24783200705

Committed 22 Apr 2026 02:12PM UTC coverage: 63.895%. First build

Build # 24783200705

Build Type

Pull #690

github

Committed by

web-flow

Commit Message

Merge 37a7ecd94 into 8dc5e5aa7

Pull Request Pull Request #690: Modular Compile process

Coverage Stats

220 of 341 new or added lines in 12 files covered. (64.52%)

30670 of 48001 relevant lines covered (63.89%)

572.96 hits per line

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71.0

/python/docc/compiler/docc_program.py

from abc import ABC, abstractmethod
import sys
from typing import Any, Optional
import os

from docc.sdfg import StructuredSDFG
from docc.sdfg._sdfg import (
    _enable_statistics,
    _statistics_enabled_by_env,
    _statistics_summary,
)
from docc.compiler.compiled_sdfg import CompiledSDFG
from docc.compiler.target_registry import (
    get_target_schedule_fn,
    get_target_compile_fn,
    get_target_expand_fn,
)


def _parse_docc_debug() -> dict[str, str]:
    debug_env = os.environ.get("DOCC_DEBUG", "")
    debug_dict = {}
    if debug_env:
        for entry in debug_env.split(";"):
            if not entry:
                continue
            parts = entry.split("=", 1)
            key = parts[0].strip()
            value = parts[1].strip() if len(parts) > 1 else ""
            debug_dict[key] = value
    return debug_dict


def _is_debug_dump(flags: dict[str, str]) -> bool:
    return "dump" in flags


def _is_debug_compile(flags: dict[str, str]) -> bool:
    return "build" in flags


class DoccProgram(ABC):

    def __init__(
        self,
        name: str,
        target: str = "none",
        category: str = "server",
        instrumentation_mode: Optional[str] = None,
        capture_args: Optional[bool] = None,
        remote_tuning: bool = False,
    ):
        self.name = name
        self.target = target
        self.category = category
        self.remote_tuning = remote_tuning
        self.last_sdfg: Optional[StructuredSDFG] = None
        self.cache: dict = {}
        debug_flags = _parse_docc_debug()
        self.debug_dump: bool = _is_debug_dump(debug_flags)
        self.debug_build: bool = _is_debug_compile(debug_flags)

        # Check environment variable DOCC_CI
        docc_ci = os.environ.get("DOCC_CI", "")
        if docc_ci:
            if docc_ci == "regions":
                if instrumentation_mode is None:
                    instrumentation_mode = "ols"
            elif docc_ci == "arg-capture":
                if capture_args is None:
                    capture_args = True
            else:
                # Full mode (or unknown value treated as full)
                if instrumentation_mode is None:
                    instrumentation_mode = "ols"
                if capture_args is None:
                    capture_args = True

        self.instrumentation_mode = instrumentation_mode
        self.capture_args = capture_args

    @abstractmethod
    def __call__(self, *args: Any) -> Any:
        pass

    @abstractmethod
    def compile(self, *args: Any, output_folder: Optional[str] = None) -> CompiledSDFG:
        pass

    def sdfg_pipe(
        self,
        sdfg: StructuredSDFG,
        output_folder: Optional[str],
        instrumentation_mode: str,
        capture_args: bool,
    ) -> str:

        if self.debug_dump:
            sdfg.dump(output_folder, "py0.parsed", dump_dot=True)

        # Enable statistics if envvar is set
        if _statistics_enabled_by_env():
            _enable_statistics()

        sdfg.validate()

        # Tensor targets keep tensor nodes
        custom_expand_fn = get_target_expand_fn(self.target)
        if custom_expand_fn is not None:
            custom_expand_fn(sdfg, self.category, {})
        else:
            sdfg.expand()
        if self.debug_dump:
            sdfg.dump(output_folder, "py1.expanded", dump_dot=True)

        # Simplify pipelines
        sdfg.simplify()
        if self.debug_dump:
            sdfg.dump(output_folder, "py2.opt", dump_dot=True)

        # Normalization for scheduling
        if self.target != "none":
            sdfg.normalize()

        if self.debug_dump or instrumentation_mode or capture_args:
            sdfg.dump(
                output_folder,
                "py3.norm",
                dump_dot=self.debug_dump,
                dump_json=True,
                record_for_instrumentation=True,
            )

        # Schedule if target is specified

        if self.target != "none":
            # Check for custom registered target first
            custom_schedule_fn = get_target_schedule_fn(self.target)
            if custom_schedule_fn is not None:
                custom_schedule_fn(
                    sdfg, self.category, {"remote_tuning": self.remote_tuning}
                )
            else:
                sdfg.schedule(self.target, self.category, self.remote_tuning)

            if self.debug_dump:
                sdfg.dump(output_folder, "py4.post_sched", dump_dot=True)

        self.last_sdfg = sdfg

        custom_compile_fn = get_target_compile_fn(self.target)
        if custom_compile_fn is not None:
            lib_path = custom_compile_fn(
                sdfg,
                output_folder,
                instrumentation_mode,
                capture_args,
                {"debug_build": self.debug_build},
            )
        else:
            lib_path = sdfg._compile(
                output_folder=output_folder,
                target=self.target,
                instrumentation_mode=instrumentation_mode,
                capture_args=capture_args,
                debug_build=self.debug_build,
            )

        # Dump statistics after compile
        if _statistics_enabled_by_env():
            print(_statistics_summary(), file=sys.stderr)

        return lib_path

    @abstractmethod
    def to_sdfg(self, *args: Any) -> StructuredSDFG:
        pass

    @abstractmethod
    def _convert_inputs(self, args: tuple) -> tuple:
        pass

    @abstractmethod
    def _convert_outputs(self, result: Any, original_args: tuple) -> Any:
        pass

    def _get_cache_key(self, *args: Any) -> str:
        return ""

1	from abc import ABC, abstractmethod	4✔
2	import sys	4✔
3	from typing import Any, Optional	4✔
4	import os	4✔
5
6	from docc.sdfg import StructuredSDFG	4✔
7	from docc.sdfg._sdfg import (	4✔
8	_enable_statistics,
9	_statistics_enabled_by_env,
10	_statistics_summary,
11	)
12	from docc.compiler.compiled_sdfg import CompiledSDFG	4✔
13	from docc.compiler.target_registry import (	4✔
14	get_target_schedule_fn,
15	get_target_compile_fn,
16	get_target_expand_fn,
17	)
18
19
20	def _parse_docc_debug() -> dict[str, str]:	4✔
21	debug_env = os.environ.get("DOCC_DEBUG", "")	4✔
22	debug_dict = {}	4✔
23	if debug_env:	4✔
NEW 24	for entry in debug_env.split(";"):	×
NEW 25	if not entry:	×
NEW 26	continue	×
NEW 27	parts = entry.split("=", 1)	×
NEW 28	key = parts[0].strip()	×
NEW 29	value = parts[1].strip() if len(parts) > 1 else ""	×
NEW 30	debug_dict[key] = value	×
31	return debug_dict	4✔
32
33
34	def _is_debug_dump(flags: dict[str, str]) -> bool:	4✔
35	return "dump" in flags	4✔
36
37
38	def _is_debug_compile(flags: dict[str, str]) -> bool:	4✔
39	return "build" in flags	4✔
40
41
42	class DoccProgram(ABC):	4✔
43
44	def __init__(	4✔
45	self,
46	name: str,
47	target: str = "none",
48	category: str = "server",
49	instrumentation_mode: Optional[str] = None,
50	capture_args: Optional[bool] = None,
51	remote_tuning: bool = False,
52	):
53	self.name = name	4✔
54	self.target = target	4✔
55	self.category = category	4✔
56	self.remote_tuning = remote_tuning	4✔
57	self.last_sdfg: Optional[StructuredSDFG] = None	4✔
58	self.cache: dict = {}	4✔
59	debug_flags = _parse_docc_debug()	4✔
60	self.debug_dump: bool = _is_debug_dump(debug_flags)	4✔
61	self.debug_build: bool = _is_debug_compile(debug_flags)	4✔
62
63	# Check environment variable DOCC_CI
64	docc_ci = os.environ.get("DOCC_CI", "")	4✔
65	if docc_ci:	4✔
66	if docc_ci == "regions":	×
67	if instrumentation_mode is None:	×
68	instrumentation_mode = "ols"	×
69	elif docc_ci == "arg-capture":	×
70	if capture_args is None:	×
71	capture_args = True	×
72	else:
73	# Full mode (or unknown value treated as full)
74	if instrumentation_mode is None:	×
75	instrumentation_mode = "ols"	×
76	if capture_args is None:	×
77	capture_args = True	×
78
79	self.instrumentation_mode = instrumentation_mode	4✔
80	self.capture_args = capture_args	4✔
81
82	@abstractmethod	4✔
83	def __call__(self, *args: Any) -> Any:	4✔
84	pass	×
85
86	@abstractmethod	4✔
87	def compile(self, *args: Any, output_folder: Optional[str] = None) -> CompiledSDFG:	4✔
88	pass	×
89
90	def sdfg_pipe(	4✔
91	self,
92	sdfg: StructuredSDFG,
93	output_folder: Optional[str],
94	instrumentation_mode: str,
95	capture_args: bool,
96	) -> str:
97
98	if self.debug_dump:	4✔
99	sdfg.dump(output_folder, "py0.parsed", dump_dot=True)	×
100
101	# Enable statistics if envvar is set
102	if _statistics_enabled_by_env():	4✔
103	_enable_statistics()	×
104
105	sdfg.validate()	4✔
106
107	# Tensor targets keep tensor nodes
108	custom_expand_fn = get_target_expand_fn(self.target)	4✔
109	if custom_expand_fn is not None:	4✔
110	custom_expand_fn(sdfg, self.category, {})	4✔
111	else:
112	sdfg.expand()	4✔
113	if self.debug_dump:	4✔
114	sdfg.dump(output_folder, "py1.expanded", dump_dot=True)	×
115
116	# Simplify pipelines
117	sdfg.simplify()	4✔
118	if self.debug_dump:	4✔
119	sdfg.dump(output_folder, "py2.opt", dump_dot=True)	×
120
121	# Normalization for scheduling
122	if self.target != "none":	4✔
123	sdfg.normalize()	4✔
124
125	if self.debug_dump or instrumentation_mode or capture_args:	4✔
126	sdfg.dump(	4✔
127	output_folder,
128	"py3.norm",
129	dump_dot=self.debug_dump,
130	dump_json=True,
131	record_for_instrumentation=True,
132	)
133
134	# Schedule if target is specified
135
136	if self.target != "none":	4✔
137	# Check for custom registered target first
138	custom_schedule_fn = get_target_schedule_fn(self.target)	4✔
139	if custom_schedule_fn is not None:	4✔
140	custom_schedule_fn(	4✔
141	sdfg, self.category, {"remote_tuning": self.remote_tuning}
142	)
143	else:
144	sdfg.schedule(self.target, self.category, self.remote_tuning)	4✔
145
146	if self.debug_dump:	4✔
147	sdfg.dump(output_folder, "py4.post_sched", dump_dot=True)	×
148
149	self.last_sdfg = sdfg	4✔
150
151	custom_compile_fn = get_target_compile_fn(self.target)	4✔
152	if custom_compile_fn is not None:	4✔
153	lib_path = custom_compile_fn(	4✔
154	sdfg,
155	output_folder,
156	instrumentation_mode,
157	capture_args,
158	{"debug_build": self.debug_build},
159	)
160	else:
161	lib_path = sdfg._compile(	4✔
162	output_folder=output_folder,
163	target=self.target,
164	instrumentation_mode=instrumentation_mode,
165	capture_args=capture_args,
166	debug_build=self.debug_build,
167	)
168
169	# Dump statistics after compile
170	if _statistics_enabled_by_env():	4✔
171	print(_statistics_summary(), file=sys.stderr)	×
172
173	return lib_path	4✔
174
175	@abstractmethod	4✔
176	def to_sdfg(self, *args: Any) -> StructuredSDFG:	4✔
177	pass	×
178
179	@abstractmethod	4✔
180	def _convert_inputs(self, args: tuple) -> tuple:	4✔
181	pass	×
182
183	@abstractmethod	4✔
184	def _convert_outputs(self, result: Any, original_args: tuple) -> Any:	4✔
185	pass	×
186
187	def _get_cache_key(self, *args: Any) -> str:	4✔
188	return ""	×

daisytuner / docc / 24783200705

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