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update samples from Release-6 as a part of 1.3.0 SDK stable release

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vizhur
2020-04-13 16:22:23 +00:00
parent c520bd1d41
commit 057e22b253
83 changed files with 3024 additions and 1249 deletions
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75
how-to-use-azureml/deployment/deploy-to-cloud/model-register-and-deploy.ipynb
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@@ -388,6 +388,14 @@
"Below is an example of how you can construct an input dataset to profile a service which expects its incoming requests to contain serialized json. In this case we created a dataset based one hundred instances of the same request data. In real world scenarios however, we suggest that you use larger datasets with various inputs, especially if your model resource usage/behavior is input dependent."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You may want to register datasets using the register() method to your workspace so they can be shared with others, reused and referred to by name in your script.\n",
"You can try get the dataset first to see if it's already registered."
]
},
{
"cell_type": "code",
"execution_count": null,
@@ -398,36 +406,45 @@
"from azureml.core.dataset import Dataset\n",
"from azureml.data import dataset_type_definitions\n",
"\n",
"dataset_name='diabetes_sample_request_data'\n",
"\n",
"# create a string that can be utf-8 encoded and\n",
"# put in the body of the request\n",
"serialized_input_json = json.dumps({\n",
" 'data': [\n",
" [ 0.03807591, 0.05068012, 0.06169621, 0.02187235, -0.0442235,\n",
" -0.03482076, -0.04340085, -0.00259226, 0.01990842, -0.01764613]\n",
" ]\n",
"})\n",
"dataset_content = []\n",
"for i in range(100):\n",
" dataset_content.append(serialized_input_json)\n",
"dataset_content = '\\n'.join(dataset_content)\n",
"file_name = 'sample_request_data.txt'\n",
"f = open(file_name, 'w')\n",
"f.write(dataset_content)\n",
"f.close()\n",
"dataset_registered = False\n",
"try:\n",
" sample_request_data = Dataset.get_by_name(workspace = ws, name = dataset_name)\n",
" dataset_registered = True\n",
"except:\n",
" print(\"The dataset {} is not registered in workspace yet.\".format(dataset_name))\n",
"\n",
"# upload the txt file created above to the Datastore and create a dataset from it\n",
"data_store = Datastore.get_default(ws)\n",
"data_store.upload_files(['./' + file_name], target_path='sample_request_data')\n",
"datastore_path = [(data_store, 'sample_request_data' +'/' + file_name)]\n",
"sample_request_data = Dataset.Tabular.from_delimited_files(\n",
" datastore_path,\n",
" separator='\\n',\n",
" infer_column_types=True,\n",
" header=dataset_type_definitions.PromoteHeadersBehavior.NO_HEADERS)\n",
"sample_request_data = sample_request_data.register(workspace=ws,\n",
" name='diabetes_sample_request_data',\n",
" create_new_version=True)"
"if not dataset_registered:\n",
" # create a string that can be utf-8 encoded and\n",
" # put in the body of the request\n",
" serialized_input_json = json.dumps({\n",
" 'data': [\n",
" [ 0.03807591, 0.05068012, 0.06169621, 0.02187235, -0.0442235,\n",
" -0.03482076, -0.04340085, -0.00259226, 0.01990842, -0.01764613]\n",
" ]\n",
" })\n",
" dataset_content = []\n",
" for i in range(100):\n",
" dataset_content.append(serialized_input_json)\n",
" dataset_content = '\\n'.join(dataset_content)\n",
" file_name = \"{}.txt\".format(dataset_name)\n",
" f = open(file_name, 'w')\n",
" f.write(dataset_content)\n",
" f.close()\n",
"\n",
" # upload the txt file created above to the Datastore and create a dataset from it\n",
" data_store = Datastore.get_default(ws)\n",
" data_store.upload_files(['./' + file_name], target_path='sample_request_data')\n",
" datastore_path = [(data_store, 'sample_request_data' +'/' + file_name)]\n",
" sample_request_data = Dataset.Tabular.from_delimited_files(\n",
" datastore_path,\n",
" separator='\\n',\n",
" infer_column_types=True,\n",
" header=dataset_type_definitions.PromoteHeadersBehavior.NO_HEADERS)\n",
" sample_request_data = sample_request_data.register(workspace=ws,\n",
" name=dataset_name,\n",
" create_new_version=True)"
]
},
{
@@ -512,7 +529,7 @@
"metadata": {
"authors": [
{
"name": "aashishb"
"name": "vaidyas"
}
],
"category": "deployment",