mirror of
https://github.com/zama-ai/concrete.git
synced 2026-02-09 03:55:04 -05:00
fix(compiler): The crt loops are unary and should be init by a alloc_tensor
This commit is contained in:
Quentin Bourgerie
committed by
Alexandre Péré
Alexandre Péré
parent
2fd9b6f0e3
commit
19fdbf652e
@@ -123,41 +123,6 @@ template <typename T> struct CrtOpPattern : public mlir::OpRewritePattern<T> {
|
||||
: mlir::OpRewritePattern<T>(context, benefit),
|
||||
loweringParameters(params) {}
|
||||
|
||||
/// Writes an `scf::for` that loops over the crt dimension of two tensors and
|
||||
/// execute the input lambda to write the loop body. Returns the first result
|
||||
/// of the op.
|
||||
///
|
||||
/// Note:
|
||||
/// -----
|
||||
///
|
||||
/// + The type of `firstArgTensor` type is used as output type.
|
||||
mlir::Value writeBinaryTensorLoop(
|
||||
mlir::Location location, mlir::Value firstTensor,
|
||||
mlir::Value secondTensor, mlir::PatternRewriter &rewriter,
|
||||
mlir::function_ref<void(mlir::OpBuilder &, mlir::Location, mlir::Value,
|
||||
mlir::ValueRange)>
|
||||
body) const {
|
||||
|
||||
// Create the loop
|
||||
mlir::arith::ConstantOp zeroConstantOp =
|
||||
rewriter.create<mlir::arith::ConstantIndexOp>(location, 0);
|
||||
mlir::arith::ConstantOp oneConstantOp =
|
||||
rewriter.create<mlir::arith::ConstantIndexOp>(location, 1);
|
||||
mlir::arith::ConstantOp crtSizeConstantOp =
|
||||
rewriter.create<mlir::arith::ConstantIndexOp>(location,
|
||||
loweringParameters.nMods);
|
||||
mlir::scf::ForOp newOp = rewriter.create<mlir::scf::ForOp>(
|
||||
location, zeroConstantOp, crtSizeConstantOp, oneConstantOp,
|
||||
mlir::ValueRange{firstTensor, secondTensor}, body);
|
||||
|
||||
// Convert the types of the new operation
|
||||
typing::TypeConverter converter(loweringParameters);
|
||||
concretelang::convertOperandAndResultTypes(rewriter, newOp,
|
||||
converter.getConversionLambda());
|
||||
|
||||
return newOp.getResult(0);
|
||||
}
|
||||
|
||||
/// Writes an `scf::for` that loops over the crt dimension of one tensor and
|
||||
/// execute the input lambda to write the loop body. Returns the first result
|
||||
/// of the op.
|
||||
@@ -167,12 +132,16 @@ template <typename T> struct CrtOpPattern : public mlir::OpRewritePattern<T> {
|
||||
///
|
||||
/// + The type of `firstArgTensor` type is used as output type.
|
||||
mlir::Value writeUnaryTensorLoop(
|
||||
mlir::Location location, mlir::Value tensor,
|
||||
mlir::Location location, mlir::Type returnType,
|
||||
mlir::PatternRewriter &rewriter,
|
||||
mlir::function_ref<void(mlir::OpBuilder &, mlir::Location, mlir::Value,
|
||||
mlir::ValueRange)>
|
||||
body) const {
|
||||
|
||||
mlir::Value tensor = rewriter.create<mlir::bufferization::AllocTensorOp>(
|
||||
location, returnType.cast<mlir::RankedTensorType>(),
|
||||
mlir::ValueRange{});
|
||||
|
||||
// Create the loop
|
||||
mlir::arith::ConstantOp zeroConstantOp =
|
||||
rewriter.create<mlir::arith::ConstantIndexOp>(location, 0);
|
||||
@@ -239,20 +208,19 @@ struct AddEintIntOpPattern : public CrtOpPattern<FHE::AddEintIntOp> {
|
||||
converter.convertType(eintOperand.getType())
|
||||
.cast<mlir::RankedTensorType>()
|
||||
.getElementType();
|
||||
mlir::Value output = writeBinaryTensorLoop(
|
||||
location, eintOperand, encodedPlaintextTensor, rewriter,
|
||||
mlir::Value output = writeUnaryTensorLoop(
|
||||
location, eintOperand.getType(), rewriter,
|
||||
[&](mlir::OpBuilder &builder, mlir::Location loc, mlir::Value iter,
|
||||
mlir::ValueRange args) {
|
||||
mlir::Value extractedEint =
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, args[0], iter);
|
||||
mlir::Value extractedInt =
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, args[1], iter);
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, eintOperand, iter);
|
||||
mlir::Value extractedInt = builder.create<mlir::tensor::ExtractOp>(
|
||||
loc, encodedPlaintextTensor, iter);
|
||||
mlir::Value output = builder.create<TFHE::AddGLWEIntOp>(
|
||||
loc, ciphertextScalarType, extractedEint, extractedInt);
|
||||
mlir::Value newTensor = builder.create<mlir::tensor::InsertOp>(
|
||||
loc, output, args[0], iter);
|
||||
builder.create<mlir::scf::YieldOp>(
|
||||
loc, mlir::ValueRange{newTensor, args[1]});
|
||||
builder.create<mlir::scf::YieldOp>(loc, mlir::ValueRange{newTensor});
|
||||
});
|
||||
|
||||
// Rewrite original op.
|
||||
@@ -292,20 +260,19 @@ struct SubIntEintOpPattern : public CrtOpPattern<FHE::SubIntEintOp> {
|
||||
converter.convertType(eintOperand.getType())
|
||||
.cast<mlir::RankedTensorType>()
|
||||
.getElementType();
|
||||
mlir::Value output = writeBinaryTensorLoop(
|
||||
location, eintOperand, encodedPlaintextTensor, rewriter,
|
||||
mlir::Value output = writeUnaryTensorLoop(
|
||||
location, eintOperand.getType(), rewriter,
|
||||
[&](mlir::OpBuilder &builder, mlir::Location loc, mlir::Value iter,
|
||||
mlir::ValueRange args) {
|
||||
mlir::Value extractedEint =
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, args[0], iter);
|
||||
mlir::Value extractedInt =
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, args[1], iter);
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, eintOperand, iter);
|
||||
mlir::Value extractedInt = builder.create<mlir::tensor::ExtractOp>(
|
||||
loc, encodedPlaintextTensor, iter);
|
||||
mlir::Value output = builder.create<TFHE::SubGLWEIntOp>(
|
||||
loc, ciphertextScalarType, extractedInt, extractedEint);
|
||||
mlir::Value newTensor = builder.create<mlir::tensor::InsertOp>(
|
||||
loc, output, args[0], iter);
|
||||
builder.create<mlir::scf::YieldOp>(
|
||||
loc, mlir::ValueRange{newTensor, args[1]});
|
||||
builder.create<mlir::scf::YieldOp>(loc, mlir::ValueRange{newTensor});
|
||||
});
|
||||
|
||||
// Rewrite original op.
|
||||
@@ -355,20 +322,19 @@ struct SubEintIntOpPattern : public CrtOpPattern<FHE::SubEintIntOp> {
|
||||
converter.convertType(eintOperand.getType())
|
||||
.cast<mlir::RankedTensorType>()
|
||||
.getElementType();
|
||||
mlir::Value output = writeBinaryTensorLoop(
|
||||
location, eintOperand, encodedPlaintextTensor, rewriter,
|
||||
mlir::Value output = writeUnaryTensorLoop(
|
||||
location, eintOperand.getType(), rewriter,
|
||||
[&](mlir::OpBuilder &builder, mlir::Location loc, mlir::Value iter,
|
||||
mlir::ValueRange args) {
|
||||
mlir::Value extractedEint =
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, args[0], iter);
|
||||
mlir::Value extractedInt =
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, args[1], iter);
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, eintOperand, iter);
|
||||
mlir::Value extractedInt = builder.create<mlir::tensor::ExtractOp>(
|
||||
loc, encodedPlaintextTensor, iter);
|
||||
mlir::Value output = builder.create<TFHE::AddGLWEIntOp>(
|
||||
loc, ciphertextScalarType, extractedEint, extractedInt);
|
||||
mlir::Value newTensor = builder.create<mlir::tensor::InsertOp>(
|
||||
loc, output, args[0], iter);
|
||||
builder.create<mlir::scf::YieldOp>(
|
||||
loc, mlir::ValueRange{newTensor, args[1]});
|
||||
builder.create<mlir::scf::YieldOp>(loc, mlir::ValueRange{newTensor});
|
||||
});
|
||||
|
||||
// Rewrite original op.
|
||||
@@ -404,20 +370,19 @@ struct AddEintOpPattern : CrtOpPattern<FHE::AddEintOp> {
|
||||
converter.convertType(lhsOperand.getType())
|
||||
.cast<mlir::RankedTensorType>()
|
||||
.getElementType();
|
||||
mlir::Value output = writeBinaryTensorLoop(
|
||||
location, lhsOperand, rhsOperand, rewriter,
|
||||
mlir::Value output = writeUnaryTensorLoop(
|
||||
location, lhsOperand.getType(), rewriter,
|
||||
[&](mlir::OpBuilder &builder, mlir::Location loc, mlir::Value iter,
|
||||
mlir::ValueRange args) {
|
||||
mlir::Value extractedLhs =
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, args[0], iter);
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, lhsOperand, iter);
|
||||
mlir::Value extractedRhs =
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, args[1], iter);
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, rhsOperand, iter);
|
||||
mlir::Value output = builder.create<TFHE::AddGLWEOp>(
|
||||
loc, ciphertextScalarType, extractedLhs, extractedRhs);
|
||||
mlir::Value newTensor = builder.create<mlir::tensor::InsertOp>(
|
||||
loc, output, args[0], iter);
|
||||
builder.create<mlir::scf::YieldOp>(
|
||||
loc, mlir::ValueRange{newTensor, args[1]});
|
||||
builder.create<mlir::scf::YieldOp>(loc, mlir::ValueRange{newTensor});
|
||||
});
|
||||
|
||||
// Rewrite original op.
|
||||
@@ -453,22 +418,21 @@ struct SubEintOpPattern : CrtOpPattern<FHE::SubEintOp> {
|
||||
converter.convertType(lhsOperand.getType())
|
||||
.cast<mlir::RankedTensorType>()
|
||||
.getElementType();
|
||||
mlir::Value output = writeBinaryTensorLoop(
|
||||
location, lhsOperand, rhsOperand, rewriter,
|
||||
mlir::Value output = writeUnaryTensorLoop(
|
||||
location, lhsOperand.getType(), rewriter,
|
||||
[&](mlir::OpBuilder &builder, mlir::Location loc, mlir::Value iter,
|
||||
mlir::ValueRange args) {
|
||||
mlir::Value extractedLhs =
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, args[0], iter);
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, lhsOperand, iter);
|
||||
mlir::Value extractedRhs =
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, args[1], iter);
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, rhsOperand, iter);
|
||||
mlir::Value negatedRhs = builder.create<TFHE::NegGLWEOp>(
|
||||
loc, ciphertextScalarType, extractedRhs);
|
||||
mlir::Value output = builder.create<TFHE::AddGLWEOp>(
|
||||
loc, ciphertextScalarType, extractedLhs, negatedRhs);
|
||||
mlir::Value newTensor = builder.create<mlir::tensor::InsertOp>(
|
||||
loc, output, args[0], iter);
|
||||
builder.create<mlir::scf::YieldOp>(
|
||||
loc, mlir::ValueRange{newTensor, args[1]});
|
||||
builder.create<mlir::scf::YieldOp>(loc, mlir::ValueRange{newTensor});
|
||||
});
|
||||
|
||||
// Rewrite original op.
|
||||
@@ -502,11 +466,11 @@ struct NegEintOpPattern : CrtOpPattern<FHE::NegEintOp> {
|
||||
.cast<mlir::RankedTensorType>()
|
||||
.getElementType();
|
||||
mlir::Value loopRes = writeUnaryTensorLoop(
|
||||
location, operand, rewriter,
|
||||
location, operand.getType(), rewriter,
|
||||
[&](mlir::OpBuilder &builder, mlir::Location loc, mlir::Value iter,
|
||||
mlir::ValueRange args) {
|
||||
mlir::Value extractedCiphertext =
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, args[0], iter);
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, operand, iter);
|
||||
mlir::Value negatedCiphertext = builder.create<TFHE::NegGLWEOp>(
|
||||
loc, ciphertextScalarType, extractedCiphertext);
|
||||
mlir::Value newTensor = builder.create<mlir::tensor::InsertOp>(
|
||||
@@ -551,11 +515,11 @@ struct MulEintIntOpPattern : CrtOpPattern<FHE::MulEintIntOp> {
|
||||
.cast<mlir::RankedTensorType>()
|
||||
.getElementType();
|
||||
mlir::Value loopRes = writeUnaryTensorLoop(
|
||||
location, eintOperand, rewriter,
|
||||
location, eintOperand.getType(), rewriter,
|
||||
[&](mlir::OpBuilder &builder, mlir::Location loc, mlir::Value iter,
|
||||
mlir::ValueRange args) {
|
||||
mlir::Value extractedCiphertext =
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, args[0], iter);
|
||||
builder.create<mlir::tensor::ExtractOp>(loc, eintOperand, iter);
|
||||
mlir::Value negatedCiphertext = builder.create<TFHE::MulGLWEIntOp>(
|
||||
loc, ciphertextScalarType, extractedCiphertext, encodedCleartext);
|
||||
mlir::Value newTensor = builder.create<mlir::tensor::InsertOp>(
|
||||
|
||||
@@ -1,19 +1,19 @@
|
||||
// RUN: concretecompiler --action=dump-tfhe %s --large-integer-crt-decomposition=2,3,5,7,11 --large-integer-circuit-bootstrap=2,9 --large-integer-packing-keyswitch=694,1024,4,9 --v0-parameter=2,10,693,4,9,7,2 2>&1| FileCheck %s
|
||||
|
||||
// CHECK-LABEL: func.func @add_eint(%arg0: tensor<5x!TFHE.glwe<{_,_,_}{7}>>, %arg1: tensor<5x!TFHE.glwe<{_,_,_}{7}>>) -> tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
//CHECK-LABEL: func.func @add_eint(%arg0: tensor<5x!TFHE.glwe<{_,_,_}{7}>>, %arg1: tensor<5x!TFHE.glwe<{_,_,_}{7}>>) -> tensor<5x!TFHE.glwe<{_,_,_}{7}>> {
|
||||
//CHECK-NEXT: %0 = bufferization.alloc_tensor() : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
//CHECK-NEXT: %c0 = arith.constant 0 : index
|
||||
//CHECK-NEXT: %c1 = arith.constant 1 : index
|
||||
//CHECK-NEXT: %c5 = arith.constant 5 : index
|
||||
//CHECK-NEXT: %1 = scf.for %arg2 = %c0 to %c5 step %c1 iter_args(%arg3 = %0) -> (tensor<5x!TFHE.glwe<{_,_,_}{7}>>) {
|
||||
//CHECK-NEXT: %2 = tensor.extract %arg0[%arg2] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
//CHECK-NEXT: %3 = tensor.extract %arg1[%arg2] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
//CHECK-NEXT: %4 = "TFHE.add_glwe"(%2, %3) : (!TFHE.glwe<{_,_,_}{7}>, !TFHE.glwe<{_,_,_}{7}>) -> !TFHE.glwe<{_,_,_}{7}>
|
||||
//CHECK-NEXT: %5 = tensor.insert %4 into %arg3[%arg2] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
//CHECK-NEXT: scf.yield %5 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
//CHECK-NEXT: }
|
||||
//CHECK-NEXT: return %1 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
func.func @add_eint(%arg0: !FHE.eint<7>, %arg1: !FHE.eint<7>) -> !FHE.eint<7> {
|
||||
// CHECK-NEXT: %c0 = arith.constant 0 : index
|
||||
// CHECK-NEXT: %c1 = arith.constant 1 : index
|
||||
// CHECK-NEXT: %c5 = arith.constant 5 : index
|
||||
// CHECK-NEXT: %0:2 = scf.for %arg2 = %c0 to %c5 step %c1 iter_args(%arg3 = %arg0, %arg4 = %arg1) -> (tensor<5x!TFHE.glwe<{_,_,_}{7}>>, tensor<5x!TFHE.glwe<{_,_,_}{7}>>) {
|
||||
// CHECK-NEXT: %1 = tensor.extract %arg3[%arg2] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: %2 = tensor.extract %arg4[%arg2] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: %3 = "TFHE.add_glwe"(%1, %2) : (!TFHE.glwe<{_,_,_}{7}>, !TFHE.glwe<{_,_,_}{7}>) -> !TFHE.glwe<{_,_,_}{7}>
|
||||
// CHECK-NEXT: %4 = tensor.insert %3 into %arg3[%arg2] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: scf.yield %4, %arg4 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>, tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: return %0#0 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
|
||||
%1 = "FHE.add_eint"(%arg0, %arg1): (!FHE.eint<7>, !FHE.eint<7>) -> (!FHE.eint<7>)
|
||||
return %1: !FHE.eint<7>
|
||||
}
|
||||
|
||||
@@ -1,22 +1,22 @@
|
||||
// RUN: concretecompiler --action=dump-tfhe %s --large-integer-crt-decomposition=2,3,5,7,11 --large-integer-circuit-bootstrap=2,9 --large-integer-packing-keyswitch=694,1024,4,9 --v0-parameter=2,10,693,4,9,7,2 2>&1| FileCheck %s
|
||||
|
||||
// CHECK-LABEL: func.func @add_eint_int(%arg0: tensor<5x!TFHE.glwe<{_,_,_}{7}>>) -> tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-LABEL: func.func @add_eint_int(%arg0: tensor<5x!TFHE.glwe<{_,_,_}{7}>>) -> tensor<5x!TFHE.glwe<{_,_,_}{7}>> {
|
||||
// CHECK-NEXT: %c1_i8 = arith.constant 1 : i8
|
||||
// CHECK-NEXT: %0 = arith.extui %c1_i8 : i8 to i64
|
||||
// CHECK-NEXT: %1 = "TFHE.encode_plaintext_with_crt"(%0) {mods = [2, 3, 5, 7, 11], modsProd = 2310 : i64} : (i64) -> tensor<5xi64>
|
||||
// CHECK-NEXT: %2 = bufferization.alloc_tensor() : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: %c0 = arith.constant 0 : index
|
||||
// CHECK-NEXT: %c1 = arith.constant 1 : index
|
||||
// CHECK-NEXT: %c5 = arith.constant 5 : index
|
||||
// CHECK-NEXT: %3 = scf.for %arg1 = %c0 to %c5 step %c1 iter_args(%arg2 = %2) -> (tensor<5x!TFHE.glwe<{_,_,_}{7}>>) {
|
||||
// CHECK-NEXT: %4 = tensor.extract %arg0[%arg1] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: %5 = tensor.extract %1[%arg1] : tensor<5xi64>
|
||||
// CHECK-NEXT: %6 = "TFHE.add_glwe_int"(%4, %5) : (!TFHE.glwe<{_,_,_}{7}>, i64) -> !TFHE.glwe<{_,_,_}{7}>
|
||||
// CHECK-NEXT: %7 = tensor.insert %6 into %arg2[%arg1] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: scf.yield %7 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: return %3 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
func.func @add_eint_int(%arg0: !FHE.eint<7>) -> !FHE.eint<7> {
|
||||
// CHECK-NEXT: %c1_i8 = arith.constant 1 : i8
|
||||
// CHECK-NEXT: %0 = arith.extui %c1_i8 : i8 to i64
|
||||
// CHECK-NEXT: %1 = "TFHE.encode_plaintext_with_crt"(%0) {mods = [2, 3, 5, 7, 11], modsProd = 2310 : i64} : (i64) -> tensor<5xi64>
|
||||
// CHECK-NEXT: %c0 = arith.constant 0 : index
|
||||
// CHECK-NEXT: %c1 = arith.constant 1 : index
|
||||
// CHECK-NEXT: %c5 = arith.constant 5 : index
|
||||
// CHECK-NEXT: %2:2 = scf.for %arg1 = %c0 to %c5 step %c1 iter_args(%arg2 = %arg0, %arg3 = %1) -> (tensor<5x!TFHE.glwe<{_,_,_}{7}>>, tensor<5xi64>) {
|
||||
// CHECK-NEXT: %3 = tensor.extract %arg2[%arg1] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: %4 = tensor.extract %arg3[%arg1] : tensor<5xi64>
|
||||
// CHECK-NEXT: %5 = "TFHE.add_glwe_int"(%3, %4) : (!TFHE.glwe<{_,_,_}{7}>, i64) -> !TFHE.glwe<{_,_,_}{7}>
|
||||
// CHECK-NEXT: %6 = tensor.insert %5 into %arg2[%arg1] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: scf.yield %6, %arg3 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>, tensor<5xi64>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: return %2#0 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
|
||||
%0 = arith.constant 1 : i8
|
||||
%1 = "FHE.add_eint_int"(%arg0, %0): (!FHE.eint<7>, i8) -> (!FHE.eint<7>)
|
||||
return %1: !FHE.eint<7>
|
||||
|
||||
@@ -1,94 +1,99 @@
|
||||
// RUN: concretecompiler --action=dump-tfhe %s --large-integer-crt-decomposition=2,3,5,7,11 --large-integer-circuit-bootstrap=2,9 --large-integer-packing-keyswitch=694,1024,4,9 --v0-parameter=2,10,693,4,9,7,2 2>&1| FileCheck %s
|
||||
|
||||
// CHECK: func.func @conv2d(%arg0: tensor<100x3x28x28x5x!TFHE.glwe<{_,_,_}{2}>>, %arg1: tensor<4x3x14x14xi3>, %arg2: tensor<4xi3>) -> tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: %c4 = arith.constant 4 : index
|
||||
// CHECK-NEXT: %c100 = arith.constant 100 : index
|
||||
// CHECK-NEXT: %c15 = arith.constant 15 : index
|
||||
// CHECK-NEXT: %c0 = arith.constant 0 : index
|
||||
// CHECK-NEXT: %c1 = arith.constant 1 : index
|
||||
// CHECK-NEXT: %c3 = arith.constant 3 : index
|
||||
// CHECK-NEXT: %c14 = arith.constant 14 : index
|
||||
// CHECK-NEXT: %0 = "TFHE.zero_tensor"() : () -> tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: %1 = scf.for %arg3 = %c0 to %c100 step %c1 iter_args(%arg4 = %0) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
// CHECK-NEXT: %3 = scf.for %arg5 = %c0 to %c4 step %c1 iter_args(%arg6 = %arg4) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
// CHECK-NEXT: %4 = scf.for %arg7 = %c0 to %c15 step %c1 iter_args(%arg8 = %arg6) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
// CHECK-NEXT: %5 = scf.for %arg9 = %c0 to %c15 step %c1 iter_args(%arg10 = %arg8) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
// CHECK-NEXT: %6 = tensor.extract %arg2[%arg5] : tensor<4xi3>
|
||||
// CHECK-NEXT: %c0_0 = arith.constant 0 : index
|
||||
// CHECK-NEXT: %7 = tensor.extract_slice %0[%arg3, %arg5, %arg7, %arg9, %c0_0] [1, 1, 1, 1, 5] [1, 1, 1, 1, 1] : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>> to tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: %8 = arith.extui %6 : i3 to i64
|
||||
// CHECK-NEXT: %9 = "TFHE.encode_plaintext_with_crt"(%8) {mods = [2, 3, 5, 7, 11], modsProd = 2310 : i64} : (i64) -> tensor<5xi64>
|
||||
// CHECK-NEXT: %c0_1 = arith.constant 0 : index
|
||||
// CHECK-NEXT: %c1_2 = arith.constant 1 : index
|
||||
// CHECK-NEXT: %c5 = arith.constant 5 : index
|
||||
// CHECK-NEXT: %10:2 = scf.for %arg11 = %c0_1 to %c5 step %c1_2 iter_args(%arg12 = %7, %arg13 = %9) -> (tensor<5x!TFHE.glwe<{_,_,_}{2}>>, tensor<5xi64>) {
|
||||
// CHECK-NEXT: %12 = tensor.extract %arg12[%arg11] : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: %13 = tensor.extract %arg13[%arg11] : tensor<5xi64>
|
||||
// CHECK-NEXT: %14 = "TFHE.add_glwe_int"(%12, %13) : (!TFHE.glwe<{_,_,_}{2}>, i64) -> !TFHE.glwe<{_,_,_}{2}>
|
||||
// CHECK-NEXT: %15 = tensor.insert %14 into %arg12[%arg11] : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: scf.yield %15, %arg13 : tensor<5x!TFHE.glwe<{_,_,_}{2}>>, tensor<5xi64>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: %c0_3 = arith.constant 0 : index
|
||||
// CHECK-NEXT: %11 = tensor.insert_slice %10#0 into %arg10[%arg3, %arg5, %arg7, %arg9, %c0_3] [1, 1, 1, 1, 5] [1, 1, 1, 1, 1] : tensor<5x!TFHE.glwe<{_,_,_}{2}>> into tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: scf.yield %11 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: scf.yield %5 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: scf.yield %4 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: scf.yield %3 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: %2 = scf.for %arg3 = %c0 to %c100 step %c1 iter_args(%arg4 = %1) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
// CHECK-NEXT: %3 = scf.for %arg5 = %c0 to %c4 step %c1 iter_args(%arg6 = %arg4) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
// CHECK-NEXT: %4 = scf.for %arg7 = %c0 to %c15 step %c1 iter_args(%arg8 = %arg6) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
// CHECK-NEXT: %5 = scf.for %arg9 = %c0 to %c15 step %c1 iter_args(%arg10 = %arg8) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
// CHECK-NEXT: %6 = scf.for %arg11 = %c0 to %c3 step %c1 iter_args(%arg12 = %arg10) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
// CHECK-NEXT: %7 = scf.for %arg13 = %c0 to %c14 step %c1 iter_args(%arg14 = %arg12) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
// CHECK-NEXT: %8 = scf.for %arg15 = %c0 to %c14 step %c1 iter_args(%arg16 = %arg14) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
// CHECK-NEXT: %9 = affine.apply #map(%arg7, %arg13)
|
||||
// CHECK-NEXT: %10 = affine.apply #map(%arg9, %arg15)
|
||||
// CHECK-NEXT: %c0_0 = arith.constant 0 : index
|
||||
// CHECK-NEXT: %11 = tensor.extract_slice %arg0[%arg3, %arg11, %9, %10, %c0_0] [1, 1, 1, 1, 5] [1, 1, 1, 1, 1] : tensor<100x3x28x28x5x!TFHE.glwe<{_,_,_}{2}>> to tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: %12 = tensor.extract %arg1[%arg5, %arg11, %arg13, %arg15] : tensor<4x3x14x14xi3>
|
||||
// CHECK-NEXT: %c0_1 = arith.constant 0 : index
|
||||
// CHECK-NEXT: %13 = tensor.extract_slice %1[%arg3, %arg5, %arg7, %arg9, %c0_1] [1, 1, 1, 1, 5] [1, 1, 1, 1, 1] : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>> to tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: %14 = arith.extsi %12 : i3 to i64
|
||||
// CHECK-NEXT: %c0_2 = arith.constant 0 : index
|
||||
// CHECK-NEXT: %c1_3 = arith.constant 1 : index
|
||||
// CHECK-NEXT: %c5 = arith.constant 5 : index
|
||||
// CHECK-NEXT: %15 = scf.for %arg17 = %c0_2 to %c5 step %c1_3 iter_args(%arg18 = %11) -> (tensor<5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
// CHECK-NEXT: %18 = tensor.extract %arg18[%arg17] : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: %19 = "TFHE.mul_glwe_int"(%18, %14) : (!TFHE.glwe<{_,_,_}{2}>, i64) -> !TFHE.glwe<{_,_,_}{2}>
|
||||
// CHECK-NEXT: %20 = tensor.insert %19 into %arg18[%arg17] : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: scf.yield %20 : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: %c0_4 = arith.constant 0 : index
|
||||
// CHECK-NEXT: %c1_5 = arith.constant 1 : index
|
||||
// CHECK-NEXT: %c5_6 = arith.constant 5 : index
|
||||
// CHECK-NEXT: %16:2 = scf.for %arg17 = %c0_4 to %c5_6 step %c1_5 iter_args(%arg18 = %13, %arg19 = %15) -> (tensor<5x!TFHE.glwe<{_,_,_}{2}>>, tensor<5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
// CHECK-NEXT: %18 = tensor.extract %arg18[%arg17] : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: %19 = tensor.extract %arg19[%arg17] : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: %20 = "TFHE.add_glwe"(%18, %19) : (!TFHE.glwe<{_,_,_}{2}>, !TFHE.glwe<{_,_,_}{2}>) -> !TFHE.glwe<{_,_,_}{2}>
|
||||
// CHECK-NEXT: %21 = tensor.insert %20 into %arg18[%arg17] : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: scf.yield %21, %arg19 : tensor<5x!TFHE.glwe<{_,_,_}{2}>>, tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: %c0_7 = arith.constant 0 : index
|
||||
// CHECK-NEXT: %17 = tensor.insert_slice %16#0 into %arg16[%arg3, %arg5, %arg7, %arg9, %c0_7] [1, 1, 1, 1, 5] [1, 1, 1, 1, 1] : tensor<5x!TFHE.glwe<{_,_,_}{2}>> into tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: scf.yield %17 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: scf.yield %8 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: scf.yield %7 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: scf.yield %6 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: scf.yield %5 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: scf.yield %4 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: scf.yield %3 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: return %2 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
|
||||
//CHECK-LABEL: func.func @conv2d(%arg0: tensor<100x3x28x28x5x!TFHE.glwe<{_,_,_}{2}>>, %arg1: tensor<4x3x14x14xi3>, %arg2: tensor<4xi3>) -> tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>> {
|
||||
//CHECK-NEXT: %c4 = arith.constant 4 : index
|
||||
//CHECK-NEXT: %c100 = arith.constant 100 : index
|
||||
//CHECK-NEXT: %c15 = arith.constant 15 : index
|
||||
//CHECK-NEXT: %c0 = arith.constant 0 : index
|
||||
//CHECK-NEXT: %c1 = arith.constant 1 : index
|
||||
//CHECK-NEXT: %c3 = arith.constant 3 : index
|
||||
//CHECK-NEXT: %c14 = arith.constant 14 : index
|
||||
//CHECK-NEXT: %0 = "TFHE.zero_tensor"() : () -> tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: %1 = scf.for %arg3 = %c0 to %c100 step %c1 iter_args(%arg4 = %0) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
//CHECK-NEXT: %3 = scf.for %arg5 = %c0 to %c4 step %c1 iter_args(%arg6 = %arg4) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
//CHECK-NEXT: %4 = scf.for %arg7 = %c0 to %c15 step %c1 iter_args(%arg8 = %arg6) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
//CHECK-NEXT: %5 = scf.for %arg9 = %c0 to %c15 step %c1 iter_args(%arg10 = %arg8) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
//CHECK-NEXT: %6 = tensor.extract %arg2[%arg5] : tensor<4xi3>
|
||||
//CHECK-NEXT: %c0_0 = arith.constant 0 : index
|
||||
//CHECK-NEXT: %7 = tensor.extract_slice %0[%arg3, %arg5, %arg7, %arg9, %c0_0] [1, 1, 1, 1, 5] [1, 1, 1, 1, 1] : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>> to tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: %8 = arith.extui %6 : i3 to i64
|
||||
//CHECK-NEXT: %9 = "TFHE.encode_plaintext_with_crt"(%8) {mods = [2, 3, 5, 7, 11], modsProd = 2310 : i64} : (i64) -> tensor<5xi64>
|
||||
//CHECK-NEXT: %10 = bufferization.alloc_tensor() : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: %c0_1 = arith.constant 0 : index
|
||||
//CHECK-NEXT: %c1_2 = arith.constant 1 : index
|
||||
//CHECK-NEXT: %c5 = arith.constant 5 : index
|
||||
//CHECK-NEXT: %11 = scf.for %arg11 = %c0_1 to %c5 step %c1_2 iter_args(%arg12 = %10) -> (tensor<5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
//CHECK-NEXT: %13 = tensor.extract %7[%arg11] : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: %14 = tensor.extract %9[%arg11] : tensor<5xi64>
|
||||
//CHECK-NEXT: %15 = "TFHE.add_glwe_int"(%13, %14) : (!TFHE.glwe<{_,_,_}{2}>, i64) -> !TFHE.glwe<{_,_,_}{2}>
|
||||
//CHECK-NEXT: %16 = tensor.insert %15 into %arg12[%arg11] : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: scf.yield %16 : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: }
|
||||
//CHECK-NEXT: %c0_3 = arith.constant 0 : index
|
||||
//CHECK-NEXT: %12 = tensor.insert_slice %11 into %arg10[%arg3, %arg5, %arg7, %arg9, %c0_3] [1, 1, 1, 1, 5] [1, 1, 1, 1, 1] : tensor<5x!TFHE.glwe<{_,_,_}{2}>> into tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: scf.yield %12 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: }
|
||||
//CHECK-NEXT: scf.yield %5 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: }
|
||||
//CHECK-NEXT: scf.yield %4 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: }
|
||||
//CHECK-NEXT: scf.yield %3 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: }
|
||||
//CHECK-NEXT: %2 = scf.for %arg3 = %c0 to %c100 step %c1 iter_args(%arg4 = %1) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
//CHECK-NEXT: %3 = scf.for %arg5 = %c0 to %c4 step %c1 iter_args(%arg6 = %arg4) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
//CHECK-NEXT: %4 = scf.for %arg7 = %c0 to %c15 step %c1 iter_args(%arg8 = %arg6) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
//CHECK-NEXT: %5 = scf.for %arg9 = %c0 to %c15 step %c1 iter_args(%arg10 = %arg8) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
//CHECK-NEXT: %6 = scf.for %arg11 = %c0 to %c3 step %c1 iter_args(%arg12 = %arg10) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
//CHECK-NEXT: %7 = scf.for %arg13 = %c0 to %c14 step %c1 iter_args(%arg14 = %arg12) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
//CHECK-NEXT: %8 = scf.for %arg15 = %c0 to %c14 step %c1 iter_args(%arg16 = %arg14) -> (tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
//CHECK-NEXT: %9 = affine.apply #map(%arg7, %arg13)
|
||||
//CHECK-NEXT: %10 = affine.apply #map(%arg9, %arg15)
|
||||
//CHECK-NEXT: %c0_0 = arith.constant 0 : index
|
||||
//CHECK-NEXT: %11 = tensor.extract_slice %arg0[%arg3, %arg11, %9, %10, %c0_0] [1, 1, 1, 1, 5] [1, 1, 1, 1, 1] : tensor<100x3x28x28x5x!TFHE.glwe<{_,_,_}{2}>> to tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: %12 = tensor.extract %arg1[%arg5, %arg11, %arg13, %arg15] : tensor<4x3x14x14xi3>
|
||||
//CHECK-NEXT: %c0_1 = arith.constant 0 : index
|
||||
//CHECK-NEXT: %13 = tensor.extract_slice %1[%arg3, %arg5, %arg7, %arg9, %c0_1] [1, 1, 1, 1, 5] [1, 1, 1, 1, 1] : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>> to tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: %14 = arith.extsi %12 : i3 to i64
|
||||
//CHECK-NEXT: %15 = bufferization.alloc_tensor() : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: %c0_2 = arith.constant 0 : index
|
||||
//CHECK-NEXT: %c1_3 = arith.constant 1 : index
|
||||
//CHECK-NEXT: %c5 = arith.constant 5 : index
|
||||
//CHECK-NEXT: %16 = scf.for %arg17 = %c0_2 to %c5 step %c1_3 iter_args(%arg18 = %15) -> (tensor<5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
//CHECK-NEXT: %20 = tensor.extract %11[%arg17] : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: %21 = "TFHE.mul_glwe_int"(%20, %14) : (!TFHE.glwe<{_,_,_}{2}>, i64) -> !TFHE.glwe<{_,_,_}{2}>
|
||||
//CHECK-NEXT: %22 = tensor.insert %21 into %arg18[%arg17] : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: scf.yield %22 : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: }
|
||||
//CHECK-NEXT: %17 = bufferization.alloc_tensor() : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: %c0_4 = arith.constant 0 : index
|
||||
//CHECK-NEXT: %c1_5 = arith.constant 1 : index
|
||||
//CHECK-NEXT: %c5_6 = arith.constant 5 : index
|
||||
//CHECK-NEXT: %18 = scf.for %arg17 = %c0_4 to %c5_6 step %c1_5 iter_args(%arg18 = %17) -> (tensor<5x!TFHE.glwe<{_,_,_}{2}>>) {
|
||||
//CHECK-NEXT: %20 = tensor.extract %13[%arg17] : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: %21 = tensor.extract %16[%arg17] : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: %22 = "TFHE.add_glwe"(%20, %21) : (!TFHE.glwe<{_,_,_}{2}>, !TFHE.glwe<{_,_,_}{2}>) -> !TFHE.glwe<{_,_,_}{2}>
|
||||
//CHECK-NEXT: %23 = tensor.insert %22 into %arg18[%arg17] : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: scf.yield %23 : tensor<5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: }
|
||||
//CHECK-NEXT: %c0_7 = arith.constant 0 : index
|
||||
//CHECK-NEXT: %19 = tensor.insert_slice %18 into %arg16[%arg3, %arg5, %arg7, %arg9, %c0_7] [1, 1, 1, 1, 5] [1, 1, 1, 1, 1] : tensor<5x!TFHE.glwe<{_,_,_}{2}>> into tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: scf.yield %19 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: }
|
||||
//CHECK-NEXT: scf.yield %8 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: }
|
||||
//CHECK-NEXT: scf.yield %7 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: }
|
||||
//CHECK-NEXT: scf.yield %6 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: }
|
||||
//CHECK-NEXT: scf.yield %5 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: }
|
||||
//CHECK-NEXT: scf.yield %4 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: }
|
||||
//CHECK-NEXT: scf.yield %3 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: }
|
||||
//CHECK-NEXT: return %2 : tensor<100x4x15x15x5x!TFHE.glwe<{_,_,_}{2}>>
|
||||
//CHECK-NEXT: }
|
||||
func.func @conv2d(%input: tensor<100x3x28x28x!FHE.eint<2>>, %weight: tensor<4x3x14x14xi3>, %bias: tensor<4xi3>) -> tensor<100x4x15x15x!FHE.eint<2>> {
|
||||
%1 = "FHELinalg.conv2d"(%input, %weight, %bias){strides = dense<[1,1]> : tensor<2xi64>, dilations = dense<[1,1]> : tensor<2xi64>, padding = dense<[0, 0, 0, 0]> : tensor<4xi64>}: (tensor<100x3x28x28x!FHE.eint<2>>, tensor<4x3x14x14xi3>, tensor<4xi3>) -> tensor<100x4x15x15x!FHE.eint<2>>
|
||||
return %1 : tensor<100x4x15x15x!FHE.eint<2>>
|
||||
|
||||
@@ -1,20 +1,20 @@
|
||||
// RUN: concretecompiler --action=dump-tfhe %s --large-integer-crt-decomposition=2,3,5,7,11 --large-integer-circuit-bootstrap=2,9 --large-integer-packing-keyswitch=694,1024,4,9 --v0-parameter=2,10,693,4,9,7,2 2>&1| FileCheck %s
|
||||
|
||||
// CHECK-LABEL: func.func @mul_eint_int(%arg0: tensor<5x!TFHE.glwe<{_,_,_}{7}>>) -> tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-LABEL: func.func @mul_eint_int(%arg0: tensor<5x!TFHE.glwe<{_,_,_}{7}>>) -> tensor<5x!TFHE.glwe<{_,_,_}{7}>> {
|
||||
// CHECK-NEXT: %c2_i8 = arith.constant 2 : i8
|
||||
// CHECK-NEXT: %0 = arith.extsi %c2_i8 : i8 to i64
|
||||
// CHECK-NEXT: %1 = bufferization.alloc_tensor() : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: %c0 = arith.constant 0 : index
|
||||
// CHECK-NEXT: %c1 = arith.constant 1 : index
|
||||
// CHECK-NEXT: %c5 = arith.constant 5 : index
|
||||
// CHECK-NEXT: %2 = scf.for %arg1 = %c0 to %c5 step %c1 iter_args(%arg2 = %1) -> (tensor<5x!TFHE.glwe<{_,_,_}{7}>>) {
|
||||
// CHECK-NEXT: %3 = tensor.extract %arg0[%arg1] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: %4 = "TFHE.mul_glwe_int"(%3, %0) : (!TFHE.glwe<{_,_,_}{7}>, i64) -> !TFHE.glwe<{_,_,_}{7}>
|
||||
// CHECK-NEXT: %5 = tensor.insert %4 into %arg2[%arg1] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: scf.yield %5 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: return %2 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
func.func @mul_eint_int(%arg0: !FHE.eint<7>) -> !FHE.eint<7> {
|
||||
// CHECK-NEXT: %c2_i8 = arith.constant 2 : i8
|
||||
// CHECK-NEXT: %0 = arith.extsi %c2_i8 : i8 to i64
|
||||
// CHECK-NEXT: %c0 = arith.constant 0 : index
|
||||
// CHECK-NEXT: %c1 = arith.constant 1 : index
|
||||
// CHECK-NEXT: %c5 = arith.constant 5 : index
|
||||
// CHECK-NEXT: %1 = scf.for %arg1 = %c0 to %c5 step %c1 iter_args(%arg2 = %arg0) -> (tensor<5x!TFHE.glwe<{_,_,_}{7}>>) {
|
||||
// CHECK-NEXT: %2 = tensor.extract %arg2[%arg1] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: %3 = "TFHE.mul_glwe_int"(%2, %0) : (!TFHE.glwe<{_,_,_}{7}>, i64) -> !TFHE.glwe<{_,_,_}{7}>
|
||||
// CHECK-NEXT: %4 = tensor.insert %3 into %arg2[%arg1] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: scf.yield %4 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: return %1 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
|
||||
%0 = arith.constant 2 : i8
|
||||
%1 = "FHE.mul_eint_int"(%arg0, %0): (!FHE.eint<7>, i8) -> (!FHE.eint<7>)
|
||||
return %1: !FHE.eint<7>
|
||||
|
||||
@@ -1,18 +1,19 @@
|
||||
// RUN: concretecompiler --action=dump-tfhe %s --large-integer-crt-decomposition=2,3,5,7,11 --large-integer-circuit-bootstrap=2,9 --large-integer-packing-keyswitch=694,1024,4,9 --v0-parameter=2,10,693,4,9,7,2 2>&1| FileCheck %s
|
||||
|
||||
// CHECK-LABEL: func.func @neg_eint(%arg0: tensor<5x!TFHE.glwe<{_,_,_}{7}>>) -> tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-LABEL: func.func @neg_eint(%arg0: tensor<5x!TFHE.glwe<{_,_,_}{7}>>) -> tensor<5x!TFHE.glwe<{_,_,_}{7}>> {
|
||||
// CHECK-NEXT: %0 = bufferization.alloc_tensor() : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: %c0 = arith.constant 0 : index
|
||||
// CHECK-NEXT: %c1 = arith.constant 1 : index
|
||||
// CHECK-NEXT: %c5 = arith.constant 5 : index
|
||||
// CHECK-NEXT: %1 = scf.for %arg1 = %c0 to %c5 step %c1 iter_args(%arg2 = %0) -> (tensor<5x!TFHE.glwe<{_,_,_}{7}>>) {
|
||||
// CHECK-NEXT: %2 = tensor.extract %arg0[%arg1] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: %3 = "TFHE.neg_glwe"(%2) : (!TFHE.glwe<{_,_,_}{7}>) -> !TFHE.glwe<{_,_,_}{7}>
|
||||
// CHECK-NEXT: %4 = tensor.insert %3 into %arg2[%arg1] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: scf.yield %4 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: return %1 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: }
|
||||
func.func @neg_eint(%arg0: !FHE.eint<7>) -> !FHE.eint<7> {
|
||||
// CHECK-NEXT: %c0 = arith.constant 0 : index
|
||||
// CHECK-NEXT: %c1 = arith.constant 1 : index
|
||||
// CHECK-NEXT: %c5 = arith.constant 5 : index
|
||||
// CHECK-NEXT: %0 = scf.for %arg1 = %c0 to %c5 step %c1 iter_args(%arg2 = %arg0) -> (tensor<5x!TFHE.glwe<{_,_,_}{7}>>) {
|
||||
// CHECK-NEXT: %1 = tensor.extract %arg2[%arg1] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: %2 = "TFHE.neg_glwe"(%1) : (!TFHE.glwe<{_,_,_}{7}>) -> !TFHE.glwe<{_,_,_}{7}>
|
||||
// CHECK-NEXT: %3 = tensor.insert %2 into %arg2[%arg1] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: scf.yield %3 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: return %0 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
|
||||
%1 = "FHE.neg_eint"(%arg0): (!FHE.eint<7>) -> (!FHE.eint<7>)
|
||||
return %1: !FHE.eint<7>
|
||||
}
|
||||
|
||||
@@ -1,23 +1,23 @@
|
||||
// RUN: concretecompiler --action=dump-tfhe %s --large-integer-crt-decomposition=2,3,5,7,11 --large-integer-circuit-bootstrap=2,9 --large-integer-packing-keyswitch=694,1024,4,9 --v0-parameter=2,10,693,4,9,7,2 2>&1| FileCheck %s
|
||||
// RUN: concretecompiler --action=dump-tfhe %s --large-integer-crt-decomposition=2,3,5,7,11 --large-integer-circuit-bootstrap=2,9 --large-integer-packing-keyswitch=694,1024,4,9 --v0-parameter=2,10,693,4,9,7,2 2>&1| FileCheck %s
|
||||
|
||||
// CHECK-LABEL: func.func @sub_int_eint(%arg0: tensor<5x!TFHE.glwe<{_,_,_}{7}>>) -> tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-LABEL: func.func @sub_int_eint(%arg0: tensor<5x!TFHE.glwe<{_,_,_}{7}>>) -> tensor<5x!TFHE.glwe<{_,_,_}{7}>> {
|
||||
// CHECK-NEXT: %c1_i8 = arith.constant 1 : i8
|
||||
// CHECK-NEXT: %0 = arith.extui %c1_i8 : i8 to i64
|
||||
// CHECK-NEXT: %1 = "TFHE.encode_plaintext_with_crt"(%0) {mods = [2, 3, 5, 7, 11], modsProd = 2310 : i64} : (i64) -> tensor<5xi64>
|
||||
// CHECK-NEXT: %2 = bufferization.alloc_tensor() : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: %c0 = arith.constant 0 : index
|
||||
// CHECK-NEXT: %c1 = arith.constant 1 : index
|
||||
// CHECK-NEXT: %c5 = arith.constant 5 : index
|
||||
// CHECK-NEXT: %3 = scf.for %arg1 = %c0 to %c5 step %c1 iter_args(%arg2 = %2) -> (tensor<5x!TFHE.glwe<{_,_,_}{7}>>) {
|
||||
// CHECK-NEXT: %4 = tensor.extract %arg0[%arg1] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: %5 = tensor.extract %1[%arg1] : tensor<5xi64>
|
||||
// CHECK-NEXT: %6 = "TFHE.sub_int_glwe"(%5, %4) : (i64, !TFHE.glwe<{_,_,_}{7}>) -> !TFHE.glwe<{_,_,_}{7}>
|
||||
// CHECK-NEXT: %7 = tensor.insert %6 into %arg2[%arg1] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: scf.yield %7 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: return %3 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: }
|
||||
func.func @sub_int_eint(%arg0: !FHE.eint<7>) -> !FHE.eint<7> {
|
||||
// CHECK-NEXT: %c1_i8 = arith.constant 1 : i8
|
||||
// CHECK-NEXT: %0 = arith.extui %c1_i8 : i8 to i64
|
||||
// CHECK-NEXT: %1 = "TFHE.encode_plaintext_with_crt"(%0) {mods = [2, 3, 5, 7, 11], modsProd = 2310 : i64} : (i64) -> tensor<5xi64>
|
||||
// CHECK-NEXT: %c0 = arith.constant 0 : index
|
||||
// CHECK-NEXT: %c1 = arith.constant 1 : index
|
||||
// CHECK-NEXT: %c5 = arith.constant 5 : index
|
||||
// CHECK-NEXT: %2:2 = scf.for %arg1 = %c0 to %c5 step %c1 iter_args(%arg2 = %arg0, %arg3 = %1) -> (tensor<5x!TFHE.glwe<{_,_,_}{7}>>, tensor<5xi64>) {
|
||||
// CHECK-NEXT: %3 = tensor.extract %arg2[%arg1] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: %4 = tensor.extract %arg3[%arg1] : tensor<5xi64>
|
||||
// CHECK-NEXT: %5 = "TFHE.sub_int_glwe"(%4, %3) : (i64, !TFHE.glwe<{_,_,_}{7}>) -> !TFHE.glwe<{_,_,_}{7}>
|
||||
// CHECK-NEXT: %6 = tensor.insert %5 into %arg2[%arg1] : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
// CHECK-NEXT: scf.yield %6, %arg3 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>, tensor<5xi64>
|
||||
// CHECK-NEXT: }
|
||||
// CHECK-NEXT: return %2#0 : tensor<5x!TFHE.glwe<{_,_,_}{7}>>
|
||||
|
||||
%0 = arith.constant 1 : i8
|
||||
%1 = "FHE.sub_int_eint"(%0, %arg0): (i8, !FHE.eint<7>) -> (!FHE.eint<7>)
|
||||
return %1: !FHE.eint<7>
|
||||
|
||||
Reference in New Issue
Block a user