def materialize_root_fb(self, first):
if (not root.finalized and not root.empty) or first:
root.finalize()
if root.finalized:
global _root_fb
_root_fb = FieldsBuilder()
def materialize_root_fb(self, first):
if not root.finalized and not root.empty:
root.finalize()
elif first:
root.finalize(raise_warning=False)
if root.finalized:
global _root_fb
_root_fb = FieldsBuilder()
def materialize_root_fb(is_first_call):
if root.finalized:
return
if not is_first_call and root.empty:
# We have to forcefully finalize when `is_first_call` is True (even
# if the root itself is empty), so that there is a valid struct
# llvm::Module, if no field has been declared before the first kernel
# invocation. Example case:
# https://github.com/taichi-dev/taichi/blob/27bb1dc3227d9273a79fcb318fdb06fd053068f5/tests/python/test_ad_basics.py#L260-L266
return
root.finalize(raise_warning=not is_first_call)
global _root_fb
_root_fb = FieldsBuilder()
def clear_all_gradients():
impl.get_runtime().materialize()
def visit(node):
places = []
for i in range(node.ptr.get_num_ch()):
ch = node.ptr.get_ch(i)
if not ch.is_place():
visit(SNode(ch))
else:
if not ch.is_primal():
places.append(ch.get_expr())
places = tuple(places)
if places:
from taichi.lang.meta import clear_gradients
clear_gradients(places)
for root_fb in FieldsBuilder.finalized_roots():
visit(root_fb)
def clear_all_gradients():
"""Set all fields' gradients to 0."""
impl.get_runtime().materialize()
def visit(node):
places = []
for _i in range(node.ptr.get_num_ch()):
ch = node.ptr.get_ch(_i)
if not ch.is_place():
visit(SNode(ch))
else:
if not ch.is_primal():
places.append(ch.get_expr())
places = tuple(places)
if places:
from taichi._kernels import \
clear_gradients # pylint: disable=C0415
clear_gradients(places)
for root_fb in FieldsBuilder.finalized_roots():
visit(root_fb)
def init(arch=None,
default_fp=None,
default_ip=None,
_test_mode=False,
**kwargs):
# Make a deepcopy in case these args reference to items from ti.cfg, which are
# actually references. If no copy is made and the args are indeed references,
# ti.reset() could override the args to their default values.
default_fp = _deepcopy(default_fp)
default_ip = _deepcopy(default_ip)
kwargs = _deepcopy(kwargs)
ti.reset()
spec_cfg = _SpecialConfig()
env_comp = _EnvironmentConfigurator(kwargs, ti.cfg)
env_spec = _EnvironmentConfigurator(kwargs, spec_cfg)
# configure default_fp/ip:
# TODO: move these stuff to _SpecialConfig too:
env_default_fp = os.environ.get("TI_DEFAULT_FP")
if env_default_fp:
if default_fp is not None:
_ti_core.warn(
f'ti.init argument "default_fp" overridden by environment variable TI_DEFAULT_FP={env_default_fp}'
)
if env_default_fp == '32':
default_fp = ti.f32
elif env_default_fp == '64':
default_fp = ti.f64
elif env_default_fp is not None:
raise ValueError(
f'Invalid TI_DEFAULT_FP={env_default_fp}, should be 32 or 64')
env_default_ip = os.environ.get("TI_DEFAULT_IP")
if env_default_ip:
if default_ip is not None:
_ti_core.warn(
f'ti.init argument "default_ip" overridden by environment variable TI_DEFAULT_IP={env_default_ip}'
)
if env_default_ip == '32':
default_ip = ti.i32
elif env_default_ip == '64':
default_ip = ti.i64
elif env_default_ip is not None:
raise ValueError(
f'Invalid TI_DEFAULT_IP={env_default_ip}, should be 32 or 64')
if default_fp is not None:
impl.get_runtime().set_default_fp(default_fp)
if default_ip is not None:
impl.get_runtime().set_default_ip(default_ip)
# submodule configurations (spec_cfg):
env_spec.add('print_preprocessed')
env_spec.add('log_level', str)
env_spec.add('gdb_trigger')
env_spec.add('excepthook')
env_spec.add('experimental_real_function')
# compiler configurations (ti.cfg):
for key in dir(ti.cfg):
if key in ['arch', 'default_fp', 'default_ip']:
continue
cast = type(getattr(ti.cfg, key))
if cast is bool:
cast = None
env_comp.add(key, cast)
unexpected_keys = kwargs.keys()
if len(unexpected_keys):
raise KeyError(
f'Unrecognized keyword argument(s) for ti.init: {", ".join(unexpected_keys)}'
)
# dispatch configurations that are not in ti.cfg:
if not _test_mode:
ti.set_gdb_trigger(spec_cfg.gdb_trigger)
impl.get_runtime().print_preprocessed = spec_cfg.print_preprocessed
impl.get_runtime().experimental_real_function = \
spec_cfg.experimental_real_function
ti.set_logging_level(spec_cfg.log_level.lower())
if spec_cfg.excepthook:
# TODO(#1405): add a way to restore old excepthook
ti.enable_excepthook()
# select arch (backend):
env_arch = os.environ.get('TI_ARCH')
if env_arch is not None:
ti.info(f'Following TI_ARCH setting up for arch={env_arch}')
arch = _ti_core.arch_from_name(env_arch)
ti.cfg.arch = adaptive_arch_select(arch)
print(f'[Taichi] Starting on arch={_ti_core.arch_name(ti.cfg.arch)}')
if _test_mode:
return spec_cfg
# create a new program:
impl.get_runtime().create_program()
impl._root_fb = FieldsBuilder()
def deactivate_all_snodes():
"""Recursively deactivate all SNodes."""
for root_fb in FieldsBuilder.finalized_roots():
root_fb.deactivate_all()
def init(arch=None,
default_fp=None,
default_ip=None,
_test_mode=False,
enable_fallback=True,
**kwargs):
"""Initializes the Taichi runtime.
This should always be the entry point of your Taichi program. Most
importantly, it sets the backend used throughout the program.
Args:
arch: Backend to use. This is usually :const:`~taichi.lang.cpu` or :const:`~taichi.lang.gpu`.
default_fp (Optional[type]): Default floating-point type.
default_ip (Optional[type]): Default integral type.
**kwargs: Taichi provides highly customizable compilation through
``kwargs``, which allows for fine grained control of Taichi compiler
behavior. Below we list some of the most frequently used ones. For a
complete list, please check out
https://github.com/taichi-dev/taichi/blob/master/taichi/program/compile_config.h.
* ``cpu_max_num_threads`` (int): Sets the number of threads used by the CPU thread pool.
* ``debug`` (bool): Enables the debug mode, under which Taichi does a few more things like boundary checks.
* ``print_ir`` (bool): Prints the CHI IR of the Taichi kernels.
* ``packed`` (bool): Enables the packed memory layout. See https://docs.taichi.graphics/lang/articles/advanced/layout.
"""
# Check version for users every 7 days if not disabled by users.
skip = os.environ.get("TI_SKIP_VERSION_CHECK")
if skip != 'ON':
try_check_version()
# Make a deepcopy in case these args reference to items from ti.cfg, which are
# actually references. If no copy is made and the args are indeed references,
# ti.reset() could override the args to their default values.
default_fp = _deepcopy(default_fp)
default_ip = _deepcopy(default_ip)
kwargs = _deepcopy(kwargs)
ti.reset()
spec_cfg = _SpecialConfig()
env_comp = _EnvironmentConfigurator(kwargs, ti.cfg)
env_spec = _EnvironmentConfigurator(kwargs, spec_cfg)
# configure default_fp/ip:
# TODO: move these stuff to _SpecialConfig too:
env_default_fp = os.environ.get("TI_DEFAULT_FP")
if env_default_fp:
if default_fp is not None:
_ti_core.warn(
f'ti.init argument "default_fp" overridden by environment variable TI_DEFAULT_FP={env_default_fp}'
)
if env_default_fp == '32':
default_fp = ti.f32
elif env_default_fp == '64':
default_fp = ti.f64
elif env_default_fp is not None:
raise ValueError(
f'Invalid TI_DEFAULT_FP={env_default_fp}, should be 32 or 64')
env_default_ip = os.environ.get("TI_DEFAULT_IP")
if env_default_ip:
if default_ip is not None:
_ti_core.warn(
f'ti.init argument "default_ip" overridden by environment variable TI_DEFAULT_IP={env_default_ip}'
)
if env_default_ip == '32':
default_ip = ti.i32
elif env_default_ip == '64':
default_ip = ti.i64
elif env_default_ip is not None:
raise ValueError(
f'Invalid TI_DEFAULT_IP={env_default_ip}, should be 32 or 64')
if default_fp is not None:
impl.get_runtime().set_default_fp(default_fp)
if default_ip is not None:
impl.get_runtime().set_default_ip(default_ip)
# submodule configurations (spec_cfg):
env_spec.add('print_preprocessed')
env_spec.add('log_level', str)
env_spec.add('gdb_trigger')
env_spec.add('excepthook')
env_spec.add('experimental_real_function')
env_spec.add('short_circuit_operators')
# compiler configurations (ti.cfg):
for key in dir(ti.cfg):
if key in ['arch', 'default_fp', 'default_ip']:
continue
_cast = type(getattr(ti.cfg, key))
if _cast is bool:
_cast = None
env_comp.add(key, _cast)
unexpected_keys = kwargs.keys()
if len(unexpected_keys):
raise KeyError(
f'Unrecognized keyword argument(s) for ti.init: {", ".join(unexpected_keys)}'
)
# dispatch configurations that are not in ti.cfg:
if not _test_mode:
ti.set_gdb_trigger(spec_cfg.gdb_trigger)
impl.get_runtime().print_preprocessed = spec_cfg.print_preprocessed
impl.get_runtime().experimental_real_function = \
spec_cfg.experimental_real_function
impl.get_runtime().short_circuit_operators = \
spec_cfg.short_circuit_operators
ti.set_logging_level(spec_cfg.log_level.lower())
if spec_cfg.excepthook:
# TODO(#1405): add a way to restore old excepthook
ti.enable_excepthook()
# select arch (backend):
env_arch = os.environ.get('TI_ARCH')
if env_arch is not None:
ti.info(f'Following TI_ARCH setting up for arch={env_arch}')
arch = _ti_core.arch_from_name(env_arch)
ti.cfg.arch = adaptive_arch_select(arch, enable_fallback, ti.cfg.use_gles)
if ti.cfg.arch == cc:
_ti_core.set_tmp_dir(locale_encode(prepare_sandbox()))
print(f'[Taichi] Starting on arch={_ti_core.arch_name(ti.cfg.arch)}')
# Torch based ndarray on opengl backend allocates memory on host instead of opengl backend.
# So it won't work.
if ti.cfg.arch == opengl and ti.cfg.ndarray_use_torch:
ti.warn(
'Opengl backend doesn\'t support torch based ndarray. Setting ndarray_use_torch to False.'
)
ti.cfg.ndarray_use_torch = False
if _test_mode:
return spec_cfg
get_default_kernel_profiler().set_kernel_profiler_mode(
ti.cfg.kernel_profiler)
# create a new program:
impl.get_runtime().create_program()
ti.trace('Materializing runtime...')
impl.get_runtime().prog.materialize_runtime()
impl._root_fb = FieldsBuilder()
if not os.environ.get("TI_DISABLE_SIGNAL_HANDLERS", False):
impl.get_runtime()._register_signal_handlers()
return None