1 | //===- TensorSpec.cpp - tensor type abstraction ---------------------------===// |
2 | // |
3 | // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. |
4 | // See https://llvm.org/LICENSE.txt for license information. |
5 | // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception |
6 | // |
7 | //===----------------------------------------------------------------------===// |
8 | // |
9 | // Implementation file for the abstraction of a tensor type, and JSON loading |
10 | // utils. |
11 | // |
12 | //===----------------------------------------------------------------------===// |
13 | #include "llvm/ADT/STLExtras.h" |
14 | #include "llvm/Config/config.h" |
15 | |
16 | #include "llvm/ADT/StringExtras.h" |
17 | #include "llvm/ADT/Twine.h" |
18 | #include "llvm/Analysis/TensorSpec.h" |
19 | #include "llvm/Support/CommandLine.h" |
20 | #include "llvm/Support/Debug.h" |
21 | #include "llvm/Support/JSON.h" |
22 | #include "llvm/Support/ManagedStatic.h" |
23 | #include "llvm/Support/raw_ostream.h" |
24 | #include <array> |
25 | #include <cassert> |
26 | #include <numeric> |
27 | |
28 | using namespace llvm; |
29 | |
30 | namespace llvm { |
31 | |
32 | #define TFUTILS_GETDATATYPE_IMPL(T, E) \ |
33 | template <> TensorType TensorSpec::getDataType<T>() { return TensorType::E; } |
34 | |
35 | SUPPORTED_TENSOR_TYPES(TFUTILS_GETDATATYPE_IMPL) |
36 | |
37 | #undef TFUTILS_GETDATATYPE_IMPL |
38 | |
39 | static std::array<std::string, static_cast<size_t>(TensorType::Total)> |
40 | TensorTypeNames{"INVALID" , |
41 | #define TFUTILS_GETNAME_IMPL(T, _) #T, |
42 | SUPPORTED_TENSOR_TYPES(TFUTILS_GETNAME_IMPL) |
43 | #undef TFUTILS_GETNAME_IMPL |
44 | }; |
45 | |
46 | StringRef toString(TensorType TT) { |
47 | return TensorTypeNames[static_cast<size_t>(TT)]; |
48 | } |
49 | |
50 | void TensorSpec::toJSON(json::OStream &OS) const { |
51 | OS.object(Contents: [&]() { |
52 | OS.attribute(Key: "name" , Contents: name()); |
53 | OS.attribute(Key: "type" , Contents: toString(TT: type())); |
54 | OS.attribute(Key: "port" , Contents: port()); |
55 | OS.attributeArray(Key: "shape" , Contents: [&]() { |
56 | for (size_t D : shape()) |
57 | OS.value(V: static_cast<int64_t>(D)); |
58 | }); |
59 | }); |
60 | } |
61 | |
62 | TensorSpec::TensorSpec(const std::string &Name, int Port, TensorType Type, |
63 | size_t ElementSize, const std::vector<int64_t> &Shape) |
64 | : Name(Name), Port(Port), Type(Type), Shape(Shape), |
65 | ElementCount(std::accumulate(first: Shape.begin(), last: Shape.end(), init: 1, |
66 | binary_op: std::multiplies<int64_t>())), |
67 | ElementSize(ElementSize) {} |
68 | |
69 | std::optional<TensorSpec> getTensorSpecFromJSON(LLVMContext &Ctx, |
70 | const json::Value &Value) { |
71 | auto EmitError = |
72 | [&](const llvm::Twine &Message) -> std::optional<TensorSpec> { |
73 | std::string S; |
74 | llvm::raw_string_ostream OS(S); |
75 | OS << Value; |
76 | Ctx.emitError(ErrorStr: "Unable to parse JSON Value as spec (" + Message + "): " + S); |
77 | return std::nullopt; |
78 | }; |
79 | // FIXME: accept a Path as a parameter, and use it for error reporting. |
80 | json::Path::Root Root("tensor_spec" ); |
81 | json::ObjectMapper Mapper(Value, Root); |
82 | if (!Mapper) |
83 | return EmitError("Value is not a dict" ); |
84 | |
85 | std::string TensorName; |
86 | int TensorPort = -1; |
87 | std::string TensorType; |
88 | std::vector<int64_t> TensorShape; |
89 | |
90 | if (!Mapper.map<std::string>(Prop: "name" , Out&: TensorName)) |
91 | return EmitError("'name' property not present or not a string" ); |
92 | if (!Mapper.map<std::string>(Prop: "type" , Out&: TensorType)) |
93 | return EmitError("'type' property not present or not a string" ); |
94 | if (!Mapper.map<int>(Prop: "port" , Out&: TensorPort)) |
95 | return EmitError("'port' property not present or not an int" ); |
96 | if (!Mapper.map<std::vector<int64_t>>(Prop: "shape" , Out&: TensorShape)) |
97 | return EmitError("'shape' property not present or not an int array" ); |
98 | |
99 | #define PARSE_TYPE(T, E) \ |
100 | if (TensorType == #T) \ |
101 | return TensorSpec::createSpec<T>(TensorName, TensorShape, TensorPort); |
102 | SUPPORTED_TENSOR_TYPES(PARSE_TYPE) |
103 | #undef PARSE_TYPE |
104 | return std::nullopt; |
105 | } |
106 | |
107 | std::string tensorValueToString(const char *Buffer, const TensorSpec &Spec) { |
108 | switch (Spec.type()) { |
109 | #define _IMR_DBG_PRINTER(T, N) \ |
110 | case TensorType::N: { \ |
111 | const T *TypedBuff = reinterpret_cast<const T *>(Buffer); \ |
112 | auto R = llvm::make_range(TypedBuff, TypedBuff + Spec.getElementCount()); \ |
113 | return llvm::join( \ |
114 | llvm::map_range(R, [](T V) { return std::to_string(V); }), ","); \ |
115 | } |
116 | SUPPORTED_TENSOR_TYPES(_IMR_DBG_PRINTER) |
117 | #undef _IMR_DBG_PRINTER |
118 | case TensorType::Total: |
119 | case TensorType::Invalid: |
120 | llvm_unreachable("invalid tensor type" ); |
121 | } |
122 | // To appease warnings about not all control paths returning a value. |
123 | return "" ; |
124 | } |
125 | |
126 | } // namespace llvm |
127 | |