ROCm/composable_kernel
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Fix test data generation script.

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This commit is contained in:
Ville Pietilä
2025-07-07 15:40:29 +00:00
parent 9e21653bd8
commit 1b8a5e815f
3 changed files with 15 additions and 7 deletions
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1
.gitignore vendored
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@@ -71,4 +71,5 @@ __pycache__/
test_data/*
script/*.csv
script/*.txt
script/**/*.png

2
script/analyze_conv_tests.py
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@@ -626,7 +626,7 @@ def main():
best_occupancy_split_k_values = df[14][valid_mask]
# 15 - rank
# 16 - strategy
#17 - total number of candidate ops.
# 17 - total number of candidate ops.
suffix = f"_{args.label}" if args.label else ""

19
script/generate_test_data.py
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@@ -102,6 +102,7 @@ def process_miopen_driver(args, unknown):
' convbfp16).')
exit(1)
def parse_ktn_command(csv_file, no_verification=False, fwd_only=False, bwd_data_only=False, bwd_weight_only=False):
if not os.path.isfile(csv_file):
print(f"Error: The specified CSV file '{csv_file}' does not exist.", file=sys.stderr)
@@ -111,18 +112,23 @@ def parse_ktn_command(csv_file, no_verification=False, fwd_only=False, bwd_data_
# Remove the KTN commands where column 'Group Size' has value 1
df = df[df['Group Size'] != 1]
assert (df['Group Size'] == 1).sum() == 0, "Filtering failed!"
assert (df['Group Size'] != 1).sum() > 0, "Filtering failed!"
print("Unique Group Size values:", df['Group Size'].unique())
print("Data types:", df.dtypes)
commands = []
parser = get_parser()
for i, cmd in enumerate(df['Command']):
cmd = cmd.strip()
cmd = cmd.split()
args, _ = parser.parse_known_args(cmd)
init_const_args(args)
process_miopen_driver(args, cmd.split()[0])
process_miopen_driver(args, cmd[0])
if no_verification:
args.verify = 0
args.verify = 0
else:
args.verify = 1
@@ -168,9 +174,9 @@ def main():
})
if not args.full_set:
# The hardest cases are at the beginning of the Fremont CSV file.
commands_fremont_df = commands_fremont_df.sample(n=min(n_fremont_shapes, len(commands_fremont_df)))
commands_ktn_df = commands_ktn_df.sample(n=min(n_ktn_shapes, len(commands_ktn_df)), random_state=seed)
# The hardest cases are at the beginning of the Fremont CSV file.
commands_fremont_df = commands_fremont_df.sample(n=min(n_fremont_shapes, len(commands_fremont_df)))
commands_ktn_df = commands_ktn_df.sample(n=min(n_ktn_shapes, len(commands_ktn_df)), random_state=seed)
# Combine the two DataFrames
commands_df = pd.concat([commands_fremont_df, commands_ktn_df], ignore_index=True)
@@ -180,6 +186,7 @@ def main():
output_file = os.path.join(args.output_path, "ck_profiler_commands.csv")
with open(output_file, "w") as f:
csv_writer = csv.writer(f, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
csv_writer.writerow(['profiler', 'op', 'datatype', 'layout', 'verify', 'init', 'log', 'time', 'Ndims', 'G', 'N', 'K', 'C', 'Y', 'X', 'Hi', 'Wi', 'Sy', 'Sx', 'Dy', 'Dx', 'LeftPy', 'LeftPx', 'RightPy', 'RightPx', 'SplitK'])
for command in commands_df['Command']:
csv_writer.writerow(command)
print(f"Commands saved to {output_file}")