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Yaman Umuroglu authoredYaman Umuroglu authored
test_data_packing_hls.py 5.54 KiB
# Copyright (c) 2020, Xilinx
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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import pytest
import numpy as np
import os
import shutil
import subprocess
import finn.util.basic as cutil
from finn.core.datatype import DataType
from finn.util.data_packing import numpy_to_hls_code
@pytest.mark.parametrize(
"dtype",
[DataType["BINARY"], DataType["INT2"], DataType["INT32"], DataType["FIXED<9,6>"]],
)
@pytest.mark.parametrize("test_shape", [(1, 2, 4), (1, 1, 64), (2, 64)])
@pytest.mark.vivado
def test_npy2apintstream(test_shape, dtype):
ndarray = cutil.gen_finn_dt_tensor(dtype, test_shape)
test_dir = cutil.make_build_dir(prefix="test_npy2apintstream_")
shape = ndarray.shape
elem_bits = dtype.bitwidth()
packed_bits = shape[-1] * elem_bits
packed_hls_type = "ap_uint<%d>" % packed_bits
elem_hls_type = dtype.get_hls_datatype_str()
npy_in = test_dir + "/in.npy"
npy_out = test_dir + "/out.npy"
# restrict the np datatypes we can handle
npyt_to_ct = {
"float32": "float",
"float64": "double",
"int8": "int8_t",
"int32": "int32_t",
"int64": "int64_t",
"uint8": "uint8_t",
"uint32": "uint32_t",
"uint64": "uint64_t",
}
npy_type = npyt_to_ct[str(ndarray.dtype)]
shape_cpp_str = str(shape).replace("(", "{").replace(")", "}")
test_app_string = []
test_app_string += ["#include <cstddef>"]
test_app_string += ["#define AP_INT_MAX_W 4096"]
test_app_string += ['#include "ap_int.h"']
test_app_string += ['#include "stdint.h"']
test_app_string += ['#include "hls_stream.h"']
test_app_string += ['#include "cnpy.h"']
test_app_string += ['#include "npy2apintstream.hpp"']
test_app_string += ["int main(int argc, char *argv[]) {"]
test_app_string += ["hls::stream<%s> teststream;" % packed_hls_type]
test_app_string += [
'npy2apintstream<%s, %s, %d, %s>("%s", teststream);'
% (packed_hls_type, elem_hls_type, elem_bits, npy_type, npy_in)
]
test_app_string += [
'apintstream2npy<%s, %s, %d, %s>(teststream, %s, "%s");'
% (packed_hls_type, elem_hls_type, elem_bits, npy_type, shape_cpp_str, npy_out)
]
test_app_string += ["return 0;"]
test_app_string += ["}"]
with open(test_dir + "/test.cpp", "w") as f:
f.write("\n".join(test_app_string))
cmd_compile = """
g++ -o test_npy2apintstream test.cpp /workspace/cnpy/cnpy.cpp \
-I/workspace/cnpy/ -I{}/include -I/workspace/finn/src/finn/qnn-data/cpp \
--std=c++11 -lz""".format(
os.environ["VIVADO_PATH"]
)
with open(test_dir + "/compile.sh", "w") as f:
f.write(cmd_compile)
compile = subprocess.Popen(
["sh", "compile.sh"], stdout=subprocess.PIPE, cwd=test_dir
)
(stdout, stderr) = compile.communicate()
# make copy before saving the array
ndarray = ndarray.copy()
np.save(npy_in, ndarray)
execute = subprocess.Popen(
"./test_npy2apintstream", stdout=subprocess.PIPE, cwd=test_dir
)
(stdout, stderr) = execute.communicate()
produced = np.load(npy_out)
success = (produced == ndarray).all()
# only delete generated code if test has passed
# useful for debug otherwise
if success:
shutil.rmtree(test_dir)
assert success
def test_numpy_to_hls_code():
def remove_all_whitespace(s):
return "".join(s.split())
A = [[1, 1, 1, 0], [0, 1, 1, 0]]
ret = numpy_to_hls_code(A, DataType["BINARY"], "test", True)
eA = """ap_uint<4> test[2] =
{ap_uint<4>("0xe", 16), ap_uint<4>("0x6", 16)};"""
assert remove_all_whitespace(ret) == remove_all_whitespace(eA)
B = [[[3, 3], [3, 3]], [[1, 3], [3, 1]]]
ret = numpy_to_hls_code(B, DataType["UINT2"], "test", True)
eB = """ap_uint<4> test[2][2] =
{{ap_uint<4>("0xf", 16), ap_uint<4>("0xf", 16)},
{ap_uint<4>("0x7", 16), ap_uint<4>("0xd", 16)}};"""
assert remove_all_whitespace(ret) == remove_all_whitespace(eB)
ret = numpy_to_hls_code(B, DataType["UINT2"], "test", True, True)
eB = """{{ap_uint<4>("0xf", 16), ap_uint<4>("0xf", 16)},
{ap_uint<4>("0x7", 16), ap_uint<4>("0xd", 16)}};"""
assert remove_all_whitespace(ret) == remove_all_whitespace(eB)