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module { |
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tt.func public @triton__0d1de(%arg0: !tt.ptr<bf16, 1> {tt.divisibility = 16 : i32}, %arg1: i32 {tt.divisibility = 16 : i32, tt.max_divisibility = 16 : i32}) attributes {noinline = false} { |
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%cst = arith.constant dense<1.000000e+00> : tensor<1024xf32> |
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%cst_0 = arith.constant dense<0.707106769> : tensor<1024xf32> |
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%cst_1 = arith.constant dense<5.000000e-01> : tensor<1024xf32> |
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%c1024_i32 = arith.constant 1024 : i32 |
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%0 = tt.get_program_id x : i32 |
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%1 = arith.muli %0, %c1024_i32 : i32 |
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%2 = tt.make_range {end = 1024 : i32, start = 0 : i32} : tensor<1024xi32> |
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%3 = tt.splat %1 : (i32) -> tensor<1024xi32> |
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%4 = arith.addi %3, %2 : tensor<1024xi32> |
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%5 = tt.splat %arg0 : (!tt.ptr<bf16, 1>) -> tensor<1024x!tt.ptr<bf16, 1>> |
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%6 = tt.addptr %5, %4 : tensor<1024x!tt.ptr<bf16, 1>>, tensor<1024xi32> |
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%7 = tt.load %6 {cache = 1 : i32, evict = 1 : i32, isVolatile = false} : tensor<1024xbf16> |
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%8 = arith.extf %7 : tensor<1024xbf16> to tensor<1024xf32> |
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%9 = arith.mulf %8, %cst_1 : tensor<1024xf32> |
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%10 = arith.mulf %8, %cst_0 : tensor<1024xf32> |
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%11 = tt.extern_elementwise %10 {libname = "libdevice", libpath = "/usr/local/lib/python3.10/dist-packages/triton/language/../third_party/cuda/lib/libdevice.10.bc", pure = true, symbol = "__nv_erff"} : (tensor<1024xf32>) -> tensor<1024xf32> |
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%12 = arith.addf %11, %cst : tensor<1024xf32> |
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%13 = arith.mulf %9, %12 : tensor<1024xf32> |
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%14 = arith.truncf %13 : tensor<1024xf32> to tensor<1024xbf16> |
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tt.store %6, %14 {cache = 1 : i32, evict = 1 : i32} : tensor<1024xbf16> |
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tt.return |
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} |
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} |
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