File: //snap/google-cloud-cli/394/lib/googlecloudsdk/command_lib/ai/endpoints_util.py
# -*- coding: utf-8 -*- #
# Copyright 2020 Google LLC. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Utilities for AI Platform endpoints commands."""
from __future__ import absolute_import
from __future__ import division
from __future__ import unicode_literals
import io
from googlecloudsdk.command_lib.ai import errors
from googlecloudsdk.core import resources
from googlecloudsdk.core import yaml
from googlecloudsdk.core.console import console_io
def ParseOperation(operation_name):
"""Parse operation resource to the operation reference object.
Args:
operation_name: The operation resource to wait on
Returns:
The operation reference object
"""
if '/endpoints/' in operation_name:
try:
return resources.REGISTRY.ParseRelativeName(
operation_name,
collection='aiplatform.projects.locations.endpoints.operations',
)
except resources.WrongResourceCollectionException:
pass
return resources.REGISTRY.ParseRelativeName(
operation_name, collection='aiplatform.projects.locations.operations'
)
def _LoadYaml(file_path, sdk_method):
"""Loads a YAML file."""
data = console_io.ReadFromFileOrStdin(file_path, binary=True)
with io.BytesIO(data) as f:
try:
return yaml.load(f)
except ValueError:
raise errors.InvalidInstancesFileError(
f'Input is not in JSON format. See `gcloud ai endpoints {sdk_method}'
' --help` for details.'
)
def ReadInstancesFromArgs(json_request):
"""Reads the instances from the given file path ('-' for stdin).
Args:
json_request: str or None, a path to a file ('-' for stdin) containing the
JSON body of a prediction request.
Returns:
A list of instances.
Raises:
InvalidInstancesFileError: If the input file is invalid (invalid format or
contains too many/zero instances), or an improper combination of input
files was given.
"""
request = _LoadYaml(json_request, sdk_method='predict')
if not isinstance(request, dict):
raise errors.InvalidInstancesFileError(
'Input instances are not in JSON format. '
'See `gcloud ai endpoints predict --help` for details.'
)
if 'instances' not in request:
raise errors.InvalidInstancesFileError(
'Invalid JSON request: missing "instances" attribute'
)
if not isinstance(request['instances'], list):
raise errors.InvalidInstancesFileError(
'Invalid JSON request: "instances" must be a list'
)
return request
def ReadInputsFromArgs(json_request):
"""Validates and reads json request for Direct Prediction."""
request = _LoadYaml(json_request, sdk_method='direct-predict')
if 'inputs' not in request:
raise errors.InvalidInstancesFileError('Input json must contain "inputs"')
return request
def ReadInputFromArgs(json_request):
"""Validates and reads json request for Direct Raw Prediction."""
request = _LoadYaml(json_request, sdk_method='direct-raw-predict')
if 'input' not in request:
raise errors.InvalidInstancesFileError('Input json must contain "input"')
if 'method_name' not in request and 'methodName' not in request:
raise errors.InvalidInstancesFileError(
'Input json must contain "method_name" or "methodName"'
)
return request
def GetDefaultFormat(predictions, key_name='predictions'):
"""Get default output format for prediction results."""
if not isinstance(predictions, list):
# This usually indicates some kind of error case, so surface the full API
# response
return 'json'
elif not predictions:
return None
# predictions is guaranteed by API contract to be a list of similarly shaped
# objects, but we don't know ahead of time what those objects look like.
elif isinstance(predictions[0], dict):
keys = ', '.join(sorted(predictions[0].keys()))
return """
table(
{}:format="table(
{}
)"
)""".format(key_name, keys)
else:
return 'table[no-heading]({})'.format(key_name)