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Added Squat Packing's rotate and sum operation and resolved type mism…
…atch issues. PiperOrigin-RevId: 715833899
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366 changes: 264 additions & 102 deletions
366
lib/Dialect/LinAlg/Conversions/LinalgToTensorExt/LinalgToTensorExt.cpp
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47 changes: 47 additions & 0 deletions
47
tests/Dialect/LinAlg/Conversions/linalg_to_tensor_ext/float_small_fc_network.mlir
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| // This test verifies that a small fully connected network lowers with returning | ||
| // an error. | ||
| // TODO: write a test that verifies the correctness of the lowering. | ||
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| // RUN: heir-opt %s --linalg-to-tensor-ext=tiling-size=4 --tosa-to-secret-arith --canonicalize | FileCheck %s | ||
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| // CHECK: func.func @test_float_small_fc_network(%[[ARG:.*]]: !secret.secret<tensor<1x4xf32>>) | ||
| module { | ||
| func.func @test_float_small_fc_network(%input : !secret.secret<tensor<1x1xf32>>) -> !secret.secret<tensor<1x1xf32>> { | ||
| %matrix1 = arith.constant dense<[[1.0, 2.0, 3.0, 4.0]]> : tensor<1x4xf32> | ||
| %bias1 = arith.constant dense<[[5.0, 6.0, 7.0, 8.0]]> : tensor<1x4xf32> | ||
| %layer1 = secret.generic ins (%input : !secret.secret<tensor<1x1xf32>>) { | ||
| ^bb0(%converted_input1: tensor<1x1xf32>): | ||
| %0 = linalg.matmul ins(%converted_input1, %matrix1 : tensor<1x1xf32>, tensor<1x4xf32>) outs(%bias1 : tensor<1x4xf32>) -> tensor<1x4xf32> | ||
| secret.yield %0 : tensor<1x4xf32> | ||
| } -> !secret.secret<tensor<1x4xf32>> | ||
|
|
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| %activation_layer1 = secret.generic ins (%layer1 : !secret.secret<tensor<1x4xf32>>) { | ||
| ^bb0(%converted_activation_layer_vec1: tensor<1x4xf32>): | ||
| %0 = tosa.sigmoid %converted_activation_layer_vec1 : (tensor<1x4xf32>) -> tensor<1x4xf32> | ||
| secret.yield %0 : tensor<1x4xf32> | ||
| } -> !secret.secret<tensor<1x4xf32>> | ||
|
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| %matrix2 = arith.constant dense<[[10.0, 20.0, 30.0, 40.0], [50.0, 60.0, 70.0, 80.0], [90.0, 100.0, 110.0, 120.0], [130.0, 140.0, 150.0, 160.0]]> : tensor<4x4xf32> | ||
| %bias2 = arith.constant dense<[[170.0, 180.0, 190.0, 200.0]]> : tensor<1x4xf32> | ||
| %layer2 = secret.generic ins (%layer1 : !secret.secret<tensor<1x4xf32>>) { | ||
| ^bb0(%converted_vec2: tensor<1x4xf32>): | ||
| %1 = linalg.matmul ins(%converted_vec2, %matrix2 : tensor<1x4xf32>, tensor<4x4xf32>) outs(%bias2 : tensor<1x4xf32>) -> tensor<1x4xf32> | ||
| secret.yield %1 : tensor<1x4xf32> | ||
| } -> !secret.secret<tensor<1x4xf32>> | ||
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| %activation_layer2 = secret.generic ins (%layer2 : !secret.secret<tensor<1x4xf32>>) { | ||
| ^bb0(%converted_activation_layer_vec2: tensor<1x4xf32>): | ||
| %0 = tosa.sigmoid %converted_activation_layer_vec2 : (tensor<1x4xf32>) -> tensor<1x4xf32> | ||
| secret.yield %0 : tensor<1x4xf32> | ||
| } -> !secret.secret<tensor<1x4xf32>> | ||
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| %matrix3 = arith.constant dense<[[100.0], [200.0], [300.0], [400.0]]> : tensor<4x1xf32> | ||
| %bias3 = arith.constant dense<[[500.0]]> : tensor<1x1xf32> | ||
| %layer3 = secret.generic ins (%activation_layer2 : !secret.secret<tensor<1x4xf32>>) { | ||
| ^bb0(%converted_vec3: tensor<1x4xf32>): | ||
| %0 = linalg.matmul ins(%converted_vec3, %matrix3 : tensor<1x4xf32>, tensor<4x1xf32>) outs(%bias3 : tensor<1x1xf32>) -> tensor<1x1xf32> | ||
| secret.yield %0 : tensor<1x1xf32> | ||
| } -> !secret.secret<tensor<1x1xf32>> | ||
| return %layer3 : !secret.secret<tensor<1x1xf32>> | ||
| } | ||
| } |
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tests/Dialect/LinAlg/Conversions/linalg_to_tensor_ext/float_vector_small_matrix_matmul.mlir
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,33 @@ | ||
| // RUN: heir-opt %s --linalg-to-tensor-ext=tiling-size=4 --canonicalize | FileCheck %s | ||
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| // CHECK: func.func @test_float_vector_small_matrix_matmul(%[[ARG:.*]]: !secret.secret<tensor<1x4xf32>>) | ||
| // CHECK-DAG: %[[TWO:.*]] = arith.constant 2 : index | ||
| // CHECK-DAG: %[[ONE:.*]] = arith.constant 1 : index | ||
| // CHECK-DAG: %[[BIAS:.*]] = arith.constant dense<5.{{0*}}e+00> : tensor<1x4xf32> | ||
| // CHECK-DAG: %[[DIAGONALIZED_MATRIX:.*]] = arith.constant dense | ||
| // CHECK-SAME{LITERAL}: <[[ | ||
| // CHECK-SAME: 1.{{0*}}e+00, 2.{{0*}}e+00, 3.{{0*}}e+00, 4.{{0*}}e+00], [2.{{0*}}e+00, 3.{{0*}}e+00, 4.{{0*}}e+00, 1.{{0*}}e+00], [3.{{0*}}e+00, 4.{{0*}}e+00, 1.{{0*}}e+00, 2.{{0*}}e+00], [4.{{0*}}e+00, 1.{{0*}}e+00, 2.{{0*}}e+00, 3.{{0*}}e+00 | ||
| // CHECK-SAME{LITERAL}: ]]> | ||
| // CHECK-DAG: %[[SLICE:.*]] = tensor.extract_slice %[[DIAGONALIZED_MATRIX]][3, 0] [1, 4] [1, 1] | ||
| // CHECK: %[[OUT:.*]] = secret.generic ins(%[[ARG]] : !secret.secret<tensor<1x4xf32>>) | ||
| // CHECK: ^bb0(%[[ARG_CONVERTED:.*]]: tensor<1x4xf32>): | ||
| // CHECK: %[[MUL:.*]] = arith.mulf %[[ARG_CONVERTED]], %[[SLICE]] | ||
| // CHECK: %[[SUM:.*]] = arith.addf %[[MUL]], %[[BIAS]] | ||
| // CHECK: %[[ROTATE1:.*]] = tensor_ext.rotate %[[SUM]], %[[TWO]] | ||
| // CHECK: %[[ROTATE_AND_SUM_1:.*]] = arith.addf %[[SUM]], %[[ROTATE1]] | ||
| // CHECK: %[[ROTATE2:.*]] = tensor_ext.rotate %[[ROTATE_AND_SUM_1]], %[[ONE]] | ||
| // CHECK: %[[FINAL_SUM:.*]] = arith.addf %[[ROTATE_AND_SUM_1]], %[[ROTATE2]] | ||
| // CHECK: secret.yield %[[FINAL_SUM]] | ||
| // CHECK: return %[[OUT]] | ||
| module { | ||
| func.func @test_float_vector_small_matrix_matmul(%vec : !secret.secret<tensor<1x4xf32>>) -> !secret.secret<tensor<1x1xf32>> { | ||
| %matrix = arith.constant dense<[[1.0], [2.0], [3.0], [4.0]]> : tensor<4x1xf32> | ||
| %bias = arith.constant dense<[[5.0]]> : tensor<1x1xf32> | ||
| %out = secret.generic ins (%vec : !secret.secret<tensor<1x4xf32>>) { | ||
| ^bb0(%converted_vec: tensor<1x4xf32>): | ||
| %0 = linalg.matmul ins(%converted_vec, %matrix : tensor<1x4xf32>, tensor<4x1xf32>) outs(%bias : tensor<1x1xf32>) -> tensor<1x1xf32> | ||
| secret.yield %0 : tensor<1x1xf32> | ||
| } -> !secret.secret<tensor<1x1xf32>> | ||
| return %out : !secret.secret<tensor<1x1xf32>> | ||
| } | ||
| } |
38 changes: 19 additions & 19 deletions
38
...Dialect/LinAlg/Conversions/linalg_to_tensor_ext/float_vector_square_matrix_matmul_op.mlir
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36 changes: 36 additions & 0 deletions
36
...Dialect/LinAlg/Conversions/linalg_to_tensor_ext/integer_rect_matrix_vector_matmul_op.mlir
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,36 @@ | ||
| // RUN: heir-opt %s --linalg-to-tensor-ext=tiling-size=4 --canonicalize | FileCheck %s | ||
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| // CHECK: func.func @test_integer_rect_matrix_vector_matmul(%[[ARG:.*]]: !secret.secret<tensor<4x1xi16>>) | ||
| // CHECK-DAG: %[[ONE:.*]] = arith.constant 1 : index | ||
| // CHECK-DAG: %[[TWO:.*]] = arith.constant 2 : index | ||
| // CHECK-DAG: %[[BIAS:.*]] = arith.constant dense | ||
| // CHECK-SAME{LITERAL}: <[[17], [18], [17], [18]]> : tensor<4x1xi16> | ||
| // CHECK-DAG: %[[DIAGONALIZED_MATRIX:.*]] = arith.constant dense | ||
| // CHECK-SAME{LITERAL}: <[[1, 2, 3, 4], [6, 7, 8, 5], [3, 4, 1, 2], [8, 5, 6, 7]]> : tensor<4x4xi16> | ||
| // CHECK-DAG: %[[LAST_SLICE:.*]] = tensor.extract_slice %[[DIAGONALIZED_MATRIX]][0, 1] [4, 1] [1, 1] | ||
| // CHECK: %[[OUT:.*]] = secret.generic ins(%[[ARG]] : !secret.secret<tensor<4x1xi16>>) | ||
| // CHECK: ^bb0(%[[ARG_CONVERTED:.*]]: tensor<4x1xi16>): | ||
| // CHECK: %[[FOR_LOOP_OUT:.*]]:2 = affine.for %[[I:.*]] = 0 to 1 iter_args(%[[RUNNING_SUM:.*]] = %[[BIAS]], %[[ROTATED_VEC:.*]] = %[[ARG_CONVERTED]]) | ||
| // CHECK: %[[SLICE:.*]] = tensor.extract_slice %[[DIAGONALIZED_MATRIX]][0, %[[I]]] [4, 1] [1, 1] | ||
| // CHECK: %[[MUL:.*]] = arith.muli %[[ROTATED_VEC]], %[[SLICE]] | ||
| // CHECK: %[[UPDATED_SUM:.*]] = arith.addi %[[RUNNING_SUM]], %[[MUL]] | ||
| // CHECK: %[[UPDATED_ROTATED_VEC:.*]] = tensor_ext.rotate %[[ROTATED_VEC]], %[[ONE]] | ||
| // CHECK: affine.yield %[[UPDATED_SUM]], %[[UPDATED_ROTATED_VEC]] | ||
| // CHECK: %[[LAST_MUL:.*]] = arith.muli %[[FOR_LOOP_OUT]]#1, %[[LAST_SLICE]] | ||
| // CHECK: %[[BEFORE_ROTATE_AND_SUM:.*]] = arith.addi %[[FOR_LOOP_OUT]]#0, %[[LAST_MUL]] | ||
| // CHECK: %[[ROTATED_SUM:.*]] = tensor_ext.rotate %[[BEFORE_ROTATE_AND_SUM]], %[[TWO]] | ||
| // CHECK: %[[FINAL_SUM:.*]] = arith.addi %[[BEFORE_ROTATE_AND_SUM]], %[[ROTATED_SUM]] | ||
| // CHECK: secret.yield %[[FINAL_SUM]] | ||
| // CHECK: return %[[OUT]] | ||
| module { | ||
| func.func @test_integer_rect_matrix_vector_matmul(%vec : !secret.secret<tensor<4x1xi16>>) -> !secret.secret<tensor<2x1xi16>> { | ||
| %matrix = arith.constant dense<[[1, 2, 3, 4], [5, 6, 7, 8]]> : tensor<2x4xi16> | ||
| %bias = arith.constant dense<[[17], [18]]> : tensor<2x1xi16> | ||
| %out = secret.generic ins (%vec : !secret.secret<tensor<4x1xi16>>) { | ||
| ^bb0(%converted_vec: tensor<4x1xi16>): | ||
| %0 = linalg.matmul ins(%matrix, %converted_vec : tensor<2x4xi16>, tensor<4x1xi16>) outs(%bias : tensor<2x1xi16>) -> tensor<2x1xi16> | ||
| secret.yield %0 : tensor<2x1xi16> | ||
| } -> !secret.secret<tensor<2x1xi16>> | ||
| return %out : !secret.secret<tensor<2x1xi16>> | ||
| } | ||
| } |
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...ialect/LinAlg/Conversions/linalg_to_tensor_ext/integer_small_vector_matrix_matmul_op.mlir
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,33 @@ | ||
| // RUN: heir-opt %s --linalg-to-tensor-ext=tiling-size=4 --canonicalize | FileCheck %s | ||
|
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| // CHECK: func.func @test_integer_square_matrix_vector_matmul(%[[ARG:.*]]: !secret.secret<tensor<4x1xi16>>) | ||
| // CHECK-DAG: %[[ONE:.*]] = arith.constant 1 : index | ||
| // CHECK-DAG: %[[DIAGONALIZED_MATRIX:.*]] = arith.constant dense | ||
| // CHECK-SAME{LITERAL}: <[[1, 2, 3, 4], [6, 7, 8, 5], [11, 12, 9, 10], [16, 13, 14, 15]]> : tensor<4x4xi16> | ||
| // CHECK-DAG: %[[BIAS:.*]] = arith.constant dense | ||
| // CHECK-SAME{LITERAL}: <[[17], [18], [19], [20]]> : tensor<4x1xi16> | ||
| // CHECK-DAG: %[[LAST_SLICE:.*]] = tensor.extract_slice %[[DIAGONALIZED_MATRIX]][0, 3] [4, 1] [1, 1] | ||
| // CHECK: %[[OUT:.*]] = secret.generic ins(%[[ARG]] : !secret.secret<tensor<4x1xi16>>) | ||
| // CHECK: ^bb0(%[[ARG_CONVERTED:.*]]: tensor<4x1xi16>): | ||
| // CHECK: %[[FOR_LOOP_OUT:.*]]:2 = affine.for %[[I:.*]] = 0 to 3 iter_args(%[[RUNNING_SUM:.*]] = %[[BIAS]], %[[ROTATED_VEC:.*]] = %[[ARG_CONVERTED]]) | ||
| // CHECK: %[[SLICE:.*]] = tensor.extract_slice %[[DIAGONALIZED_MATRIX]][0, %[[I]]] [4, 1] [1, 1] | ||
| // CHECK: %[[MUL:.*]] = arith.muli %[[ROTATED_VEC]], %[[SLICE]] | ||
| // CHECK: %[[UPDATED_SUM:.*]] = arith.addi %[[RUNNING_SUM]], %[[MUL]] | ||
| // CHECK: %[[UPDATED_ROTATED_VEC:.*]] = tensor_ext.rotate %[[ROTATED_VEC]], %[[ONE]] | ||
| // CHECK: affine.yield %[[UPDATED_SUM]], %[[UPDATED_ROTATED_VEC]] | ||
| // CHECK: %[[LAST_MUL:.*]] = arith.muli %[[FOR_LOOP_OUT]]#1, %[[LAST_SLICE]] | ||
| // CHECK: %[[FINAL_SUM:.*]] = arith.addi %[[FOR_LOOP_OUT]]#0, %[[LAST_MUL]] | ||
| // CHECK: secret.yield %[[FINAL_SUM]] | ||
| // CHECK: return %[[OUT]] | ||
| module { | ||
| func.func @test_integer_square_matrix_vector_matmul(%vec : !secret.secret<tensor<4x1xi16>>) -> !secret.secret<tensor<4x1xi16>> { | ||
| %matrix = arith.constant dense<[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12], [13, 14, 15, 16]]> : tensor<4x4xi16> | ||
| %bias = arith.constant dense<[[17], [18], [19], [20]]> : tensor<4x1xi16> | ||
| %out = secret.generic ins (%vec : !secret.secret<tensor<4x1xi16>>) { | ||
| ^bb0(%converted_vec: tensor<4x1xi16>): | ||
| %0 = linalg.matmul ins(%matrix, %converted_vec : tensor<4x4xi16>, tensor<4x1xi16>) outs(%bias : tensor<4x1xi16>) -> tensor<4x1xi16> | ||
| secret.yield %0 : tensor<4x1xi16> | ||
| } -> !secret.secret<tensor<4x1xi16>> | ||
| return %out : !secret.secret<tensor<4x1xi16>> | ||
| } | ||
| } |
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