredToEndpoint(u *unstructured.Resource) (*dclService.Endpoint, err return nil, fmt.Errorf("rDeployedModels.DedicatedResources: expected map[string]interface{}") } } - if _, ok := objval["disableContainerLogging"]; ok { - if b, ok := objval["disableContainerLogging"].(bool); ok { - rDeployedModels.DisableContainerLogging = dcl.Bool(b) - } else { - return nil, fmt.Errorf("rDeployedModels.DisableContainerLogging: expected bool") - } - } if _, ok := objval["displayName"]; ok { if s, ok := objval["displayName"].(string); ok { rDeployedModels.DisplayName = dcl.String(s) diff --git a/unstructured/google/vertexai/endpoint.go b/unstructured/google/vertexai/endpoint.go index 57dbaecf82..847038fa15 100755 --- a/unstructured/google/vertexai/endpoint.go +++ b/unstructured/google/vertexai/endpoint.go @@ -86,9 +86,6 @@ func EndpointToUnstructured(r *dclService.Endpoint) *unstructured.Resource { } rDeployedModelsObject["dedicatedResources"] = rDeployedModelsValDedicatedResources } - if rDeployedModelsVal.DisableContainerLogging != nil { - rDeployedModelsObject["disableContainerLogging"] = *rDeployedModelsVal.DisableContainerLogging - } if rDeployedModelsVal.DisplayName != nil { rDeployedModelsObject["displayName"] = *rDeployedModelsVal.DisplayName } @@ -287,13 +284,6 @@ func UnstructuredToEndpoint(u *unstructured.Resource) (*dclService.Endpoint, err return nil, fmt.Errorf("rDeployedModels.DedicatedResources: expected map[string]interface{}") } } - if _, ok := objval["disableContainerLogging"]; ok { - if b, ok := objval["disableContainerLogging"].(bool); ok { - rDeployedModels.DisableContainerLogging = dcl.Bool(b) - } else { - return nil, fmt.Errorf("rDeployedModels.DisableContainerLogging: expected bool") - } - } if _, ok := objval["displayName"]; ok { if s, ok := objval["displayName"].(string); ok { rDeployedModels.DisplayName = dcl.String(s)