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conftest.py
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conftest.py
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import contextlib
import doctest
import io
import itertools
import numpy as np
import pytest
import re
import sys
import psyneulink
from psyneulink import clear_registry, primary_registries, torch_available
from psyneulink.core import llvm as pnlvm
from psyneulink.core.globals.utilities import set_global_seed
try:
import torch
except ImportError:
pass
else:
# Check that torch is usable if installed
assert torch_available, "Torch module is available, but not usable by PNL"
# def pytest_addoption(parser):
# parser.addoption(
# '--pnl-seed',
# action='store',
# default=int(time.time() * 256),
# help='the seed to use for each test'
# )
mark_stress_tests = 'stress'
marks_default_skip = [mark_stress_tests]
# skip stress tests by default, add command option to include
# http://blog.devork.be/2009/12/skipping-slow-test-by-default-in-pytest.html
def pytest_addoption(parser):
parser.addoption('--{0}'.format(mark_stress_tests), action='store_true', default=False, help='Run {0} tests (long)'.format(mark_stress_tests))
parser.addoption('--fp-precision', action='store', default='fp64', choices=['fp32', 'fp64'],
help='Set default fp precision for the runtime compiler. Default: fp64')
def pytest_runtest_setup(item):
# Check that all 'cuda' tests are also marked 'llvm'
assert 'llvm' in item.keywords or 'cuda' not in item.keywords
for m in marks_default_skip:
if m in item.keywords and not item.config.getvalue(m):
pytest.skip('{0} tests not requested'.format(m))
if 'cuda' in item.keywords and not pnlvm.ptx_enabled:
pytest.skip('PTX engine not enabled/available')
if 'pytorch' in item.keywords and not torch_available:
pytest.skip('pytorch not available')
doctest.ELLIPSIS_MARKER = "[...]"
def pytest_generate_tests(metafunc):
mech_and_func_modes = ['Python',
pytest.param('LLVM', marks=pytest.mark.llvm),
pytest.param('PTX', marks=[pytest.mark.llvm,
pytest.mark.cuda])
]
if "func_mode" in metafunc.fixturenames:
metafunc.parametrize("func_mode", mech_and_func_modes)
if "mech_mode" in metafunc.fixturenames:
metafunc.parametrize("mech_mode", mech_and_func_modes)
if "comp_mode_no_llvm" in metafunc.fixturenames:
modes = [m for m in get_comp_execution_modes()
if m.values[0] is not pnlvm.ExecutionMode.LLVM]
metafunc.parametrize("comp_mode", modes)
elif "comp_mode" in metafunc.fixturenames:
metafunc.parametrize("comp_mode", get_comp_execution_modes())
if "autodiff_mode" in metafunc.fixturenames:
auto_modes = [
# pnlvm.ExecutionMode.Python,
pytest.param(pnlvm.ExecutionMode.PyTorch, marks=pytest.mark.pytorch),
pytest.param(pnlvm.ExecutionMode.LLVMRun, marks=pytest.mark.llvm)
]
metafunc.parametrize("autodiff_mode", auto_modes)
_old_register_prefix = None
# Collection hooks
def pytest_sessionstart(session):
"""Initialize session with the right floating point precision and component name prefix."""
precision = session.config.getvalue("--fp-precision")
if precision == 'fp64':
pnlvm.LLVMBuilderContext.default_float_ty = pnlvm.ir.DoubleType()
elif precision == 'fp32':
pnlvm.LLVMBuilderContext.default_float_ty = pnlvm.ir.FloatType()
else:
assert False, "Unsupported precision parameter: {}".format(precision)
global _old_register_prefix
_old_register_prefix = psyneulink.core.globals.registry._register_auto_name_prefix
psyneulink.core.globals.registry._register_auto_name_prefix = "__pnl_pytest_"
def pytest_collection_finish(session):
"""Restore component prefix at the end of test collection."""
psyneulink.core.globals.registry._register_auto_name_prefix = _old_register_prefix
# Runtest hooks
def pytest_runtest_call(item):
# seed = int(item.config.getoption('--pnl-seed'))
seed = 0
np.random.seed(seed)
set_global_seed(seed)
if 'pytorch' in item.keywords:
assert torch_available
torch.manual_seed(seed)
def pytest_runtest_teardown(item):
for registry in primary_registries:
# Clear Registry to have a stable reference for indexed suffixes of default names
clear_registry(registry)
pnlvm.cleanup()
@pytest.fixture
def comp_mode_no_llvm():
# dummy fixture to allow 'comp_mode' filtering
pass
class FirstBench():
def __init__(self, benchmark):
super().__setattr__("benchmark", benchmark)
def __call__(self, f, *args, **kwargs):
res = []
# Compute the first result if benchmark is enabled
if self.benchmark.enabled:
res.append(f(*args, **kwargs))
res.append(self.benchmark(f, *args, **kwargs))
return res[0]
def __getattr__(self, attr):
return getattr(self.benchmark, attr)
def __setattr__(self, attr, val):
return setattr(self.benchmark, attr, val)
@pytest.fixture
def benchmark(benchmark):
return FirstBench(benchmark)
@pytest.helpers.register
def llvm_current_fp_precision():
float_ty = pnlvm.LLVMBuilderContext.get_current().float_ty
if float_ty == pnlvm.ir.DoubleType():
return 'fp64'
elif float_ty == pnlvm.ir.FloatType():
return 'fp32'
else:
assert False, "Unknown floating point type: {}".format(float_ty)
@pytest.helpers.register
def get_comp_execution_modes():
return [pytest.param(pnlvm.ExecutionMode.Python),
pytest.param(pnlvm.ExecutionMode.LLVM, marks=pytest.mark.llvm),
pytest.param(pnlvm.ExecutionMode.LLVMExec, marks=pytest.mark.llvm),
pytest.param(pnlvm.ExecutionMode.LLVMRun, marks=pytest.mark.llvm),
pytest.param(pnlvm.ExecutionMode.PTXExec, marks=[pytest.mark.llvm, pytest.mark.cuda]),
pytest.param(pnlvm.ExecutionMode.PTXRun, marks=[pytest.mark.llvm, pytest.mark.cuda])
]
@pytest.helpers.register
def get_comp_and_ocm_execution_modes():
# The first part converts composition execution mode to (comp_mod, ocm_mode) pair.
# All comp_mode-s other than Python set ocm_mode to None, which is invalid and will
# fail assertion if executed in Python mode, ExecutionMode.Python sets ocm_mode to 'Python'.
return [pytest.param(x.values[0], 'Python' if x.values[0] is pnlvm.ExecutionMode.Python else 'None', id=str(x.values[0]), marks=x.marks) for x in get_comp_execution_modes()] + \
[pytest.param(pnlvm.ExecutionMode.Python, 'LLVM', id='Python-LLVM', marks=pytest.mark.llvm),
pytest.param(pnlvm.ExecutionMode.Python, 'PTX', id='Python-PTX', marks=[pytest.mark.llvm, pytest.mark.cuda])]
@pytest.helpers.register
def cuda_param(val):
return pytest.param(val, marks=[pytest.mark.llvm, pytest.mark.cuda])
@pytest.helpers.register
def get_func_execution(func, func_mode, *, writeback:bool=True):
if func_mode == 'LLVM':
ex = pnlvm.execution.FuncExecution(func)
# Calling writeback here will replace parameter values
# with numpy instances that share memory with the binary
# structure used by the compiled function
if writeback:
ex.writeback_params_to_pnl()
return ex.execute
elif func_mode == 'PTX':
ex = pnlvm.execution.FuncExecution(func)
# Calling writeback here will replace parameter values
# with numpy instances that share memory with the binary
# structure used by the compiled function
if writeback:
ex.writeback_params_to_pnl()
return ex.cuda_execute
elif func_mode == 'Python':
return func.function
else:
assert False, "Unknown function mode: {}".format(func_mode)
@pytest.helpers.register
def get_mech_execution(mech, mech_mode):
if mech_mode == 'LLVM':
return pnlvm.execution.MechExecution(mech).execute
elif mech_mode == 'PTX':
return pnlvm.execution.MechExecution(mech).cuda_execute
elif mech_mode == 'Python':
def mech_wrapper(x):
mech.execute(x)
return mech.output_values
return mech_wrapper
else:
assert False, "Unknown mechanism mode: {}".format(mech_mode)
@pytest.helpers.register
def numpy_uses_avx512():
out = io.StringIO()
with contextlib.redirect_stdout(out):
np.show_config()
return re.search(' found = .*AVX512.*', out.getvalue()) is not None
@pytest.helpers.register
def expand_np_ndarray(arr):
# this will fail on an input containing a float (not np.ndarray)
try:
iter(arr)
except TypeError:
return arr.tolist()
results_list = []
for elem in arr:
try:
iter(elem)
except TypeError:
elem = [elem]
for nested_elem in elem:
nested_elem = nested_elem.tolist()
try:
iter(nested_elem)
except TypeError:
nested_elem = [nested_elem]
results_list.extend(nested_elem)
return results_list
@pytest.helpers.register
def power_set(s):
"""Set of all potential subsets."""
vals = list(s)
return (c for l in range(len(vals) + 1) for c in itertools.combinations(vals, l))
# flag when run from pytest
# https://docs.pytest.org/en/stable/example/simple.html#detect-if-running-from-within-a-pytest-run
def pytest_configure(config):
psyneulink._called_from_pytest = True