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[CI] [Dot] Reduced test suite (#302)

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Use upstream list of test for dot op on machines with no MFMA support.
This is needed to reduce time required for PR testing.
This commit is contained in:
Alexander Efimov
2023-08-18 14:47:14 +02:00
committed by GitHub
parent 01b0108c94
commit d86b19f7a3
1 changed files with 33 additions and 22 deletions
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55
python/test/unit/language/test_core_amd.py
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@@ -1,4 +1,5 @@
# flake8: noqa: F821,F841
import triton.language.semantic
import itertools
import os
import re
@@ -1204,30 +1205,38 @@ def test_permute(dtype_str, shape, perm, device='cuda'):
# test dot
# ---------------
# @pytest.mark.parametrize("M, N, K, num_warps, col_a, col_b, epilogue, allow_tf32, dtype",
# [(*shape, 4, False, False, epilogue, allow_tf32, dtype)
# for shape in [(64, 64, 64), (16, 16, 16)]
# for epilogue in ['none', 'trans', 'add-matrix', 'add-rows', 'add-cols', 'softmax', 'chain-dot']
# for allow_tf32 in [True, False]
# for dtype in ['float16', 'float32']
# if not (allow_tf32 and (dtype in ['float16']))] +
# [(*shape_nw, col_a, col_b, 'none', allow_tf32, dtype)
# for shape_nw in [[128, 256, 32, 8],
# [128, 16, 32, 4],
# [32, 128, 64, 4],
# [128, 128, 64, 4],
# [64, 128, 128, 4],
# [32, 128, 64, 2],
# [128, 128, 64, 2],
# [64, 128, 128, 2]]
# for allow_tf32 in [True]
# for col_a in [True, False]
# for col_b in [True, False]
# for dtype in ['int8', 'float16', 'float32']])
# MFMA Test Dot tests
@pytest.mark.parametrize("M, N, K, num_warps, col_a, col_b, epilogue, allow_tf32, in_dtype, out_dtype",
# FMA Test Dot tests
[(*shape, 4, False, False, epilogue, allow_tf32, in_dtype, out_dtype)
for shape in [(64, 64, 64), (16, 16, 16)]
for epilogue in ['none', 'trans', 'add-matrix', 'add-rows', 'add-cols', 'softmax', 'chain-dot']
for allow_tf32 in [True, False]
for in_dtype, out_dtype in [('float16', 'float16'),
('float16', 'float32'),
('float32', 'float32')]
if not (allow_tf32 and (in_dtype in ['float16']))] +
[(*shape_nw, col_a, col_b, 'none', allow_tf32, in_dtype, out_dtype)
for shape_nw in [[128, 256, 32, 8],
[128, 16, 32, 4],
[32, 128, 64, 4],
[128, 128, 64, 4],
[64, 128, 128, 4],
[32, 128, 64, 2],
[64, 64, 32, 4],
[32, 32, 128, 16],
[128, 128, 64, 2],
[64, 128, 128, 2]]
for allow_tf32 in [True]
for col_a in [True, False]
for col_b in [True, False]
for in_dtype, out_dtype in [('int8', 'int8'),
('float16', 'float16'),
('float16', 'float32'),
('float32', 'float32')]]
if not triton.language.semantic.gpu_has_mfma() else
# MFMA Test Dot tests
[(*shape, 2, False, False, epilogue, allow_tf32, in_dtype, out_dtype)
for shape in [(64, 64, 64), (32, 32, 32), (16, 16, 16)]
for epilogue in ['none', 'trans', 'add-matrix', 'chain-dot', 'softmax']
@@ -1273,6 +1282,8 @@ def test_dot(M, N, K, num_warps, col_a, col_b, epilogue, allow_tf32, in_dtype, o
if torch.version.hip is not None:
# set capability to large number to jump over check below
# check are not relevant to amd gpu, left them for smaller diff between test_core.py and test_core_amd.py tests
if (M, N, K) == (128, 256, 32):
pytest.skip("Out of resources")
capability = (100, 100)
if out_dtype is None:
if in_dtype in float_dtypes: