146 lines
4.8 KiB
Python
146 lines
4.8 KiB
Python
# -*- coding: utf-8 -*- #
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# Copyright 2021 Google LLC. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Vertex AI endpoints raw-predict command."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import unicode_literals
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import json
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import sys
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from googlecloudsdk.api_lib.ai.endpoints import client
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from googlecloudsdk.calliope import base
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from googlecloudsdk.command_lib.ai import constants
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from googlecloudsdk.command_lib.ai import endpoint_util
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from googlecloudsdk.command_lib.ai import flags
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from googlecloudsdk.command_lib.ai import region_util
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from googlecloudsdk.core import exceptions as core_exceptions
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from googlecloudsdk.core.console import console_io
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import six
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def _AddArgs(parser):
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flags.AddEndpointResourceArg(
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parser,
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'to do online raw prediction',
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prompt_func=region_util.PromptForOpRegion)
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flags.GetRawPredictHeadersArg().AddToParser(parser)
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flags.GetRawPredictRequestArg().AddToParser(parser)
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def _Run(args, version):
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"""Run Vertex AI online prediction."""
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endpoint_ref = args.CONCEPTS.endpoint.Parse()
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args.region = endpoint_ref.AsDict()['locationsId']
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with endpoint_util.AiplatformEndpointOverrides(version, region=args.region):
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if args.request.startswith('@'):
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request = console_io.ReadFromFileOrStdin(args.request[1:], binary=True)
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else:
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request = args.request.encode('utf-8')
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endpoints_client = client.EndpointsClient(version=version)
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_, response = endpoints_client.RawPredict(endpoint_ref, args.http_headers,
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request)
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# Workaround since gcloud only supports protobufs as JSON objects. Since
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# raw predict can return anything, write raw bytes to stdout.
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if not args.IsSpecified('format'):
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sys.stdout.buffer.write(response)
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return None
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# If user asked for formatting, assume it's a JSON object.
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try:
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return json.loads(response.decode('utf-8'))
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except ValueError:
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raise core_exceptions.Error('No JSON object could be decoded from the '
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'HTTP response body:\n' +
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six.text_type(response))
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@base.ReleaseTracks(base.ReleaseTrack.GA)
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@base.UniverseCompatible
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class RawPredict(base.Command):
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"""Run Vertex AI online raw prediction.
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`{command}` sends a raw prediction request to a Vertex AI endpoint. The
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request can be given on the command line or read from a file or stdin.
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## EXAMPLES
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To predict against an endpoint ``123'' under project ``example'' in region
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``us-central1'', reading the request from the command line, run:
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$ {command} 123 --project=example --region=us-central1 --request='{
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"instances": [
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{ "values": [1, 2, 3, 4], "key": 1 },
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{ "values": [5, 6, 7, 8], "key": 2 }
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]
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}'
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If the request body was in the file ``input.json'', run:
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$ {command} 123 --project=example --region=us-central1 --request=@input.json
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To send the image file ``image.jpeg'' and set the *content type*, run:
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$ {command} 123 --project=example --region=us-central1
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--http-headers=Content-Type=image/jpeg --request=@image.jpeg
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"""
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@staticmethod
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def Args(parser):
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_AddArgs(parser)
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def Run(self, args):
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return _Run(args, constants.GA_VERSION)
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@base.ReleaseTracks(base.ReleaseTrack.BETA, base.ReleaseTrack.ALPHA)
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@base.UniverseCompatible
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class RawPredictBeta(RawPredict):
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"""Run Vertex AI online raw prediction.
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`{command}` sends a raw prediction request to a Vertex AI endpoint. The
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request can be given on the command line or read from a file or stdin.
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## EXAMPLES
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To predict against an endpoint ``123'' under project ``example'' in region
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``us-central1'', reading the request from the command line, run:
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$ {command} 123 --project=example --region=us-central1 --request='{
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"instances": [
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{ "values": [1, 2, 3, 4], "key": 1 },
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{ "values": [5, 6, 7, 8], "key": 2 }
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]
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}'
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If the request body was in the file ``input.json'', run:
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$ {command} 123 --project=example --region=us-central1 --request=@input.json
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To send the image file ``image.jpeg'' and set the *content type*, run:
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$ {command} 123 --project=example --region=us-central1
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--http-headers=Content-Type=image/jpeg --request=@image.jpeg
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"""
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def Run(self, args):
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return _Run(args, constants.BETA_VERSION)
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