Merge pull request aws#125 from awslabs/arpin_sagemaker_runtime_fix

Fixed: sagemaker-runtime to runtime.sagemaker.  Awaiting confirmation

Author: owen-t

advanced_functionality/data_distribution_types/data_distribution_types.ipynb

@@ -661,7 +661,7 @@
     "    rows = 5. * 1024. * 1024. / sys.getsizeof(np2csv(data[0, :]))\n",
     "    split_array = np.array_split(data, int(data.shape[0] / float(rows) + 1))\n",
     "    predictions = []\n",
-    "    runtime = boto3.Session().client('sagemaker-runtime')\n",
+    "    runtime = boto3.Session().client('runtime.sagemaker')\n",
     "    for array in split_array:\n",
     "        payload = np2csv(array)\n",
     "        response = runtime.invoke_endpoint(EndpointName=endpoint,\n",

advanced_functionality/handling_kms_encrypted_data/handling_kms_encrypted_data.ipynb

@@ -452,7 +452,7 @@
    },
    "outputs": [],
    "source": [
-    "runtime_client = boto3.client('sagemaker-runtime')"
+    "runtime_client = boto3.client('runtime.sagemaker')"
    ]
   },
   {

advanced_functionality/kmeans_bring_your_own_model/kmeans_bring_your_own_model.ipynb

@@ -307,7 +307,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "runtime = boto3.Session().client('sagemaker-runtime')\n",
+    "runtime = boto3.Session().client('runtime.sagemaker')\n",
     "\n",
     "payload = np2csv(train_set[0][0:100])\n",
     "response = runtime.invoke_endpoint(EndpointName=kmeans_endpoint,\n",

advanced_functionality/r_bring_your_own/r_bring_your_own.ipynb

@@ -597,7 +597,7 @@
    "source": [
     "iris = pd.read_csv('iris.csv')\n",
     "\n",
-    "runtime = boto3.Session().client('sagemaker-runtime')\n",
+    "runtime = boto3.Session().client('runtime.sagemaker')\n",
     "\n",
     "payload = iris.drop(['Sepal.Length'], axis=1).to_csv(index=False)\n",
     "response = runtime.invoke_endpoint(EndpointName=r_endpoint,\n",

advanced_functionality/xgboost_bring_your_own_model/xgboost_bring_your_own_model.ipynb

@@ -387,7 +387,7 @@
    },
    "outputs": [],
    "source": [
-    "runtime_client = boto3.client('sagemaker-runtime')"
+    "runtime_client = boto3.client('runtime.sagemaker')"
    ]
   },
   {

introduction_to_amazon_algorithms/imageclassification_caltech/Image-classification-fulltraining.ipynb

@@ -497,7 +497,7 @@
    "outputs": [],
    "source": [
     "import boto3\n",
-    "runtime = boto3.Session().client(service_name='sagemaker-runtime') "
+    "runtime = boto3.Session().client(service_name='runtime.sagemaker') "
    ]
   },
   {

introduction_to_amazon_algorithms/imageclassification_caltech/Image-classification-transfer-learning.ipynb

@@ -513,7 +513,7 @@
    "outputs": [],
    "source": [
     "import boto3\n",
-    "runtime = boto3.Session().client(service_name='sagemaker-runtime') "
+    "runtime = boto3.Session().client(service_name='runtime.sagemaker') "
    ]
   },
   {

introduction_to_amazon_algorithms/seq2seq_translation_en-de/SageMaker-Seq2Seq-Translation-English-German.ipynb

@@ -545,7 +545,7 @@
    },
    "outputs": [],
    "source": [
-    "runtime = boto3.client(service_name='sagemaker-runtime') "
+    "runtime = boto3.client(service_name='runtime.sagemaker') "
    ]
   },
   {

introduction_to_amazon_algorithms/xgboost_abalone/xgboost_abalone.ipynb

@@ -417,7 +417,7 @@
    },
    "outputs": [],
    "source": [
-    "runtime_client = boto3.client('sagemaker-runtime')"
+    "runtime_client = boto3.client('runtime.sagemaker')"
    ]
   },
   {

introduction_to_amazon_algorithms/xgboost_mnist/xgboost_mnist.ipynb

@@ -529,7 +529,7 @@
    },
    "outputs": [],
    "source": [
-    "runtime_client = boto3.client('sagemaker-runtime')"
+    "runtime_client = boto3.client('runtime.sagemaker')"
    ]
   },
   {

introduction_to_applying_machine_learning/breast_cancer_prediction/Breast Cancer Prediction.ipynb

@@ -577,7 +577,7 @@
    },
    "outputs": [],
    "source": [
-    "runtime= boto3.client('sagemaker-runtime')\n",
+    "runtime= boto3.client('runtime.sagemaker')\n",
     "\n",
     "payload = np2csv(test_X)\n",
     "response = runtime.invoke_endpoint(EndpointName=linear_endpoint,\n",

introduction_to_applying_machine_learning/ensemble_modeling/EnsembleLearnerCensusIncome.ipynb

@@ -566,7 +566,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "runtime= boto3.client('sagemaker-runtime')\n"
+    "runtime= boto3.client('runtime.sagemaker')\n"
    ]
   },
   {

sagemaker-python-sdk/1P_kmeans_lowlevel/kmeans_mnist_lowlevel.ipynb

@@ -384,7 +384,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "runtime = boto3.Session().client('sagemaker-runtime')"
+    "runtime = boto3.Session().client('runtime.sagemaker')"
    ]
   },
   {