The previous approach is too restrictive; we end up forbidding all dialect-specific
types as element types. Changed to not consider element types entirely.
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PiperOrigin-RevId: 247486537
This CL adds support for functions in the Linalg dialect to run with mlir-cpu-runner.
For this purpose, this CL adds BufferAllocOp, BufferDeallocOp, LoadOp and StoreOp to the Linalg dialect as well as their lowering to LLVM. To avoid collisions with mlir::LoadOp/StoreOp (which should really become mlir::affine::LoadOp/StoreOp), the mlir::linalg namespace is added.
The execution uses a dummy linalg_dot function that just returns for now. In the future a proper library call will be used.
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PiperOrigin-RevId: 247476061
Historically, the conversion from standard and built-in types to the LLVM IR
dialect types was performed by a dedicated class, TypeConverter. This class
served to contain references to the LLVM IR dialect and to the LLVM IR Module
to allow querying the data layout. Recently, the LLVMLowering class was
introduced to make the conversion to the LLVM IR dialect extensible to other
source dialects. This class also includes the references to the LLVM IR
dialect and module. TypeConverter was extended with basic support for
dialect-specific type conversion through callbacks. This is not sufficient in
cases where dialect-specific types appear inside other types, such as function
or container types.
Integrate TypeConverter into LLVMLowering. Whenever a subtype needs to be
converted during standard type conversion (e.g. an argument or a result of a
FunctionType), the conversion will call to the virtual function
`LLVMLowering::convertType`, which can be extended to support dialect-specific
types.
Provide a new LLVMOpConversion class that serves as a base class for all
conversions to the LLVM IR dialect and gives them access to LLVMLowering for
the purpose of type conversion. Update Linalg to LLVM IR lowering to use this
class.
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PiperOrigin-RevId: 247407314
The string was referenced but not captured in the lambda, which causes
a failure when compiling with MSVC.
This issue was discovered by @loic-joly-sonarsource with a proposed fix
in https://github.com/tensorflow/mlir/pull/22.
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PiperOrigin-RevId: 247085897
This closely mirrors the llvm fcmp instruction, defining 16 different predicates
Constant folding is unsupported for NaN and Inf because there's no way to represent those as constants at the moment
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PiperOrigin-RevId: 246932358
`#` alias `=` attribute-value
This also allows for dialects to define aliases for attributes in the AsmPrinter. The printer supports two types of attribute aliases, 'direct' and 'kind'.
* Direct aliases are synonymous with the current support for type aliases, i.e. this maps an alias to a specific instance of an attribute.
// A direct alias ("foo_str") for the string attribute "foo".
#foo_str = "foo"
* Kind aliases generates unique names for all instances of a given attribute kind. The generated aliases are of the form: `alias[0-9]+`.
// A kind alias ("strattr") for all string attributes could generate.
#strattr0 = "foo"
#strattr1 = "bar"
...
#strattrN = "baz"
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PiperOrigin-RevId: 246851916
The idea is to lower `gpu.launch` operations into `gpu.launch_func` operations by outlining the kernel body into a function, which is closer to the NVVM model.
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PiperOrigin-RevId: 246806890
This syntax removes boilerplate and verbose list of region arguments in the
header of the entry block. It groups operands into segments related to GPU
blocks, GPU threads as well as the operands that are forwarded to the kernel.
The two former segments are also used to give names to the region arguments
that are used for GPU blocks and threads inside the kernel body region.
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PiperOrigin-RevId: 246792329
The generic form of operations currently supports optional regions to be
located after the operation type. As we are going to add a type to each
region in a leading position in the region syntax, similarly to functions, it
becomes ambiguous to have regions immediately after the operation type. Put
regions between operands the optional list of successors in the generic
operation syntax and wrap them in parentheses. The effect on the exisitng IR
syntax is minimal since only three operations (`affine.for`, `affine.if` and
`gpu.kernel`) currently use regions.
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PiperOrigin-RevId: 246787087
Region is the generalization of a function body (a list of blocks forming a CFG) to be allowed to be enclosed inside any operation. This nesting of IR is already leveraged in the affine dialect to support `affine.for`, `affine.if`, and `gpu.launch` operations.
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PiperOrigin-RevId: 246766830
This trait only works for tensor and vector types at the moment, verifying that the element type of an op with only tensor and vector types match. Added a unit test for it as there is no op currently in core that uses this trait.
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PiperOrigin-RevId: 246661697
Thomas Joerg