示例#1
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文件: impl.py 项目: bobcao3/taichi
    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()
示例#2
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文件: impl.py 项目: quadpixels/taichi
    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()
示例#3
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 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()
示例#4
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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()
示例#5
0
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