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Added Atan2Op support #1056

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Added Atan2Op support #1056

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93d1814
Added Atan2Op to TTIR and TTNN ops. Added stablehlo to ttir conversio…
kmitrovicTT Oct 24, 2024
84e0fe3
Trying ttmetal fix
kmitrovicTT Oct 25, 2024
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16 changes: 16 additions & 0 deletions include/ttmlir/Dialect/TTIR/IR/TTIROps.td
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Original file line number Diff line number Diff line change
Expand Up @@ -336,6 +336,22 @@ def TTIR_MaximumOp : TTIR_ElementwiseBinaryOp<"maximum"> {
}];
}

def TTIR_Atan2Op : TTIR_ElementwiseBinaryOp<"atan2"> {
let summary = "Eltwise atan2 OP.";
let description = [{
Performs element-wise atan2 operation on lhs and rhs tensor and produces a result
tensor.

Example:
```
// %lhs: [0.0, 1.0, -1.0]
// %rhs: [0.0, 0.0, 0.0]
%result = "ttir.atan2"(%lhs, %rhs) : (tensor<3xf64>, tensor<3xf64>) -> tensor<3xf64>
// %result: [0.0, 1.57079637, -1.57079637] // [0.0, pi/2, -pi/2]
```
}];
}

class TTIR_ReductionOp<string mnemonic, list<Trait> traits = []> :
TTIR_DPSOp<mnemonic, !listconcat(traits, [TTIR_GenericRegionOpInterface])> {

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16 changes: 16 additions & 0 deletions include/ttmlir/Dialect/TTNN/IR/TTNNOps.td
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Expand Up @@ -284,6 +284,22 @@ def TTNN_MaximumOp : TTNN_ElementwiseBinaryOp<"maximum"> {
}];
}

def TTNN_Atan2Op : TTNN_ElementwiseBinaryOp<"atan2"> {
let summary = "Eltwise atan2 OP.";
let description = [{
Performs element-wise atan2 operation on lhs and rhs tensor and produces a result
tensor.

Example:
```
// %lhs: [0.0, 1.0, -1.0]
// %rhs: [0.0, 0.0, 0.0]
%result = "ttnn.atan2"(%lhs, %rhs) : (tensor<3xf64>, tensor<3xf64>) -> tensor<3xf64>
// %result: [0.0, 1.57079637, -1.57079637] // [0.0, pi/2, -pi/2]
```
}];
}

class TTNN_ReductionOp<string mnemonic, list<Trait> traits = []> : TTNN_Op<mnemonic, traits> {
let summary = "Reduction op.";
let description = [{
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1 change: 1 addition & 0 deletions include/ttmlir/Target/TTNN/program.fbs
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Expand Up @@ -73,6 +73,7 @@ enum EltwiseOpType: uint32 {
LogicalAnd = 20,
LogicalOr = 21,
LogicalNot = 22,
Atan2 = 23,
}

table EltwiseOp {
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2 changes: 2 additions & 0 deletions lib/Conversion/StableHLOToTTIR/StableHLOToTTIRPatterns.cpp
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Expand Up @@ -832,6 +832,8 @@ void addElementwiseBinaryOpsConversionPatterns(MLIRContext *ctx,
mlir::stablehlo::DivOp, mlir::tt::ttir::DivOp>>(typeConverter, ctx);
patterns.add<StableHLOToTTIROpDefaultConversionPattern<
mlir::stablehlo::MaxOp, mlir::tt::ttir::MaximumOp>>(typeConverter, ctx);
patterns.add<StableHLOToTTIROpDefaultConversionPattern<
mlir::stablehlo::Atan2Op, mlir::tt::ttir::Atan2Op>>(typeConverter, ctx);
}

void addReduceOpsConversionPatterns(MLIRContext *ctx,
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1 change: 1 addition & 0 deletions lib/Conversion/TTIRToTTNN/TTIRToTTNN.cpp
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Expand Up @@ -749,6 +749,7 @@ void populateTTIRToTTNNPatterns(MLIRContext *ctx, RewritePatternSet &patterns,
ElementwiseOpConversionPattern<ttir::ReciprocalOp, ttnn::ReciprocalOp>,
ElementwiseOpConversionPattern<ttir::ExpOp, ttnn::ExpOp>,
ElementwiseOpConversionPattern<ttir::DivOp, ttnn::DivOp>,
ElementwiseOpConversionPattern<ttir::Atan2Op, ttnn::Atan2Op>,
ReductionOpConversionPattern<ttir::SumOp, ttnn::SumOp>,
ReductionOpConversionPattern<ttir::MeanOp, ttnn::MeanOp>,
ReductionOpConversionPattern<ttir::MaxOp, ttnn::MaxOp>,
Expand Down
3 changes: 2 additions & 1 deletion lib/Conversion/TTNNToEmitC/TTNNToEmitC.cpp
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Expand Up @@ -551,7 +551,8 @@ void populateTTNNToEmitCPatterns(mlir::MLIRContext *ctx,
DefaultOpConversionPattern<ttnn::LessEqualOp>,
DefaultOpConversionPattern<ttnn::LessThanOp>,
DefaultOpConversionPattern<ttnn::MaximumOp>,
DefaultOpConversionPattern<ttnn::DivOp>>(typeConverter, ctx);
DefaultOpConversionPattern<ttnn::DivOp>,
DefaultOpConversionPattern<ttnn::Atan2Op>>(typeConverter, ctx);

// Tensor manipulation ops
//
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5 changes: 5 additions & 0 deletions lib/Target/TTNN/TTNNToFlatbuffer.cpp
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Expand Up @@ -300,6 +300,8 @@ createEltwiseOp(FlatbufferObjectCache &cache, EltwiseOp op) {
type = ::tt::target::ttnn::EltwiseOpType::Typecast;
} else if constexpr (std::is_same_v<EltwiseOp, ExpOp>) {
type = ::tt::target::ttnn::EltwiseOpType::Exp;
} else if constexpr (std::is_same_v<EltwiseOp, Atan2Op>) {
type = ::tt::target::ttnn::EltwiseOpType::Atan2;
} else {
llvm_unreachable("unhandled EltwiseOp");
}
Expand Down Expand Up @@ -546,6 +548,9 @@ emitTTNNOperation(FlatbufferObjectCache &cache, Operation *op,
if (auto divOp = dyn_cast<DivOp>(op); divOp) {
return createOperation(cache, createEltwiseOp(cache, divOp), debugString);
}
if (auto atan2Op = dyn_cast<Atan2Op>(op); atan2Op) {
return createOperation(cache, createEltwiseOp(cache, atan2Op), debugString);
}
if (auto matmulOp = dyn_cast<MatmulOp>(op); matmulOp) {
return createOperation(cache, createOp(cache, matmulOp), debugString);
}
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5 changes: 5 additions & 0 deletions runtime/lib/ttnn/operations/eltwise/binary.cpp
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Expand Up @@ -5,6 +5,7 @@
#include "tt/runtime/detail/logger.h"
#include "tt/runtime/detail/ttnn.h"
#include "tt/runtime/ttnn/operations/utils.h"
#include "ttnn/operations/eltwise/binary/binary_composite.hpp"

namespace tt::runtime::ttnn::operations::binary {

Expand Down Expand Up @@ -123,6 +124,10 @@ void run(const ::tt::target::ttnn::EltwiseOp *op, ProgramContext &context) {
runEltwiseBinaryCompositeOP(op, tensorPool, ::ttnn::maximum);
break;
}
case ::tt::target::ttnn::EltwiseOpType::Atan2: {
runEltwiseBinaryCompositeOP(op, tensorPool, ::ttnn::atan2);
break;
}
default:
throw std::invalid_argument("Unsupported Eltwise Binary operation");
}
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11 changes: 11 additions & 0 deletions test/ttmlir/Conversion/StableHLOToTTIR/atan2_op.mlir
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@@ -0,0 +1,11 @@
// REQUIRES: stablehlo
// RUN: ttmlir-opt --stablehlo-to-ttir-pipeline %s | FileCheck %s
#any_device = #tt.operand_constraint<dram|l1|scalar|tile|any_device|any_device_tile>
module @jit_eltwise_atan2 attributes {} {
func.func public @test_atan2(%arg0: tensor<32x32xf32>, %arg1: tensor<32x32xf32>) -> tensor<32x32xf32> {
%0 = stablehlo.atan2 %arg0, %arg1 : tensor<32x32xf32>
// CHECK: %[[C:.*]] = tensor.empty[[C:.*]]
// CHECK: %[[C:.*]] = "ttir.atan2"[[C:.*]]
return %0 : tensor<32x32xf32>
}
}
11 changes: 11 additions & 0 deletions test/ttmlir/Dialect/TTNN/eltwise/binary/atan2/simple_atan2.mlir
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@@ -0,0 +1,11 @@
// RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s | FileCheck %s
#any_device = #tt.operand_constraint<dram|l1|scalar|tile|any_device|any_device_tile>
module attributes {} {
func.func @atan2(%arg0: tensor<32x32xf32>, %arg1: tensor<32x32xf32>) -> tensor<32x32xf32> {
// CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
%0 = tensor.empty() : tensor<32x32xf32>
// CHECK: %[[C:.*]] = "ttnn.atan2"[[C:.*]]
%1 = "ttir.atan2"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>, operand_constraints = [#any_device, #any_device, #any_device]}> : (tensor<32x32xf32>, tensor<32x32xf32>, tensor<32x32xf32>) -> tensor<32x32xf32>
return %1 : tensor<32x32xf32>
}
}
8 changes: 8 additions & 0 deletions test/ttmlir/Silicon/TTNN/simple_eltwise.mlir
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Expand Up @@ -134,3 +134,11 @@ func.func @maximum(%arg0: tensor<64x128xf32>, %arg1: tensor<64x128xf32>) -> tens
%1 = "ttir.maximum"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>, operand_constraints = [#any_device, #any_device, #any_device]}> : (tensor<64x128xf32>, tensor<64x128xf32>, tensor<64x128xf32>) -> tensor<64x128xf32>
return %1 : tensor<64x128xf32>
}

func.func @atan2(%arg0: tensor<32x32xf32>, %arg1: tensor<32x32xf32>) -> tensor<32x32xf32> {
// CHECK: %[[C:.*]] = "ttnn.empty"[[C:.*]]
%0 = tensor.empty() : tensor<32x32xf32>
// CHECK: %[[C:.*]] = "ttnn.atan2"[[C:.*]]
%1 = "ttir.atan2"(%arg0, %arg1, %0) <{operandSegmentSizes = array<i32: 2, 1>, operand_constraints = [#any_device, #any_device, #any_device]}> : (tensor<32x32xf32>, tensor<32x32xf32>, tensor<32x32xf32>) -> tensor<32x32xf32>
return %1 : tensor<32x32xf32>
}
2 changes: 1 addition & 1 deletion third_party/CMakeLists.txt
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@@ -1,6 +1,6 @@
include(ExternalProject)

set(TT_METAL_VERSION "047cdd97fa26b229208ce2f6f8b149c3df277be0")
set(TT_METAL_VERSION "fccd6929c7a065b9145af92b1a429b2e8f63907b")
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Not sure if this was intentional, or just got picked up during git add. Leaving comment as a reminder to remove before merging.


if ("$ENV{ARCH_NAME}" STREQUAL "grayskull")
set(ARCH_NAME "grayskull")
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