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import pycuda.autoinit
import pycuda.driver as drv
import pycuda.tools as py_tools
from pathlib import PurePath
import numpy as np
from os import path
import os
import itertools
import sys
# It's impossible to discern what is the type of a buffer, here you can override equality checks
def assert_array_equal_override(kernel_name, idx, arr1, arr2):
if kernel_name == 'knn_match' and idx == 6:
arr1_view = np.frombuffer(arr1, dtype=np.dtype([('f1', np.uint32), ('f2', np.uint32), ('f3', np.uint32)]))
np.ndarray.sort(arr1_view)
arr2_view = np.frombuffer(arr2, dtype=np.dtype([('f1', np.uint32), ('f2', np.uint32), ('f3', np.uint32)]))
np.ndarray.sort(arr2_view)
if kernel_name == 'nonmax_suppression' and idx == 7:
arr1_view = np.frombuffer(arr1, dtype=np.dtype(np.uint32))
np.ndarray.sort(arr1_view)
arr2_view = np.frombuffer(arr2, dtype=np.dtype(np.uint32))
np.ndarray.sort(arr2_view)
np.testing.assert_array_equal(arr1, arr2)
def load_arguments(arg_path):
is_buffer = arg_path.endswith(".buffer")
with open(arg_path, "rb") as f:
arg_bytes = f.read()
if not is_buffer:
if len(arg_bytes) == 1:
return np.frombuffer(arg_bytes, dtype=np.uint8)[0], None
elif len(arg_bytes) == 2:
return np.frombuffer(arg_bytes, dtype=np.uint16)[0], None
elif len(arg_bytes) == 4:
return np.frombuffer(arg_bytes, dtype=np.uint32)[0], None
elif len(arg_bytes) == 8:
return np.frombuffer(arg_bytes, dtype=np.uint64)[0], None
else:
raise Exception('Incorrect size of {}: {}'.format(arg_path, len(arg_bytes)))
else:
buff = np.frombuffer(bytearray(arg_bytes), dtype=np.uint8)
buff.setflags(write=1, align=1)
return drv.InOut(buff), buff
def parse_arguments(dump_path, prefix):
dir = path.join(dump_path, prefix)
arg_files = os.listdir(dir)
return [load_arguments(path.join(dir, f)) for f in sorted(arg_files)]
def append_debug_buffer(args):
args = list(args)
debug_buff = np.zeros(1024 * 1024, np.single)
args.append((drv.InOut(debug_buff), debug_buff))
return args
def verify_single_dump(input_path, max_block_threads):
print(input_path)
kernel_name = path.basename(input_path).split("_", 1)[1]
with open(path.join(input_path, "launch.txt"), "r") as launch_f:
launch_lines = list(map(int, launch_f.readlines()))
block = tuple(launch_lines[3:6])
launch_block_size = block[0] * block[1] * block[2]
if launch_block_size > max_block_threads:
print(
f" Skipping, launch block size ({launch_block_size}) bigger than maximum block size ({max_block_threads})")
return
module = drv.module_from_file(path.join(input_path, "module.ptx"))
kernel = module.get_function(kernel_name)
pre_args = append_debug_buffer(parse_arguments(input_path, "pre"))
kernel_pre_args, host_pre_args = zip(*pre_args)
kernel(*list(kernel_pre_args), grid=tuple(launch_lines[:3]), block=block, shared=launch_lines[6])
post_args = parse_arguments(input_path, "post")
_, host_post_args_args = zip(*post_args)
for idx, (pre_arg, post_arg) in enumerate(zip(host_pre_args, host_post_args_args)):
if pre_arg is None:
continue
try:
assert_array_equal_override(kernel_name, idx, pre_arg, post_arg)
except Exception as e:
print(f"{idx}: {e}")
def main(argv):
device = drv.Device(0)
max_threads = device.get_attribute(drv.device_attribute.MAX_THREADS_PER_BLOCK)
print(device.name())
input_path = argv[1]
if os.path.exists(path.join(input_path, "launch.txt")):
verify_single_dump(input_path, max_threads)
else:
for input_subdir in sorted([path.join(input_path, dir_name) for dir_name in os.listdir(input_path)]):
verify_single_dump(input_subdir, max_threads)
if __name__ == "__main__":
main(sys.argv)
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