Bump llvm to llvm/llvm-project@a58e774 (#19863)

Bump llvm to
llvm/llvm-project@a58e774
with cherry picks: 

llvm/llvm-project@b108fbe

llvm/llvm-project@4eb7c34

llvm/llvm-project@3a1e157

Bump torch-mlir to
llvm/torch-mlir@eefc553ffca45fd243
Bump stablehlo to openxla/stablehlo@8993ef70

compiler/bindings/python/iree/compiler/tools/__init__.py

@@ -20,7 +20,8 @@
 
   SIMPLE_MUL_ASM = """
   func.func @simple_mul(%arg0: tensor<4xf32>, %arg1: tensor<4xf32>) -> tensor<4xf32> {
-      %0 = tosa.mul %arg0, %arg1 {shift = 0 : i8} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32>
+      %shift = "tosa.const"() {value = dense<0> : tensor<1xi8>} : () -> tensor<1xi8>
+      %0 = tosa.mul %arg0, %arg1, %shift : (tensor<4xf32>, tensor<4xf32>, tensor<1xi8>) -> tensor<4xf32>
       return %0 : tensor<4xf32>
   }
   """

tests/e2e/regression/layernorm.mlir

@@ -7,16 +7,17 @@
 //   %x = util.unfoldable_constant dense<5.0> : tensor<128x384xf32>
 //   %c384 = util.unfoldable_constant dense<384.0> : tensor<128x1xf32>
 //   %sum = tosa.reduce_sum %x {axis = 1 : i64} : (tensor<128x384xf32>) -> tensor<128x1xf32>
+//   %shift = "tosa.const"() {value = dense<0> : tensor<1xi8>} : () -> tensor<1xi8>
 //   %r384 = tosa.reciprocal %c384 : (tensor<128x1xf32>) -> tensor<128x1xf32>
-//   %mean = tosa.mul %sum, %r384 {shift = 0 : i8} : (tensor<128x1xf32>, tensor<128x1xf32>) -> tensor<128x1xf32>
+//   %mean = tosa.mul %sum, %r384, %shift : (tensor<128x1xf32>, tensor<128x1xf32>, tensor<1xi8>) -> tensor<128x1xf32>
 //   %x_sub_mean = tosa.sub %x, %mean : (tensor<128x384xf32>, tensor<128x1xf32>) -> tensor<128x384xf32>
-//   %square = tosa.mul %x_sub_mean, %x_sub_mean {shift = 0 : i8} : (tensor<128x384xf32>, tensor<128x384xf32>) -> tensor<128x384xf32>
+//   %square = tosa.mul %x_sub_mean, %x_sub_mean, %shift : (tensor<128x384xf32>, tensor<128x384xf32>, tensor<1xi8>) -> tensor<128x384xf32>
 //   %square_sum = tosa.reduce_sum %square {axis = 1 : i64} : (tensor<128x384xf32>) -> tensor<128x1xf32>
-//   %variance = tosa.mul %square_sum, %r384 {shift = 0 : i8} : (tensor<128x1xf32>, tensor<128x1xf32>) -> tensor<128x1xf32>
+//   %variance = tosa.mul %square_sum, %r384, %shift : (tensor<128x1xf32>, tensor<128x1xf32>, tensor<1xi8>) -> tensor<128x1xf32>
 //   %epsilon = util.unfoldable_constant dense<9.99999996E-13> : tensor<128x1xf32>
 //   %var_eps = tosa.add %variance, %epsilon : (tensor<128x1xf32>, tensor<128x1xf32>) -> tensor<128x1xf32>
 //   %rsigma = tosa.rsqrt %var_eps : (tensor<128x1xf32>) -> tensor<128x1xf32>
-//   %norm = tosa.mul %x_sub_mean, %rsigma {shift = 0 : i8} : (tensor<128x384xf32>, tensor<128x1xf32>) -> tensor<128x384xf32>
+//   %norm = tosa.mul %x_sub_mean, %rsigma, %shift : (tensor<128x384xf32>, tensor<128x1xf32>, tensor<1xi8>) -> tensor<128x384xf32>
 //   check.expect_almost_eq_const(%norm, dense<0.0> : tensor<128x384xf32>) : tensor<128x384xf32>
 //   return
 // }

tests/e2e/regression/softmax.mlir

@@ -7,7 +7,8 @@
 //   %exp = tosa.exp %sub : (tensor<12x128x128xf32>) -> tensor<12x128x128xf32>
 //   %sum = tosa.reduce_sum %exp {axis = 2 : i64} : (tensor<12x128x128xf32>) -> tensor<12x128x1xf32>
 //   %rec = tosa.reciprocal %sum : (tensor<12x128x1xf32>) -> tensor<12x128x1xf32>
-//   %mul = tosa.mul %exp, %rec {shift = 0 : i8} : (tensor<12x128x128xf32>, tensor<12x128x1xf32>) -> tensor<12x128x128xf32>
+//   %shift = "tosa.const"() {value = dense<0> : tensor<1xi8>} : () -> tensor<1xi8>
+//   %mul = tosa.mul %exp, %rec, %shift : (tensor<12x128x128xf32>, tensor<12x128x1xf32>, tensor<1xi8>) -> tensor<12x128x128xf32>
 //   check.expect_almost_eq_const(%mul, dense<0.0078125> : tensor<12x128x128xf32>) : tensor<12x128x128xf32>
 //   return
 // }

tests/e2e/tosa_ops/mul.mlir

@@ -1,15 +1,17 @@
 func.func @tensor_float() {
   %0 = util.unfoldable_constant dense<[1.0, 0.0, 3.0, 4.0]> : tensor<4xf32>
   %1 = util.unfoldable_constant dense<[5.0, 6.0, -3.0, 8.0]> : tensor<4xf32>
-  %result = tosa.mul %0, %1 {shift = 0 : i8} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32>
+  %shift = "tosa.const"() {value = dense<0> : tensor<1xi8>} : () -> tensor<1xi8>
+  %result = tosa.mul %0, %1, %shift : (tensor<4xf32>, tensor<4xf32>, tensor<1xi8>) -> tensor<4xf32>
   check.expect_almost_eq_const(%result, dense<[5.0, 0.0, -9.0, 32.0]> : tensor<4xf32>) : tensor<4xf32>
   return
 }
 
 func.func @tensor_int() {
   %0 = util.unfoldable_constant dense<[1, 0, 3, 4]> : tensor<4xi32>
   %1 = util.unfoldable_constant dense<[5, 6, -3, 8]> : tensor<4xi32>
-  %result = tosa.mul %0, %1 {shift = 0 : i8} : (tensor<4xi32>, tensor<4xi32>) -> tensor<4xi32>
+  %shift = "tosa.const"() {value = dense<0> : tensor<1xi8>} : () -> tensor<1xi8>
+  %result = tosa.mul %0, %1, %shift : (tensor<4xi32>, tensor<4xi32>, tensor<1xi8>) -> tensor<4xi32>
   check.expect_eq_const(%result, dense<[5, 0, -9, 32]> : tensor<4xi32>) : tensor<4xi32>
   return
 }

tests/e2e/tosa_ops/mul_shift.mlir

@@ -5,7 +5,8 @@
 func.func @tensor_int_shifted() {
   %0 = util.unfoldable_constant dense<[1, 0, 3, 4, 4]> : tensor<5xi32>
   %1 = util.unfoldable_constant dense<[5, 6, -3, 8, 8]> : tensor<5xi32>
-  %result = tosa.mul %0, %1 {shift = 1 : i8} : (tensor<5xi32>, tensor<5xi32>) -> tensor<5xi32>
+  %shift = "tosa.const"() {value = dense<1> : tensor<1xi8>} : () -> tensor<1xi8>
+  %result = tosa.mul %0, %1, %shift : (tensor<5xi32>, tensor<5xi32>, tensor<1xi8>) -> tensor<5xi32>
   check.expect_eq_const(%result, dense<[3, 0, -4, 16, 16]> : tensor<5xi32>) : tensor<5xi32>
   return
 }