We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
storage-initialiser fails to copy model from S3
Upon using a Secret and Service account that look like this:

```
apiVersion: v1
metadata:
  name: kfserving-aws-secret
  namespace: {namespace}
  annotations:
    serving.kubeflow.org/s3-endpoint: s3.eu-east-1.amazonaws.com
    serving.kubeflow.org/s3-usehttps: "1"
    serving.kubeflow.org/s3-verifyssl: "1"
    serving.kubeflow.org/s3-region: eu-east-1
data:
  AWS_ACCESS_KEY_ID: {access_key_base64}
  AWS_SECRET_ACCESS_KEY: {secret_key_base64}
kind: Secret
type: Opaque
---
apiVersion: v1
kind: ServiceAccount
metadata:
  name: kfserving-sa
  namespace: {namespace}
secrets:
  - name: kfserving-aws-secret  
```
...and an InferenceService like this:

```
apiVersion: "serving.kubeflow.org/v1alpha2"
kind: "InferenceService"
metadata:
  name: {model_name}
  namespace: {namespace}
spec:
  default:
    predictor:
      serviceAccountName: kfserving-sa
      tensorflow:
        storageUri: {model_base_path}    
```

...the model fails to serve, with the `storage-initialiser` pod throwing the following error:

```
[I 200226 14:09:42 initializer-entrypoint:13] Initializing, args: src_uri [s3://at-kubeflow-training/tf-job/ksc-ebce76a1] dest_path[ [/mnt/models]
[I 200226 14:09:42 storage:35] Copying contents of s3://at-kubeflow-training/tf-job/ksc-ebce76a1 to local
Traceback (most recent call last):
  File "/storage-initializer/scripts/initializer-entrypoint", line 14, in <module>
    kfserving.Storage.download(src_uri, dest_path)
  File "/usr/local/lib/python3.7/site-packages/kfserving/storage.py", line 50, in download
    Storage._download_s3(uri, out_dir)
  File "/usr/local/lib/python3.7/site-packages/kfserving/storage.py", line 65, in _download_s3
    client = Storage._create_minio_client()
  File "/usr/local/lib/python3.7/site-packages/kfserving/storage.py", line 217, in _create_minio_client
    secure=use_ssl)
  File "/usr/local/lib/python3.7/site-packages/minio/api.py", line 150, in __init__
    is_valid_endpoint(endpoint)
  File "/usr/local/lib/python3.7/site-packages/minio/helpers.py", line 301, in is_valid_endpoint
    if hostname[-1] == '.':
IndexError: string index out of range
```

This was using Kubeflow 1.0.0RC4, KFServing 0.2.2 and KNative 0.11.1

--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `python/kfserving/kfserving/constants/constants.py`
Content:
```
1 # Copyright 2020 kubeflow.org.
2 #
3 # Licensed under the Apache License, Version 2.0 (the "License");
4 # you may not use this file except in compliance with the License.
5 # You may obtain a copy of the License at
6 #
7 #    http://www.apache.org/licenses/LICENSE-2.0
8 #
9 # Unless required by applicable law or agreed to in writing, software
10 # distributed under the License is distributed on an "AS IS" BASIS,
11 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 # See the License for the specific language governing permissions and
13 # limitations under the License.
14 
15 import os
16 
17 # KFServing K8S constants
18 KFSERVING_GROUP = 'serving.kubeflow.org'
19 KFSERVING_KIND = 'InferenceService'
20 KFSERVING_PLURAL = 'inferenceservices'
21 KFSERVING_VERSION = os.environ.get('KFSERVING_VERSION', 'v1alpha2')
22 KFSERVING_API_VERSION = KFSERVING_GROUP + '/' + KFSERVING_VERSION
23 
24 KFSERVING_LOGLEVEL = os.environ.get('KFSERVING_LOGLEVEL', 'INFO').upper()
25 
26 # INFERENCESERVICE credentials common constants
27 INFERENCESERVICE_CONFIG_MAP_NAME = 'inferenceservice-config'
28 INFERENCESERVICE_SYSTEM_NAMESPACE = 'kfserving-system'
29 DEFAULT_SECRET_NAME = "kfserving-secret-"
30 DEFAULT_SA_NAME = "kfserving-service-credentials"
31 
32 # S3 credentials constants
33 S3_ACCESS_KEY_ID_DEFAULT_NAME = "awsAccessKeyID"
34 S3_SECRET_ACCESS_KEY_DEFAULT_NAME = "awsSecretAccessKey"
35 S3_DEFAULT_CREDS_FILE = '~/.aws/credentials'
36 
37 # GCS credentials constants
38 GCS_CREDS_FILE_DEFAULT_NAME = 'gcloud-application-credentials.json'
39 GCS_DEFAULT_CREDS_FILE = '~/.config/gcloud/application_default_credentials.json'
40 
41 # Azure credentials constants
42 AZ_DEFAULT_CREDS_FILE = '~/.azure/azure_credentials.json'
43
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/python/kfserving/kfserving/constants/constants.py b/python/kfserving/kfserving/constants/constants.py
--- a/python/kfserving/kfserving/constants/constants.py
+++ b/python/kfserving/kfserving/constants/constants.py
@@ -30,8 +30,8 @@
 DEFAULT_SA_NAME = "kfserving-service-credentials"
 
 # S3 credentials constants
-S3_ACCESS_KEY_ID_DEFAULT_NAME = "awsAccessKeyID"
-S3_SECRET_ACCESS_KEY_DEFAULT_NAME = "awsSecretAccessKey"
+S3_ACCESS_KEY_ID_DEFAULT_NAME = "AWS_ACCESS_KEY_ID"
+S3_SECRET_ACCESS_KEY_DEFAULT_NAME = "AWS_SECRET_ACCESS_KEY"
 S3_DEFAULT_CREDS_FILE = '~/.aws/credentials'
 
 # GCS credentials constants

{"golden_diff": "diff --git a/python/kfserving/kfserving/constants/constants.py b/python/kfserving/kfserving/constants/constants.py\n--- a/python/kfserving/kfserving/constants/constants.py\n+++ b/python/kfserving/kfserving/constants/constants.py\n@@ -30,8 +30,8 @@\n DEFAULT_SA_NAME = \"kfserving-service-credentials\"\n \n # S3 credentials constants\n-S3_ACCESS_KEY_ID_DEFAULT_NAME = \"awsAccessKeyID\"\n-S3_SECRET_ACCESS_KEY_DEFAULT_NAME = \"awsSecretAccessKey\"\n+S3_ACCESS_KEY_ID_DEFAULT_NAME = \"AWS_ACCESS_KEY_ID\"\n+S3_SECRET_ACCESS_KEY_DEFAULT_NAME = \"AWS_SECRET_ACCESS_KEY\"\n S3_DEFAULT_CREDS_FILE = '~/.aws/credentials'\n \n # GCS credentials constants\n", "issue": "storage-initialiser fails to copy model from S3\nUpon using a Secret and Service account that look like this:\r\n\r\n```\r\napiVersion: v1\r\nmetadata:\r\n  name: kfserving-aws-secret\r\n  namespace: {namespace}\r\n  annotations:\r\n    serving.kubeflow.org/s3-endpoint: s3.eu-east-1.amazonaws.com\r\n    serving.kubeflow.org/s3-usehttps: \"1\"\r\n    serving.kubeflow.org/s3-verifyssl: \"1\"\r\n    serving.kubeflow.org/s3-region: eu-east-1\r\ndata:\r\n  AWS_ACCESS_KEY_ID: {access_key_base64}\r\n  AWS_SECRET_ACCESS_KEY: {secret_key_base64}\r\nkind: Secret\r\ntype: Opaque\r\n---\r\napiVersion: v1\r\nkind: ServiceAccount\r\nmetadata:\r\n  name: kfserving-sa\r\n  namespace: {namespace}\r\nsecrets:\r\n  - name: kfserving-aws-secret  \r\n```\r\n...and an InferenceService like this:\r\n\r\n```\r\napiVersion: \"serving.kubeflow.org/v1alpha2\"\r\nkind: \"InferenceService\"\r\nmetadata:\r\n  name: {model_name}\r\n  namespace: {namespace}\r\nspec:\r\n  default:\r\n    predictor:\r\n      serviceAccountName: kfserving-sa\r\n      tensorflow:\r\n        storageUri: {model_base_path}    \r\n```\r\n\r\n...the model fails to serve, with the `storage-initialiser` pod throwing the following error:\r\n\r\n```\r\n[I 200226 14:09:42 initializer-entrypoint:13] Initializing, args: src_uri [s3://at-kubeflow-training/tf-job/ksc-ebce76a1] dest_path[ [/mnt/models]\r\n[I 200226 14:09:42 storage:35] Copying contents of s3://at-kubeflow-training/tf-job/ksc-ebce76a1 to local\r\nTraceback (most recent call last):\r\n  File \"/storage-initializer/scripts/initializer-entrypoint\", line 14, in <module>\r\n    kfserving.Storage.download(src_uri, dest_path)\r\n  File \"/usr/local/lib/python3.7/site-packages/kfserving/storage.py\", line 50, in download\r\n    Storage._download_s3(uri, out_dir)\r\n  File \"/usr/local/lib/python3.7/site-packages/kfserving/storage.py\", line 65, in _download_s3\r\n    client = Storage._create_minio_client()\r\n  File \"/usr/local/lib/python3.7/site-packages/kfserving/storage.py\", line 217, in _create_minio_client\r\n    secure=use_ssl)\r\n  File \"/usr/local/lib/python3.7/site-packages/minio/api.py\", line 150, in __init__\r\n    is_valid_endpoint(endpoint)\r\n  File \"/usr/local/lib/python3.7/site-packages/minio/helpers.py\", line 301, in is_valid_endpoint\r\n    if hostname[-1] == '.':\r\nIndexError: string index out of range\r\n```\r\n\r\nThis was using Kubeflow 1.0.0RC4, KFServing 0.2.2 and KNative 0.11.1\n", "before_files": [{"content": "# Copyright 2020 kubeflow.org.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#    http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport os\n\n# KFServing K8S constants\nKFSERVING_GROUP = 'serving.kubeflow.org'\nKFSERVING_KIND = 'InferenceService'\nKFSERVING_PLURAL = 'inferenceservices'\nKFSERVING_VERSION = os.environ.get('KFSERVING_VERSION', 'v1alpha2')\nKFSERVING_API_VERSION = KFSERVING_GROUP + '/' + KFSERVING_VERSION\n\nKFSERVING_LOGLEVEL = os.environ.get('KFSERVING_LOGLEVEL', 'INFO').upper()\n\n# INFERENCESERVICE credentials common constants\nINFERENCESERVICE_CONFIG_MAP_NAME = 'inferenceservice-config'\nINFERENCESERVICE_SYSTEM_NAMESPACE = 'kfserving-system'\nDEFAULT_SECRET_NAME = \"kfserving-secret-\"\nDEFAULT_SA_NAME = \"kfserving-service-credentials\"\n\n# S3 credentials constants\nS3_ACCESS_KEY_ID_DEFAULT_NAME = \"awsAccessKeyID\"\nS3_SECRET_ACCESS_KEY_DEFAULT_NAME = \"awsSecretAccessKey\"\nS3_DEFAULT_CREDS_FILE = '~/.aws/credentials'\n\n# GCS credentials constants\nGCS_CREDS_FILE_DEFAULT_NAME = 'gcloud-application-credentials.json'\nGCS_DEFAULT_CREDS_FILE = '~/.config/gcloud/application_default_credentials.json'\n\n# Azure credentials constants\nAZ_DEFAULT_CREDS_FILE = '~/.azure/azure_credentials.json'\n", "path": "python/kfserving/kfserving/constants/constants.py"}], "after_files": [{"content": "# Copyright 2020 kubeflow.org.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#    http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport os\n\n# KFServing K8S constants\nKFSERVING_GROUP = 'serving.kubeflow.org'\nKFSERVING_KIND = 'InferenceService'\nKFSERVING_PLURAL = 'inferenceservices'\nKFSERVING_VERSION = os.environ.get('KFSERVING_VERSION', 'v1alpha2')\nKFSERVING_API_VERSION = KFSERVING_GROUP + '/' + KFSERVING_VERSION\n\nKFSERVING_LOGLEVEL = os.environ.get('KFSERVING_LOGLEVEL', 'INFO').upper()\n\n# INFERENCESERVICE credentials common constants\nINFERENCESERVICE_CONFIG_MAP_NAME = 'inferenceservice-config'\nINFERENCESERVICE_SYSTEM_NAMESPACE = 'kfserving-system'\nDEFAULT_SECRET_NAME = \"kfserving-secret-\"\nDEFAULT_SA_NAME = \"kfserving-service-credentials\"\n\n# S3 credentials constants\nS3_ACCESS_KEY_ID_DEFAULT_NAME = \"AWS_ACCESS_KEY_ID\"\nS3_SECRET_ACCESS_KEY_DEFAULT_NAME = \"AWS_SECRET_ACCESS_KEY\"\nS3_DEFAULT_CREDS_FILE = '~/.aws/credentials'\n\n# GCS credentials constants\nGCS_CREDS_FILE_DEFAULT_NAME = 'gcloud-application-credentials.json'\nGCS_DEFAULT_CREDS_FILE = '~/.config/gcloud/application_default_credentials.json'\n\n# Azure credentials constants\nAZ_DEFAULT_CREDS_FILE = '~/.azure/azure_credentials.json'\n", "path": "python/kfserving/kfserving/constants/constants.py"}]}