protocol-buffers

问题 Is it possible to detect the type of a raw protocol buffer message (in byte[]) I have a situation where an endpoint can receive different messages and I need to be able to detect the type before I can deserialize it. I am using protobuf-net 回答1: You can't detect the type in isolation, since the protobuf spec doesn't add any data to the stream for this; however, there are a number of ways of making this easy, depending on the context: a union type (as mentioned by Jon) covers a range of

问题 Is it possible to detect the type of a raw protocol buffer message (in byte[]) I have a situation where an endpoint can receive different messages and I need to be able to detect the type before I can deserialize it. I am using protobuf-net 回答1: You can't detect the type in isolation, since the protobuf spec doesn't add any data to the stream for this; however, there are a number of ways of making this easy, depending on the context: a union type (as mentioned by Jon) covers a range of

问题 Is it possible to detect the type of a raw protocol buffer message (in byte[]) I have a situation where an endpoint can receive different messages and I need to be able to detect the type before I can deserialize it. I am using protobuf-net 回答1: You can't detect the type in isolation, since the protobuf spec doesn't add any data to the stream for this; however, there are a number of ways of making this easy, depending on the context: a union type (as mentioned by Jon) covers a range of

问题 Is it possible to detect the type of a raw protocol buffer message (in byte[]) I have a situation where an endpoint can receive different messages and I need to be able to detect the type before I can deserialize it. I am using protobuf-net 回答1: You can't detect the type in isolation, since the protobuf spec doesn't add any data to the stream for this; however, there are a number of ways of making this easy, depending on the context: a union type (as mentioned by Jon) covers a range of

问题 I want to write a custom Tensorflow op in Python and register it in the Protobuf registry for operations like explained here. The Protobuf registration is key because I will not be using this op directly from Python, but if it is registered like a C++ op and loaded into the Python runtime environment then I can run it in my environment. I would expect the code to look something like, import tensorflow as tf from google.protobuf import json_format from tensorflow.python.ops.data_flow_ops

问题 I'm trying to do a CMake with Caffe, but my system cannot find protobuf compiler. I have previously installed protobuf2.7.0. Now I switched back to 2.6.1. How could I configure my CMake to recognize the protobuf2.6.1 compiler? I have done $ sudo apt-get install libprotobuf-dev protobuf-compiler $ protoc --version libprotoc 2.6.1 But when I try to cmake Caffe, it still gives me the error user@user-computer:~/caffe/build$ cmake -DBLAS=open .. -- Boost version: 1.58.0 -- Found the following

问题 How does one get the options associated with a protocol buffer field? E.g., suppose I have a field with a custom options: message Foo { optional string title = 1 [(indexed) = true]; } I can get a list of fields: for f in foo.ListFields(): print f How do I access the "indexed" state? (I can see there is a list of f "_options", but that seems "internal"? Is there a proper way to access option extensions by name)? 回答1: I'll use as an example the nanopb custom options, as defined here. However

问题 How does one get the options associated with a protocol buffer field? E.g., suppose I have a field with a custom options: message Foo { optional string title = 1 [(indexed) = true]; } I can get a list of fields: for f in foo.ListFields(): print f How do I access the "indexed" state? (I can see there is a list of f "_options", but that seems "internal"? Is there a proper way to access option extensions by name)? 回答1: I'll use as an example the nanopb custom options, as defined here. However

问题 How does one get the options associated with a protocol buffer field? E.g., suppose I have a field with a custom options: message Foo { optional string title = 1 [(indexed) = true]; } I can get a list of fields: for f in foo.ListFields(): print f How do I access the "indexed" state? (I can see there is a list of f "_options", but that seems "internal"? Is there a proper way to access option extensions by name)? 回答1: I'll use as an example the nanopb custom options, as defined here. However

问题 Given the address of a GRPC service at, say, ipv4:127.0.0.1:25000 , are there any standardized queries or tools I can use to discover what GRPC requests the service is capable of receiving? e.g. I'm looking for something like: ./magic-grpc-service-tool 127.0.0.1:25000 > service Greeter { > rpc Greet(HelloMessage) returns (HelloResponse) {} > } 回答1: Update: the reflection service is supported across the various languages and grpc CLI is able to consume it. At the moment, no. We will be adding