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| namespace | mlir |
| | Include the generated interface declarations.
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| namespace | mlir::impl |
| | Attribute collections provide a dictionary-like interface.
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◆ CONV_OP_SPECIALIZER
| #define CONV_OP_SPECIALIZER |
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| ConvOpTy | ) |
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Value:
return specializeToConvOp<ConvOpTy>(rewriter, genericOp, dilations, \
strides); \
bool isaConvolutionOpOfType(LinalgOp op, SmallVector< int64_t > *dilations, SmallVector< int64_t > *strides)
Given a linalg op this function returns true if it is a convolution op of type ConvOpTy and populates...
◆ DEBUG_TYPE
| #define DEBUG_TYPE "linalg-specialization" |
◆ GEN_PASS_DEF_LINALGSPECIALIZEGENERICOPSPASS
| #define GEN_PASS_DEF_LINALGSPECIALIZEGENERICOPSPASS |
◆ REPLACE_BINARY_OP
| #define REPLACE_BINARY_OP |
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| NEWOP, |
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| OPERANDS_SWAP ) |
Value: (rewriter.replaceOpWithNewOp<NEWOP>( \
genericOp, \
ValueRange{genericOp.getDpsInputs()[(OPERANDS_SWAP) ? 1 : 0], \
genericOp.getDpsInputs()[(OPERANDS_SWAP) ? 0 : 1]}, \
This class provides an abstraction over the different types of ranges over Values.
Definition at line 30 of file Specialize.cpp.
Referenced by mlir::linalg::specializeGenericOp().
◆ REPLACE_UNARY_OP
| #define REPLACE_UNARY_OP |
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| NEWOP | ) |
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◆ areBinOpsSwapped()
| bool areBinOpsSwapped |
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GenericOp | genericOp | ) |
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static |