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Handle one-sided constants in insert-rotate
This PR ports the gx_kernel evaluation artifact from HECO, and supports it by doing two things: - Adding a canonicalize pass before insert-rotate but after full-loop-unroll, to ensure that ND tensors of constants are materialized to constants of tensors. - Adding two patterns to splat constants into tensors during rotations insertion. This leaves unanswered an important question: how should we detect and handle plaintext types that are not constants (say, function inputs or function inputs that are modified by some IR-internal ops). I will file a followup issue on that topic. Note canonicalize slows the box_blur_64x64 test to a crawl (> 15m), so I converted it to "enormous" size so that it is skipped in CI. Part of #571 PiperOrigin-RevId: 621247689
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// RUN: heir-opt --secretize=entry-function=gx_kernel --wrap-generic --canonicalize --cse \ | ||
// RUN: --heir-simd-vectorizer %s | FileCheck %s | ||
|
||
// CHECK-LABEL: @gx_kernel | ||
// CHECK: secret.generic | ||
// CHECK-COUNT-6: tensor_ext.rotate | ||
// CHECK-NOT: tensor_ext.rotate | ||
func.func @gx_kernel(%arg0: tensor<64xi16>) -> tensor<64xi16> { | ||
%c64 = arith.constant 64 : index | ||
%c8 = arith.constant 8 : index | ||
%c1_index = arith.constant 1 : index | ||
%c0_si16 = arith.constant 0 : i16 | ||
%c0 = arith.constant 0 : i16 | ||
%c1 = arith.constant 1 : i16 | ||
%c2 = arith.constant 2 : i16 | ||
%cm1= arith.constant -1 : i16 | ||
%cm2 = arith.constant -2 : i16 | ||
%weight_matrix = tensor.from_elements %c1, %cm1, %c2, %cm2, %c1, %cm1, %c0, %c0, %c0 : tensor<3x3xi16> | ||
%0 = affine.for %x = 0 to 8 iter_args(%arg0_x = %arg0) -> (tensor<64xi16>) { | ||
%1 = affine.for %y = 0 to 8 iter_args(%arg0_y = %arg0_x) -> (tensor<64xi16>) { | ||
%2 = affine.for %j = -1 to 2 iter_args(%value_j = %c0_si16) -> (i16) { | ||
%6 = affine.for %i = -1 to 2 iter_args(%value_i = %value_j) -> (i16) { | ||
%7 = arith.addi %x, %i : index | ||
%8 = arith.muli %7, %c8 : index | ||
%9 = arith.addi %y, %j : index | ||
%10 = arith.addi %8, %9 : index | ||
%11 = arith.remui %10, %c64 : index | ||
%12 = tensor.extract %arg0[%11] : tensor<64xi16> | ||
// Get the weight from the weight matrix! | ||
%ip = arith.addi %i,%c1_index : index | ||
%jp = arith.addi %j,%c1_index : index | ||
%w = tensor.extract %weight_matrix[%ip,%jp] : tensor<3x3xi16> | ||
%mul = arith.muli %12, %w : i16 | ||
%13 = arith.addi %value_i, %mul : i16 | ||
affine.yield %13 : i16 | ||
} | ||
affine.yield %6 : i16 | ||
} | ||
%3 = arith.muli %c8, %x : index | ||
%4 = arith.addi %3, %y : index | ||
%5 = arith.remui %4, %c64 : index | ||
%6 = tensor.insert %2 into %arg0_y[%5] : tensor<64xi16> | ||
affine.yield %6 : tensor<64xi16> | ||
} | ||
affine.yield %1 : tensor<64xi16> | ||
} | ||
return %0 : tensor<64xi16> | ||
} |
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