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AWS SDK for Go v2 automation user
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Update API model
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-45
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‎codegen/sdk-codegen/aws-models/iot-events.json

+23-23
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@@ -222,7 +222,7 @@
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"traits": {
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"smithy.api#length": {
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"min": 0,
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"max": 128
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"max": 1024
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}
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}
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},
@@ -1829,7 +1829,7 @@
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"traits": {
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"smithy.api#length": {
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"min": 0,
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"max": 128
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"max": 1024
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}
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}
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},
@@ -2462,7 +2462,7 @@
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"traits": {
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"smithy.api#length": {
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"min": 0,
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"max": 128
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"max": 1024
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}
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}
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},
@@ -2756,7 +2756,6 @@
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]
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}
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],
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"type": "tree",
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"rules": [
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{
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"conditions": [
@@ -2799,7 +2798,8 @@
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},
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"type": "endpoint"
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}
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]
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],
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"type": "tree"
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},
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{
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"conditions": [
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]
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}
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],
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"type": "tree",
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"rules": [
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{
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"conditions": [
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"assign": "PartitionResult"
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}
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],
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"type": "tree",
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"rules": [
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{
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"conditions": [
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]
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}
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],
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"type": "tree",
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"rules": [
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{
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"conditions": [
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]
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}
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],
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"type": "tree",
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"rules": [
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{
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"conditions": [],
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},
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"type": "endpoint"
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}
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]
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],
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"type": "tree"
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},
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{
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"conditions": [],
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"error": "FIPS and DualStack are enabled, but this partition does not support one or both",
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"type": "error"
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}
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]
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],
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"type": "tree"
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},
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{
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"conditions": [
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]
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}
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],
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"type": "tree",
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"rules": [
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{
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"conditions": [
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{
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"fn": "booleanEquals",
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"argv": [
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true,
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{
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"fn": "getAttr",
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"argv": [
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},
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"supportsFIPS"
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]
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}
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},
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true
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]
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}
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],
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"type": "tree",
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"rules": [
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{
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"conditions": [],
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},
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"type": "endpoint"
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}
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]
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],
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"type": "tree"
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},
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{
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"conditions": [],
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"error": "FIPS is enabled but this partition does not support FIPS",
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"type": "error"
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}
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]
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],
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"type": "tree"
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},
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{
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"conditions": [
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]
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}
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],
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"type": "tree",
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"rules": [
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{
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"conditions": [
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]
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}
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],
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"type": "tree",
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"rules": [
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{
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"conditions": [],
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},
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"type": "endpoint"
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}
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]
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],
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"type": "tree"
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},
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{
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"conditions": [],
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"error": "DualStack is enabled but this partition does not support DualStack",
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"type": "error"
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}
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]
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],
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"type": "tree"
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},
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{
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"conditions": [],
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},
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"type": "endpoint"
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}
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]
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],
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"type": "tree"
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}
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]
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],
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"type": "tree"
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},
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{
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"conditions": [],

‎codegen/sdk-codegen/aws-models/lookoutequipment.json

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@@ -1256,6 +1256,12 @@
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"traits": {
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"smithy.api#documentation": "<p>Indicates the status of the <code>CreateInferenceScheduler</code> operation. </p>"
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}
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},
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"ModelQuality": {
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"target": "com.amazonaws.lookoutequipment#ModelQuality",
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"traits": {
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"smithy.api#documentation": "<p>Provides a quality assessment for a model that uses labels. \n If Lookout for Equipment determines that the\n model quality is poor based on training metrics, the value is\n <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is\n <code>QUALITY_THRESHOLD_MET</code>. </p>\n <p>If the model is unlabeled, the model quality can't\n be assessed and the value of <code>ModelQuality</code> is\n <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model quality\n assessment by adding labels to the input dataset and retraining the model.</p>\n <p>For information about using labels with your models, see <a href=\"https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-labeling.html\">Understanding labeling</a>.</p>\n <p>For information about improving the quality of a model, see <a href=\"https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html\">Best practices with\n Amazon Lookout for Equipment</a>.</p>"
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}
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}
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},
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"traits": {
@@ -3265,6 +3271,12 @@
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"traits": {
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"smithy.api#documentation": "<p>Configuration information for the model's pointwise model diagnostics.</p>"
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}
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},
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"ModelQuality": {
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"target": "com.amazonaws.lookoutequipment#ModelQuality",
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"traits": {
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"smithy.api#documentation": "<p>Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the\n model quality is poor based on training metrics, the value is\n <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is\n <code>QUALITY_THRESHOLD_MET</code>.</p>\n <p>If the model is unlabeled, the model quality can't\n be assessed and the value of <code>ModelQuality</code> is\n <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model quality\n assessment by adding labels to the input dataset and retraining the model.</p>\n <p>For information about using labels with your models, see <a href=\"https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-labeling.html\">Understanding labeling</a>.</p>\n <p>For information about improving the quality of a model, see <a href=\"https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html\">Best practices with\n Amazon Lookout for Equipment</a>.</p>"
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}
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}
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},
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"traits": {
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"traits": {
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"smithy.api#documentation": "<p>The Amazon S3 output prefix for where Lookout for Equipment saves the pointwise model diagnostics for the model version.</p>"
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}
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},
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"ModelQuality": {
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"target": "com.amazonaws.lookoutequipment#ModelQuality",
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"traits": {
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"smithy.api#documentation": "<p>Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the\n model quality is poor based on training metrics, the value is\n <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is\n <code>QUALITY_THRESHOLD_MET</code>.</p>\n <p>If the model is unlabeled, the model quality can't\n be assessed and the value of <code>ModelQuality</code> is\n <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model quality\n assessment by adding labels to the input dataset and retraining the model.</p>\n <p>For information about using labels with your models, see <a href=\"https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-labeling.html\">Understanding labeling</a>.</p>\n <p>For information about improving the quality of a model, see <a href=\"https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html\">Best practices with\n Amazon Lookout for Equipment</a>.</p>"
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}
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}
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},
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"traits": {
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}
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}
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},
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"com.amazonaws.lookoutequipment#ModelQuality": {
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"type": "enum",
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"members": {
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"QUALITY_THRESHOLD_MET": {
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"target": "smithy.api#Unit",
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"traits": {
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"smithy.api#enumValue": "QUALITY_THRESHOLD_MET"
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}
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},
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"CANNOT_DETERMINE_QUALITY": {
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"target": "smithy.api#Unit",
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"traits": {
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"smithy.api#enumValue": "CANNOT_DETERMINE_QUALITY"
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}
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},
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"POOR_QUALITY_DETECTED": {
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"target": "smithy.api#Unit",
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"traits": {
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"smithy.api#enumValue": "POOR_QUALITY_DETECTED"
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}
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}
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}
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},
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"com.amazonaws.lookoutequipment#ModelStatus": {
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"type": "enum",
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"members": {
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},
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"ModelDiagnosticsOutputConfiguration": {
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"target": "com.amazonaws.lookoutequipment#ModelDiagnosticsOutputConfiguration"
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},
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"ModelQuality": {
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"target": "com.amazonaws.lookoutequipment#ModelQuality",
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"traits": {
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"smithy.api#documentation": "<p>Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the\n model quality is poor based on training metrics, the value is\n <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is\n <code>QUALITY_THRESHOLD_MET</code>.</p>\n <p>If the model is unlabeled, the model quality can't\n be assessed and the value of <code>ModelQuality</code> is\n <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model quality\n assessment by adding labels to the input dataset and retraining the model.</p>\n <p>For information about using labels with your models, see <a href=\"https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/understanding-labeling.html\">Understanding labeling</a>.</p>\n <p>For information about improving the quality of a model, see <a href=\"https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html\">Best practices with\n Amazon Lookout for Equipment</a>.</p>"
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}
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}
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},
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"traits": {
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"traits": {
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"smithy.api#documentation": "<p>Indicates how this model version was generated.</p>"
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}
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},
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"ModelQuality": {
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"target": "com.amazonaws.lookoutequipment#ModelQuality",
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"traits": {
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"smithy.api#documentation": "<p>Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the\n model quality is poor based on training metrics, the value is\n <code>POOR_QUALITY_DETECTED</code>. Otherwise, the value is\n <code>QUALITY_THRESHOLD_MET</code>. </p>\n <p>If the model is unlabeled, the model quality can't\n be assessed and the value of <code>ModelQuality</code> is\n <code>CANNOT_DETERMINE_QUALITY</code>. In this situation, you can get a model quality\n assessment by adding labels to the input dataset and retraining the model.</p>\n <p>For information about improving the quality of a model, see <a href=\"https://docs.aws.amazon.com/lookout-for-equipment/latest/ug/best-practices.html\">Best practices with\n Amazon Lookout for Equipment</a>.</p>"
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}
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}
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},
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"traits": {

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