File size: 5,305 Bytes
c490c3c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 |
# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
"""Client and server classes corresponding to protobuf-defined services."""
import grpc
import warnings
import inference_pb2 as inference__pb2
GRPC_GENERATED_VERSION = '1.64.1'
GRPC_VERSION = grpc.__version__
EXPECTED_ERROR_RELEASE = '1.65.0'
SCHEDULED_RELEASE_DATE = 'June 25, 2024'
_version_not_supported = False
try:
from grpc._utilities import first_version_is_lower
_version_not_supported = first_version_is_lower(GRPC_VERSION, GRPC_GENERATED_VERSION)
except ImportError:
_version_not_supported = True
if _version_not_supported:
warnings.warn(
f'The grpc package installed is at version {GRPC_VERSION},'
+ f' but the generated code in inference_pb2_grpc.py depends on'
+ f' grpcio>={GRPC_GENERATED_VERSION}.'
+ f' Please upgrade your grpc module to grpcio>={GRPC_GENERATED_VERSION}'
+ f' or downgrade your generated code using grpcio-tools<={GRPC_VERSION}.'
+ f' This warning will become an error in {EXPECTED_ERROR_RELEASE},'
+ f' scheduled for release on {SCHEDULED_RELEASE_DATE}.',
RuntimeWarning
)
class SFEServiceStub(object):
"""Missing associated documentation comment in .proto file."""
def __init__(self, channel):
"""Constructor.
Args:
channel: A grpc.Channel.
"""
self.edit = channel.unary_unary(
'/inference.SFEService/edit',
request_serializer=inference__pb2.SFERequest.SerializeToString,
response_deserializer=inference__pb2.SFEResponse.FromString,
_registered_method=True)
self.generate_mask = channel.unary_unary(
'/inference.SFEService/generate_mask',
request_serializer=inference__pb2.SFERequestMask.SerializeToString,
response_deserializer=inference__pb2.SFEResponseMask.FromString,
_registered_method=True)
class SFEServiceServicer(object):
"""Missing associated documentation comment in .proto file."""
def edit(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def generate_mask(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def add_SFEServiceServicer_to_server(servicer, server):
rpc_method_handlers = {
'edit': grpc.unary_unary_rpc_method_handler(
servicer.edit,
request_deserializer=inference__pb2.SFERequest.FromString,
response_serializer=inference__pb2.SFEResponse.SerializeToString,
),
'generate_mask': grpc.unary_unary_rpc_method_handler(
servicer.generate_mask,
request_deserializer=inference__pb2.SFERequestMask.FromString,
response_serializer=inference__pb2.SFEResponseMask.SerializeToString,
),
}
generic_handler = grpc.method_handlers_generic_handler(
'inference.SFEService', rpc_method_handlers)
server.add_generic_rpc_handlers((generic_handler,))
server.add_registered_method_handlers('inference.SFEService', rpc_method_handlers)
# This class is part of an EXPERIMENTAL API.
class SFEService(object):
"""Missing associated documentation comment in .proto file."""
@staticmethod
def edit(request,
target,
options=(),
channel_credentials=None,
call_credentials=None,
insecure=False,
compression=None,
wait_for_ready=None,
timeout=None,
metadata=None):
return grpc.experimental.unary_unary(
request,
target,
'/inference.SFEService/edit',
inference__pb2.SFERequest.SerializeToString,
inference__pb2.SFEResponse.FromString,
options,
channel_credentials,
insecure,
call_credentials,
compression,
wait_for_ready,
timeout,
metadata,
_registered_method=True)
@staticmethod
def generate_mask(request,
target,
options=(),
channel_credentials=None,
call_credentials=None,
insecure=False,
compression=None,
wait_for_ready=None,
timeout=None,
metadata=None):
return grpc.experimental.unary_unary(
request,
target,
'/inference.SFEService/generate_mask',
inference__pb2.SFERequestMask.SerializeToString,
inference__pb2.SFEResponseMask.FromString,
options,
channel_credentials,
insecure,
call_credentials,
compression,
wait_for_ready,
timeout,
metadata,
_registered_method=True)
|