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Aug 31, 2025
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Update expected test results #541

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41 changes: 21 additions & 20 deletions test/test_examples.expected
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Original file line number Diff line number Diff line change
Expand Up @@ -568,6 +568,7 @@ import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch._inductor.runtime.triton_compat import libdevice
from helion.runtime import default_launcher as _default_launcher

@triton.jit
Expand All @@ -587,7 +588,7 @@ def _helion_cross_entropy(labels, logits_flat, logits, losses, labels_stride_0,
_mask_to = tl.where(tl.broadcast_to(mask_1[None, :], [1, _RDIM_SIZE_1]), logits_rows, float('-inf'))
max_logits = tl.reshape(tl.max(_mask_to, 1), [1, 1])
v_4 = logits_rows - max_logits
v_5 = tl_math.exp(v_4)
v_5 = libdevice.exp(v_4)
_mask_to_1 = tl.where(tl.broadcast_to(mask_1[None, :], [1, _RDIM_SIZE_1]), v_5, 0)
sum_exp = tl.reshape(tl.sum(_mask_to_1, 1), [1, 1])
squeeze = tl.reshape(max_logits, [1])
Expand Down Expand Up @@ -1020,7 +1021,7 @@ import torch
import triton
import triton.language as tl
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch._inductor.runtime.triton_compat import libdevice
from helion.runtime import default_launcher as _default_launcher

@triton.jit
Expand Down Expand Up @@ -1085,14 +1086,14 @@ def _helion_jagged_softmax_kernel(x_offsets, x_flat, out, out_stride_0, x_flat_s
slice_max = tl.max(_mask_to_1, 1)
block_new_max = triton_helpers.maximum(block_max_copy_0, slice_max)
v_17 = block_max_copy_0 - block_new_max
v_18 = tl_math.exp(v_17)
v_18 = libdevice.exp(v_17)
v_19 = block_L_copy_0 * v_18
subscript_8 = block_new_max[:, None, :]
v_20 = x_slice - subscript_8
v_21 = float('-inf')
v_22 = v_21[None, None, None]
v_23 = tl.where(v_12, v_20, v_22)
v_24 = tl_math.exp(v_23)
v_24 = libdevice.exp(v_23)
_mask_to_2 = tl.where(mask_0[:, None, None] & mask_2[None, :, None] & mask_1[None, None, :], v_24, 0)
sum_1 = tl.sum(_mask_to_2, 1)
block_L = v_19 + sum_1
Expand Down Expand Up @@ -1129,7 +1130,7 @@ def _helion_jagged_softmax_kernel(x_offsets, x_flat, out, out_stride_0, x_flat_s
x_slice_1 = tl.load(x_flat + v_30 * x_flat_stride_0, mask_0[:, None, None] & mask_3[None, :, None] & mask_1[None, None, :] & v_35, other=0)
subscript_17 = block_max_copy_1_0[:, None, :]
v_36 = x_slice_1 - subscript_17
v_37 = tl_math.exp(v_36)
v_37 = libdevice.exp(v_36)
subscript_18 = block_L_copy_1_0[:, None, :]
v_38 = v_37 / subscript_18
tl.store(out + v_30 * out_stride_0, v_38, mask_0[:, None, None] & mask_3[None, :, None] & mask_1[None, None, :] & v_35)
Expand Down Expand Up @@ -1713,7 +1714,7 @@ from __future__ import annotations
import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch._inductor.runtime.triton_compat import libdevice
from helion.runtime import default_launcher as _default_launcher

@triton.jit
Expand All @@ -1726,7 +1727,7 @@ def _helion_softmax(x, out, out_size_0, out_size_1, x_size_0, x_size_1, out_stri
_mask_to = tl.where(tl.broadcast_to(mask_1[None, :], [1, _RDIM_SIZE_1]), load, float('-inf'))
amax = tl.reshape(tl.max(_mask_to, 1), [1, 1])
v_0 = load - amax
v_1 = tl_math.exp(v_0)
v_1 = libdevice.exp(v_0)
_mask_to_1 = tl.where(tl.broadcast_to(mask_1[None, :], [1, _RDIM_SIZE_1]), v_1, 0)
sum_1 = tl.reshape(tl.sum(_mask_to_1, 1), [1, 1])
v_2 = v_1 / sum_1
Expand All @@ -1752,7 +1753,7 @@ from __future__ import annotations
import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch._inductor.runtime.triton_compat import libdevice
from helion.runtime import default_launcher as _default_launcher

@triton.jit
Expand All @@ -1765,7 +1766,7 @@ def _helion_softmax_decomposed(x, out, out_size_0, out_size_1, x_size_0, x_size_
_mask_to = tl.where(tl.broadcast_to(mask_1[None, :], [1, _RDIM_SIZE_1]), values, float('-inf'))
amax = tl.reshape(tl.max(_mask_to, 1), [1, 1])
v_0 = values - amax
v_1 = tl_math.exp(v_0)
v_1 = libdevice.exp(v_0)
_mask_to_1 = tl.where(tl.broadcast_to(mask_1[None, :], [1, _RDIM_SIZE_1]), v_1, 0)
sum_exp = tl.reshape(tl.sum(_mask_to_1, 1), [1, 1])
v_2 = v_1 / sum_exp
Expand Down Expand Up @@ -1793,7 +1794,7 @@ import torch
import triton
import triton.language as tl
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch._inductor.runtime.triton_compat import libdevice
from helion.runtime import default_launcher as _default_launcher

@triton.jit
Expand All @@ -1816,7 +1817,7 @@ def _helion_softmax(x, out, out_size_0, out_size_1, x_size_0, x_size_1, out_stri
amax_copy = amax
load_1 = tl.load(tl.make_block_ptr(x, [x_size_0, x_size_1], [x_stride_0, x_stride_1], [offset_0, roffset_1], [1, _REDUCTION_BLOCK_1], [1, 0]), boundary_check=[0, 1], padding_option='zero')
v_1 = load_1 - amax_copy
v_2 = tl_math.exp(v_1)
v_2 = libdevice.exp(v_1)
_mask_to_1 = tl.where(tl.broadcast_to(mask_1[None, :], [1, _REDUCTION_BLOCK_1]), v_2, 0)
v_3 = sum_1_acc + _mask_to_1
sum_1_acc = v_3
Expand All @@ -1828,7 +1829,7 @@ def _helion_softmax(x, out, out_size_0, out_size_1, x_size_0, x_size_1, out_stri
sum_1_copy = sum_1
load_2 = tl.load(tl.make_block_ptr(x, [x_size_0, x_size_1], [x_stride_0, x_stride_1], [offset_0, roffset_1], [1, _REDUCTION_BLOCK_1], [1, 0]), boundary_check=[0, 1], padding_option='zero')
v_4 = load_2 - amax_copy_1
v_5 = tl_math.exp(v_4)
v_5 = libdevice.exp(v_4)
v_6 = v_5 / sum_1_copy
tl.store(tl.make_block_ptr(out, [out_size_0, out_size_1], [out_stride_0, out_stride_1], [offset_0, roffset_1], [1, _REDUCTION_BLOCK_1], [1, 0]), v_6, boundary_check=[0, 1])

Expand All @@ -1853,7 +1854,7 @@ import torch
import triton
import triton.language as tl
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch._inductor.runtime.triton_compat import libdevice
from helion.runtime import default_launcher as _default_launcher

@triton.jit
Expand All @@ -1876,11 +1877,11 @@ def _helion_softmax_two_pass(x, out, out_stride_0, out_stride_1, x_stride_0, x_s
local_amax = tl.max(_mask_to, 1)
v_0 = triton_helpers.maximum(mi_copy_0, local_amax)
v_1 = mi_copy_0 - v_0
v_2 = tl_math.exp(v_1)
v_2 = libdevice.exp(v_1)
v_3 = di_copy_0 * v_2
subscript = v_0[:, None]
v_4 = values - subscript
v_5 = tl_math.exp(v_4)
v_5 = libdevice.exp(v_4)
_mask_to_1 = tl.where(mask_0[:, None] & mask_1[None, :], v_5, 0)
sum_1 = tl.sum(_mask_to_1, 1)
di = v_3 + sum_1
Expand All @@ -1895,7 +1896,7 @@ def _helion_softmax_two_pass(x, out, out_stride_0, out_stride_1, x_stride_0, x_s
values_1 = tl.load(x + (indices_0[:, None] * x_stride_0 + indices_2[None, :] * x_stride_1), mask_0[:, None] & mask_2[None, :], other=0)
subscript_1 = mi_copy_1_0[:, None]
v_7 = values_1 - subscript_1
v_8 = tl_math.exp(v_7)
v_8 = libdevice.exp(v_7)
subscript_2 = di_copy_1_0[:, None]
v_9 = v_8 / subscript_2
tl.store(out + (indices_0[:, None] * out_stride_0 + indices_2[None, :] * out_stride_1), v_9, mask_0[:, None] & mask_2[None, :])
Expand Down Expand Up @@ -1923,7 +1924,7 @@ import torch
import triton
import triton.language as tl
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch._inductor.runtime.triton_compat import libdevice
from helion.runtime import default_launcher as _default_launcher

@triton.jit
Expand All @@ -1946,11 +1947,11 @@ def _helion_softmax_two_pass(x, out, out_size_0, out_size_1, x_size_0, x_size_1,
local_amax = tl.max(_mask_to, 1)
v_0 = triton_helpers.maximum(mi_copy_0, local_amax)
v_1 = mi_copy_0 - v_0
v_2 = tl_math.exp(v_1)
v_2 = libdevice.exp(v_1)
v_3 = di_copy_0 * v_2
subscript = v_0[:, None]
v_4 = values - subscript
v_5 = tl_math.exp(v_4)
v_5 = libdevice.exp(v_4)
_mask_to_1 = tl.where(mask_0[:, None] & mask_1[None, :], v_5, 0)
sum_1 = tl.sum(_mask_to_1, 1)
di = v_3 + sum_1
Expand All @@ -1964,7 +1965,7 @@ def _helion_softmax_two_pass(x, out, out_size_0, out_size_1, x_size_0, x_size_1,
values_1 = tl.load(tl.make_block_ptr(x, [x_size_0, x_size_1], [x_stride_0, x_stride_1], [offset_0, offset_2], [_BLOCK_SIZE_0, _BLOCK_SIZE_1], [1, 0]), boundary_check=[0, 1], padding_option='zero')
subscript_1 = mi_copy_1_0[:, None]
v_7 = values_1 - subscript_1
v_8 = tl_math.exp(v_7)
v_8 = libdevice.exp(v_7)
subscript_2 = di_copy_1_0[:, None]
v_9 = v_8 / subscript_2
tl.store(tl.make_block_ptr(out, [out_size_0, out_size_1], [out_stride_0, out_stride_1], [offset_0, offset_2], [_BLOCK_SIZE_0, _BLOCK_SIZE_1], [1, 0]), v_9, boundary_check=[0, 1])
Expand Down
2 changes: 1 addition & 1 deletion test/test_reductions.expected
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Original file line number Diff line number Diff line change
Expand Up @@ -194,7 +194,7 @@ def _helion_multi_math_ops_fp16_kernel(x, result, x_size_0, result_stride_0, res
tl.store(result + (indices_0 * result_stride_0 + 6 * result_stride_1), v_20, mask_0)
load_7 = tl.load(x + indices_0 * x_stride_0, mask_0, other=0)
v_21 = load_7.to(tl.float32)
v_22 = tl_math.exp(v_21)
v_22 = libdevice.exp(v_21)
v_23 = v_22.to(tl.float16)
tl.store(result + (indices_0 * result_stride_0 + 7 * result_stride_1), v_23, mask_0)

Expand Down
8 changes: 4 additions & 4 deletions test/test_views.expected
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Original file line number Diff line number Diff line change
Expand Up @@ -44,7 +44,7 @@ from __future__ import annotations
import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch._inductor.runtime.triton_compat import libdevice
from helion.runtime import default_launcher as _default_launcher

@triton.jit
Expand All @@ -60,7 +60,7 @@ def _helion_softmax(x, out, out_stride_0, out_stride_1, x_stride_0, x_stride_1,
amax_1 = amax[:, None]
v_0 = values - amax_1
v_1 = v_0.to(tl.float32)
v_2 = tl_math.exp(v_1)
v_2 = libdevice.exp(v_1)
v_3 = v_2.to(tl.float16)
_mask_to_1 = tl.where(tl.broadcast_to(mask_1[None, :], [1, _RDIM_SIZE_1]), v_3, 0)
sum_1 = tl.sum(_mask_to_1, 1)
Expand All @@ -81,7 +81,7 @@ from __future__ import annotations
import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch._inductor.runtime.triton_compat import libdevice
from helion.runtime import default_launcher as _default_launcher

@triton.jit
Expand All @@ -97,7 +97,7 @@ def _helion_softmax(x, out, out_stride_0, out_stride_1, x_stride_0, x_stride_1,
amax_1 = tl.reshape(amax, [1, 1])
v_0 = values - amax_1
v_1 = v_0.to(tl.float32)
v_2 = tl_math.exp(v_1)
v_2 = libdevice.exp(v_1)
v_3 = v_2.to(tl.float16)
_mask_to_1 = tl.where(tl.broadcast_to(mask_1[None, :], [1, _RDIM_SIZE_1]), v_3, 0)
sum_1 = tl.sum(_mask_to_1, 1)
Expand Down
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