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llvm-project/mlir/test/Conversion/AffineToStandard/lower-affine.mlir

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Merge LowerAffineApplyPass into LowerIfAndForPass, rename to LowerAffinePass This change is mechanical and merges the LowerAffineApplyPass and LowerIfAndForPass into a single LowerAffinePass. It makes a step towards defining an "affine dialect" that would contain all polyhedral-related constructs. The motivation for merging these two passes is based on retiring MLFunctions and, eventually, transforming If and For statements into regular operations. After that happens, LowerAffinePass becomes yet another legalization. PiperOrigin-RevId: 227566113
2019-01-03 04:52:41 +08:00
// RUN: mlir-opt -lower-affine %s | FileCheck %s
Scaffolding for convertToCFG pass that replaces all instances of ML functions with equivalent CFG functions. Traverses module MLIR, generates CFG functions (empty for now) and removes ML functions. Adds Transforms library and tests. PiperOrigin-RevId: 205848367
2018-07-25 01:15:13 +08:00
Eliminate extfunc/cfgfunc/mlfunc as a concept, and just use 'func' instead. The entire compiler now looks at structural properties of the function (e.g. does it have one block, does it contain an if/for stmt, etc) so the only thing holding up this difference is round tripping through the parser/printer syntax. Removing this shrinks the compile by ~140LOC. This is step 31/n towards merging instructions and statements. The last step is updating the docs, which I will do as a separate patch in order to split it from this mostly mechanical patch. PiperOrigin-RevId: 227540453
2019-01-03 02:20:00 +08:00
// CHECK-LABEL: func @empty() {
func @empty() {
Scaffolding for convertToCFG pass that replaces all instances of ML functions with equivalent CFG functions. Traverses module MLIR, generates CFG functions (empty for now) and removes ML functions. Adds Transforms library and tests. PiperOrigin-RevId: 205848367
2018-07-25 01:15:13 +08:00
return // CHECK: return
} // CHECK: }
Basic conversion of MLFunctions to CFGFunctions. Implement a pass converting a subset of MLFunctions to CFGFunctions. Currently supports arbitrarily complex imperfect loop nests with statically constant (i.e., not affine map) bounds filled with operations. Does NOT support branches and non-constant loop bounds. Conversion is performed per-function and the function names are preserved to avoid breaking any external references to the current module. In-memory IR is updated to point to the right functions in direct calls and constant loads. This behavior is tested via a really hidden flag that enables function renaming. Inside each function, the control flow conversion is based on single-entry single-exit regions, i.e. subgraphs of the CFG that have exactly one incoming and exactly one outgoing edge. Since an MLFunction must have a single "return" statement as per MLIR spec, it constitutes an SESE region. Individual operations are appended to this region. Control flow statements are recursively converted into such regions that are concatenated with the current region. Bodies of the compound statement also form SESE regions, which allows to nest control flow statements easily. Note that SESE regions are not materialized in the code. It is sufficent to keep track of the end of the region as the current instruction insertion point as long as all recursive calls update the insertion point in the end. The converter maintains a mapping between SSA values in ML functions and their CFG counterparts. The mapping is used to find the operands for each operation and is updated to contain the results of each operation as the conversion continues. PiperOrigin-RevId: 221162602
2018-11-13 06:58:36 +08:00
[MLIR] Extend Symbol verification to reject public symbol declarations. - Extend the Symbol interface with `isDeclaration` to identify operations that declare a symbol as opposed to define it. - Extend verification to disallow public declarations as per the discussion in https://llvm.discourse.group/t/rfc-symbol-definition-declaration-x-visibility-checks/2140 - Adopt the new interface for `FuncOp` and fix test and code to not have/create public function declarations. Differential Revision: https://reviews.llvm.org/D91456
2020-11-14 05:04:53 +08:00
func private @body(index) -> ()
Basic conversion of MLFunctions to CFGFunctions. Implement a pass converting a subset of MLFunctions to CFGFunctions. Currently supports arbitrarily complex imperfect loop nests with statically constant (i.e., not affine map) bounds filled with operations. Does NOT support branches and non-constant loop bounds. Conversion is performed per-function and the function names are preserved to avoid breaking any external references to the current module. In-memory IR is updated to point to the right functions in direct calls and constant loads. This behavior is tested via a really hidden flag that enables function renaming. Inside each function, the control flow conversion is based on single-entry single-exit regions, i.e. subgraphs of the CFG that have exactly one incoming and exactly one outgoing edge. Since an MLFunction must have a single "return" statement as per MLIR spec, it constitutes an SESE region. Individual operations are appended to this region. Control flow statements are recursively converted into such regions that are concatenated with the current region. Bodies of the compound statement also form SESE regions, which allows to nest control flow statements easily. Note that SESE regions are not materialized in the code. It is sufficent to keep track of the end of the region as the current instruction insertion point as long as all recursive calls update the insertion point in the end. The converter maintains a mapping between SSA values in ML functions and their CFG counterparts. The mapping is used to find the operands for each operation and is updated to contain the results of each operation as the conversion continues. PiperOrigin-RevId: 221162602
2018-11-13 06:58:36 +08:00
// Simple loops are properly converted.
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-LABEL: func @simple_loop
// CHECK-NEXT: %[[c1:.*]] = constant 1 : index
// CHECK-NEXT: %[[c42:.*]] = constant 42 : index
// CHECK-NEXT: %[[c1_0:.*]] = constant 1 : index
// CHECK-NEXT: for %{{.*}} = %[[c1]] to %[[c42]] step %[[c1_0]] {
// CHECK-NEXT: call @body(%{{.*}}) : (index) -> ()
// CHECK-NEXT: }
Basic conversion of MLFunctions to CFGFunctions. Implement a pass converting a subset of MLFunctions to CFGFunctions. Currently supports arbitrarily complex imperfect loop nests with statically constant (i.e., not affine map) bounds filled with operations. Does NOT support branches and non-constant loop bounds. Conversion is performed per-function and the function names are preserved to avoid breaking any external references to the current module. In-memory IR is updated to point to the right functions in direct calls and constant loads. This behavior is tested via a really hidden flag that enables function renaming. Inside each function, the control flow conversion is based on single-entry single-exit regions, i.e. subgraphs of the CFG that have exactly one incoming and exactly one outgoing edge. Since an MLFunction must have a single "return" statement as per MLIR spec, it constitutes an SESE region. Individual operations are appended to this region. Control flow statements are recursively converted into such regions that are concatenated with the current region. Bodies of the compound statement also form SESE regions, which allows to nest control flow statements easily. Note that SESE regions are not materialized in the code. It is sufficent to keep track of the end of the region as the current instruction insertion point as long as all recursive calls update the insertion point in the end. The converter maintains a mapping between SSA values in ML functions and their CFG counterparts. The mapping is used to find the operands for each operation and is updated to contain the results of each operation as the conversion continues. PiperOrigin-RevId: 221162602
2018-11-13 06:58:36 +08:00
// CHECK-NEXT: return
// CHECK-NEXT: }
Eliminate extfunc/cfgfunc/mlfunc as a concept, and just use 'func' instead. The entire compiler now looks at structural properties of the function (e.g. does it have one block, does it contain an if/for stmt, etc) so the only thing holding up this difference is round tripping through the parser/printer syntax. Removing this shrinks the compile by ~140LOC. This is step 31/n towards merging instructions and statements. The last step is updating the docs, which I will do as a separate patch in order to split it from this mostly mechanical patch. PiperOrigin-RevId: 227540453
2019-01-03 02:20:00 +08:00
func @simple_loop() {
NFC: Rename the 'for' operation in the AffineOps dialect to 'affine.for' and set the namespace of the AffineOps dialect to 'affine'. PiperOrigin-RevId: 240165792
2019-03-26 01:14:34 +08:00
affine.for %i = 1 to 42 {
Basic conversion of MLFunctions to CFGFunctions. Implement a pass converting a subset of MLFunctions to CFGFunctions. Currently supports arbitrarily complex imperfect loop nests with statically constant (i.e., not affine map) bounds filled with operations. Does NOT support branches and non-constant loop bounds. Conversion is performed per-function and the function names are preserved to avoid breaking any external references to the current module. In-memory IR is updated to point to the right functions in direct calls and constant loads. This behavior is tested via a really hidden flag that enables function renaming. Inside each function, the control flow conversion is based on single-entry single-exit regions, i.e. subgraphs of the CFG that have exactly one incoming and exactly one outgoing edge. Since an MLFunction must have a single "return" statement as per MLIR spec, it constitutes an SESE region. Individual operations are appended to this region. Control flow statements are recursively converted into such regions that are concatenated with the current region. Bodies of the compound statement also form SESE regions, which allows to nest control flow statements easily. Note that SESE regions are not materialized in the code. It is sufficent to keep track of the end of the region as the current instruction insertion point as long as all recursive calls update the insertion point in the end. The converter maintains a mapping between SSA values in ML functions and their CFG counterparts. The mapping is used to find the operands for each operation and is updated to contain the results of each operation as the conversion continues. PiperOrigin-RevId: 221162602
2018-11-13 06:58:36 +08:00
call @body(%i) : (index) -> ()
}
return
}
/////////////////////////////////////////////////////////////////////
[MLIR] Fix lowering of affine operations with return values This commit addresses the issue of lowering affine.for and affine.parallel having return values. Relevant test cases are also added. Signed-off-by: Prateek Gupta <prateek@polymagelabs.com> Differential Revision: https://reviews.llvm.org/D93090
2020-12-23 00:10:17 +08:00
func @for_with_yield(%buffer: memref<1024xf32>) -> (f32) {
%sum_0 = constant 0.0 : f32
%sum = affine.for %i = 0 to 10 step 2 iter_args(%sum_iter = %sum_0) -> (f32) {
%t = affine.load %buffer[%i] : memref<1024xf32>
%sum_next = addf %sum_iter, %t : f32
affine.yield %sum_next : f32
}
return %sum : f32
}
// CHECK-LABEL: func @for_with_yield
// CHECK: %[[INIT_SUM:.*]] = constant 0.000000e+00 : f32
// CHECK-NEXT: %[[LOWER:.*]] = constant 0 : index
// CHECK-NEXT: %[[UPPER:.*]] = constant 10 : index
// CHECK-NEXT: %[[STEP:.*]] = constant 2 : index
// CHECK-NEXT: %[[SUM:.*]] = scf.for %[[IV:.*]] = %[[LOWER]] to %[[UPPER]] step %[[STEP]] iter_args(%[[SUM_ITER:.*]] = %[[INIT_SUM]]) -> (f32) {
// CHECK-NEXT: load
// CHECK-NEXT: %[[SUM_NEXT:.*]] = addf
// CHECK-NEXT: scf.yield %[[SUM_NEXT]] : f32
// CHECK-NEXT: }
// CHECK-NEXT: return %[[SUM]] : f32
/////////////////////////////////////////////////////////////////////
[MLIR] Extend Symbol verification to reject public symbol declarations. - Extend the Symbol interface with `isDeclaration` to identify operations that declare a symbol as opposed to define it. - Extend verification to disallow public declarations as per the discussion in https://llvm.discourse.group/t/rfc-symbol-definition-declaration-x-visibility-checks/2140 - Adopt the new interface for `FuncOp` and fix test and code to not have/create public function declarations. Differential Revision: https://reviews.llvm.org/D91456
2020-11-14 05:04:53 +08:00
func private @pre(index) -> ()
func private @body2(index, index) -> ()
func private @post(index) -> ()
Basic conversion of MLFunctions to CFGFunctions. Implement a pass converting a subset of MLFunctions to CFGFunctions. Currently supports arbitrarily complex imperfect loop nests with statically constant (i.e., not affine map) bounds filled with operations. Does NOT support branches and non-constant loop bounds. Conversion is performed per-function and the function names are preserved to avoid breaking any external references to the current module. In-memory IR is updated to point to the right functions in direct calls and constant loads. This behavior is tested via a really hidden flag that enables function renaming. Inside each function, the control flow conversion is based on single-entry single-exit regions, i.e. subgraphs of the CFG that have exactly one incoming and exactly one outgoing edge. Since an MLFunction must have a single "return" statement as per MLIR spec, it constitutes an SESE region. Individual operations are appended to this region. Control flow statements are recursively converted into such regions that are concatenated with the current region. Bodies of the compound statement also form SESE regions, which allows to nest control flow statements easily. Note that SESE regions are not materialized in the code. It is sufficent to keep track of the end of the region as the current instruction insertion point as long as all recursive calls update the insertion point in the end. The converter maintains a mapping between SSA values in ML functions and their CFG counterparts. The mapping is used to find the operands for each operation and is updated to contain the results of each operation as the conversion continues. PiperOrigin-RevId: 221162602
2018-11-13 06:58:36 +08:00
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-LABEL: func @imperfectly_nested_loops
// CHECK-NEXT: %[[c0:.*]] = constant 0 : index
// CHECK-NEXT: %[[c42:.*]] = constant 42 : index
// CHECK-NEXT: %[[c1:.*]] = constant 1 : index
// CHECK-NEXT: for %{{.*}} = %[[c0]] to %[[c42]] step %[[c1]] {
// CHECK-NEXT: call @pre(%{{.*}}) : (index) -> ()
// CHECK-NEXT: %[[c7:.*]] = constant 7 : index
// CHECK-NEXT: %[[c56:.*]] = constant 56 : index
// CHECK-NEXT: %[[c2:.*]] = constant 2 : index
// CHECK-NEXT: for %{{.*}} = %[[c7]] to %[[c56]] step %[[c2]] {
// CHECK-NEXT: call @body2(%{{.*}}, %{{.*}}) : (index, index) -> ()
// CHECK-NEXT: }
// CHECK-NEXT: call @post(%{{.*}}) : (index) -> ()
// CHECK-NEXT: }
Basic conversion of MLFunctions to CFGFunctions. Implement a pass converting a subset of MLFunctions to CFGFunctions. Currently supports arbitrarily complex imperfect loop nests with statically constant (i.e., not affine map) bounds filled with operations. Does NOT support branches and non-constant loop bounds. Conversion is performed per-function and the function names are preserved to avoid breaking any external references to the current module. In-memory IR is updated to point to the right functions in direct calls and constant loads. This behavior is tested via a really hidden flag that enables function renaming. Inside each function, the control flow conversion is based on single-entry single-exit regions, i.e. subgraphs of the CFG that have exactly one incoming and exactly one outgoing edge. Since an MLFunction must have a single "return" statement as per MLIR spec, it constitutes an SESE region. Individual operations are appended to this region. Control flow statements are recursively converted into such regions that are concatenated with the current region. Bodies of the compound statement also form SESE regions, which allows to nest control flow statements easily. Note that SESE regions are not materialized in the code. It is sufficent to keep track of the end of the region as the current instruction insertion point as long as all recursive calls update the insertion point in the end. The converter maintains a mapping between SSA values in ML functions and their CFG counterparts. The mapping is used to find the operands for each operation and is updated to contain the results of each operation as the conversion continues. PiperOrigin-RevId: 221162602
2018-11-13 06:58:36 +08:00
// CHECK-NEXT: return
// CHECK-NEXT: }
Eliminate extfunc/cfgfunc/mlfunc as a concept, and just use 'func' instead. The entire compiler now looks at structural properties of the function (e.g. does it have one block, does it contain an if/for stmt, etc) so the only thing holding up this difference is round tripping through the parser/printer syntax. Removing this shrinks the compile by ~140LOC. This is step 31/n towards merging instructions and statements. The last step is updating the docs, which I will do as a separate patch in order to split it from this mostly mechanical patch. PiperOrigin-RevId: 227540453
2019-01-03 02:20:00 +08:00
func @imperfectly_nested_loops() {
NFC: Rename the 'for' operation in the AffineOps dialect to 'affine.for' and set the namespace of the AffineOps dialect to 'affine'. PiperOrigin-RevId: 240165792
2019-03-26 01:14:34 +08:00
affine.for %i = 0 to 42 {
Basic conversion of MLFunctions to CFGFunctions. Implement a pass converting a subset of MLFunctions to CFGFunctions. Currently supports arbitrarily complex imperfect loop nests with statically constant (i.e., not affine map) bounds filled with operations. Does NOT support branches and non-constant loop bounds. Conversion is performed per-function and the function names are preserved to avoid breaking any external references to the current module. In-memory IR is updated to point to the right functions in direct calls and constant loads. This behavior is tested via a really hidden flag that enables function renaming. Inside each function, the control flow conversion is based on single-entry single-exit regions, i.e. subgraphs of the CFG that have exactly one incoming and exactly one outgoing edge. Since an MLFunction must have a single "return" statement as per MLIR spec, it constitutes an SESE region. Individual operations are appended to this region. Control flow statements are recursively converted into such regions that are concatenated with the current region. Bodies of the compound statement also form SESE regions, which allows to nest control flow statements easily. Note that SESE regions are not materialized in the code. It is sufficent to keep track of the end of the region as the current instruction insertion point as long as all recursive calls update the insertion point in the end. The converter maintains a mapping between SSA values in ML functions and their CFG counterparts. The mapping is used to find the operands for each operation and is updated to contain the results of each operation as the conversion continues. PiperOrigin-RevId: 221162602
2018-11-13 06:58:36 +08:00
call @pre(%i) : (index) -> ()
NFC: Rename the 'for' operation in the AffineOps dialect to 'affine.for' and set the namespace of the AffineOps dialect to 'affine'. PiperOrigin-RevId: 240165792
2019-03-26 01:14:34 +08:00
affine.for %j = 7 to 56 step 2 {
Basic conversion of MLFunctions to CFGFunctions. Implement a pass converting a subset of MLFunctions to CFGFunctions. Currently supports arbitrarily complex imperfect loop nests with statically constant (i.e., not affine map) bounds filled with operations. Does NOT support branches and non-constant loop bounds. Conversion is performed per-function and the function names are preserved to avoid breaking any external references to the current module. In-memory IR is updated to point to the right functions in direct calls and constant loads. This behavior is tested via a really hidden flag that enables function renaming. Inside each function, the control flow conversion is based on single-entry single-exit regions, i.e. subgraphs of the CFG that have exactly one incoming and exactly one outgoing edge. Since an MLFunction must have a single "return" statement as per MLIR spec, it constitutes an SESE region. Individual operations are appended to this region. Control flow statements are recursively converted into such regions that are concatenated with the current region. Bodies of the compound statement also form SESE regions, which allows to nest control flow statements easily. Note that SESE regions are not materialized in the code. It is sufficent to keep track of the end of the region as the current instruction insertion point as long as all recursive calls update the insertion point in the end. The converter maintains a mapping between SSA values in ML functions and their CFG counterparts. The mapping is used to find the operands for each operation and is updated to contain the results of each operation as the conversion continues. PiperOrigin-RevId: 221162602
2018-11-13 06:58:36 +08:00
call @body2(%i, %j) : (index, index) -> ()
}
call @post(%i) : (index) -> ()
}
return
}
/////////////////////////////////////////////////////////////////////
[MLIR] Extend Symbol verification to reject public symbol declarations. - Extend the Symbol interface with `isDeclaration` to identify operations that declare a symbol as opposed to define it. - Extend verification to disallow public declarations as per the discussion in https://llvm.discourse.group/t/rfc-symbol-definition-declaration-x-visibility-checks/2140 - Adopt the new interface for `FuncOp` and fix test and code to not have/create public function declarations. Differential Revision: https://reviews.llvm.org/D91456
2020-11-14 05:04:53 +08:00
func private @mid(index) -> ()
func private @body3(index, index) -> ()
Basic conversion of MLFunctions to CFGFunctions. Implement a pass converting a subset of MLFunctions to CFGFunctions. Currently supports arbitrarily complex imperfect loop nests with statically constant (i.e., not affine map) bounds filled with operations. Does NOT support branches and non-constant loop bounds. Conversion is performed per-function and the function names are preserved to avoid breaking any external references to the current module. In-memory IR is updated to point to the right functions in direct calls and constant loads. This behavior is tested via a really hidden flag that enables function renaming. Inside each function, the control flow conversion is based on single-entry single-exit regions, i.e. subgraphs of the CFG that have exactly one incoming and exactly one outgoing edge. Since an MLFunction must have a single "return" statement as per MLIR spec, it constitutes an SESE region. Individual operations are appended to this region. Control flow statements are recursively converted into such regions that are concatenated with the current region. Bodies of the compound statement also form SESE regions, which allows to nest control flow statements easily. Note that SESE regions are not materialized in the code. It is sufficent to keep track of the end of the region as the current instruction insertion point as long as all recursive calls update the insertion point in the end. The converter maintains a mapping between SSA values in ML functions and their CFG counterparts. The mapping is used to find the operands for each operation and is updated to contain the results of each operation as the conversion continues. PiperOrigin-RevId: 221162602
2018-11-13 06:58:36 +08:00
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-LABEL: func @more_imperfectly_nested_loops
// CHECK-NEXT: %[[c0:.*]] = constant 0 : index
// CHECK-NEXT: %[[c42:.*]] = constant 42 : index
// CHECK-NEXT: %[[c1:.*]] = constant 1 : index
// CHECK-NEXT: for %{{.*}} = %[[c0]] to %[[c42]] step %[[c1]] {
// CHECK-NEXT: call @pre(%{{.*}}) : (index) -> ()
// CHECK-NEXT: %[[c7:.*]] = constant 7 : index
// CHECK-NEXT: %[[c56:.*]] = constant 56 : index
// CHECK-NEXT: %[[c2:.*]] = constant 2 : index
// CHECK-NEXT: for %{{.*}} = %[[c7]] to %[[c56]] step %[[c2]] {
// CHECK-NEXT: call @body2(%{{.*}}, %{{.*}}) : (index, index) -> ()
// CHECK-NEXT: }
// CHECK-NEXT: call @mid(%{{.*}}) : (index) -> ()
// CHECK-NEXT: %[[c18:.*]] = constant 18 : index
// CHECK-NEXT: %[[c37:.*]] = constant 37 : index
// CHECK-NEXT: %[[c3:.*]] = constant 3 : index
// CHECK-NEXT: for %{{.*}} = %[[c18]] to %[[c37]] step %[[c3]] {
// CHECK-NEXT: call @body3(%{{.*}}, %{{.*}}) : (index, index) -> ()
// CHECK-NEXT: }
// CHECK-NEXT: call @post(%{{.*}}) : (index) -> ()
// CHECK-NEXT: }
Basic conversion of MLFunctions to CFGFunctions. Implement a pass converting a subset of MLFunctions to CFGFunctions. Currently supports arbitrarily complex imperfect loop nests with statically constant (i.e., not affine map) bounds filled with operations. Does NOT support branches and non-constant loop bounds. Conversion is performed per-function and the function names are preserved to avoid breaking any external references to the current module. In-memory IR is updated to point to the right functions in direct calls and constant loads. This behavior is tested via a really hidden flag that enables function renaming. Inside each function, the control flow conversion is based on single-entry single-exit regions, i.e. subgraphs of the CFG that have exactly one incoming and exactly one outgoing edge. Since an MLFunction must have a single "return" statement as per MLIR spec, it constitutes an SESE region. Individual operations are appended to this region. Control flow statements are recursively converted into such regions that are concatenated with the current region. Bodies of the compound statement also form SESE regions, which allows to nest control flow statements easily. Note that SESE regions are not materialized in the code. It is sufficent to keep track of the end of the region as the current instruction insertion point as long as all recursive calls update the insertion point in the end. The converter maintains a mapping between SSA values in ML functions and their CFG counterparts. The mapping is used to find the operands for each operation and is updated to contain the results of each operation as the conversion continues. PiperOrigin-RevId: 221162602
2018-11-13 06:58:36 +08:00
// CHECK-NEXT: return
// CHECK-NEXT: }
Eliminate extfunc/cfgfunc/mlfunc as a concept, and just use 'func' instead. The entire compiler now looks at structural properties of the function (e.g. does it have one block, does it contain an if/for stmt, etc) so the only thing holding up this difference is round tripping through the parser/printer syntax. Removing this shrinks the compile by ~140LOC. This is step 31/n towards merging instructions and statements. The last step is updating the docs, which I will do as a separate patch in order to split it from this mostly mechanical patch. PiperOrigin-RevId: 227540453
2019-01-03 02:20:00 +08:00
func @more_imperfectly_nested_loops() {
NFC: Rename the 'for' operation in the AffineOps dialect to 'affine.for' and set the namespace of the AffineOps dialect to 'affine'. PiperOrigin-RevId: 240165792
2019-03-26 01:14:34 +08:00
affine.for %i = 0 to 42 {
Basic conversion of MLFunctions to CFGFunctions. Implement a pass converting a subset of MLFunctions to CFGFunctions. Currently supports arbitrarily complex imperfect loop nests with statically constant (i.e., not affine map) bounds filled with operations. Does NOT support branches and non-constant loop bounds. Conversion is performed per-function and the function names are preserved to avoid breaking any external references to the current module. In-memory IR is updated to point to the right functions in direct calls and constant loads. This behavior is tested via a really hidden flag that enables function renaming. Inside each function, the control flow conversion is based on single-entry single-exit regions, i.e. subgraphs of the CFG that have exactly one incoming and exactly one outgoing edge. Since an MLFunction must have a single "return" statement as per MLIR spec, it constitutes an SESE region. Individual operations are appended to this region. Control flow statements are recursively converted into such regions that are concatenated with the current region. Bodies of the compound statement also form SESE regions, which allows to nest control flow statements easily. Note that SESE regions are not materialized in the code. It is sufficent to keep track of the end of the region as the current instruction insertion point as long as all recursive calls update the insertion point in the end. The converter maintains a mapping between SSA values in ML functions and their CFG counterparts. The mapping is used to find the operands for each operation and is updated to contain the results of each operation as the conversion continues. PiperOrigin-RevId: 221162602
2018-11-13 06:58:36 +08:00
call @pre(%i) : (index) -> ()
NFC: Rename the 'for' operation in the AffineOps dialect to 'affine.for' and set the namespace of the AffineOps dialect to 'affine'. PiperOrigin-RevId: 240165792
2019-03-26 01:14:34 +08:00
affine.for %j = 7 to 56 step 2 {
Basic conversion of MLFunctions to CFGFunctions. Implement a pass converting a subset of MLFunctions to CFGFunctions. Currently supports arbitrarily complex imperfect loop nests with statically constant (i.e., not affine map) bounds filled with operations. Does NOT support branches and non-constant loop bounds. Conversion is performed per-function and the function names are preserved to avoid breaking any external references to the current module. In-memory IR is updated to point to the right functions in direct calls and constant loads. This behavior is tested via a really hidden flag that enables function renaming. Inside each function, the control flow conversion is based on single-entry single-exit regions, i.e. subgraphs of the CFG that have exactly one incoming and exactly one outgoing edge. Since an MLFunction must have a single "return" statement as per MLIR spec, it constitutes an SESE region. Individual operations are appended to this region. Control flow statements are recursively converted into such regions that are concatenated with the current region. Bodies of the compound statement also form SESE regions, which allows to nest control flow statements easily. Note that SESE regions are not materialized in the code. It is sufficent to keep track of the end of the region as the current instruction insertion point as long as all recursive calls update the insertion point in the end. The converter maintains a mapping between SSA values in ML functions and their CFG counterparts. The mapping is used to find the operands for each operation and is updated to contain the results of each operation as the conversion continues. PiperOrigin-RevId: 221162602
2018-11-13 06:58:36 +08:00
call @body2(%i, %j) : (index, index) -> ()
}
call @mid(%i) : (index) -> ()
NFC: Rename the 'for' operation in the AffineOps dialect to 'affine.for' and set the namespace of the AffineOps dialect to 'affine'. PiperOrigin-RevId: 240165792
2019-03-26 01:14:34 +08:00
affine.for %k = 18 to 37 step 3 {
Basic conversion of MLFunctions to CFGFunctions. Implement a pass converting a subset of MLFunctions to CFGFunctions. Currently supports arbitrarily complex imperfect loop nests with statically constant (i.e., not affine map) bounds filled with operations. Does NOT support branches and non-constant loop bounds. Conversion is performed per-function and the function names are preserved to avoid breaking any external references to the current module. In-memory IR is updated to point to the right functions in direct calls and constant loads. This behavior is tested via a really hidden flag that enables function renaming. Inside each function, the control flow conversion is based on single-entry single-exit regions, i.e. subgraphs of the CFG that have exactly one incoming and exactly one outgoing edge. Since an MLFunction must have a single "return" statement as per MLIR spec, it constitutes an SESE region. Individual operations are appended to this region. Control flow statements are recursively converted into such regions that are concatenated with the current region. Bodies of the compound statement also form SESE regions, which allows to nest control flow statements easily. Note that SESE regions are not materialized in the code. It is sufficent to keep track of the end of the region as the current instruction insertion point as long as all recursive calls update the insertion point in the end. The converter maintains a mapping between SSA values in ML functions and their CFG counterparts. The mapping is used to find the operands for each operation and is updated to contain the results of each operation as the conversion continues. PiperOrigin-RevId: 221162602
2018-11-13 06:58:36 +08:00
call @body3(%i, %k) : (index, index) -> ()
}
call @post(%i) : (index) -> ()
}
return
}
ConvertToCFG: handle loop 1D affine loop bounds. In the general case, loop bounds can be expressed as affine maps of the outer loop iterators and function arguments. Relax the check for loop bounds to be known integer constants and also accept one-dimensional affine bounds in ConvertToCFG ForStmt lowering. Emit affine_apply operations for both the upper and the lower bound. The semantics of MLFunctions guarantees that both bounds can be computed before the loop starts iterating. Constant bounds are merely a short-hand notation for zero-dimensional affine maps and get supported transparently. Multidimensional affine bounds are not yet supported because the target IR dialect lacks min/max operations necessary to implement the corresponding semantics. PiperOrigin-RevId: 222275801
2018-11-21 03:15:03 +08:00
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-LABEL: func @affine_apply_loops_shorthand
// CHECK-NEXT: %[[c0:.*]] = constant 0 : index
// CHECK-NEXT: %[[c1:.*]] = constant 1 : index
// CHECK-NEXT: for %{{.*}} = %[[c0]] to %{{.*}} step %[[c1]] {
// CHECK-NEXT: %[[c42:.*]] = constant 42 : index
// CHECK-NEXT: %[[c1_0:.*]] = constant 1 : index
// CHECK-NEXT: for %{{.*}} = %{{.*}} to %[[c42]] step %[[c1_0]] {
// CHECK-NEXT: call @body2(%{{.*}}, %{{.*}}) : (index, index) -> ()
// CHECK-NEXT: }
// CHECK-NEXT: }
LowerForAndIf: expand affine_apply's inplace Existing implementation was created before ML/CFG unification refactoring and did not concern itself with further lowering to separate concerns. As a result, it emitted `affine_apply` instructions to implement `for` loop bounds and `if` conditions and required a follow-up function pass to lower those `affine_apply` to arithmetic primitives. In the unified function world, LowerForAndIf is mostly a lowering pass with low complexity. As we move towards a dialect for affine operations (including `for` and `if`), it makes sense to lower `for` and `if` conditions directly to arithmetic primitives instead of relying on `affine_apply`. Expose `expandAffineExpr` function in LoweringUtils. Use this function together with `expandAffineMaps` to emit primitives that implement loop and branch conditions directly. Also remove tests that become unnecessary after transforming LowerForAndIf into a function pass. PiperOrigin-RevId: 227563608
2019-01-03 04:36:58 +08:00
// CHECK-NEXT: return
// CHECK-NEXT: }
Eliminate extfunc/cfgfunc/mlfunc as a concept, and just use 'func' instead. The entire compiler now looks at structural properties of the function (e.g. does it have one block, does it contain an if/for stmt, etc) so the only thing holding up this difference is round tripping through the parser/printer syntax. Removing this shrinks the compile by ~140LOC. This is step 31/n towards merging instructions and statements. The last step is updating the docs, which I will do as a separate patch in order to split it from this mostly mechanical patch. PiperOrigin-RevId: 227540453
2019-01-03 02:20:00 +08:00
func @affine_apply_loops_shorthand(%N : index) {
NFC: Rename the 'for' operation in the AffineOps dialect to 'affine.for' and set the namespace of the AffineOps dialect to 'affine'. PiperOrigin-RevId: 240165792
2019-03-26 01:14:34 +08:00
affine.for %i = 0 to %N {
[mlir] Change the syntax of AffineMapAttr and IntegerSetAttr to avoid conflicts with function types. Summary: The current syntax for AffineMapAttr and IntegerSetAttr conflict with function types, making it currently impossible to round-trip function types(and e.g. FuncOp) in the IR. This revision changes the syntax for the attributes by wrapping them in a keyword. AffineMapAttr is wrapped with `affine_map<>` and IntegerSetAttr is wrapped with `affine_set<>`. Reviewed By: nicolasvasilache, ftynse Differential Revision: https://reviews.llvm.org/D72429
2020-01-14 05:12:37 +08:00
affine.for %j = affine_map<(d0)[]->(d0)>(%i)[] to 42 {
ConvertToCFG: handle loop 1D affine loop bounds. In the general case, loop bounds can be expressed as affine maps of the outer loop iterators and function arguments. Relax the check for loop bounds to be known integer constants and also accept one-dimensional affine bounds in ConvertToCFG ForStmt lowering. Emit affine_apply operations for both the upper and the lower bound. The semantics of MLFunctions guarantees that both bounds can be computed before the loop starts iterating. Constant bounds are merely a short-hand notation for zero-dimensional affine maps and get supported transparently. Multidimensional affine bounds are not yet supported because the target IR dialect lacks min/max operations necessary to implement the corresponding semantics. PiperOrigin-RevId: 222275801
2018-11-21 03:15:03 +08:00
call @body2(%i, %j) : (index, index) -> ()
}
}
return
}
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
/////////////////////////////////////////////////////////////////////
[MLIR] Extend Symbol verification to reject public symbol declarations. - Extend the Symbol interface with `isDeclaration` to identify operations that declare a symbol as opposed to define it. - Extend verification to disallow public declarations as per the discussion in https://llvm.discourse.group/t/rfc-symbol-definition-declaration-x-visibility-checks/2140 - Adopt the new interface for `FuncOp` and fix test and code to not have/create public function declarations. Differential Revision: https://reviews.llvm.org/D91456
2020-11-14 05:04:53 +08:00
func private @get_idx() -> (index)
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
[mlir] Change the syntax of AffineMapAttr and IntegerSetAttr to avoid conflicts with function types. Summary: The current syntax for AffineMapAttr and IntegerSetAttr conflict with function types, making it currently impossible to round-trip function types(and e.g. FuncOp) in the IR. This revision changes the syntax for the attributes by wrapping them in a keyword. AffineMapAttr is wrapped with `affine_map<>` and IntegerSetAttr is wrapped with `affine_set<>`. Reviewed By: nicolasvasilache, ftynse Differential Revision: https://reviews.llvm.org/D72429
2020-01-14 05:12:37 +08:00
#set1 = affine_set<(d0) : (20 - d0 >= 0)>
#set2 = affine_set<(d0) : (d0 - 10 >= 0)>
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-LABEL: func @if_only
// CHECK-NEXT: %[[v0:.*]] = call @get_idx() : () -> index
// CHECK-NEXT: %[[c0:.*]] = constant 0 : index
// CHECK-NEXT: %[[cm1:.*]] = constant -1 : index
// CHECK-NEXT: %[[v1:.*]] = muli %[[v0]], %[[cm1]] : index
// CHECK-NEXT: %[[c20:.*]] = constant 20 : index
// CHECK-NEXT: %[[v2:.*]] = addi %[[v1]], %[[c20]] : index
// CHECK-NEXT: %[[v3:.*]] = cmpi "sge", %[[v2]], %[[c0]] : index
// CHECK-NEXT: if %[[v3]] {
// CHECK-NEXT: call @body(%[[v0:.*]]) : (index) -> ()
// CHECK-NEXT: }
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
// CHECK-NEXT: return
// CHECK-NEXT: }
Eliminate extfunc/cfgfunc/mlfunc as a concept, and just use 'func' instead. The entire compiler now looks at structural properties of the function (e.g. does it have one block, does it contain an if/for stmt, etc) so the only thing holding up this difference is round tripping through the parser/printer syntax. Removing this shrinks the compile by ~140LOC. This is step 31/n towards merging instructions and statements. The last step is updating the docs, which I will do as a separate patch in order to split it from this mostly mechanical patch. PiperOrigin-RevId: 227540453
2019-01-03 02:20:00 +08:00
func @if_only() {
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
%i = call @get_idx() : () -> (index)
NFC: Rename the 'if' operation in the AffineOps dialect to 'affine.if'. PiperOrigin-RevId: 240071154
2019-03-25 11:35:07 +08:00
affine.if #set1(%i) {
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
call @body(%i) : (index) -> ()
}
return
}
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-LABEL: func @if_else
// CHECK-NEXT: %[[v0:.*]] = call @get_idx() : () -> index
// CHECK-NEXT: %[[c0:.*]] = constant 0 : index
// CHECK-NEXT: %[[cm1:.*]] = constant -1 : index
// CHECK-NEXT: %[[v1:.*]] = muli %[[v0]], %[[cm1]] : index
// CHECK-NEXT: %[[c20:.*]] = constant 20 : index
// CHECK-NEXT: %[[v2:.*]] = addi %[[v1]], %[[c20]] : index
// CHECK-NEXT: %[[v3:.*]] = cmpi "sge", %[[v2]], %[[c0]] : index
// CHECK-NEXT: if %[[v3]] {
// CHECK-NEXT: call @body(%[[v0:.*]]) : (index) -> ()
// CHECK-NEXT: } else {
// CHECK-NEXT: call @mid(%[[v0:.*]]) : (index) -> ()
// CHECK-NEXT: }
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
// CHECK-NEXT: return
// CHECK-NEXT: }
Eliminate extfunc/cfgfunc/mlfunc as a concept, and just use 'func' instead. The entire compiler now looks at structural properties of the function (e.g. does it have one block, does it contain an if/for stmt, etc) so the only thing holding up this difference is round tripping through the parser/printer syntax. Removing this shrinks the compile by ~140LOC. This is step 31/n towards merging instructions and statements. The last step is updating the docs, which I will do as a separate patch in order to split it from this mostly mechanical patch. PiperOrigin-RevId: 227540453
2019-01-03 02:20:00 +08:00
func @if_else() {
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
%i = call @get_idx() : () -> (index)
NFC: Rename the 'if' operation in the AffineOps dialect to 'affine.if'. PiperOrigin-RevId: 240071154
2019-03-25 11:35:07 +08:00
affine.if #set1(%i) {
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
call @body(%i) : (index) -> ()
} else {
call @mid(%i) : (index) -> ()
}
return
}
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-LABEL: func @nested_ifs
// CHECK-NEXT: %[[v0:.*]] = call @get_idx() : () -> index
// CHECK-NEXT: %[[c0:.*]] = constant 0 : index
// CHECK-NEXT: %[[cm1:.*]] = constant -1 : index
// CHECK-NEXT: %[[v1:.*]] = muli %[[v0]], %[[cm1]] : index
// CHECK-NEXT: %[[c20:.*]] = constant 20 : index
// CHECK-NEXT: %[[v2:.*]] = addi %[[v1]], %[[c20]] : index
// CHECK-NEXT: %[[v3:.*]] = cmpi "sge", %[[v2]], %[[c0]] : index
// CHECK-NEXT: if %[[v3]] {
// CHECK-NEXT: %[[c0_0:.*]] = constant 0 : index
// CHECK-NEXT: %[[cm10:.*]] = constant -10 : index
// CHECK-NEXT: %[[v4:.*]] = addi %[[v0]], %[[cm10]] : index
// CHECK-NEXT: %[[v5:.*]] = cmpi "sge", %[[v4]], %[[c0_0]] : index
// CHECK-NEXT: if %[[v5]] {
// CHECK-NEXT: call @body(%[[v0:.*]]) : (index) -> ()
// CHECK-NEXT: }
// CHECK-NEXT: } else {
// CHECK-NEXT: %[[c0_0:.*]] = constant 0 : index
// CHECK-NEXT: %[[cm10:.*]] = constant -10 : index
// CHECK-NEXT: %{{.*}} = addi %[[v0]], %[[cm10]] : index
// CHECK-NEXT: %{{.*}} = cmpi "sge", %{{.*}}, %[[c0_0]] : index
// CHECK-NEXT: if %{{.*}} {
// CHECK-NEXT: call @mid(%[[v0:.*]]) : (index) -> ()
// CHECK-NEXT: }
// CHECK-NEXT: }
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
// CHECK-NEXT: return
// CHECK-NEXT: }
Eliminate extfunc/cfgfunc/mlfunc as a concept, and just use 'func' instead. The entire compiler now looks at structural properties of the function (e.g. does it have one block, does it contain an if/for stmt, etc) so the only thing holding up this difference is round tripping through the parser/printer syntax. Removing this shrinks the compile by ~140LOC. This is step 31/n towards merging instructions and statements. The last step is updating the docs, which I will do as a separate patch in order to split it from this mostly mechanical patch. PiperOrigin-RevId: 227540453
2019-01-03 02:20:00 +08:00
func @nested_ifs() {
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
%i = call @get_idx() : () -> (index)
NFC: Rename the 'if' operation in the AffineOps dialect to 'affine.if'. PiperOrigin-RevId: 240071154
2019-03-25 11:35:07 +08:00
affine.if #set1(%i) {
affine.if #set2(%i) {
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
call @body(%i) : (index) -> ()
}
} else {
NFC: Rename the 'if' operation in the AffineOps dialect to 'affine.if'. PiperOrigin-RevId: 240071154
2019-03-25 11:35:07 +08:00
affine.if #set2(%i) {
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
call @mid(%i) : (index) -> ()
}
}
return
}
[mlir] Change the syntax of AffineMapAttr and IntegerSetAttr to avoid conflicts with function types. Summary: The current syntax for AffineMapAttr and IntegerSetAttr conflict with function types, making it currently impossible to round-trip function types(and e.g. FuncOp) in the IR. This revision changes the syntax for the attributes by wrapping them in a keyword. AffineMapAttr is wrapped with `affine_map<>` and IntegerSetAttr is wrapped with `affine_set<>`. Reviewed By: nicolasvasilache, ftynse Differential Revision: https://reviews.llvm.org/D72429
2020-01-14 05:12:37 +08:00
#setN = affine_set<(d0)[N,M,K,L] : (N - d0 + 1 >= 0, N - 1 >= 0, M - 1 >= 0, K - 1 >= 0, L - 42 == 0)>
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-LABEL: func @multi_cond
// CHECK-NEXT: %[[v0:.*]] = call @get_idx() : () -> index
// CHECK-NEXT: %[[c0:.*]] = constant 0 : index
// CHECK-NEXT: %[[cm1:.*]] = constant -1 : index
// CHECK-NEXT: %[[v1:.*]] = muli %[[v0]], %[[cm1]] : index
// CHECK-NEXT: %[[v2:.*]] = addi %[[v1]], %{{.*}} : index
// CHECK-NEXT: %[[c1:.*]] = constant 1 : index
// CHECK-NEXT: %[[v3:.*]] = addi %[[v2]], %[[c1]] : index
// CHECK-NEXT: %[[v4:.*]] = cmpi "sge", %[[v3]], %[[c0]] : index
// CHECK-NEXT: %[[cm1_0:.*]] = constant -1 : index
// CHECK-NEXT: %[[v5:.*]] = addi %{{.*}}, %[[cm1_0]] : index
// CHECK-NEXT: %[[v6:.*]] = cmpi "sge", %[[v5]], %[[c0]] : index
// CHECK-NEXT: %[[v7:.*]] = and %[[v4]], %[[v6]] : i1
// CHECK-NEXT: %[[cm1_1:.*]] = constant -1 : index
// CHECK-NEXT: %[[v8:.*]] = addi %{{.*}}, %[[cm1_1]] : index
// CHECK-NEXT: %[[v9:.*]] = cmpi "sge", %[[v8]], %[[c0]] : index
// CHECK-NEXT: %[[v10:.*]] = and %[[v7]], %[[v9]] : i1
// CHECK-NEXT: %[[cm1_2:.*]] = constant -1 : index
// CHECK-NEXT: %[[v11:.*]] = addi %{{.*}}, %[[cm1_2]] : index
// CHECK-NEXT: %[[v12:.*]] = cmpi "sge", %[[v11]], %[[c0]] : index
// CHECK-NEXT: %[[v13:.*]] = and %[[v10]], %[[v12]] : i1
// CHECK-NEXT: %[[cm42:.*]] = constant -42 : index
// CHECK-NEXT: %[[v14:.*]] = addi %{{.*}}, %[[cm42]] : index
// CHECK-NEXT: %[[v15:.*]] = cmpi "eq", %[[v14]], %[[c0]] : index
// CHECK-NEXT: %[[v16:.*]] = and %[[v13]], %[[v15]] : i1
// CHECK-NEXT: if %[[v16]] {
// CHECK-NEXT: call @body(%[[v0:.*]]) : (index) -> ()
// CHECK-NEXT: } else {
// CHECK-NEXT: call @mid(%[[v0:.*]]) : (index) -> ()
// CHECK-NEXT: }
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
// CHECK-NEXT: return
// CHECK-NEXT: }
Eliminate extfunc/cfgfunc/mlfunc as a concept, and just use 'func' instead. The entire compiler now looks at structural properties of the function (e.g. does it have one block, does it contain an if/for stmt, etc) so the only thing holding up this difference is round tripping through the parser/printer syntax. Removing this shrinks the compile by ~140LOC. This is step 31/n towards merging instructions and statements. The last step is updating the docs, which I will do as a separate patch in order to split it from this mostly mechanical patch. PiperOrigin-RevId: 227540453
2019-01-03 02:20:00 +08:00
func @multi_cond(%N : index, %M : index, %K : index, %L : index) {
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
%i = call @get_idx() : () -> (index)
NFC: Rename the 'if' operation in the AffineOps dialect to 'affine.if'. PiperOrigin-RevId: 240071154
2019-03-25 11:35:07 +08:00
affine.if #setN(%i)[%N,%M,%K,%L] {
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
call @body(%i) : (index) -> ()
} else {
call @mid(%i) : (index) -> ()
}
return
}
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-LABEL: func @if_for
Eliminate extfunc/cfgfunc/mlfunc as a concept, and just use 'func' instead. The entire compiler now looks at structural properties of the function (e.g. does it have one block, does it contain an if/for stmt, etc) so the only thing holding up this difference is round tripping through the parser/printer syntax. Removing this shrinks the compile by ~140LOC. This is step 31/n towards merging instructions and statements. The last step is updating the docs, which I will do as a separate patch in order to split it from this mostly mechanical patch. PiperOrigin-RevId: 227540453
2019-01-03 02:20:00 +08:00
func @if_for() {
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: %[[v0:.*]] = call @get_idx() : () -> index
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
%i = call @get_idx() : () -> (index)
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: %[[c0:.*]] = constant 0 : index
// CHECK-NEXT: %[[cm1:.*]] = constant -1 : index
// CHECK-NEXT: %[[v1:.*]] = muli %[[v0]], %[[cm1]] : index
// CHECK-NEXT: %[[c20:.*]] = constant 20 : index
// CHECK-NEXT: %[[v2:.*]] = addi %[[v1]], %[[c20]] : index
// CHECK-NEXT: %[[v3:.*]] = cmpi "sge", %[[v2]], %[[c0]] : index
// CHECK-NEXT: if %[[v3]] {
// CHECK-NEXT: %[[c0:.*]]{{.*}} = constant 0 : index
// CHECK-NEXT: %[[c42:.*]]{{.*}} = constant 42 : index
// CHECK-NEXT: %[[c1:.*]]{{.*}} = constant 1 : index
// CHECK-NEXT: for %{{.*}} = %[[c0:.*]]{{.*}} to %[[c42:.*]]{{.*}} step %[[c1:.*]]{{.*}} {
// CHECK-NEXT: %[[c0_:.*]]{{.*}} = constant 0 : index
// CHECK-NEXT: %[[cm10:.*]] = constant -10 : index
// CHECK-NEXT: %[[v4:.*]] = addi %{{.*}}, %[[cm10]] : index
// CHECK-NEXT: %[[v5:.*]] = cmpi "sge", %[[v4]], %[[c0_:.*]]{{.*}} : index
// CHECK-NEXT: if %[[v5]] {
// CHECK-NEXT: call @body2(%[[v0]], %{{.*}}) : (index, index) -> ()
NFC: Rename the 'if' operation in the AffineOps dialect to 'affine.if'. PiperOrigin-RevId: 240071154
2019-03-25 11:35:07 +08:00
affine.if #set1(%i) {
NFC: Rename the 'for' operation in the AffineOps dialect to 'affine.for' and set the namespace of the AffineOps dialect to 'affine'. PiperOrigin-RevId: 240165792
2019-03-26 01:14:34 +08:00
affine.for %j = 0 to 42 {
NFC: Rename the 'if' operation in the AffineOps dialect to 'affine.if'. PiperOrigin-RevId: 240071154
2019-03-25 11:35:07 +08:00
affine.if #set2(%j) {
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
call @body2(%i, %j) : (index, index) -> ()
}
}
}
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK: %[[c0:.*]]{{.*}} = constant 0 : index
// CHECK-NEXT: %[[c42:.*]]{{.*}} = constant 42 : index
// CHECK-NEXT: %[[c1:.*]]{{.*}} = constant 1 : index
// CHECK-NEXT: for %{{.*}} = %[[c0:.*]]{{.*}} to %[[c42:.*]]{{.*}} step %[[c1:.*]]{{.*}} {
// CHECK-NEXT: %[[c0:.*]]{{.*}} = constant 0 : index
// CHECK-NEXT: %[[cm10:.*]]{{.*}} = constant -10 : index
// CHECK-NEXT: %{{.*}} = addi %{{.*}}, %[[cm10:.*]]{{.*}} : index
// CHECK-NEXT: %{{.*}} = cmpi "sge", %{{.*}}, %[[c0:.*]]{{.*}} : index
// CHECK-NEXT: if %{{.*}} {
// CHECK-NEXT: %[[c0_:.*]]{{.*}} = constant 0 : index
// CHECK-NEXT: %[[c42_:.*]]{{.*}} = constant 42 : index
// CHECK-NEXT: %[[c1_:.*]]{{.*}} = constant 1 : index
// CHECK-NEXT: for %{{.*}} = %[[c0_:.*]]{{.*}} to %[[c42_:.*]]{{.*}} step %[[c1_:.*]]{{.*}} {
NFC: Rename the 'for' operation in the AffineOps dialect to 'affine.for' and set the namespace of the AffineOps dialect to 'affine'. PiperOrigin-RevId: 240165792
2019-03-26 01:14:34 +08:00
affine.for %k = 0 to 42 {
NFC: Rename the 'if' operation in the AffineOps dialect to 'affine.if'. PiperOrigin-RevId: 240071154
2019-03-25 11:35:07 +08:00
affine.if #set2(%k) {
NFC: Rename the 'for' operation in the AffineOps dialect to 'affine.for' and set the namespace of the AffineOps dialect to 'affine'. PiperOrigin-RevId: 240165792
2019-03-26 01:14:34 +08:00
affine.for %l = 0 to 42 {
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
call @body3(%k, %l) : (index, index) -> ()
}
}
}
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK: return
ConvertToCFG: convert "if" statements. The condition of the "if" statement is an integer set, defined as a conjunction of affine constraints. An affine constraints consists of an affine expression and a flag indicating whether the expression is strictly equal to zero or is also allowed to be greater than zero. Affine maps, accepted by `affine_apply` are also formed from affine expressions. Leverage this fact to implement the checking of "if" conditions. Each affine expression from the integer set is converted into an affine map. This map is applied to the arguments of the "if" statement. The result of the application is compared with zero given the equality flag to obtain the final boolean value. The conjunction of conditions is tested sequentially with short-circuit branching to the "else" branch if any of the condition evaluates to false. Create an SESE region for the if statement (including its "then" and optional "else" statement blocks) and append it to the end of the current region. The conditional region consists of a sequence of condition-checking blocks that implement the short-circuit scheme, followed by a "then" SESE region and an "else" SESE region, and the continuation block that post-dominates all blocks of the "if" statement. The flow of blocks that correspond to the "then" and "else" clauses are constructed recursively, enabling easy nesting of "if" statements and if-then-else-if chains. Note that MLIR semantics does not require nor prohibit short-circuit evaluation. Since affine expressions do not have side effects, there is no observable difference in the program behavior. We may trade off extra operations for operation-level parallelism opportunity by first performing all `affine_apply` and comparison operations independently, and then performing a tree pattern reduction of the resulting boolean values with the `muli i1` operations (in absence of the dedicated bit operations). The pros and cons are not clear, and since MLIR does not include parallel semantics, we prefer to minimize the number of sequentially executed operations. PiperOrigin-RevId: 223970248
2018-12-04 23:04:44 +08:00
return
}
ConvertToCFG: support min/max in loop bounds. The recently introduced `select` operation enables ConvertToCFG to support min(max) in loop bounds. Individual min(max) is implemented as `cmpi "lt"`(`cmpi "gt"`) followed by a `select` between the compared values. Multiple results of an `affine_apply` operation extracted from the loop bounds are reduced using min(max) in a sequential manner. While this may decrease the potential for instruction-level parallelism, it is easier to recognize for the following passes, in particular for the vectorizer. PiperOrigin-RevId: 224376233
2018-12-07 03:34:27 +08:00
[mlir] Change the syntax of AffineMapAttr and IntegerSetAttr to avoid conflicts with function types. Summary: The current syntax for AffineMapAttr and IntegerSetAttr conflict with function types, making it currently impossible to round-trip function types(and e.g. FuncOp) in the IR. This revision changes the syntax for the attributes by wrapping them in a keyword. AffineMapAttr is wrapped with `affine_map<>` and IntegerSetAttr is wrapped with `affine_set<>`. Reviewed By: nicolasvasilache, ftynse Differential Revision: https://reviews.llvm.org/D72429
2020-01-14 05:12:37 +08:00
#lbMultiMap = affine_map<(d0)[s0] -> (d0, s0 - d0)>
#ubMultiMap = affine_map<(d0)[s0] -> (s0, d0 + 10)>
ConvertToCFG: support min/max in loop bounds. The recently introduced `select` operation enables ConvertToCFG to support min(max) in loop bounds. Individual min(max) is implemented as `cmpi "lt"`(`cmpi "gt"`) followed by a `select` between the compared values. Multiple results of an `affine_apply` operation extracted from the loop bounds are reduced using min(max) in a sequential manner. While this may decrease the potential for instruction-level parallelism, it is easier to recognize for the following passes, in particular for the vectorizer. PiperOrigin-RevId: 224376233
2018-12-07 03:34:27 +08:00
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-LABEL: func @loop_min_max
// CHECK-NEXT: %[[c0:.*]] = constant 0 : index
// CHECK-NEXT: %[[c42:.*]] = constant 42 : index
// CHECK-NEXT: %[[c1:.*]] = constant 1 : index
// CHECK-NEXT: for %{{.*}} = %[[c0]] to %[[c42]] step %[[c1]] {
// CHECK-NEXT: %[[cm1:.*]] = constant -1 : index
// CHECK-NEXT: %[[a:.*]] = muli %{{.*}}, %[[cm1]] : index
// CHECK-NEXT: %[[b:.*]] = addi %[[a]], %{{.*}} : index
// CHECK-NEXT: %[[c:.*]] = cmpi "sgt", %{{.*}}, %[[b]] : index
// CHECK-NEXT: %[[d:.*]] = select %[[c]], %{{.*}}, %[[b]] : index
// CHECK-NEXT: %[[c10:.*]] = constant 10 : index
// CHECK-NEXT: %[[e:.*]] = addi %{{.*}}, %[[c10]] : index
// CHECK-NEXT: %[[f:.*]] = cmpi "slt", %{{.*}}, %[[e]] : index
// CHECK-NEXT: %[[g:.*]] = select %[[f]], %{{.*}}, %[[e]] : index
// CHECK-NEXT: %[[c1_0:.*]] = constant 1 : index
Enable FileCheck -enable-var-scope by default in MLIR test This option avoids to accidentally reuse variable across -LABEL match, it can be explicitly opted-in by prefixing the variable name with $ Differential Revision: https://reviews.llvm.org/D81531
2020-06-12 08:34:35 +08:00
// CHECK-NEXT: for %{{.*}} = %[[d]] to %[[g]] step %[[c1_0]] {
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: call @body2(%{{.*}}, %{{.*}}) : (index, index) -> ()
// CHECK-NEXT: }
// CHECK-NEXT: }
ConvertToCFG: support min/max in loop bounds. The recently introduced `select` operation enables ConvertToCFG to support min(max) in loop bounds. Individual min(max) is implemented as `cmpi "lt"`(`cmpi "gt"`) followed by a `select` between the compared values. Multiple results of an `affine_apply` operation extracted from the loop bounds are reduced using min(max) in a sequential manner. While this may decrease the potential for instruction-level parallelism, it is easier to recognize for the following passes, in particular for the vectorizer. PiperOrigin-RevId: 224376233
2018-12-07 03:34:27 +08:00
// CHECK-NEXT: return
// CHECK-NEXT: }
Eliminate extfunc/cfgfunc/mlfunc as a concept, and just use 'func' instead. The entire compiler now looks at structural properties of the function (e.g. does it have one block, does it contain an if/for stmt, etc) so the only thing holding up this difference is round tripping through the parser/printer syntax. Removing this shrinks the compile by ~140LOC. This is step 31/n towards merging instructions and statements. The last step is updating the docs, which I will do as a separate patch in order to split it from this mostly mechanical patch. PiperOrigin-RevId: 227540453
2019-01-03 02:20:00 +08:00
func @loop_min_max(%N : index) {
NFC: Rename the 'for' operation in the AffineOps dialect to 'affine.for' and set the namespace of the AffineOps dialect to 'affine'. PiperOrigin-RevId: 240165792
2019-03-26 01:14:34 +08:00
affine.for %i = 0 to 42 {
affine.for %j = max #lbMultiMap(%i)[%N] to min #ubMultiMap(%i)[%N] {
ConvertToCFG: support min/max in loop bounds. The recently introduced `select` operation enables ConvertToCFG to support min(max) in loop bounds. Individual min(max) is implemented as `cmpi "lt"`(`cmpi "gt"`) followed by a `select` between the compared values. Multiple results of an `affine_apply` operation extracted from the loop bounds are reduced using min(max) in a sequential manner. While this may decrease the potential for instruction-level parallelism, it is easier to recognize for the following passes, in particular for the vectorizer. PiperOrigin-RevId: 224376233
2018-12-07 03:34:27 +08:00
call @body2(%i, %j) : (index, index) -> ()
}
}
return
}
[MLIR] Add method to drop duplicate result exprs from AffineMap Add a method that given an affine map returns another with just its unique results. Use this to drop redundant bounds in max/min for affine.for. Update affine.for's canonicalization pattern and createCanonicalizedForOp to use this. Differential Revision: https://reviews.llvm.org/D77237
2020-04-02 03:58:09 +08:00
#map_7_values = affine_map<(d0, d1, d2, d3, d4, d5, d6) -> (d0, d1, d2, d3, d4, d5, d6)>
ConvertToCFG: support min/max in loop bounds. The recently introduced `select` operation enables ConvertToCFG to support min(max) in loop bounds. Individual min(max) is implemented as `cmpi "lt"`(`cmpi "gt"`) followed by a `select` between the compared values. Multiple results of an `affine_apply` operation extracted from the loop bounds are reduced using min(max) in a sequential manner. While this may decrease the potential for instruction-level parallelism, it is easier to recognize for the following passes, in particular for the vectorizer. PiperOrigin-RevId: 224376233
2018-12-07 03:34:27 +08:00
// Check that the "min" (cmpi "slt" + select) reduction sequence is emitted
[mlir] NFC: Fix trivial typo Differential Revision: https://reviews.llvm.org/D77473
2020-04-05 10:30:01 +08:00
// correctly for an affine map with 7 results.
ConvertToCFG: support min/max in loop bounds. The recently introduced `select` operation enables ConvertToCFG to support min(max) in loop bounds. Individual min(max) is implemented as `cmpi "lt"`(`cmpi "gt"`) followed by a `select` between the compared values. Multiple results of an `affine_apply` operation extracted from the loop bounds are reduced using min(max) in a sequential manner. While this may decrease the potential for instruction-level parallelism, it is easier to recognize for the following passes, in particular for the vectorizer. PiperOrigin-RevId: 224376233
2018-12-07 03:34:27 +08:00
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-LABEL: func @min_reduction_tree
// CHECK-NEXT: %[[c0:.*]] = constant 0 : index
Standardize the value numbering in the AsmPrinter. Change the AsmPrinter to number values breadth-first so that values in adjacent regions can have the same name. This allows for ModuleOp to contain operations that produce results. This also standardizes the special name of region entry arguments to "arg[0-9+]" now that Functions are also operations. PiperOrigin-RevId: 257225069
2019-07-10 01:40:29 +08:00
// CHECK-NEXT: %[[c01:.+]] = cmpi "slt", %{{.*}}, %{{.*}} : index
// CHECK-NEXT: %[[r01:.+]] = select %[[c01]], %{{.*}}, %{{.*}} : index
// CHECK-NEXT: %[[c012:.+]] = cmpi "slt", %[[r01]], %{{.*}} : index
// CHECK-NEXT: %[[r012:.+]] = select %[[c012]], %[[r01]], %{{.*}} : index
// CHECK-NEXT: %[[c0123:.+]] = cmpi "slt", %[[r012]], %{{.*}} : index
// CHECK-NEXT: %[[r0123:.+]] = select %[[c0123]], %[[r012]], %{{.*}} : index
// CHECK-NEXT: %[[c01234:.+]] = cmpi "slt", %[[r0123]], %{{.*}} : index
// CHECK-NEXT: %[[r01234:.+]] = select %[[c01234]], %[[r0123]], %{{.*}} : index
// CHECK-NEXT: %[[c012345:.+]] = cmpi "slt", %[[r01234]], %{{.*}} : index
// CHECK-NEXT: %[[r012345:.+]] = select %[[c012345]], %[[r01234]], %{{.*}} : index
// CHECK-NEXT: %[[c0123456:.+]] = cmpi "slt", %[[r012345]], %{{.*}} : index
// CHECK-NEXT: %[[r0123456:.+]] = select %[[c0123456]], %[[r012345]], %{{.*}} : index
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: %[[c1:.*]] = constant 1 : index
Enable FileCheck -enable-var-scope by default in MLIR test This option avoids to accidentally reuse variable across -LABEL match, it can be explicitly opted-in by prefixing the variable name with $ Differential Revision: https://reviews.llvm.org/D81531
2020-06-12 08:34:35 +08:00
// CHECK-NEXT: for %{{.*}} = %[[c0]] to %[[r0123456]] step %[[c1]] {
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: call @body(%{{.*}}) : (index) -> ()
// CHECK-NEXT: }
ConvertToCFG: support min/max in loop bounds. The recently introduced `select` operation enables ConvertToCFG to support min(max) in loop bounds. Individual min(max) is implemented as `cmpi "lt"`(`cmpi "gt"`) followed by a `select` between the compared values. Multiple results of an `affine_apply` operation extracted from the loop bounds are reduced using min(max) in a sequential manner. While this may decrease the potential for instruction-level parallelism, it is easier to recognize for the following passes, in particular for the vectorizer. PiperOrigin-RevId: 224376233
2018-12-07 03:34:27 +08:00
// CHECK-NEXT: return
// CHECK-NEXT: }
[MLIR] Add method to drop duplicate result exprs from AffineMap Add a method that given an affine map returns another with just its unique results. Use this to drop redundant bounds in max/min for affine.for. Update affine.for's canonicalization pattern and createCanonicalizedForOp to use this. Differential Revision: https://reviews.llvm.org/D77237
2020-04-02 03:58:09 +08:00
func @min_reduction_tree(%v1 : index, %v2 : index, %v3 : index, %v4 : index, %v5 : index, %v6 : index, %v7 : index) {
affine.for %i = 0 to min #map_7_values(%v1, %v2, %v3, %v4, %v5, %v6, %v7)[] {
ConvertToCFG: support min/max in loop bounds. The recently introduced `select` operation enables ConvertToCFG to support min(max) in loop bounds. Individual min(max) is implemented as `cmpi "lt"`(`cmpi "gt"`) followed by a `select` between the compared values. Multiple results of an `affine_apply` operation extracted from the loop bounds are reduced using min(max) in a sequential manner. While this may decrease the potential for instruction-level parallelism, it is easier to recognize for the following passes, in particular for the vectorizer. PiperOrigin-RevId: 224376233
2018-12-07 03:34:27 +08:00
call @body(%i) : (index) -> ()
}
return
}
Merge LowerAffineApplyPass into LowerIfAndForPass, rename to LowerAffinePass This change is mechanical and merges the LowerAffineApplyPass and LowerIfAndForPass into a single LowerAffinePass. It makes a step towards defining an "affine dialect" that would contain all polyhedral-related constructs. The motivation for merging these two passes is based on retiring MLFunctions and, eventually, transforming If and For statements into regular operations. After that happens, LowerAffinePass becomes yet another legalization. PiperOrigin-RevId: 227566113
2019-01-03 04:52:41 +08:00
/////////////////////////////////////////////////////////////////////
[mlir] Change the syntax of AffineMapAttr and IntegerSetAttr to avoid conflicts with function types. Summary: The current syntax for AffineMapAttr and IntegerSetAttr conflict with function types, making it currently impossible to round-trip function types(and e.g. FuncOp) in the IR. This revision changes the syntax for the attributes by wrapping them in a keyword. AffineMapAttr is wrapped with `affine_map<>` and IntegerSetAttr is wrapped with `affine_set<>`. Reviewed By: nicolasvasilache, ftynse Differential Revision: https://reviews.llvm.org/D72429
2020-01-14 05:12:37 +08:00
#map0 = affine_map<() -> (0)>
#map1 = affine_map<()[s0] -> (s0)>
#map2 = affine_map<(d0) -> (d0)>
#map3 = affine_map<(d0)[s0] -> (d0 + s0 + 1)>
#map4 = affine_map<(d0,d1,d2,d3)[s0,s1,s2] -> (d0 + 2*d1 + 3*d2 + 4*d3 + 5*s0 + 6*s1 + 7*s2)>
#map5 = affine_map<(d0,d1,d2) -> (d0,d1,d2)>
#map6 = affine_map<(d0,d1,d2) -> (d0 + d1 + d2)>
Merge LowerAffineApplyPass into LowerIfAndForPass, rename to LowerAffinePass This change is mechanical and merges the LowerAffineApplyPass and LowerIfAndForPass into a single LowerAffinePass. It makes a step towards defining an "affine dialect" that would contain all polyhedral-related constructs. The motivation for merging these two passes is based on retiring MLFunctions and, eventually, transforming If and For statements into regular operations. After that happens, LowerAffinePass becomes yet another legalization. PiperOrigin-RevId: 227566113
2019-01-03 04:52:41 +08:00
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-LABEL: func @affine_applies(
Try to fold operations in DialectConversion when trying to legalize. This change allows for DialectConversion to attempt folding as a mechanism to legalize illegal operations. This also expands folding support in OpBuilder::createOrFold to generate new constants when folding, and also enables it to work in the context of a PatternRewriter. PiperOrigin-RevId: 285448440
2019-12-14 04:21:42 +08:00
func @affine_applies(%arg0 : index) {
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK: %[[c0:.*]] = constant 0 : index
NFC: Rename affine_apply to affine.apply. This is the first step to adding a namespace to the affine dialect. PiperOrigin-RevId: 232707862
2019-02-07 03:08:18 +08:00
%zero = affine.apply #map0()
Merge LowerAffineApplyPass into LowerIfAndForPass, rename to LowerAffinePass This change is mechanical and merges the LowerAffineApplyPass and LowerIfAndForPass into a single LowerAffinePass. It makes a step towards defining an "affine dialect" that would contain all polyhedral-related constructs. The motivation for merging these two passes is based on retiring MLFunctions and, eventually, transforming If and For statements into regular operations. After that happens, LowerAffinePass becomes yet another legalization. PiperOrigin-RevId: 227566113
2019-01-03 04:52:41 +08:00
// Identity maps are just discarded.
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: %[[c101:.*]] = constant 101 : index
Merge LowerAffineApplyPass into LowerIfAndForPass, rename to LowerAffinePass This change is mechanical and merges the LowerAffineApplyPass and LowerIfAndForPass into a single LowerAffinePass. It makes a step towards defining an "affine dialect" that would contain all polyhedral-related constructs. The motivation for merging these two passes is based on retiring MLFunctions and, eventually, transforming If and For statements into regular operations. After that happens, LowerAffinePass becomes yet another legalization. PiperOrigin-RevId: 227566113
2019-01-03 04:52:41 +08:00
%101 = constant 101 : index
NFC: Rename affine_apply to affine.apply. This is the first step to adding a namespace to the affine dialect. PiperOrigin-RevId: 232707862
2019-02-07 03:08:18 +08:00
%symbZero = affine.apply #map1()[%zero]
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: %[[c102:.*]] = constant 102 : index
Merge LowerAffineApplyPass into LowerIfAndForPass, rename to LowerAffinePass This change is mechanical and merges the LowerAffineApplyPass and LowerIfAndForPass into a single LowerAffinePass. It makes a step towards defining an "affine dialect" that would contain all polyhedral-related constructs. The motivation for merging these two passes is based on retiring MLFunctions and, eventually, transforming If and For statements into regular operations. After that happens, LowerAffinePass becomes yet another legalization. PiperOrigin-RevId: 227566113
2019-01-03 04:52:41 +08:00
%102 = constant 102 : index
NFC: Rename affine_apply to affine.apply. This is the first step to adding a namespace to the affine dialect. PiperOrigin-RevId: 232707862
2019-02-07 03:08:18 +08:00
%copy = affine.apply #map2(%zero)
Merge LowerAffineApplyPass into LowerIfAndForPass, rename to LowerAffinePass This change is mechanical and merges the LowerAffineApplyPass and LowerIfAndForPass into a single LowerAffinePass. It makes a step towards defining an "affine dialect" that would contain all polyhedral-related constructs. The motivation for merging these two passes is based on retiring MLFunctions and, eventually, transforming If and For statements into regular operations. After that happens, LowerAffinePass becomes yet another legalization. PiperOrigin-RevId: 227566113
2019-01-03 04:52:41 +08:00
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: %[[v0:.*]] = addi %[[c0]], %[[c0]] : index
// CHECK-NEXT: %[[c1:.*]] = constant 1 : index
// CHECK-NEXT: %[[v1:.*]] = addi %[[v0]], %[[c1]] : index
NFC: Rename affine_apply to affine.apply. This is the first step to adding a namespace to the affine dialect. PiperOrigin-RevId: 232707862
2019-02-07 03:08:18 +08:00
%one = affine.apply #map3(%symbZero)[%zero]
Merge LowerAffineApplyPass into LowerIfAndForPass, rename to LowerAffinePass This change is mechanical and merges the LowerAffineApplyPass and LowerIfAndForPass into a single LowerAffinePass. It makes a step towards defining an "affine dialect" that would contain all polyhedral-related constructs. The motivation for merging these two passes is based on retiring MLFunctions and, eventually, transforming If and For statements into regular operations. After that happens, LowerAffinePass becomes yet another legalization. PiperOrigin-RevId: 227566113
2019-01-03 04:52:41 +08:00
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: %[[c2:.*]] = constant 2 : index
Try to fold operations in DialectConversion when trying to legalize. This change allows for DialectConversion to attempt folding as a mechanism to legalize illegal operations. This also expands folding support in OpBuilder::createOrFold to generate new constants when folding, and also enables it to work in the context of a PatternRewriter. PiperOrigin-RevId: 285448440
2019-12-14 04:21:42 +08:00
// CHECK-NEXT: %[[v2:.*]] = muli %arg0, %[[c2]] : index
// CHECK-NEXT: %[[v3:.*]] = addi %arg0, %[[v2]] : index
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: %[[c3:.*]] = constant 3 : index
Try to fold operations in DialectConversion when trying to legalize. This change allows for DialectConversion to attempt folding as a mechanism to legalize illegal operations. This also expands folding support in OpBuilder::createOrFold to generate new constants when folding, and also enables it to work in the context of a PatternRewriter. PiperOrigin-RevId: 285448440
2019-12-14 04:21:42 +08:00
// CHECK-NEXT: %[[v4:.*]] = muli %arg0, %[[c3]] : index
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: %[[v5:.*]] = addi %[[v3]], %[[v4]] : index
// CHECK-NEXT: %[[c4:.*]] = constant 4 : index
Try to fold operations in DialectConversion when trying to legalize. This change allows for DialectConversion to attempt folding as a mechanism to legalize illegal operations. This also expands folding support in OpBuilder::createOrFold to generate new constants when folding, and also enables it to work in the context of a PatternRewriter. PiperOrigin-RevId: 285448440
2019-12-14 04:21:42 +08:00
// CHECK-NEXT: %[[v6:.*]] = muli %arg0, %[[c4]] : index
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: %[[v7:.*]] = addi %[[v5]], %[[v6]] : index
// CHECK-NEXT: %[[c5:.*]] = constant 5 : index
Try to fold operations in DialectConversion when trying to legalize. This change allows for DialectConversion to attempt folding as a mechanism to legalize illegal operations. This also expands folding support in OpBuilder::createOrFold to generate new constants when folding, and also enables it to work in the context of a PatternRewriter. PiperOrigin-RevId: 285448440
2019-12-14 04:21:42 +08:00
// CHECK-NEXT: %[[v8:.*]] = muli %arg0, %[[c5]] : index
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: %[[v9:.*]] = addi %[[v7]], %[[v8]] : index
// CHECK-NEXT: %[[c6:.*]] = constant 6 : index
Try to fold operations in DialectConversion when trying to legalize. This change allows for DialectConversion to attempt folding as a mechanism to legalize illegal operations. This also expands folding support in OpBuilder::createOrFold to generate new constants when folding, and also enables it to work in the context of a PatternRewriter. PiperOrigin-RevId: 285448440
2019-12-14 04:21:42 +08:00
// CHECK-NEXT: %[[v10:.*]] = muli %arg0, %[[c6]] : index
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: %[[v11:.*]] = addi %[[v9]], %[[v10]] : index
// CHECK-NEXT: %[[c7:.*]] = constant 7 : index
Try to fold operations in DialectConversion when trying to legalize. This change allows for DialectConversion to attempt folding as a mechanism to legalize illegal operations. This also expands folding support in OpBuilder::createOrFold to generate new constants when folding, and also enables it to work in the context of a PatternRewriter. PiperOrigin-RevId: 285448440
2019-12-14 04:21:42 +08:00
// CHECK-NEXT: %[[v12:.*]] = muli %arg0, %[[c7]] : index
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: %[[v13:.*]] = addi %[[v11]], %[[v12]] : index
Try to fold operations in DialectConversion when trying to legalize. This change allows for DialectConversion to attempt folding as a mechanism to legalize illegal operations. This also expands folding support in OpBuilder::createOrFold to generate new constants when folding, and also enables it to work in the context of a PatternRewriter. PiperOrigin-RevId: 285448440
2019-12-14 04:21:42 +08:00
%four = affine.apply #map4(%arg0, %arg0, %arg0, %arg0)[%arg0, %arg0, %arg0]
Merge LowerAffineApplyPass into LowerIfAndForPass, rename to LowerAffinePass This change is mechanical and merges the LowerAffineApplyPass and LowerIfAndForPass into a single LowerAffinePass. It makes a step towards defining an "affine dialect" that would contain all polyhedral-related constructs. The motivation for merging these two passes is based on retiring MLFunctions and, eventually, transforming If and For statements into regular operations. After that happens, LowerAffinePass becomes yet another legalization. PiperOrigin-RevId: 227566113
2019-01-03 04:52:41 +08:00
return
}
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-LABEL: func @args_ret_affine_apply(
Merge LowerAffineApplyPass into LowerIfAndForPass, rename to LowerAffinePass This change is mechanical and merges the LowerAffineApplyPass and LowerIfAndForPass into a single LowerAffinePass. It makes a step towards defining an "affine dialect" that would contain all polyhedral-related constructs. The motivation for merging these two passes is based on retiring MLFunctions and, eventually, transforming If and For statements into regular operations. After that happens, LowerAffinePass becomes yet another legalization. PiperOrigin-RevId: 227566113
2019-01-03 04:52:41 +08:00
func @args_ret_affine_apply(index, index) -> (index, index) {
^bb0(%0 : index, %1 : index):
Standardize the value numbering in the AsmPrinter. Change the AsmPrinter to number values breadth-first so that values in adjacent regions can have the same name. This allows for ModuleOp to contain operations that produce results. This also standardizes the special name of region entry arguments to "arg[0-9+]" now that Functions are also operations. PiperOrigin-RevId: 257225069
2019-07-10 01:40:29 +08:00
// CHECK-NEXT: return %{{.*}}, %{{.*}} : index, index
NFC: Rename affine_apply to affine.apply. This is the first step to adding a namespace to the affine dialect. PiperOrigin-RevId: 232707862
2019-02-07 03:08:18 +08:00
%00 = affine.apply #map2 (%0)
%11 = affine.apply #map1 ()[%1]
Merge LowerAffineApplyPass into LowerIfAndForPass, rename to LowerAffinePass This change is mechanical and merges the LowerAffineApplyPass and LowerIfAndForPass into a single LowerAffinePass. It makes a step towards defining an "affine dialect" that would contain all polyhedral-related constructs. The motivation for merging these two passes is based on retiring MLFunctions and, eventually, transforming If and For statements into regular operations. After that happens, LowerAffinePass becomes yet another legalization. PiperOrigin-RevId: 227566113
2019-01-03 04:52:41 +08:00
return %00, %11 : index, index
}
Implement branch-free single-division lowering of affine division/remainder This implements the lowering of `floordiv`, `ceildiv` and `mod` operators from affine expressions to the arithmetic primitive operations. Integer division rules in affine expressions explicitly require rounding towards either negative or positive infinity unlike machine implementations that round towards zero. In the general case, implementing `floordiv` and `ceildiv` using machine signed division requires computing both the quotient and the remainder. When the divisor is positive, this can be simplified by adjusting the dividend and the quotient by one and switching signs. In the current use cases, we are unlikely to encounter affine expressions with negative divisors (affine divisions appear in loop transformations such as tiling that guarantee that divisors are positive by construction). Therefore, it is reasonable to use branch-free single-division implementation. In case of affine maps, divisors can only be literals so we can check the sign and implement the case for negative divisors when the need arises. The affine lowering pass can still fail when applied to semi-affine maps (division or modulo by a symbol). PiperOrigin-RevId: 228668181
2019-01-10 17:44:32 +08:00
//===---------------------------------------------------------------------===//
// Test lowering of Euclidean (floor) division, ceil division and modulo
// operation used in affine expressions. In addition to testing the
Replace remaining usages of the Instruction class with Operation. PiperOrigin-RevId: 240777521
2019-03-28 23:24:38 +08:00
// operation-level output, check that the obtained results are correct by
Implement branch-free single-division lowering of affine division/remainder This implements the lowering of `floordiv`, `ceildiv` and `mod` operators from affine expressions to the arithmetic primitive operations. Integer division rules in affine expressions explicitly require rounding towards either negative or positive infinity unlike machine implementations that round towards zero. In the general case, implementing `floordiv` and `ceildiv` using machine signed division requires computing both the quotient and the remainder. When the divisor is positive, this can be simplified by adjusting the dividend and the quotient by one and switching signs. In the current use cases, we are unlikely to encounter affine expressions with negative divisors (affine divisions appear in loop transformations such as tiling that guarantee that divisors are positive by construction). Therefore, it is reasonable to use branch-free single-division implementation. In case of affine maps, divisors can only be literals so we can check the sign and implement the case for negative divisors when the need arises. The affine lowering pass can still fail when applied to semi-affine maps (division or modulo by a symbol). PiperOrigin-RevId: 228668181
2019-01-10 17:44:32 +08:00
// applying constant folding transformation after affine lowering.
//===---------------------------------------------------------------------===//
[mlir] Change the syntax of AffineMapAttr and IntegerSetAttr to avoid conflicts with function types. Summary: The current syntax for AffineMapAttr and IntegerSetAttr conflict with function types, making it currently impossible to round-trip function types(and e.g. FuncOp) in the IR. This revision changes the syntax for the attributes by wrapping them in a keyword. AffineMapAttr is wrapped with `affine_map<>` and IntegerSetAttr is wrapped with `affine_set<>`. Reviewed By: nicolasvasilache, ftynse Differential Revision: https://reviews.llvm.org/D72429
2020-01-14 05:12:37 +08:00
#mapmod = affine_map<(i) -> (i mod 42)>
Implement branch-free single-division lowering of affine division/remainder This implements the lowering of `floordiv`, `ceildiv` and `mod` operators from affine expressions to the arithmetic primitive operations. Integer division rules in affine expressions explicitly require rounding towards either negative or positive infinity unlike machine implementations that round towards zero. In the general case, implementing `floordiv` and `ceildiv` using machine signed division requires computing both the quotient and the remainder. When the divisor is positive, this can be simplified by adjusting the dividend and the quotient by one and switching signs. In the current use cases, we are unlikely to encounter affine expressions with negative divisors (affine divisions appear in loop transformations such as tiling that guarantee that divisors are positive by construction). Therefore, it is reasonable to use branch-free single-division implementation. In case of affine maps, divisors can only be literals so we can check the sign and implement the case for negative divisors when the need arises. The affine lowering pass can still fail when applied to semi-affine maps (division or modulo by a symbol). PiperOrigin-RevId: 228668181
2019-01-10 17:44:32 +08:00
// --------------------------------------------------------------------------//
// IMPORTANT NOTE: if you change this test, also change the @lowered_affine_mod
// test in the "constant-fold.mlir" test to reflect the expected output of
NFC: Rename affine_apply to affine.apply. This is the first step to adding a namespace to the affine dialect. PiperOrigin-RevId: 232707862
2019-02-07 03:08:18 +08:00
// affine.apply lowering.
Implement branch-free single-division lowering of affine division/remainder This implements the lowering of `floordiv`, `ceildiv` and `mod` operators from affine expressions to the arithmetic primitive operations. Integer division rules in affine expressions explicitly require rounding towards either negative or positive infinity unlike machine implementations that round towards zero. In the general case, implementing `floordiv` and `ceildiv` using machine signed division requires computing both the quotient and the remainder. When the divisor is positive, this can be simplified by adjusting the dividend and the quotient by one and switching signs. In the current use cases, we are unlikely to encounter affine expressions with negative divisors (affine divisions appear in loop transformations such as tiling that guarantee that divisors are positive by construction). Therefore, it is reasonable to use branch-free single-division implementation. In case of affine maps, divisors can only be literals so we can check the sign and implement the case for negative divisors when the need arises. The affine lowering pass can still fail when applied to semi-affine maps (division or modulo by a symbol). PiperOrigin-RevId: 228668181
2019-01-10 17:44:32 +08:00
// --------------------------------------------------------------------------//
// CHECK-LABEL: func @affine_apply_mod
func @affine_apply_mod(%arg0 : index) -> (index) {
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: %[[c42:.*]] = constant 42 : index
Add integer bit-shift operations to the standard dialect. Rename the 'shlis' operation in the standard dialect to 'shift_left'. Add tests for this operation (these have been missing so far) and add a lowering to the 'shl' operation in the LLVM dialect. Add also 'shift_right_signed' (lowered to LLVM's 'ashr') and 'shift_right_unsigned' (lowered to 'lshr'). The original plan was to name these operations 'shift.left', 'shift.right.signed' and 'shift.right.unsigned'. This works if the operations are prefixed with 'std.' in MLIR assembly. Unfortunately during import the short form is ambigous with operations from a hypothetical 'shift' dialect. The best solution seems to omit dots in standard operations for now. Closes tensorflow/mlir#226 PiperOrigin-RevId: 286803388
2019-12-23 02:01:35 +08:00
// CHECK-NEXT: %[[v0:.*]] = remi_signed %{{.*}}, %[[c42]] : index
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: %[[c0:.*]] = constant 0 : index
// CHECK-NEXT: %[[v1:.*]] = cmpi "slt", %[[v0]], %[[c0]] : index
// CHECK-NEXT: %[[v2:.*]] = addi %[[v0]], %[[c42]] : index
// CHECK-NEXT: %[[v3:.*]] = select %[[v1]], %[[v2]], %[[v0]] : index
NFC: Rename affine_apply to affine.apply. This is the first step to adding a namespace to the affine dialect. PiperOrigin-RevId: 232707862
2019-02-07 03:08:18 +08:00
%0 = affine.apply #mapmod (%arg0)
Implement branch-free single-division lowering of affine division/remainder This implements the lowering of `floordiv`, `ceildiv` and `mod` operators from affine expressions to the arithmetic primitive operations. Integer division rules in affine expressions explicitly require rounding towards either negative or positive infinity unlike machine implementations that round towards zero. In the general case, implementing `floordiv` and `ceildiv` using machine signed division requires computing both the quotient and the remainder. When the divisor is positive, this can be simplified by adjusting the dividend and the quotient by one and switching signs. In the current use cases, we are unlikely to encounter affine expressions with negative divisors (affine divisions appear in loop transformations such as tiling that guarantee that divisors are positive by construction). Therefore, it is reasonable to use branch-free single-division implementation. In case of affine maps, divisors can only be literals so we can check the sign and implement the case for negative divisors when the need arises. The affine lowering pass can still fail when applied to semi-affine maps (division or modulo by a symbol). PiperOrigin-RevId: 228668181
2019-01-10 17:44:32 +08:00
return %0 : index
}
[mlir] Change the syntax of AffineMapAttr and IntegerSetAttr to avoid conflicts with function types. Summary: The current syntax for AffineMapAttr and IntegerSetAttr conflict with function types, making it currently impossible to round-trip function types(and e.g. FuncOp) in the IR. This revision changes the syntax for the attributes by wrapping them in a keyword. AffineMapAttr is wrapped with `affine_map<>` and IntegerSetAttr is wrapped with `affine_set<>`. Reviewed By: nicolasvasilache, ftynse Differential Revision: https://reviews.llvm.org/D72429
2020-01-14 05:12:37 +08:00
#mapfloordiv = affine_map<(i) -> (i floordiv 42)>
Implement branch-free single-division lowering of affine division/remainder This implements the lowering of `floordiv`, `ceildiv` and `mod` operators from affine expressions to the arithmetic primitive operations. Integer division rules in affine expressions explicitly require rounding towards either negative or positive infinity unlike machine implementations that round towards zero. In the general case, implementing `floordiv` and `ceildiv` using machine signed division requires computing both the quotient and the remainder. When the divisor is positive, this can be simplified by adjusting the dividend and the quotient by one and switching signs. In the current use cases, we are unlikely to encounter affine expressions with negative divisors (affine divisions appear in loop transformations such as tiling that guarantee that divisors are positive by construction). Therefore, it is reasonable to use branch-free single-division implementation. In case of affine maps, divisors can only be literals so we can check the sign and implement the case for negative divisors when the need arises. The affine lowering pass can still fail when applied to semi-affine maps (division or modulo by a symbol). PiperOrigin-RevId: 228668181
2019-01-10 17:44:32 +08:00
// --------------------------------------------------------------------------//
// IMPORTANT NOTE: if you change this test, also change the @lowered_affine_mod
// test in the "constant-fold.mlir" test to reflect the expected output of
NFC: Rename affine_apply to affine.apply. This is the first step to adding a namespace to the affine dialect. PiperOrigin-RevId: 232707862
2019-02-07 03:08:18 +08:00
// affine.apply lowering.
Implement branch-free single-division lowering of affine division/remainder This implements the lowering of `floordiv`, `ceildiv` and `mod` operators from affine expressions to the arithmetic primitive operations. Integer division rules in affine expressions explicitly require rounding towards either negative or positive infinity unlike machine implementations that round towards zero. In the general case, implementing `floordiv` and `ceildiv` using machine signed division requires computing both the quotient and the remainder. When the divisor is positive, this can be simplified by adjusting the dividend and the quotient by one and switching signs. In the current use cases, we are unlikely to encounter affine expressions with negative divisors (affine divisions appear in loop transformations such as tiling that guarantee that divisors are positive by construction). Therefore, it is reasonable to use branch-free single-division implementation. In case of affine maps, divisors can only be literals so we can check the sign and implement the case for negative divisors when the need arises. The affine lowering pass can still fail when applied to semi-affine maps (division or modulo by a symbol). PiperOrigin-RevId: 228668181
2019-01-10 17:44:32 +08:00
// --------------------------------------------------------------------------//
// CHECK-LABEL: func @affine_apply_floordiv
func @affine_apply_floordiv(%arg0 : index) -> (index) {
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: %[[c42:.*]] = constant 42 : index
// CHECK-NEXT: %[[c0:.*]] = constant 0 : index
// CHECK-NEXT: %[[cm1:.*]] = constant -1 : index
// CHECK-NEXT: %[[v0:.*]] = cmpi "slt", %{{.*}}, %[[c0]] : index
// CHECK-NEXT: %[[v1:.*]] = subi %[[cm1]], %{{.*}} : index
// CHECK-NEXT: %[[v2:.*]] = select %[[v0]], %[[v1]], %{{.*}} : index
Add integer bit-shift operations to the standard dialect. Rename the 'shlis' operation in the standard dialect to 'shift_left'. Add tests for this operation (these have been missing so far) and add a lowering to the 'shl' operation in the LLVM dialect. Add also 'shift_right_signed' (lowered to LLVM's 'ashr') and 'shift_right_unsigned' (lowered to 'lshr'). The original plan was to name these operations 'shift.left', 'shift.right.signed' and 'shift.right.unsigned'. This works if the operations are prefixed with 'std.' in MLIR assembly. Unfortunately during import the short form is ambigous with operations from a hypothetical 'shift' dialect. The best solution seems to omit dots in standard operations for now. Closes tensorflow/mlir#226 PiperOrigin-RevId: 286803388
2019-12-23 02:01:35 +08:00
// CHECK-NEXT: %[[v3:.*]] = divi_signed %[[v2]], %[[c42]] : index
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: %[[v4:.*]] = subi %[[cm1]], %[[v3]] : index
// CHECK-NEXT: %[[v5:.*]] = select %[[v0]], %[[v4]], %[[v3]] : index
NFC: Rename affine_apply to affine.apply. This is the first step to adding a namespace to the affine dialect. PiperOrigin-RevId: 232707862
2019-02-07 03:08:18 +08:00
%0 = affine.apply #mapfloordiv (%arg0)
Implement branch-free single-division lowering of affine division/remainder This implements the lowering of `floordiv`, `ceildiv` and `mod` operators from affine expressions to the arithmetic primitive operations. Integer division rules in affine expressions explicitly require rounding towards either negative or positive infinity unlike machine implementations that round towards zero. In the general case, implementing `floordiv` and `ceildiv` using machine signed division requires computing both the quotient and the remainder. When the divisor is positive, this can be simplified by adjusting the dividend and the quotient by one and switching signs. In the current use cases, we are unlikely to encounter affine expressions with negative divisors (affine divisions appear in loop transformations such as tiling that guarantee that divisors are positive by construction). Therefore, it is reasonable to use branch-free single-division implementation. In case of affine maps, divisors can only be literals so we can check the sign and implement the case for negative divisors when the need arises. The affine lowering pass can still fail when applied to semi-affine maps (division or modulo by a symbol). PiperOrigin-RevId: 228668181
2019-01-10 17:44:32 +08:00
return %0 : index
}
[mlir] Change the syntax of AffineMapAttr and IntegerSetAttr to avoid conflicts with function types. Summary: The current syntax for AffineMapAttr and IntegerSetAttr conflict with function types, making it currently impossible to round-trip function types(and e.g. FuncOp) in the IR. This revision changes the syntax for the attributes by wrapping them in a keyword. AffineMapAttr is wrapped with `affine_map<>` and IntegerSetAttr is wrapped with `affine_set<>`. Reviewed By: nicolasvasilache, ftynse Differential Revision: https://reviews.llvm.org/D72429
2020-01-14 05:12:37 +08:00
#mapceildiv = affine_map<(i) -> (i ceildiv 42)>
Implement branch-free single-division lowering of affine division/remainder This implements the lowering of `floordiv`, `ceildiv` and `mod` operators from affine expressions to the arithmetic primitive operations. Integer division rules in affine expressions explicitly require rounding towards either negative or positive infinity unlike machine implementations that round towards zero. In the general case, implementing `floordiv` and `ceildiv` using machine signed division requires computing both the quotient and the remainder. When the divisor is positive, this can be simplified by adjusting the dividend and the quotient by one and switching signs. In the current use cases, we are unlikely to encounter affine expressions with negative divisors (affine divisions appear in loop transformations such as tiling that guarantee that divisors are positive by construction). Therefore, it is reasonable to use branch-free single-division implementation. In case of affine maps, divisors can only be literals so we can check the sign and implement the case for negative divisors when the need arises. The affine lowering pass can still fail when applied to semi-affine maps (division or modulo by a symbol). PiperOrigin-RevId: 228668181
2019-01-10 17:44:32 +08:00
// --------------------------------------------------------------------------//
// IMPORTANT NOTE: if you change this test, also change the @lowered_affine_mod
// test in the "constant-fold.mlir" test to reflect the expected output of
NFC: Rename affine_apply to affine.apply. This is the first step to adding a namespace to the affine dialect. PiperOrigin-RevId: 232707862
2019-02-07 03:08:18 +08:00
// affine.apply lowering.
Implement branch-free single-division lowering of affine division/remainder This implements the lowering of `floordiv`, `ceildiv` and `mod` operators from affine expressions to the arithmetic primitive operations. Integer division rules in affine expressions explicitly require rounding towards either negative or positive infinity unlike machine implementations that round towards zero. In the general case, implementing `floordiv` and `ceildiv` using machine signed division requires computing both the quotient and the remainder. When the divisor is positive, this can be simplified by adjusting the dividend and the quotient by one and switching signs. In the current use cases, we are unlikely to encounter affine expressions with negative divisors (affine divisions appear in loop transformations such as tiling that guarantee that divisors are positive by construction). Therefore, it is reasonable to use branch-free single-division implementation. In case of affine maps, divisors can only be literals so we can check the sign and implement the case for negative divisors when the need arises. The affine lowering pass can still fail when applied to semi-affine maps (division or modulo by a symbol). PiperOrigin-RevId: 228668181
2019-01-10 17:44:32 +08:00
// --------------------------------------------------------------------------//
// CHECK-LABEL: func @affine_apply_ceildiv
func @affine_apply_ceildiv(%arg0 : index) -> (index) {
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: %[[c42:.*]] = constant 42 : index
// CHECK-NEXT: %[[c0:.*]] = constant 0 : index
// CHECK-NEXT: %[[c1:.*]] = constant 1 : index
// CHECK-NEXT: %[[v0:.*]] = cmpi "sle", %{{.*}}, %[[c0]] : index
// CHECK-NEXT: %[[v1:.*]] = subi %[[c0]], %{{.*}} : index
// CHECK-NEXT: %[[v2:.*]] = subi %{{.*}}, %[[c1]] : index
// CHECK-NEXT: %[[v3:.*]] = select %[[v0]], %[[v1]], %[[v2]] : index
Add integer bit-shift operations to the standard dialect. Rename the 'shlis' operation in the standard dialect to 'shift_left'. Add tests for this operation (these have been missing so far) and add a lowering to the 'shl' operation in the LLVM dialect. Add also 'shift_right_signed' (lowered to LLVM's 'ashr') and 'shift_right_unsigned' (lowered to 'lshr'). The original plan was to name these operations 'shift.left', 'shift.right.signed' and 'shift.right.unsigned'. This works if the operations are prefixed with 'std.' in MLIR assembly. Unfortunately during import the short form is ambigous with operations from a hypothetical 'shift' dialect. The best solution seems to omit dots in standard operations for now. Closes tensorflow/mlir#226 PiperOrigin-RevId: 286803388
2019-12-23 02:01:35 +08:00
// CHECK-NEXT: %[[v4:.*]] = divi_signed %[[v3]], %[[c42]] : index
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK-NEXT: %[[v5:.*]] = subi %[[c0]], %[[v4]] : index
// CHECK-NEXT: %[[v6:.*]] = addi %[[v4]], %[[c1]] : index
// CHECK-NEXT: %[[v7:.*]] = select %[[v0]], %[[v5]], %[[v6]] : index
NFC: Rename affine_apply to affine.apply. This is the first step to adding a namespace to the affine dialect. PiperOrigin-RevId: 232707862
2019-02-07 03:08:18 +08:00
%0 = affine.apply #mapceildiv (%arg0)
Implement branch-free single-division lowering of affine division/remainder This implements the lowering of `floordiv`, `ceildiv` and `mod` operators from affine expressions to the arithmetic primitive operations. Integer division rules in affine expressions explicitly require rounding towards either negative or positive infinity unlike machine implementations that round towards zero. In the general case, implementing `floordiv` and `ceildiv` using machine signed division requires computing both the quotient and the remainder. When the divisor is positive, this can be simplified by adjusting the dividend and the quotient by one and switching signs. In the current use cases, we are unlikely to encounter affine expressions with negative divisors (affine divisions appear in loop transformations such as tiling that guarantee that divisors are positive by construction). Therefore, it is reasonable to use branch-free single-division implementation. In case of affine maps, divisors can only be literals so we can check the sign and implement the case for negative divisors when the need arises. The affine lowering pass can still fail when applied to semi-affine maps (division or modulo by a symbol). PiperOrigin-RevId: 228668181
2019-01-10 17:44:32 +08:00
return %0 : index
}
Add affine-to-standard lowerings for affine.load/store/dma_start/dma_wait. PiperOrigin-RevId: 255960171
2019-07-01 23:32:44 +08:00
// CHECK-LABEL: func @affine_load
func @affine_load(%arg0 : index) {
%0 = alloc() : memref<10xf32>
affine.for %i0 = 0 to 10 {
%1 = affine.load %0[%i0 + symbol(%arg0) + 7] : memref<10xf32>
}
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK: %[[a:.*]] = addi %{{.*}}, %{{.*}} : index
// CHECK-NEXT: %[[c7:.*]] = constant 7 : index
// CHECK-NEXT: %[[b:.*]] = addi %[[a]], %[[c7]] : index
// CHECK-NEXT: %{{.*}} = load %[[v0:.*]][%[[b]]] : memref<10xf32>
Add affine-to-standard lowerings for affine.load/store/dma_start/dma_wait. PiperOrigin-RevId: 255960171
2019-07-01 23:32:44 +08:00
return
}
// CHECK-LABEL: func @affine_store
func @affine_store(%arg0 : index) {
%0 = alloc() : memref<10xf32>
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
%1 = constant 11.0 : f32
Add affine-to-standard lowerings for affine.load/store/dma_start/dma_wait. PiperOrigin-RevId: 255960171
2019-07-01 23:32:44 +08:00
affine.for %i0 = 0 to 10 {
affine.store %1, %0[%i0 - symbol(%arg0) + 7] : memref<10xf32>
}
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK: %c-1 = constant -1 : index
// CHECK-NEXT: %[[a:.*]] = muli %arg0, %c-1 : index
// CHECK-NEXT: %[[b:.*]] = addi %{{.*}}, %[[a]] : index
// CHECK-NEXT: %c7 = constant 7 : index
// CHECK-NEXT: %[[c:.*]] = addi %[[b]], %c7 : index
// CHECK-NEXT: store %cst, %0[%[[c]]] : memref<10xf32>
Add affine-to-standard lowerings for affine.load/store/dma_start/dma_wait. PiperOrigin-RevId: 255960171
2019-07-01 23:32:44 +08:00
return
}
Correctly parse empty affine maps. Previously the test case crashes / produces an error. PiperOrigin-RevId: 281630540
2019-11-21 08:30:14 +08:00
// CHECK-LABEL: func @affine_load_store_zero_dim
func @affine_load_store_zero_dim(%arg0 : memref<i32>, %arg1 : memref<i32>) {
%0 = affine.load %arg0[] : memref<i32>
affine.store %0, %arg1[] : memref<i32>
// CHECK: %[[x:.*]] = load %arg0[] : memref<i32>
// CHECK: store %[[x]], %arg1[] : memref<i32>
return
}
Introduce prefetch op: affine -> std -> llvm intrinsic Introduce affine.prefetch: op to prefetch using a multi-dimensional subscript on a memref; similar to affine.load but has no effect on semantics, but only on performance. Provide lowering through std.prefetch, llvm.prefetch and map to llvm's prefetch instrinsic. All attributes reflected through the lowering - locality hint, rw, and instr/data cache. affine.prefetch %0[%i, %j + 5], false, 3, true : memref<400x400xi32> Signed-off-by: Uday Bondhugula <uday@polymagelabs.com> Closes tensorflow/mlir#225 COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/225 from bondhugula:prefetch 4c3b4e93bc64d9a5719504e6d6e1657818a2ead0 PiperOrigin-RevId: 286212997
2019-12-19 01:59:37 +08:00
// CHECK-LABEL: func @affine_prefetch
func @affine_prefetch(%arg0 : index) {
%0 = alloc() : memref<10xf32>
affine.for %i0 = 0 to 10 {
affine.prefetch %0[%i0 + symbol(%arg0) + 7], read, locality<3>, data : memref<10xf32>
}
// CHECK: %[[a:.*]] = addi %{{.*}}, %{{.*}} : index
// CHECK-NEXT: %[[c7:.*]] = constant 7 : index
// CHECK-NEXT: %[[b:.*]] = addi %[[a]], %[[c7]] : index
// CHECK-NEXT: prefetch %[[v0:.*]][%[[b]]], read, locality<3>, data : memref<10xf32>
return
}
Add affine-to-standard lowerings for affine.load/store/dma_start/dma_wait. PiperOrigin-RevId: 255960171
2019-07-01 23:32:44 +08:00
// CHECK-LABEL: func @affine_dma_start
func @affine_dma_start(%arg0 : index) {
%0 = alloc() : memref<100xf32>
%1 = alloc() : memref<100xf32, 2>
%2 = alloc() : memref<1xi32>
%c0 = constant 0 : index
%c64 = constant 64 : index
affine.for %i0 = 0 to 10 {
affine.dma_start %0[%i0 + 7], %1[%arg0 + 11], %2[%c0], %c64
: memref<100xf32>, memref<100xf32, 2>, memref<1xi32>
}
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK: %c7 = constant 7 : index
// CHECK-NEXT: %[[a:.*]] = addi %{{.*}}, %c7 : index
// CHECK-NEXT: %c11 = constant 11 : index
// CHECK-NEXT: %[[b:.*]] = addi %arg0, %c11 : index
// CHECK-NEXT: dma_start %0[%[[a]]], %1[%[[b]]], %c64, %2[%c0] : memref<100xf32>, memref<100xf32, 2>, memref<1xi32>
Add affine-to-standard lowerings for affine.load/store/dma_start/dma_wait. PiperOrigin-RevId: 255960171
2019-07-01 23:32:44 +08:00
return
}
// CHECK-LABEL: func @affine_dma_wait
func @affine_dma_wait(%arg0 : index) {
%2 = alloc() : memref<1xi32>
%c64 = constant 64 : index
affine.for %i0 = 0 to 10 {
affine.dma_wait %2[%i0 + %arg0 + 17], %c64 : memref<1xi32>
}
Lower affine control flow to std control flow to LLVM dialect This CL splits the lowering of affine to LLVM into 2 parts: 1. affine -> std 2. std -> LLVM The conversions mostly consists of splitting concerns between the affine and non-affine worlds from existing conversions. Short-circuiting of affine `if` conditions was never tested or exercised and is removed in the process, it can be reintroduced later if needed. LoopParametricTiling.cpp is updated to reflect the newly added ForOp::build. PiperOrigin-RevId: 257794436
2019-07-12 21:48:45 +08:00
// CHECK: %[[a:.*]] = addi %{{.*}}, %arg0 : index
// CHECK-NEXT: %c17 = constant 17 : index
// CHECK-NEXT: %[[b:.*]] = addi %[[a]], %c17 : index
// CHECK-NEXT: dma_wait %0[%[[b]]], %c64 : memref<1xi32>
Add affine-to-standard lowerings for affine.load/store/dma_start/dma_wait. PiperOrigin-RevId: 255960171
2019-07-01 23:32:44 +08:00
return
}
[mlir] add lowering from affine.min to std Summary: Affine minimum computation will be used in tiling transformation. The implementation is mostly boilerplate as we already lower the minimum in the upper bound of an affine loop. Differential Revision: https://reviews.llvm.org/D73488
2020-01-28 00:14:56 +08:00
// CHECK-LABEL: func @affine_min
// CHECK-SAME: %[[ARG0:.*]]: index, %[[ARG1:.*]]: index
func @affine_min(%arg0: index, %arg1: index) -> index{
// CHECK: %[[Cm1:.*]] = constant -1
// CHECK: %[[neg1:.*]] = muli %[[ARG1]], %[[Cm1:.*]]
// CHECK: %[[first:.*]] = addi %[[ARG0]], %[[neg1]]
// CHECK: %[[Cm2:.*]] = constant -1
// CHECK: %[[neg2:.*]] = muli %[[ARG0]], %[[Cm2:.*]]
// CHECK: %[[second:.*]] = addi %[[ARG1]], %[[neg2]]
// CHECK: %[[cmp:.*]] = cmpi "slt", %[[first]], %[[second]]
// CHECK: select %[[cmp]], %[[first]], %[[second]]
%0 = affine.min affine_map<(d0,d1) -> (d0 - d1, d1 - d0)>(%arg0, %arg1)
return %0 : index
}
[mlir] Add AffineMaxOp Differential Revision: https://reviews.llvm.org/D73848
2020-02-06 17:25:55 +08:00
// CHECK-LABEL: func @affine_max
// CHECK-SAME: %[[ARG0:.*]]: index, %[[ARG1:.*]]: index
func @affine_max(%arg0: index, %arg1: index) -> index{
// CHECK: %[[Cm1:.*]] = constant -1
// CHECK: %[[neg1:.*]] = muli %[[ARG1]], %[[Cm1:.*]]
// CHECK: %[[first:.*]] = addi %[[ARG0]], %[[neg1]]
// CHECK: %[[Cm2:.*]] = constant -1
// CHECK: %[[neg2:.*]] = muli %[[ARG0]], %[[Cm2:.*]]
// CHECK: %[[second:.*]] = addi %[[ARG1]], %[[neg2]]
// CHECK: %[[cmp:.*]] = cmpi "sgt", %[[first]], %[[second]]
// CHECK: select %[[cmp]], %[[first]], %[[second]]
%0 = affine.max affine_map<(d0,d1) -> (d0 - d1, d1 - d0)>(%arg0, %arg1)
return %0 : index
[MLIR] Add method to drop duplicate result exprs from AffineMap Add a method that given an affine map returns another with just its unique results. Use this to drop redundant bounds in max/min for affine.for. Update affine.for's canonicalization pattern and createCanonicalizedForOp to use this. Differential Revision: https://reviews.llvm.org/D77237
2020-04-02 03:58:09 +08:00
}
[MLIR] Add lowering for affine.parallel to scf.parallel Add lowering conversion from affine.parallel to scf.parallel. Differential Revision: https://reviews.llvm.org/D83239
2020-07-18 15:39:30 +08:00
// CHECK-LABEL: func @affine_parallel(
// CHECK-SAME: %[[ARG0:.*]]: memref<100x100xf32>, %[[ARG1:.*]]: memref<100x100xf32>) {
func @affine_parallel(%o: memref<100x100xf32>, %a: memref<100x100xf32>) {
affine.parallel (%i, %j) = (0, 0) to (100, 100) {
}
return
}
// CHECK-DAG: %[[C100:.*]] = constant 100
// CHECK-DAG: %[[C100_1:.*]] = constant 100
// CHECK-DAG: %[[C0:.*]] = constant 0
// CHECK-DAG: %[[C0_1:.*]] = constant 0
// CHECK-DAG: %[[C1:.*]] = constant 1
// CHECK-DAG: %[[C1_1:.*]] = constant 1
// CHECK-DAG: scf.parallel (%arg2, %arg3) = (%[[C0]], %[[C0_1]]) to (%[[C100]], %[[C100_1]]) step (%[[C1]], %[[C1_1]]) {
// CHECK-LABEL: func @affine_parallel_tiled(
// CHECK-SAME: %[[ARG0:.*]]: memref<100x100xf32>, %[[ARG1:.*]]: memref<100x100xf32>, %[[ARG2:.*]]: memref<100x100xf32>) {
func @affine_parallel_tiled(%o: memref<100x100xf32>, %a: memref<100x100xf32>, %b: memref<100x100xf32>) {
affine.parallel (%i0, %j0, %k0) = (0, 0, 0) to (100, 100, 100) step (10, 10, 10) {
affine.parallel (%i1, %j1, %k1) = (%i0, %j0, %k0) to (%i0 + 10, %j0 + 10, %k0 + 10) {
%0 = affine.load %a[%i1, %k1] : memref<100x100xf32>
%1 = affine.load %b[%k1, %j1] : memref<100x100xf32>
%2 = mulf %0, %1 : f32
}
}
return
}
// CHECK-DAG: %[[C100:.*]] = constant 100
// CHECK-DAG: %[[C100_0:.*]] = constant 100
// CHECK-DAG: %[[C100_1:.*]] = constant 100
// CHECK-DAG: %[[C0:.*]] = constant 0
// CHECK-DAG: %[[C0_2:.*]] = constant 0
// CHECK-DAG: %[[C0_3:.*]] = constant 0
// CHECK-DAG: %[[C10:.*]] = constant 10
// CHECK-DAG: %[[C10_4:.*]] = constant 10
// CHECK-DAG: %[[C10_5:.*]] = constant 10
// CHECK: scf.parallel (%[[arg3:.*]], %[[arg4:.*]], %[[arg5:.*]]) = (%[[C0]], %[[C0_2]], %[[C0_3]]) to (%[[C100]], %[[C100_0]], %[[C100_1]]) step (%[[C10]], %[[C10_4]], %[[C10_5]]) {
// CHECK-DAG: %[[C10_6:.*]] = constant 10
// CHECK-DAG: %[[A0:.*]] = addi %[[arg3]], %[[C10_6]]
// CHECK-DAG: %[[C10_7:.*]] = constant 10
// CHECK-DAG: %[[A1:.*]] = addi %[[arg4]], %[[C10_7]]
// CHECK-DAG: %[[C10_8:.*]] = constant 10
// CHECK-DAG: %[[A2:.*]] = addi %[[arg5]], %[[C10_8]]
// CHECK-DAG: %[[C1:.*]] = constant 1
// CHECK-DAG: %[[C1_9:.*]] = constant 1
// CHECK-DAG: %[[C1_10:.*]] = constant 1
// CHECK: scf.parallel (%[[arg6:.*]], %[[arg7:.*]], %[[arg8:.*]]) = (%[[arg3]], %[[arg4]], %[[arg5]]) to (%[[A0]], %[[A1]], %[[A2]]) step (%[[C1]], %[[C1_9]], %[[C1_10]]) {
// CHECK: %[[A3:.*]] = load %[[ARG1]][%[[arg6]], %[[arg8]]] : memref<100x100xf32>
// CHECK: %[[A4:.*]] = load %[[ARG2]][%[[arg8]], %[[arg7]]] : memref<100x100xf32>
// CHECK: mulf %[[A3]], %[[A4]] : f32
// CHECK: scf.yield
[MLIR] Fix lowering of affine operations with return values This commit addresses the issue of lowering affine.for and affine.parallel having return values. Relevant test cases are also added. Signed-off-by: Prateek Gupta <prateek@polymagelabs.com> Differential Revision: https://reviews.llvm.org/D93090
2020-12-23 00:10:17 +08:00
/////////////////////////////////////////////////////////////////////
func @affine_parallel_simple(%arg0: memref<3x3xf32>, %arg1: memref<3x3xf32>) -> (memref<3x3xf32>) {
%O = alloc() : memref<3x3xf32>
affine.parallel (%kx, %ky) = (0, 0) to (2, 2) {
%1 = affine.load %arg0[%kx, %ky] : memref<3x3xf32>
%2 = affine.load %arg1[%kx, %ky] : memref<3x3xf32>
%3 = mulf %1, %2 : f32
affine.store %3, %O[%kx, %ky] : memref<3x3xf32>
}
return %O : memref<3x3xf32>
}
// CHECK-LABEL: func @affine_parallel_simple
// CHECK: %[[LOWER_1:.*]] = constant 0 : index
// CHECK-NEXT: %[[LOWER_2:.*]] = constant 0 : index
// CHECK-NEXT: %[[UPPER_1:.*]] = constant 2 : index
// CHECK-NEXT: %[[UPPER_2:.*]] = constant 2 : index
// CHECK-NEXT: %[[STEP_1:.*]] = constant 1 : index
// CHECK-NEXT: %[[STEP_2:.*]] = constant 1 : index
// CHECK-NEXT: scf.parallel (%[[I:.*]], %[[J:.*]]) = (%[[LOWER_1]], %[[LOWER_2]]) to (%[[UPPER_1]], %[[UPPER_2]]) step (%[[STEP_1]], %[[STEP_2]]) {
// CHECK-NEXT: %[[VAL_1:.*]] = load
// CHECK-NEXT: %[[VAL_2:.*]] = load
// CHECK-NEXT: %[[PRODUCT:.*]] = mulf
// CHECK-NEXT: store
// CHECK-NEXT: scf.yield
// CHECK-NEXT: }
// CHECK-NEXT: return
// CHECK-NEXT: }
/////////////////////////////////////////////////////////////////////
func @affine_parallel_simple_dynamic_bounds(%arg0: memref<?x?xf32>, %arg1: memref<?x?xf32>, %arg2: memref<?x?xf32>) {
%c_0 = constant 0 : index
%output_dim = dim %arg0, %c_0 : memref<?x?xf32>
affine.parallel (%kx, %ky) = (%c_0, %c_0) to (%output_dim, %output_dim) {
%1 = affine.load %arg0[%kx, %ky] : memref<?x?xf32>
%2 = affine.load %arg1[%kx, %ky] : memref<?x?xf32>
%3 = mulf %1, %2 : f32
affine.store %3, %arg2[%kx, %ky] : memref<?x?xf32>
}
return
}
// CHECK-LABEL: func @affine_parallel_simple_dynamic_bounds
// CHECK-SAME: %[[ARG_0:.*]]: memref<?x?xf32>, %[[ARG_1:.*]]: memref<?x?xf32>, %[[ARG_2:.*]]: memref<?x?xf32>
// CHECK: %[[DIM_INDEX:.*]] = constant 0 : index
// CHECK-NEXT: %[[UPPER:.*]] = dim %[[ARG_0]], %[[DIM_INDEX]] : memref<?x?xf32>
// CHECK-NEXT: %[[LOWER_1:.*]] = constant 0 : index
// CHECK-NEXT: %[[LOWER_2:.*]] = constant 0 : index
// CHECK-NEXT: %[[STEP_1:.*]] = constant 1 : index
// CHECK-NEXT: %[[STEP_2:.*]] = constant 1 : index
// CHECK-NEXT: scf.parallel (%[[I:.*]], %[[J:.*]]) = (%[[LOWER_1]], %[[LOWER_2]]) to (%[[UPPER]], %[[UPPER]]) step (%[[STEP_1]], %[[STEP_2]]) {
// CHECK-NEXT: %[[VAL_1:.*]] = load
// CHECK-NEXT: %[[VAL_2:.*]] = load
// CHECK-NEXT: %[[PRODUCT:.*]] = mulf
// CHECK-NEXT: store
// CHECK-NEXT: scf.yield
// CHECK-NEXT: }
// CHECK-NEXT: return
// CHECK-NEXT: }
/////////////////////////////////////////////////////////////////////
func @affine_parallel_with_reductions(%arg0: memref<3x3xf32>, %arg1: memref<3x3xf32>) -> (f32, f32) {
%0:2 = affine.parallel (%kx, %ky) = (0, 0) to (2, 2) reduce ("addf", "mulf") -> (f32, f32) {
%1 = affine.load %arg0[%kx, %ky] : memref<3x3xf32>
%2 = affine.load %arg1[%kx, %ky] : memref<3x3xf32>
%3 = mulf %1, %2 : f32
%4 = addf %1, %2 : f32
affine.yield %3, %4 : f32, f32
}
return %0#0, %0#1 : f32, f32
}
// CHECK-LABEL: func @affine_parallel_with_reductions
// CHECK: %[[LOWER_1:.*]] = constant 0 : index
// CHECK-NEXT: %[[LOWER_2:.*]] = constant 0 : index
// CHECK-NEXT: %[[UPPER_1:.*]] = constant 2 : index
// CHECK-NEXT: %[[UPPER_2:.*]] = constant 2 : index
// CHECK-NEXT: %[[STEP_1:.*]] = constant 1 : index
// CHECK-NEXT: %[[STEP_2:.*]] = constant 1 : index
// CHECK-NEXT: %[[INIT_1:.*]] = constant 0.000000e+00 : f32
// CHECK-NEXT: %[[INIT_2:.*]] = constant 1.000000e+00 : f32
// CHECK-NEXT: %[[RES:.*]] = scf.parallel (%[[I:.*]], %[[J:.*]]) = (%[[LOWER_1]], %[[LOWER_2]]) to (%[[UPPER_1]], %[[UPPER_2]]) step (%[[STEP_1]], %[[STEP_2]]) init (%[[INIT_1]], %[[INIT_2]]) -> (f32, f32) {
// CHECK-NEXT: %[[VAL_1:.*]] = load
// CHECK-NEXT: %[[VAL_2:.*]] = load
// CHECK-NEXT: %[[PRODUCT:.*]] = mulf
// CHECK-NEXT: %[[SUM:.*]] = addf
// CHECK-NEXT: scf.reduce(%[[PRODUCT]]) : f32 {
// CHECK-NEXT: ^bb0(%[[LHS:.*]]: f32, %[[RHS:.*]]: f32):
// CHECK-NEXT: %[[RES:.*]] = addf
// CHECK-NEXT: scf.reduce.return %[[RES]] : f32
// CHECK-NEXT: }
// CHECK-NEXT: scf.reduce(%[[SUM]]) : f32 {
// CHECK-NEXT: ^bb0(%[[LHS:.*]]: f32, %[[RHS:.*]]: f32):
// CHECK-NEXT: %[[RES:.*]] = mulf
// CHECK-NEXT: scf.reduce.return %[[RES]] : f32
// CHECK-NEXT: }
// CHECK-NEXT: scf.yield
// CHECK-NEXT: }
// CHECK-NEXT: return
// CHECK-NEXT: }