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Notebook update #312

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merged 5 commits into from
Jul 10, 2018
Merged

Notebook update #312

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7a6b883
update notebooks with python sdk get_image_url method (#1)
Jul 4, 2018
cdf63b0
update notebooks with python sdk get_image_url method (#2)
Jul 4, 2018
a4e39b0
update notebooks with python sdk get_image_url method (#3)
Jul 4, 2018
1e76baf
sync rcf notebook with upstream
Jul 10, 2018
eb59174
Merge remote-tracking branch 'upstream/master' into notebook_update
Jul 10, 2018
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114 changes: 81 additions & 33 deletions advanced_functionality/data_distribution_types/data_distribution_types.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -43,6 +43,7 @@
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true,
"isConfigCell": true
},
"outputs": [],
Expand All @@ -69,7 +70,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import boto3\n",
Expand Down Expand Up @@ -102,7 +105,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def get_gdelt(filename):\n",
Expand All @@ -117,7 +122,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"data = get_gdelt('1979.csv')\n",
Expand All @@ -142,7 +149,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"data = data[['EventCode', 'NumArticles', 'AvgTone', 'Actor1Geo_Lat', 'Actor1Geo_Long', 'Actor2Geo_Lat', 'Actor2Geo_Long']]\n",
Expand Down Expand Up @@ -172,7 +181,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"events = pd.crosstab(index=data['EventCode'], columns='count').sort_values(by='count', ascending=False).index[:20]"
Expand All @@ -190,7 +201,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def write_to_s3(bucket, prefix, channel, file_prefix, X, y):\n",
Expand Down Expand Up @@ -219,7 +232,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"for year in range(1979, 1984):\n",
Expand All @@ -244,22 +259,21 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"containers = {'us-west-2': '174872318107.dkr.ecr.us-west-2.amazonaws.com/linear-learner:latest',\n",
" 'us-east-1': '382416733822.dkr.ecr.us-east-1.amazonaws.com/linear-learner:latest',\n",
" 'us-east-2': '404615174143.dkr.ecr.us-east-2.amazonaws.com/linear-learner:latest',\n",
" 'eu-west-1': '438346466558.dkr.ecr.eu-west-1.amazonaws.com/linear-learner:latest',\n",
" 'ap-northeast-1': '351501993468.dkr.ecr.ap-northeast-1.amazonaws.com/linear-learner:latest',\n",
" 'ap-northeast-2': '835164637446.dkr.ecr.ap-northeast-2.amazonaws.com/linear-learner:latest'}\n",
"container = containers[boto3.Session().region_name]"
"from sagemaker.amazon.amazon_estimator import get_image_uri\n",
"container = get_image_uri(boto3.Session().region_name, 'linear-learner')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"common_training_params = {\n",
Expand Down Expand Up @@ -326,7 +340,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"sharded_job = 'DEMO-linear-sharded-' + time.strftime(\"%Y-%m-%d-%H-%M-%S\", time.gmtime())\n",
Expand All @@ -341,7 +357,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"replicated_job = 'DEMO-linear-replicated-' + time.strftime(\"%Y-%m-%d-%H-%M-%S\", time.gmtime())\n",
Expand All @@ -363,7 +381,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"%%time\n",
Expand Down Expand Up @@ -395,7 +415,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"print('Sharded:', sm.describe_training_job(TrainingJobName=sharded_job)['TrainingJobStatus'])\n",
Expand All @@ -416,7 +438,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def get_train_timing(job):\n",
Expand All @@ -435,7 +459,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"print('Sharded:', get_train_timing(sharded_job), 'minutes')\n",
Expand Down Expand Up @@ -467,7 +493,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"sharded_model_response = sm.create_model(\n",
Expand All @@ -483,7 +511,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"replicated_model_response = sm.create_model(\n",
Expand Down Expand Up @@ -511,7 +541,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"sharded_endpoint_config = 'DEMO-sharded-endpoint-config-' + time.strftime(\"%Y-%m-%d-%H-%M-%S\", time.gmtime())\n",
Expand All @@ -530,7 +562,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"replicated_endpoint_config = 'DEMO-replicated-endpoint-config-' + time.strftime(\"%Y-%m-%d-%H-%M-%S\", time.gmtime())\n",
Expand All @@ -556,7 +590,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"%%time\n",
Expand Down Expand Up @@ -600,7 +636,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"print('Sharded:', sm.describe_endpoint(EndpointName=sharded_endpoint)['EndpointStatus'])\n",
Expand All @@ -619,7 +657,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"test_data = transform_gdelt(get_gdelt('1984.csv'), events).as_matrix()\n",
Expand All @@ -637,7 +677,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def np2csv(arr):\n",
Expand All @@ -656,7 +698,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def predict_batches(data, endpoint):\n",
Expand Down Expand Up @@ -684,7 +728,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"sharded_predictions = predict_batches(test_X, sharded_endpoint)\n",
Expand Down Expand Up @@ -728,7 +774,9 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"sm.delete_endpoint(EndpointName=sharded_endpoint)\n",
Expand Down
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