Release v1.38.1 (2021-03-19) (#3829)

Release v1.38.1 (2021-03-19)
===

### Service Client Updates
* `service/ec2`: Updates service API
  * X2gd instances are the next generation of memory-optimized instances powered by AWS-designed, Arm-based AWS Graviton2 processors.
* `service/sagemaker`: Updates service API and documentation
  * Adding authentication support for pulling images stored in private Docker registries to build containers for real-time inference.

CHANGELOG.md

@@ -1,3 +1,12 @@
+Release v1.38.1 (2021-03-19)
+===
+
+### Service Client Updates
+* `service/ec2`: Updates service API
+  * X2gd instances are the next generation of memory-optimized instances powered by AWS-designed, Arm-based AWS Graviton2 processors.
+* `service/sagemaker`: Updates service API and documentation
+  * Adding authentication support for pulling images stored in private Docker registries to build containers for real-time inference.
+
 Release v1.38.0 (2021-03-18)
 ===
 

aws/version.go

@@ -5,4 +5,4 @@ package aws
 const SDKName = "aws-sdk-go"
 
 // SDKVersion is the version of this SDK
-const SDKVersion = "1.38.0"
+const SDKVersion = "1.38.1"

models/apis/ec2/2016-11-15/api-2.json

@@ -20176,7 +20176,16 @@
         "m6gd.8xlarge",
         "m6gd.12xlarge",
         "m6gd.16xlarge",
-        "mac1.metal"
+        "mac1.metal",
+        "x2gd.medium",
+        "x2gd.large",
+        "x2gd.xlarge",
+        "x2gd.2xlarge",
+        "x2gd.4xlarge",
+        "x2gd.8xlarge",
+        "x2gd.12xlarge",
+        "x2gd.16xlarge",
+        "x2gd.metal"
       ]
     },
     "InstanceTypeHypervisor":{

models/apis/sagemaker/2017-07-24/api-2.json

@@ -8430,7 +8430,8 @@
       "type":"structure",
       "required":["RepositoryAccessMode"],
       "members":{
-        "RepositoryAccessMode":{"shape":"RepositoryAccessMode"}
+        "RepositoryAccessMode":{"shape":"RepositoryAccessMode"},
+        "RepositoryAuthConfig":{"shape":"RepositoryAuthConfig"}
       }
     },
     "ImageContainerImage":{
@@ -12488,6 +12489,19 @@
         "Vpc"
       ]
     },
+    "RepositoryAuthConfig":{
+      "type":"structure",
+      "required":["RepositoryCredentialsProviderArn"],
+      "members":{
+        "RepositoryCredentialsProviderArn":{"shape":"RepositoryCredentialsProviderArn"}
+      }
+    },
+    "RepositoryCredentialsProviderArn":{
+      "type":"string",
+      "max":2048,
+      "min":1,
+      "pattern":".*"
+    },
     "ResolvedAttributes":{
       "type":"structure",
       "members":{

models/apis/sagemaker/2017-07-24/docs-2.json

@@ -1394,7 +1394,7 @@
     "CompilerOptions": {
       "base": null,
       "refs": {
-        "OutputConfig$CompilerOptions": "<p>Specifies additional parameters for compiler options in JSON format. The compiler options are <code>TargetPlatform</code> specific. It is required for NVIDIA accelerators and highly recommended for CPU compilations. For any other cases, it is optional to specify <code>CompilerOptions.</code> </p> <ul> <li> <p> <code>CPU</code>: Compilation for CPU supports the following compiler options.</p> <ul> <li> <p> <code>mcpu</code>: CPU micro-architecture. For example, <code>{'mcpu': 'skylake-avx512'}</code> </p> </li> <li> <p> <code>mattr</code>: CPU flags. For example, <code>{'mattr': ['+neon', '+vfpv4']}</code> </p> </li> </ul> </li> <li> <p> <code>ARM</code>: Details of ARM CPU compilations.</p> <ul> <li> <p> <code>NEON</code>: NEON is an implementation of the Advanced SIMD extension used in ARMv7 processors.</p> <p>For example, add <code>{'mattr': ['+neon']}</code> to the compiler options if compiling for ARM 32-bit platform with the NEON support.</p> </li> </ul> </li> <li> <p> <code>NVIDIA</code>: Compilation for NVIDIA GPU supports the following compiler options.</p> <ul> <li> <p> <code>gpu_code</code>: Specifies the targeted architecture.</p> </li> <li> <p> <code>trt-ver</code>: Specifies the TensorRT versions in x.y.z. format.</p> </li> <li> <p> <code>cuda-ver</code>: Specifies the CUDA version in x.y format.</p> </li> </ul> <p>For example, <code>{'gpu-code': 'sm_72', 'trt-ver': '6.0.1', 'cuda-ver': '10.1'}</code> </p> </li> <li> <p> <code>ANDROID</code>: Compilation for the Android OS supports the following compiler options:</p> <ul> <li> <p> <code>ANDROID_PLATFORM</code>: Specifies the Android API levels. Available levels range from 21 to 29. For example, <code>{'ANDROID_PLATFORM': 28}</code>.</p> </li> <li> <p> <code>mattr</code>: Add <code>{'mattr': ['+neon']}</code> to compiler options if compiling for ARM 32-bit platform with NEON support.</p> </li> </ul> </li> <li> <p> <code>INFERENTIA</code>: Compilation for target ml_inf1 uses compiler options passed in as a JSON string. For example, <code>\"CompilerOptions\": \"\\\"--verbose 1 --num-neuroncores 2 -O2\\\"\"</code>. </p> <p>For information about supported compiler options, see <a href=\"https://github.com/aws/aws-neuron-sdk/blob/master/docs/neuron-cc/command-line-reference.md\"> Neuron Compiler CLI</a>. </p> </li> <li> <p> <code>CoreML</code>: Compilation for the CoreML <a>OutputConfig$TargetDevice</a> supports the following compiler options:</p> <ul> <li> <p> <code>class_labels</code>: Specifies the classification labels file name inside input tar.gz file. For example, <code>{\"class_labels\": \"imagenet_labels_1000.txt\"}</code>. Labels inside the txt file should be separated by newlines.</p> </li> </ul> </li> <li> <p> <code>EIA</code>: Compilation for the Elastic Inference Accelerator supports the following compiler options:</p> <ul> <li> <p> <code>precision_mode</code>: Specifies the precision of compiled artifacts. Supported values are <code>\"FP16\"</code> and <code>\"FP32\"</code>. Default is <code>\"FP32\"</code>.</p> </li> <li> <p> <code>signature_def_key</code>: Specifies the signature to use for models in SavedModel format. Defaults is TensorFlow's default signature def key.</p> </li> <li> <p> <code>output_names</code>: Specifies a list of output tensor names for models in FrozenGraph format. Set at most one API field, either: <code>signature_def_key</code> or <code>output_names</code>.</p> </li> </ul> <p>For example: <code>{\"precision_mode\": \"FP32\", \"output_names\": [\"output:0\"]}</code> </p> </li> </ul>"
+        "OutputConfig$CompilerOptions": "<p>Specifies additional parameters for compiler options in JSON format. The compiler options are <code>TargetPlatform</code> specific. It is required for NVIDIA accelerators and highly recommended for CPU compilations. For any other cases, it is optional to specify <code>CompilerOptions.</code> </p> <ul> <li> <p> <code>DTYPE</code>: Specifies the data type for the input. When compiling for <code>ml_*</code> (except for <code>ml_inf</code>) instances using PyTorch framework, provide the data type (dtype) of the model's input. <code>\"float32\"</code> is used if <code>\"DTYPE\"</code> is not specified. Options for data type are:</p> <ul> <li> <p>float32: Use either <code>\"float\"</code> or <code>\"float32\"</code>.</p> </li> <li> <p>int64: Use either <code>\"int64\"</code> or <code>\"long\"</code>.</p> </li> </ul> <p> For example, <code>{\"dtype\" : \"float32\"}</code>.</p> </li> <li> <p> <code>CPU</code>: Compilation for CPU supports the following compiler options.</p> <ul> <li> <p> <code>mcpu</code>: CPU micro-architecture. For example, <code>{'mcpu': 'skylake-avx512'}</code> </p> </li> <li> <p> <code>mattr</code>: CPU flags. For example, <code>{'mattr': ['+neon', '+vfpv4']}</code> </p> </li> </ul> </li> <li> <p> <code>ARM</code>: Details of ARM CPU compilations.</p> <ul> <li> <p> <code>NEON</code>: NEON is an implementation of the Advanced SIMD extension used in ARMv7 processors.</p> <p>For example, add <code>{'mattr': ['+neon']}</code> to the compiler options if compiling for ARM 32-bit platform with the NEON support.</p> </li> </ul> </li> <li> <p> <code>NVIDIA</code>: Compilation for NVIDIA GPU supports the following compiler options.</p> <ul> <li> <p> <code>gpu_code</code>: Specifies the targeted architecture.</p> </li> <li> <p> <code>trt-ver</code>: Specifies the TensorRT versions in x.y.z. format.</p> </li> <li> <p> <code>cuda-ver</code>: Specifies the CUDA version in x.y format.</p> </li> </ul> <p>For example, <code>{'gpu-code': 'sm_72', 'trt-ver': '6.0.1', 'cuda-ver': '10.1'}</code> </p> </li> <li> <p> <code>ANDROID</code>: Compilation for the Android OS supports the following compiler options:</p> <ul> <li> <p> <code>ANDROID_PLATFORM</code>: Specifies the Android API levels. Available levels range from 21 to 29. For example, <code>{'ANDROID_PLATFORM': 28}</code>.</p> </li> <li> <p> <code>mattr</code>: Add <code>{'mattr': ['+neon']}</code> to compiler options if compiling for ARM 32-bit platform with NEON support.</p> </li> </ul> </li> <li> <p> <code>INFERENTIA</code>: Compilation for target ml_inf1 uses compiler options passed in as a JSON string. For example, <code>\"CompilerOptions\": \"\\\"--verbose 1 --num-neuroncores 2 -O2\\\"\"</code>. </p> <p>For information about supported compiler options, see <a href=\"https://github.com/aws/aws-neuron-sdk/blob/master/docs/neuron-cc/command-line-reference.md\"> Neuron Compiler CLI</a>. </p> </li> <li> <p> <code>CoreML</code>: Compilation for the CoreML <a>OutputConfig$TargetDevice</a> supports the following compiler options:</p> <ul> <li> <p> <code>class_labels</code>: Specifies the classification labels file name inside input tar.gz file. For example, <code>{\"class_labels\": \"imagenet_labels_1000.txt\"}</code>. Labels inside the txt file should be separated by newlines.</p> </li> </ul> </li> <li> <p> <code>EIA</code>: Compilation for the Elastic Inference Accelerator supports the following compiler options:</p> <ul> <li> <p> <code>precision_mode</code>: Specifies the precision of compiled artifacts. Supported values are <code>\"FP16\"</code> and <code>\"FP32\"</code>. Default is <code>\"FP32\"</code>.</p> </li> <li> <p> <code>signature_def_key</code>: Specifies the signature to use for models in SavedModel format. Defaults is TensorFlow's default signature def key.</p> </li> <li> <p> <code>output_names</code>: Specifies a list of output tensor names for models in FrozenGraph format. Set at most one API field, either: <code>signature_def_key</code> or <code>output_names</code>.</p> </li> </ul> <p>For example: <code>{\"precision_mode\": \"FP32\", \"output_names\": [\"output:0\"]}</code> </p> </li> </ul>"
       }
     },
     "CompressionType": {
@@ -7946,6 +7946,18 @@
         "ImageConfig$RepositoryAccessMode": "<p>Set this to one of the following values:</p> <ul> <li> <p> <code>Platform</code> - The model image is hosted in Amazon ECR.</p> </li> <li> <p> <code>Vpc</code> - The model image is hosted in a private Docker registry in your VPC.</p> </li> </ul>"
       }
     },
+    "RepositoryAuthConfig": {
+      "base": "<p>Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified <code>Vpc</code> as the value for the <code>RepositoryAccessMode</code> field of the <code>ImageConfig</code> object that you passed to a call to <a>CreateModel</a> and the private Docker registry where the model image is hosted requires authentication.</p>",
+      "refs": {
+        "ImageConfig$RepositoryAuthConfig": "<p>(Optional) Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified <code>Vpc</code> as the value for the <code>RepositoryAccessMode</code> field, and the private Docker registry where the model image is hosted requires authentication.</p>"
+      }
+    },
+    "RepositoryCredentialsProviderArn": {
+      "base": null,
+      "refs": {
+        "RepositoryAuthConfig$RepositoryCredentialsProviderArn": "<p>The Amazon Resource Name (ARN) of an AWS Lambda function that provides credentials to authenticate to the private Docker registry where your model image is hosted. For information about how to create an AWS Lambda function, see <a href=\"https://docs.aws.amazon.com/lambda/latest/dg/getting-started-create-function.html\">Create a Lambda function with the console</a> in the <i>AWS Lambda Developer Guide</i>.</p>"
+      }
+    },
     "ResolvedAttributes": {
       "base": "<p>The resolved attributes.</p>",
       "refs": {