vertex-ai: add :UPLOAD support for model resource

mmv1/products/vertexai/Model.yaml

@@ -44,11 +44,18 @@ custom_diff:
   - 'vertexAiModelDiffSuppress'
 custom_code:
   constants: templates/terraform/constants/vertex_ai_model.go.tmpl
+  update_encoder: templates/terraform/update_encoder/vertex_ai_model.go.tmpl
   decoder: templates/terraform/decoders/vertex_ai_models.go.tmpl
   encoder: templates/terraform/encoders/vertex_ai_models.go.tmpl
   pre_create: templates/terraform/pre_create/vertex_ai_models.go.tmpl
   post_create: templates/terraform/post_create/vertex_ai_models.go.tmpl
 examples:
+  - name: 'vertex_ai_model_upload_basic'
+    exclude_import_test: true
+    primary_resource_id: 'model'
+    vars:
+      project_name: 'PROJECT_NAME'
+      model_name: 'MODEL_NAME'
   - name: 'vertex_ai_model_source_basic_1'
     exclude_import_test: true
     primary_resource_id: 'model'
@@ -103,6 +110,7 @@ properties:
       The description of this version
   - type: String
     name: 'metadataSchemaUri'
+    ignore_read: true
     immutable: true
     description: |
       Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it.
@@ -297,8 +305,11 @@ properties:
     description: |
       The timestamp of when the MetadataStore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
   - type: String
-    name: 'displayName'
+    name: 'modelName'
     default_from_api: true
+    at_least_one_of:
+      - modelName
+      - sourceModel
     description:
       The display name of the Model. The name can be up to 128 characters long
       and can consist of any UTF-8 characters.
@@ -309,9 +320,9 @@ properties:
     ignore_read: true
   - type: Array
     name: 'versionAliases'
-    default_from_api: true
     description:
       user provided version aliases so that a model version can be referenced via alias.
+    ignore_read: true
     item_type:
       type: String
   - type: NestedObject
@@ -326,105 +337,23 @@ properties:
           Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource.
           Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the resource is created.
         immutable: true
-  - type: NestedObject
-    name: 'metadata'
-    description: An additional information about the Index
-    properties:
-      - type: NestedObject
-        name: 'config'
-        immutable: true
-        description: The configuration of the Matching Engine Index.
-        properties:
-          - type: Integer
-            name: 'dimensions'
-            description: The number of dimensions of the input vectors.
-            required: true
-          - type: Integer
-            name: 'approximateNeighborsCount'
-            description: |-
-              The default number of neighbors to find via approximate search before exact reordering is
-              performed. Exact reordering is a procedure where results returned by an
-              approximate search algorithm are reordered via a more expensive distance computation.
-              Required if tree-AH algorithm is used.
-          - type: String
-            name: 'shardSize'
-            description: |-
-              Index data is split into equal parts to be processed. These are called "shards".
-              The shard size must be specified when creating an index. The value must be one of the followings:
-              * SHARD_SIZE_SMALL: Small (2GB)
-              * SHARD_SIZE_MEDIUM: Medium (20GB)
-              * SHARD_SIZE_LARGE: Large (50GB)
-            immutable: true
-            default_from_api: true
-          - type: String
-            name: 'distanceMeasureType'
-            description: |-
-              The distance measure used in nearest neighbor search. The value must be one of the followings:
-              * SQUARED_L2_DISTANCE: Euclidean (L_2) Distance
-              * L1_DISTANCE: Manhattan (L_1) Distance
-              * COSINE_DISTANCE: Cosine Distance. Defined as 1 - cosine similarity.
-              * DOT_PRODUCT_DISTANCE: Dot Product Distance. Defined as a negative of the dot product
-            default_value: 'DOT_PRODUCT_DISTANCE'
-          - type: String
-            name: 'featureNormType'
-            description: |-
-              Type of normalization to be carried out on each vector. The value must be one of the followings:
-              * UNIT_L2_NORM: Unit L2 normalization type
-              * NONE: No normalization type is specified.
-            default_value: 'NONE'
-            ignore_read: true
-          - type: NestedObject
-            name: 'algorithmConfig'
-            description:
-              The configuration with regard to the algorithms used for efficient
-              search.
-            properties:
-              - type: NestedObject
-                name: 'treeAhConfig'
-                exactly_one_of:
-                  - treeAhConfig
-                  - bruteForceConfig
-                description: |-
-                  Configuration options for using the tree-AH algorithm (Shallow tree + Asymmetric Hashing).
-                  Please refer to this paper for more details: https://arxiv.org/abs/1908.10396
-                properties:
-                  - type: Integer
-                    name: 'leafNodeEmbeddingCount'
-                    description:
-                      Number of embeddings on each leaf node. The default value
-                      is 1000 if not set.
-                    default_value: 1000
-                  - type: Integer
-                    name: 'leafNodesToSearchPercent'
-                    description: |-
-                      The default percentage of leaf nodes that any query may be searched. Must be in
-                      range 1-100, inclusive. The default value is 10 (means 10%) if not set.
-                    default_value: 10
-              - type: NestedObject
-                name: 'bruteForceConfig'
-                allow_empty_object: true
-                send_empty_value: true
-                properties: []
-                exactly_one_of:
-                  - treeAhConfig
-                  - bruteForceConfig
-                description: |-
-                  Configuration options for using brute force search, which simply implements the
-                  standard linear search in the database for each query.
+  - name: 'metadata'
+    type: KeyValuePairs
+    description: An additional information about the Model; the schema of the metadata can be found in metadataSchemaUri. Unset if the Model does not have any additional information.
   - type: String
     name: 'sourceModel'
-    ignore_read: true
-    immutable: true
+    default_from_api: true
     at_least_one_of:
+      - modelName
       - sourceModel
     description: |
       The resource name of the Model to copy. That Model must be in the same Project
   - type: String
     name: 'modelId'
     immutable: true
     ignore_read: true
+    default_from_api: true
     # modelId is never returned from the API as a field, but we set its value from API-returned data when it's not
     # provided by the user as an input
-    default_from_api: true
     description: |
       Copy sourceModel into a new Model with this ID. The ID will become the final component of the model resource name.

mmv1/templates/terraform/constants/vertex_ai_model.go.tmpl

@@ -1,4 +1,8 @@
 func vertexAiModelDiffSuppress(ctx context.Context, diff *schema.ResourceDiff, meta interface{}) error {
+	// we require diffSuppress on COPY method and not UPLOAD
+	if _, ok := diff.GetOkExists("model_name"); ok {
+		return nil
+	}
 	// If the resource has no id then it hasn't been created yet
 	// Check to see if any fields are set in the config at create time that shouldn't be there
 	if diff.Id() == "" {

mmv1/templates/terraform/custom_flatten/vertex_ai_name_from_model.go.tmpl

@@ -0,0 +1,7 @@
+func flatten{{$.GetPrefix}}{{$.TitlelizeProperty}}(v interface{}, d *schema.ResourceData, config *transport_tpg.Config) interface{} {
+  if d.Get("name").(string) == "" {
+    return v.(string)
+  }
+
+  return d.Get("name")
+}

mmv1/templates/terraform/decoders/vertex_ai_models.go.tmpl

@@ -2,5 +2,14 @@ if modelName, ok := res["model"].(string); ok && modelName != "" {
 	res["name"] = modelName
 }
 
+if _, ok := d.GetOk("source_model"); ok {
+	res["sourceModel"] = d.Get("source_model").(string)
+}
+
+if _, ok := d.GetOk("model_id"); ok {
+	res["modelId"] = d.Get("model_id").(string)
+}
+
+res["modelName"] = res["displayName"]
 
 return res, nil

mmv1/templates/terraform/encoders/vertex_ai_models.go.tmpl

@@ -1 +1,17 @@
-return obj, nil
+// Copy encoder
+if obj["sourceModel"] != nil {
+    delete(obj, "labels")
+    delete(obj, "metadata")
+    return obj, nil
+}
+
+// Upload encoder
+obj["displayName"] = obj["modelName"]
+delete(obj, "modelName")
+
+newObj := make(map[string]interface{})
+newObj["model"] = obj
+newObj["modelId"] = obj["modelId"]
+delete(obj, "modelId")
+
+return newObj, nil

mmv1/templates/terraform/examples/vertex_ai_model_source_basic_1.tf.tmpl

@@ -1,6 +1,31 @@
 resource "google_vertex_ai_model" "{{$.PrimaryResourceId}}" {
   project = "{{index $.TestEnvVars "project_name"}}"
-  source_model = "projects/{{index $.TestEnvVars "project_name"}}/locations/us-central1/models/tf-static-1"
+  source_model = google_vertex_ai_model.model_upload.name
 
   region       = "us-central1"
+}
+
+resource "google_vertex_ai_model" "model_upload" {
+  model_name = "tf_test_model_upload_source_1"
+  description  = "basic upload model for source testing"
+  region       = "us-central1"
+
+  container_spec {
+      image_uri             = "us-docker.pkg.dev/vertex-ai/prediction/tf2-cpu.2-12:latest"
+    command     = ["/usr/bin/python3"]
+    args        = ["model_server.py"]
+
+    env {
+      name  = "MODEL_NAME"
+      value = "example-model"
+    }
+
+    health_route = "/health"
+    predict_route = "/predict"
+    ports {
+      container_port = 8080
+    }
+  }
+  artifact_uri = "gs://cloud-samples-data/ai-platform/mnist_tfrecord/pretrained"
+
 }

mmv1/templates/terraform/examples/vertex_ai_model_source_basic_2.tf.tmpl

@@ -1,7 +1,32 @@
 resource "google_vertex_ai_model" "{{$.PrimaryResourceId}}" {
   model_id = "{{index $.Vars "model_id"}}"
   project = "{{index $.TestEnvVars "project_name"}}"
-  source_model = "projects/{{index $.TestEnvVars "project_name"}}/locations/us-central1/models/tf-static-1"
+  source_model = google_vertex_ai_model.model_upload.name
 
   region       = "us-central1"
+}
+
+resource "google_vertex_ai_model" "model_upload" {
+  model_name = "tf_test_model_upload_source_1"
+  description  = "basic upload model for source testing"
+  region       = "us-central1"
+
+  container_spec {
+      image_uri             = "us-docker.pkg.dev/vertex-ai/prediction/tf2-cpu.2-12:latest"
+    command     = ["/usr/bin/python3"]
+    args        = ["model_server.py"]
+
+    env {
+      name  = "MODEL_NAME"
+      value = "example-model"
+    }
+
+    health_route = "/health"
+    predict_route = "/predict"
+    ports {
+      container_port = 8080
+    }
+  }
+  artifact_uri = "gs://cloud-samples-data/ai-platform/mnist_tfrecord/pretrained"
+
 }

mmv1/templates/terraform/examples/vertex_ai_model_upload_basic.tf.tmpl

@@ -0,0 +1,11 @@
+resource "google_vertex_ai_model" "{{$.PrimaryResourceId}}" {
+  model_name = "{{index $.Vars "model_name"}}"
+  description  = "basic upload model"
+
+  version_aliases = ["v2beta1"]
+  model_id = "id_upload_test"
+
+  metadata_schema_uri = "gs://google-cloud-aiplatform/schema/model/metadata/custom_1.0.0.yaml"
+
+  region       = "us-central1"
+}

mmv1/templates/terraform/pre_create/vertex_ai_models.go.tmpl

@@ -1,4 +1,7 @@
 var postRequestType string
+if _, ok := d.GetOk("model_name"); ok {
+	postRequestType = ":upload"
+}
 
 if _, ok := d.GetOk("source_model"); ok {
 	postRequestType = ":copy"

mmv1/templates/terraform/update_encoder/vertex_ai_model.go.tmpl

@@ -0,0 +1,4 @@
+obj["displayName"] = obj["modelName"]
+delete(obj, "modelName")
+delete(obj, "sourceModel")
+return obj, nil