tool for compiling a swiftmodule in memory #26848
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@swift-ci please test tensorflow |
marcrasi
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@swift-ci please test tensorflow |
marcrasi
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@swift-ci please test tensorflow linux |
burmako
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Aug 26, 2019
include/swift/Subsystems.h
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| const SerializationOptions &options, | ||
| std::unique_ptr<llvm::MemoryBuffer> *moduleBuffer, | ||
| std::unique_ptr<llvm::MemoryBuffer> *moduleDocBuffer, | ||
| const SILModule *M); |
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Why does the method above default to M == nullptr and this one doesn't?
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I'll change this to be consistent.
lib/Serialization/Serialization.cpp
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| std::unique_ptr<llvm::MemoryBuffer> *moduleBuffer, | ||
| std::unique_ptr<llvm::MemoryBuffer> *moduleDocBuffer, const SILModule *M) { | ||
| if (moduleBuffer) { | ||
| SharedTimer timer("Serialization, swiftmodule, to buffer"); |
lib/Serialization/Serialization.cpp
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| } | ||
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| if (moduleDocBuffer) { | ||
| SharedTimer timer("Serialization, swiftdoc, to buffer"); |
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| using namespace swift; | ||
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| class StreamDiagConsumer : public DiagnosticConsumer { |
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Looks like this is a copy/paste of StreamDiagConsumer from SwiftASTManager, but I don't mind that for apple/swift:tensorflow.
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This is a tool for compiling swiftmodules in memory. There is a single entry point
compileSwiftModulewith comments. There are also tests.The purpose is to make it possible to develop a code intelligence server that doesn't rely on an external build system to build dependencies and that doesn't write to the filesystem. See https://forums.swift.org/t/building-swiftmodules-for-sourcekit/28030 for more discussion.
This should be very upstreamable, but I want to get it into the tensorflow branch first so that I can unblock development of the internal google code intelligence server.