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Feature/multi model artifact handler #869

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6d9fa4a
Initial commit
YashPandit4u May 27, 2024
6a930f1
rename in main module file
YashPandit4u May 27, 2024
5f3b316
Logger used for prints, error handling improved, one extra file creat…
YashPandit4u Jun 1, 2024
802e438
Merge branch 'oracle:main' into feature/multi-model-artifact-handler
YashPandit4u Jun 1, 2024
35e8464
Reformatted using black.
YashPandit4u Jun 1, 2024
e625107
Merge branch 'feature/multi-model-artifact-handler' of https://github…
YashPandit4u Jun 1, 2024
74a235e
Separate logger used.
YashPandit4u Jun 1, 2024
848972e
Added python docs for all methods.
YashPandit4u Jun 1, 2024
d35b917
Added class DataScienceModelCollection that extends from DataScienceM…
YashPandit4u Jun 5, 2024
3ac5338
removed old model description class
YashPandit4u Jun 5, 2024
822c7e8
formatted using black
YashPandit4u Jun 5, 2024
3d4d950
black formatter used and one return type added.
YashPandit4u Jun 5, 2024
d4ef023
Added add_artifact and remove_artifact method in main DataScienceMode…
YashPandit4u Jun 11, 2024
c40ea8b
Removed new added class.
YashPandit4u Jun 11, 2024
d0309f4
Added uri based approach
YashPandit4u Jun 13, 2024
19ec921
Added unit tests.
YashPandit4u Jun 13, 2024
9089028
Changed the pydocs according to ads specifications
YashPandit4u Jun 13, 2024
464cb37
Merge branch 'main' into feature/multi-model-artifact-handler
YashPandit4u Jun 13, 2024
49be8f8
replaces regex with normal splitting for uri
YashPandit4u Jun 13, 2024
a2894a5
Merge branch 'feature/multi-model-artifact-handler' of https://github…
YashPandit4u Jun 13, 2024
5d327cd
removed default_signer
YashPandit4u Jun 13, 2024
b7e7d74
Used ObjectStorageDetails.from_path(uri) for url decoding.
YashPandit4u Jun 13, 2024
4418bf8
namespace, bucket, prefix way added again.
YashPandit4u Jun 14, 2024
e2e7099
Merge branch 'main' into feature/multi-model-artifact-handler
YashPandit4u Jun 14, 2024
4cc8823
Given options for both uri and (namespace, bucket) in add_artifact, r…
YashPandit4u Jun 15, 2024
7f3cc7f
Updated python docs
YashPandit4u Jun 15, 2024
32f4826
Ran black formatter.
YashPandit4u Jun 15, 2024
9f69e35
Ran black formatter of UTs.
YashPandit4u Jun 15, 2024
ad0ce2e
Added uri UTs.
YashPandit4u Jun 15, 2024
eec2b4d
Prefix null check added.
YashPandit4u Jun 15, 2024
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328 changes: 328 additions & 0 deletions ads/model/model_description.py
Original file line number Diff line number Diff line change
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import json
import ads.common
import oci
import pytz
import datetime
import os
from oci.data_science.models import Metadata
import ads

# from ads.common import logger
import logging

logger = logging.getLogger("ads.model_description")
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can we reuse the logger from ads.common?

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When I used logger from ads.common I don't see any info messages and for some methods in this class I want to show info messages.

logger.setLevel(logging.INFO)


class ModelDescription:
"""
Represents a model description for multi model artifacts. Provides methods to ease the process of creating such models.

Methods:
- add(namespace, bucket, prefix=None, files=None): Adds information about objects to the model description JSON.
- remove(namespace, bucket, prefix=None): Removes information about objects from the model description JSON.
- show(): Displays the current model description JSON in a human-readable format.
- build(): Builds the model description JSON and writes it to a file.
- save(project_ocid, compartment_ocid, display_name=None): Saves the model to the Model Catalog of OCI Data Science service.
"""

empty_json = {
"version": "1.0",
"type": "modelOSSReferenceDescription",
"models": [],
}

def auth(self):
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"""
Internal method that authenticates the model description instance by initializing OCI clients.

Parameters:
- None

Returns:
- None

Note:
- This method retrieves authentication data using default signer from the `ads.common.auth` module.
- The region information is extracted from the authentication data.
"""
authData = ads.common.auth.default_signer()
signer = authData["signer"]
self.region = authData["config"]["region"]

# data science client
self.data_science_client = oci.data_science.DataScienceClient(
{"region": self.region}, signer=signer
)
# oss client
self.object_storage_client = oci.object_storage.ObjectStorageClient(
{"region": self.region}, signer=signer
)

def __init__(self, model_ocid=None):
"""
Initializes a new instance of the ModelDescription class.

Parameters:
- model_ocid (str, optional): The OCID (Oracle Cloud Identifier) of the model.
If provided, retrieves the takes the model artifact content as starting point or else initializes from blank artifact.

Returns:
- None

Raises:
- json.JSONDecodeError: If there is an error decoding the JSON content retrieved
from the backend.
- Exception: If an unexpected error occurs while retrieving the model artifact content.

Note:
- If `model_ocid` is provided, this method attempts to retrieve the model artifact
content from the backend using the provided OCID. If successful, it initializes
`modelDescriptionJson` with the retrieved content. If unsuccessful, it logs the
error and raises an exception.
- If `model_ocid` is not provided, `modelDescriptionJson` is initialized with an
empty JSON structure.
"""

self.region = ""
self.auth()

if model_ocid == None:
# if no model given then start from scratch
self.modelDescriptionJson = self.empty_json
else:
# if model given then get that as the starting reference point
logger.info("Getting model details from backend")
try:
get_model_artifact_content_response = (
self.data_science_client.get_model_artifact_content(
model_id=model_ocid,
)
)
content = get_model_artifact_content_response.data.content
self.modelDescriptionJson = json.loads(content)
except json.JSONDecodeError as e:
logger.error(f"Error decoding JSON: {e}")
raise e
except Exception as e:
logger.error(f"An unexpected error occurred: {e}")
raise e

def add(self, namespace, bucket, prefix=None, files=None):
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recommend using type hinting for all the functions, for example:
def add(self, namespace: str, bucket: str, ... ): -> None

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+1

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Added type hints.

"""
Adds information about objects in a specified bucket to the model description JSON.

Parameters:
- namespace (str): The namespace of the object storage.
- bucket (str): The name of the bucket containing the objects.
- prefix (str, optional): The prefix used to filter objects within the bucket. Defaults to None.
- files (list of str, optional): A list of file names to include in the model description.
If provided, only objects with matching file names will be included. Defaults to None.

Returns:
- None

Raises:
- ValueError: If no files are found to add to the model description.

Note:
- If `files` is not provided, it retrieves information about all objects in the bucket.
If `files` is provided, it only retrieves information about objects with matching file names.
- If no objects are found to add to the model description, a ValueError is raised.
"""

# Remove if the model already exists
self.remove(namespace, bucket, prefix)

def checkIfFileExists(fileName):
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can we reuse is_path_exists from ads.common.utils instead?

isExists = False
try:
headResponse = self.object_storage_client.head_object(
namespace, bucket, object_name=fileName
)
if headResponse.status == 200:
isExists = True
except Exception as e:
if hasattr(e, "status") and e.status == 404:
logger.error(f"File not found in bucket: {fileName}")
else:
logger.error(f"An error occured: {e}")
return isExists

# Function to un-paginate the api call with while loop
def listObjectVersionsUnpaginated():
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ads.common.object_storage_details.list_object_versions can be used instead?

objectStorageList = []
has_next_page, opc_next_page = True, None
while has_next_page:
response = self.object_storage_client.list_object_versions(
namespace_name=namespace,
bucket_name=bucket,
prefix=prefix,
fields="name,size",
page=opc_next_page,
)
objectStorageList.extend(response.data.items)
has_next_page = response.has_next_page
opc_next_page = response.next_page
return objectStorageList

# Fetch object details and put it into the objects variable
objectStorageList = []
if files == None:
objectStorageList = listObjectVersionsUnpaginated()
else:
for fileName in files:
if checkIfFileExists(fileName=fileName):
objectStorageList.append(
self.object_storage_client.list_object_versions(
namespace_name=namespace,
bucket_name=bucket,
prefix=fileName,
fields="name,size",
).data.items[0]
)

objects = [
{"name": obj.name, "version": obj.version_id, "sizeInBytes": obj.size}
for obj in objectStorageList
if obj.size > 0
]

if len(objects) == 0:
error_message = (
f"No files to add in the bucket: {bucket} with namespace: {namespace} "
f"and prefix: {prefix}. File names: {files}"
)
logger.error(error_message)
raise ValueError(error_message)

self.modelDescriptionJson["models"].append(
{
"namespace": namespace,
"bucketName": bucket,
"prefix": prefix,
"objects": objects,
}
)

def remove(self, namespace, bucket, prefix=None):
"""
Removes information about objects in a specified bucket from the model description JSON.

Parameters:
- namespace (str): The namespace of the object storage.
- bucket (str): The name of the bucket containing the objects.
- prefix (str, optional): The prefix used to filter objects within the bucket. Defaults to None.

Returns:
- None

Note:
- This method removes information about objects in the specified bucket from the
instance of the ModelDescription.
- If a matching model (with the specified namespace, bucket name, and prefix) is found
in the model description JSON, it is removed.
- If no matching model is found, the method returns without making any changes.
"""

def findModelIdx():
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for idx, model in enumerate(self.modelDescriptionJson["models"]):
if (
model["namespace"],
model["bucketName"],
(model["prefix"] if ("prefix" in model) else None),
) == (namespace, bucket, prefix):
return idx
return -1

modelSearchIdx = findModelIdx()
if modelSearchIdx == -1:
return
else:
# model found case
self.modelDescriptionJson["models"].pop(modelSearchIdx)

def show(self):
"""
Displays the current model description JSON in a human-readable format.

Parameters:
- None

Returns:
- None

Note:
- The JSON representation of the model description is formatted with an indentation
of 4 spaces.
"""
logger.info(json.dumps(self.modelDescriptionJson, indent=4))
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def build(self):
"""
Builds the model description JSON and writes it to a file.

Parameters:
- None

Returns:
- str: The absolute file path where the model description JSON is stored.

Note:
- This method serializes the current model description attribute to a JSON file named 'resultModelDescription.json' with an indentation of 2 spaces.
"""
logger.info("Building...")
file_path = "resultModelDescription.json"
try:
with open(file_path, "w") as json_file:
json.dump(self.modelDescriptionJson, json_file, indent=2)
except IOError as e:
logger.error(
f"Error writing to file '{file_path}': {e}"
) # Handle the exception accordingly, e.g., log the error, retry writing, etc.
except Exception as e:
logger.error(
f"An unexpected error occurred: {e}"
) # Handle other unexpected exceptions
logger.info("Model Artifact stored successfully.")
return os.path.abspath(file_path)

def save(self, project_ocid, compartment_ocid, display_name=None):
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"""
Saves the model to the Model Catalog of Oracle Cloud Infrastructure (OCI) Data Science service.

Parameters:
- project_ocid (str): The OCID (Oracle Cloud Identifier) of the OCI Data Science project.
- compartment_ocid (str): The OCID of the compartment in which the model will be created.
- display_name (str, optional): The display name for the created model. If not provided,
a default display name indicating the creation timestamp is used. Defaults to None.

Returns:
- str: The OCID of the created model.

Note:
- The display name defaults to a string indicating the creation timestamp if not provided.
"""
display_name = (
"Created by MMS SDK on "
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+ datetime.datetime.now(pytz.utc).strftime("%Y-%m-%d %H:%M:%S %Z")
if (display_name == None)
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nit: use if display_name: instead?

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The suggested statement will trigger even when we have blank string.

else display_name
)
customMetadataList = [Metadata(key="modelDescription", value="true")]
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model_details = oci.data_science.models.CreateModelDetails(
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compartment_id=compartment_ocid,
project_id=project_ocid,
display_name=display_name,
custom_metadata_list=customMetadataList,
)
logger.info("Created model details")
model = self.data_science_client.create_model(model_details)
logger.info("Created model")
self.data_science_client.create_model_artifact(
model.data.id,
json.dumps(self.modelDescriptionJson),
content_disposition='attachment; filename="modelDescription.json"',
)
logger.info(f"Successfully created model with OCID: {model.data.id}")
return model.data.id
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