Support MLIR (first e2e)

[tucan9389]

#1044

Please correct the table if there is wrong

mlir.js	MLIR concept	Note
mlir.Graph	Region or Function	Graph or Model
mlir.Parameter	Value (Operation's Operand or Result)	Edge
mlir.Argument	Value (Operation's Operand or Result)	Edge
mlir.Node	Operation	Node
mlir.Attributes	Operation's Attribute	Node's metadata
mlir.Tensor	Constant Operation	Kind of node
mlir.TensorType		Edge's metadata
mlir.TensorShape		Edge's metadata

[lutzroeder]

@tucan9389 let's review and merge this once the scenario works E2E.

[tucan9389]

@lutzroeder cc. @chococigar

Thanks for waiting. I made the first e2e code. Please review and find some missing parts.

stablehlo_sample.mlir	issue_1043.mlir

How it work

1. Parsing the .mlir text file with the existing decoder and mlir.Tokenizer and get the parsed js object(ex1, ex2)
2. With the parsed object, create the mlir.Model (inside of mlir.Model, the constructor makes mlir.Gragh, mlir.Node, mlir.Parameter, mlir.Attribute, etc.)

Note

• Since the MLIR syntax is super flexible, we should consider and parse it well. Please note that there are a lot of dialects and rules for those.
• Here is the MLIR structure: https://mlir.llvm.org/docs/Tutorials/UnderstandingTheIRStructure/
• Here is the MLIR syntax: https://mlir.llvm.org/docs/LangRef/
• I couldn't support all the syntax of MLIR in this PR... but this PR can be the starting point to support MLIR

Done

• Implement the initial version of mlir.Parser and mlir.Tokenizer
• Can parse the module, function, operation, attribute(arg, function, operation) of MLIR
• Can parse the tensor<...> type into mlir.TensorType
• Implement the constructors(mlir.Graph, mlir.Node, mlir.TensorType, mlir.TensorShape, etc.) for View level
• Type parsing: I'm not sure this will work with primitive types, like float32, int8
• Support module as optional: currently, the .mlir file should have the module { ... }

TODO

• Cannot parse the basic block(^bb). Tokenizer will just skip it.
• There are a lot of constant expressions in MLIR, so we need to think about it more.

Detail cases of constant expression dialect by dialect

// syntax group 1: the case containing the value in the constant operation itself
// Standard Dialect (std)
%std_const_i32 = constant 42 : i32
%std_const_f32 = constant 3.14 : f32
%std_const_vec = constant dense<[1, 2, 3, 4]> : vector<4xi32>

// Affine Dialect (affine)
%affine_const_i32 = affine.constant 42 : i32
%affine_const_i64 = affine.constant 42 : i64

// SPIR-V Dialect (spirv)
%spirv_const_i32 = spirv.constant 42 : i32
%spirv_const_f32 = spirv.constant 3.14 : f32

// GPU Dialect (gpu)
%gpu_const_i32 = gpu.constant 42 : i32
%gpu_const_f32 = gpu.constant 3.14 : f32

// syntax group 2: the case specifying the value by attribute
// TensorFlow Dialect (tf)
%tf_const_i32 = "tf.Const"() {value = dense<42> : tensor<i32>} : () -> tensor<i32>
%tf_const_f32 = "tf.Const"() {value = dense<3.14> : tensor<f32>} : () -> tensor<f32>
%tf_const_vec = "tf.Const"() {value = dense<[1, 2, 3, 4]> : tensor<4xi32>} : () -> tensor<4xi32>

// TOSA Dialect (tosa)
%tosa_const_f32 = "tosa.const"() {value = dense<3.14> : tensor<f32>} : () -> tensor<f32>
%tosa_const_vec = "tosa.const"() {value = dense<[1, 2, 3, 4]> : tensor<4xi32>} : () -> tensor<4xi32>

// ONNX Dialect (onnx)
%onnx_const_i32 = "onnx.Constant"() {value = dense<42> : tensor<i32>} : () -> tensor<i32>
%onnx_const_vec = "onnx.Constant"() {value = dense<[1, 2, 3, 4]> : tensor<4xi32>} : () -> tensor<4xi32>

// XLA HLO Dialect (mhlo)
%mhlo_const_i32 = "mhlo.const"() {value = dense<42> : tensor<i32>} : () -> tensor<i32>
%mhlo_const_f32 = "mhlo.const"() {value = dense<3.14> : tensor<f32>} : () -> tensor<f32>
%mhlo_const_vec = "mhlo.const"() {value = dense<[1, 2, 3, 4]> : tensor<4xi32>} : () -> tensor<4xi32>

// syntax group 3: the case specifying with function call format
%llvm_const_i32 = llvm.mlir.constant(42 : i32) : i32
%llvm_const_f32 = llvm.mlir.constant(3.14 : f32) : f32
%llvm_const_vec = llvm.mlir.constant(dense<[1, 2, 3, 4]> : vector<4xi32>) : !llvm<"<4 x i32>">

• Parse the value of attribute: currently, the attribute's value is all parsed string. We can parse it correctly.

Please comment if you have any questions or feedback.
Thanks.