blob: 79e67203c322cf0beec7e4ba93c971bd5671cea8 [file] [log] [blame]
"""Tests for tosa_reference_model."""
# Copyright (c) 2022, ARM Limited.
# SPDX-License-Identifier: Apache-2.0
import json
import re
from pathlib import Path
from shutil import rmtree
import numpy as np
import pytest
from checker.tosa_result_checker import test_check as tosa_check
from checker.tosa_result_checker import TestResult as TosaResult
from generator.tosa_verif_build_tests import main as tosa_builder
from runner.run_command import run_sh_command
from runner.run_command import RunShCommandError
# Note: Must rename imports so that pytest doesn't assume its a test function/class
# Set this to False if you want ot preserve the test directories after running
CLEAN_UP_TESTS = True
# Location of reference model binary
REF_MODEL_PATH = Path(__file__).resolve().parents[2] / "build" / "reference_model"
REF_MODEL_EXE = "tosa_reference_model"
REF_MODEL = REF_MODEL_PATH / REF_MODEL_EXE
# Default tensor shape information
SHAPE_LIST = ["10", "5"]
SHAPE_DIMS = len(SHAPE_LIST)
SHAPE_ARG = ",".join(SHAPE_LIST)
SHAPE_OUT = "x".join(SHAPE_LIST)
# Output file information
OUTPUT_DIR_PREFIX = "_pytest_vtest"
OUTPUT_OFM_FILE = "result_refmodel_pytest.npy"
OUTPUT_RESULT_FILE = "result_numpy_pytest.npy"
OUTPUT_CONST_GLOB = "const-*.npy"
TEST_DESC_FILENAME = "desc.json"
TOSA_LEVEL = "EIGHTK"
# Conversion from refmodel type into the type abbreviation used in the test output
REF_MODEL_TYPE_TO_OUT = {
"bool": "b",
"int8": "i8",
"uint8": "u8",
"int16": "i16",
"int32": "i32",
"fp32": "f32",
"fp16": "f16",
"bf16": "bf16",
}
@pytest.mark.postcommit
def test_refmodel_built():
"""First test to check the reference model has been built."""
assert REF_MODEL.is_file()
class BuildTosaTest:
"""Wrapper for managing lifecycle of TOSA unit tests."""
def __init__(self, op_name, ref_model_type, num_expected_tests):
self.op_name = op_name
self.ref_model_type = ref_model_type
self.num_expected_tests = num_expected_tests
self.output_dir = None
self.test_dirs = None
def create_test(self):
"""Helper to generate a TOSA unit test."""
if self.output_dir is not None:
# Already created
return self.test_dir
self.output_dir = (
Path(__file__).parent
/ f"{OUTPUT_DIR_PREFIX}_{self.op_name}_{self.ref_model_type}"
)
# Generate tests without any zero-point
build_args = [
"--filter",
self.op_name,
"--target-shape",
SHAPE_ARG,
"--target-dtype",
self.ref_model_type,
"--zero-point",
"0",
"--num-const-inputs-concat",
"1",
"--dump-const-tensors",
"-o",
str(self.output_dir),
]
print(f"### Building tests: tosa_verif_build_tests {' '.join(build_args)}")
tosa_builder(build_args)
# Find the created test
test_dir = self.output_dir / self.op_name
# Can't assume exact name due to broadcasting and other changes to shape
test_glob = f"{self.op_name}_*_{REF_MODEL_TYPE_TO_OUT[self.ref_model_type]}*"
test_dirs = sorted(test_dir.glob(test_glob))
assert len(test_dirs) == self.num_expected_tests
for test_dir in test_dirs:
assert test_dir.is_dir()
self.test_dirs = test_dirs
return self.test_dirs
def remove_test(self):
if self.output_dir is not None and self.output_dir.is_dir():
# Delete directory
test_tree = self.output_dir.resolve()
if CLEAN_UP_TESTS:
print(f"Deleting {test_tree}")
rmtree(str(test_tree))
self.output_dir = None
else:
print(f"Skipped clean up of {test_tree}")
# Tests - op_name, ref_model_type, num_expected_tests
TEST_PARAMS = [
("add", "int32", 1),
("add", "fp32", 1),
("abs", "int32", 1),
("abs", "fp32", 1),
("abs", "fp16", 1),
("abs", "bf16", 1),
("negate", "int8", 1),
("negate", "int16", 1),
("negate", "int32", 1),
("negate", "fp32", 1),
("negate", "fp16", 1),
("negate", "bf16", 1),
# One test per axis (shape dimensions)
("concat", "bool", SHAPE_DIMS),
("concat", "int8", SHAPE_DIMS),
("concat", "int16", SHAPE_DIMS),
("concat", "int32", SHAPE_DIMS),
("concat", "fp32", SHAPE_DIMS),
("concat", "fp16", SHAPE_DIMS),
("concat", "bf16", SHAPE_DIMS),
]
def id_2_name(id):
"""Convert test id to name - otherwise it will be tosaTestN."""
op_name, ref_model_type, _ = id
return f"{op_name}-{ref_model_type}"
@pytest.fixture(params=TEST_PARAMS, ids=id_2_name)
def tosaTest(request):
"""Fixture to generate the required test params and clean up."""
op_name, ref_model_type, num_expected_tests = request.param
tst = BuildTosaTest(op_name, ref_model_type, num_expected_tests)
yield tst
tst.remove_test()
@pytest.mark.postcommit
def test_refmodel_simple_op(tosaTest):
"""Operator testing versus Numpy."""
op_name = tosaTest.op_name
# Generate TOSA test(s) (mostly should be single test)
test_dirs = tosaTest.create_test()
# Indicate miscellaneous checks to run in tosa_check
misc_checks = []
for test_dir in test_dirs:
# Run ref model
desc_file = test_dir / TEST_DESC_FILENAME
assert desc_file.is_file()
refmodel_cmd = [
str(REF_MODEL),
"--test_desc",
str(desc_file),
"--ofm_file",
OUTPUT_OFM_FILE,
"--tosa_level",
TOSA_LEVEL,
]
try:
run_sh_command(refmodel_cmd, verbose=True, capture_output=True)
except RunShCommandError as err:
assert False, f"Unexpected exception {err}"
# Find output
ofm_file = test_dir / OUTPUT_OFM_FILE
assert ofm_file.is_file()
# Load inputs for Numpy
with desc_file.open("r") as fp:
test_desc = json.load(fp)
tensors = []
assert "ifm_file" in test_desc
for input_name in test_desc["ifm_file"]:
input_file = test_dir / input_name
assert input_file.is_file()
tensors.append(np.load(str(input_file)))
# Load constants for Numpy
const_files = sorted(test_dir.glob(OUTPUT_CONST_GLOB))
consts = []
for const_file in const_files:
assert const_file.is_file()
consts.append(np.load(str(const_file)))
# Perform Numpy operation
if op_name == "abs":
assert len(tensors) == 1
result = np.abs(tensors[0])
elif op_name == "add":
assert len(tensors) == 2
result = np.add(tensors[0], tensors[1])
elif op_name == "concat":
assert len(consts) == 1
# Get axis from test directory name
match = re.search(r"axis([0-9]+)", test_dir.name)
assert match is not None
axis = int(match.group(1))
result = np.concatenate((*tensors, consts[0]), axis=axis)
elif op_name == "negate":
assert len(tensors) == 1
result = np.negative(tensors[0])
else:
assert False, f"Unknown operation {op_name}"
# Save Numpy result
result_file = test_dir / OUTPUT_RESULT_FILE
np.save(str(result_file), result)
assert result_file.is_file()
# Ensure valid bf16
if tosaTest.ref_model_type == "bf16":
misc_checks.append("bf16")
# Check Numpy result versus refmodel
check_result, tolerance, msg = tosa_check(
result_file,
ofm_file,
test_name=test_dir.name,
misc_checks=misc_checks,
)
assert check_result == TosaResult.PASS