things that are only used in one place don't belong in helpers [pr] (#6878)

* things that are only used in one place don't belong in helpers [pr]

* pretty print moved

extra/ops.py

@@ -3,8 +3,8 @@ from typing import Dict, Union, Tuple, Any, List, cast
 import functools, hashlib
 from enum import Enum, auto
 from dataclasses import dataclass
-from tinygrad.helpers import dedup, pretty_print, prod
-from tinygrad.ops import ReduceOps, UnaryOps, BinaryOps, TernaryOps, UOp, UOps
+from tinygrad.helpers import dedup, prod
+from tinygrad.ops import ReduceOps, UnaryOps, BinaryOps, TernaryOps, UOp, UOps, pretty_print
 from tinygrad.dtype import ImageDType, PtrDType, dtypes, DType, ConstType
 from tinygrad.shape.symbolic import Variable, sint
 from tinygrad.shape.shapetracker import ShapeTracker

test/test_profiler.py

@@ -1,7 +1,7 @@
 import unittest, struct, contextlib, tempfile, pathlib, json, time, atexit, random
 from tinygrad import Device, Tensor, dtypes, TinyJit
-from tinygrad.helpers import CI, getenv, Context, ProfileLogger
-from tinygrad.device import Buffer, BufferOptions, HCQCompiled
+from tinygrad.helpers import CI, getenv, Context
+from tinygrad.device import Buffer, BufferOptions, ProfileLogger, HCQCompiled
 from tinygrad.engine.schedule import create_schedule
 from tinygrad.engine.realize import get_runner
 

test/unit/test_helpers.py

@@ -1,7 +1,9 @@
 import gzip, unittest
 from PIL import Image
 from tinygrad.helpers import Context, ContextVar
-from tinygrad.helpers import merge_dicts, strip_parens, prod, round_up, fetch, fully_flatten, from_mv, to_mv, get_contraction, get_shape
+from tinygrad.helpers import merge_dicts, strip_parens, prod, round_up, fetch, fully_flatten, from_mv, to_mv
+from tinygrad.tensor import get_shape
+from tinygrad.codegen.lowerer import get_contraction
 from tinygrad.shape.symbolic import Variable, NumNode
 import numpy as np
 

tinygrad/codegen/kernel.py

@@ -10,13 +10,13 @@ from tinygrad.ops import resolve
 from tinygrad.device import Device
 from tinygrad.renderer import Renderer, TensorCore, Program
 from tinygrad.dtype import ImageDType, PtrDType
-from tinygrad.helpers import all_same, colored, ansilen, dedup, getenv, prod, round_up, all_int, get_contraction, to_function_name, diskcache_put
+from tinygrad.helpers import all_same, colored, ansilen, dedup, getenv, prod, round_up, all_int, to_function_name, diskcache_put
 from tinygrad.helpers import DEBUG, TC_OPT, USE_TC, AMX
 from tinygrad.shape.shapetracker import ShapeTracker
 from tinygrad.shape.symbolic import Variable, sint
 from tinygrad.shape.view import strides_for_shape
 from tinygrad.codegen.uopgraph import linearize_uop, full_graph_rewrite
-from tinygrad.codegen.lowerer import ast_to_uop
+from tinygrad.codegen.lowerer import ast_to_uop, get_contraction
 
 class OptOps(Enum):
   TC = auto(); UPCAST = auto(); UPCASTMID = auto(); UNROLL = auto(); LOCAL = auto() # noqa: E702

tinygrad/codegen/lowerer.py

@@ -1,6 +1,6 @@
 # the job of the lowerer is to do indexing
 from __future__ import annotations
-import functools
+import functools, itertools, operator
 from dataclasses import dataclass
 from typing import List, Tuple, cast, Optional
 from tinygrad.shape.shapetracker import ShapeTracker, variable_to_uop
@@ -8,7 +8,14 @@ from tinygrad.shape.symbolic import sint
 from tinygrad.dtype import dtypes
 from tinygrad.ops import KernelInfo, BinaryOps, UOp, UOps, graph_rewrite, PatternMatcher, UPat, resolve
 from tinygrad.renderer import Renderer
-from tinygrad.helpers import all_int, get_contraction, prod, partition, flatten
+from tinygrad.helpers import all_int, prod, partition, flatten
+
+# returns the axes to create new_shape if new_shape can be created by combining axis from old_shape
+def get_contraction(old_shape:Tuple[sint, ...], new_shape:Tuple[sint, ...]) -> Optional[List[List[int]]]:
+  acc_old, acc_new = list(itertools.accumulate(old_shape, operator.mul)), list(itertools.accumulate(new_shape, operator.mul))
+  try: split = [acc_old.index(acc)+1 if acc != 1 else 0 for acc in acc_new]
+  except ValueError: return None
+  return [list(range(st,ed)) for st,ed in zip([0]+split[:-1], split[:-1]+[len(old_shape)])]
 
 # ***** indexing *****
 

tinygrad/device.py

@@ -1,10 +1,10 @@
 from __future__ import annotations
-import multiprocessing, decimal, statistics, random
+import multiprocessing, decimal, statistics, random, json
 from dataclasses import dataclass, replace
 from collections import defaultdict
-from typing import List, Optional, Dict, Tuple, Any, cast, Protocol, Type, Iterator
+from typing import List, Optional, Dict, Tuple, Any, cast, Protocol, Type, Iterator, Union
 import importlib, inspect, functools, pathlib, os, ctypes, atexit, time, contextlib, array
-from tinygrad.helpers import SAVE_SCHEDULE, getenv, diskcache_get, diskcache_put, DEBUG, GlobalCounters, flat_mv, from_mv, ProfileLogger, PROFILE
+from tinygrad.helpers import SAVE_SCHEDULE, getenv, diskcache_get, diskcache_put, DEBUG, GlobalCounters, flat_mv, from_mv, PROFILEPATH, PROFILE
 from tinygrad.dtype import DType, ImageDType
 from tinygrad.renderer import Renderer
 
@@ -495,6 +495,44 @@ class HCQProgram:
     if wait: self.device.timeline_signal.wait(self.device.timeline_value - 1)
     return (float(sig_en.timestamp - sig_st.timestamp) / 1e6) if wait else None
 
+class ProfileLogger:
+  writers: int = 0
+  mjson: List[Dict] = []
+  actors: Dict[Union[str, Tuple[str, str]], int] = {}
+
+  def __init__(self): self.events, self.deps, ProfileLogger.writers = [], [], ProfileLogger.writers + 1
+
+  def add_event(self, ev_name, ev_start, ev_end, actor, subactor=None, args=None): self.events += [(ev_name, ev_start, ev_end, actor, subactor, args)]
+
+  def _ensure_actor(self, actor_name, subactor_name):
+    if actor_name not in self.actors:
+      self.actors[actor_name] = (pid:=len(self.actors))
+      self.mjson.append({"name": "process_name", "ph": "M", "pid": pid, "args": {"name": actor_name}})
+
+    if (subactor_key:=(actor_name,subactor_name)) not in self.actors:
+      self.actors[subactor_key] = (tid:=len(self.actors))
+      self.mjson.append({"name": "thread_name", "ph": "M", "pid": self.actors[actor_name], "tid":tid, "args": {"name": subactor_name}})
+
+    return self.actors[actor_name], self.actors.get(subactor_key, -1)
+
+  def __del__(self):
+    # perfetto json docs: https://docs.google.com/document/d/1CvAClvFfyA5R-PhYUmn5OOQtYMH4h6I0nSsKchNAySU/preview
+    for name, st, et, actor_name, subactor_name, args in self.events:
+      pid, tid = self._ensure_actor(actor_name,subactor_name)
+      args = {k: (v if v.__class__ is str else v(et-st)) for k, v in args.items()} if args is not None else None
+      self.mjson.append({"name": name, "ph": "X", "pid": pid, "tid": tid, "ts": st, "dur": et-st, "args": args})
+
+    for en,st,dep_actor_name,dep_subactor_name,actor_name,subactor_name in self.deps:
+      dep_pid, dep_tid = self._ensure_actor(dep_actor_name,dep_subactor_name)
+      pid, tid = self._ensure_actor(actor_name,subactor_name)
+      self.mjson.append({"ph": "s", "pid": dep_pid, "tid": dep_tid, "id": len(self.mjson), "ts": en, "bp": "e"})
+      self.mjson.append({"ph": "f", "pid": pid, "tid": tid, "id": len(self.mjson)-1, "ts": st, "bp": "e"})
+
+    ProfileLogger.writers -= 1
+    if ProfileLogger.writers == 0 and len(self.mjson) > 0:
+      with open(PROFILEPATH.value, "w") as f: f.write(json.dumps({"traceEvents": self.mjson}))
+      print(f"Saved profile to {PROFILEPATH.value}. Use https://ui.perfetto.dev/ to open it.")
+
 class HCQCompiled(Compiled):
   """
   A base class for devices compatible with the HCQ (Hardware Command Queue) API.

tinygrad/helpers.py

@@ -1,11 +1,10 @@
 from __future__ import annotations
 import os, functools, platform, time, re, contextlib, operator, hashlib, pickle, sqlite3, tempfile, pathlib, string, ctypes, sys, gzip
-import itertools, urllib.request, subprocess, shutil, math, json, contextvars, types, copyreg, inspect, importlib
+import urllib.request, subprocess, shutil, math, contextvars, types, copyreg, inspect, importlib
 from dataclasses import dataclass
 from typing import Dict, Tuple, Union, List, ClassVar, Optional, Iterable, Any, TypeVar, TYPE_CHECKING, Callable, Sequence
 if TYPE_CHECKING:  # TODO: remove this and import TypeGuard from typing once minimum python supported version is 3.10
   from typing_extensions import TypeGuard
-  from tinygrad.shape.shapetracker import sint
 
 T = TypeVar("T")
 U = TypeVar("U")
@@ -68,21 +67,6 @@ def get_child(obj, key):
     else: obj = getattr(obj, k)
   return obj
 
-def get_shape(x) -> Tuple[int, ...]:
-  if not hasattr(x, "__len__") or not hasattr(x, "__getitem__") or isinstance(x, str): return ()
-  if (aapi := (hasattr(x, "shape") and x.shape == ())): return ()
-  subs = [get_shape(xi) for xi in x]
-  if not all_same(subs): raise ValueError(f"inhomogeneous shape from {x}")
-  slen = 1 if aapi else len(subs)
-  return (slen,) + (subs[0] if subs else ())
-
-# returns the axes to create new_shape if new_shape can be created by combining axis from old_shape
-def get_contraction(old_shape:Tuple[sint, ...], new_shape:Tuple[sint, ...]) -> Optional[List[List[int]]]:
-  acc_old, acc_new = list(itertools.accumulate(old_shape, operator.mul)), list(itertools.accumulate(new_shape, operator.mul))
-  try: split = [acc_old.index(acc)+1 if acc != 1 else 0 for acc in acc_new]
-  except ValueError: return None
-  return [list(range(st,ed)) for st,ed in zip([0]+split[:-1], split[:-1]+[len(old_shape)])]
-
 @functools.lru_cache(maxsize=None)
 def to_function_name(s:str): return ''.join([c if c in (string.ascii_letters+string.digits+'_') else f'{ord(c):02X}' for c in ansistrip(s)])
 @functools.lru_cache(maxsize=None)
@@ -171,44 +155,6 @@ class Profiling(contextlib.ContextDecorator):
               colored(_format_fcn(fcn).ljust(50), "yellow"),
               colored(f"<- {(scallers[0][1][2]/tottime)*100:3.0f}% {_format_fcn(scallers[0][0])}", "BLACK") if scallers else '')
 
-class ProfileLogger:
-  writers: int = 0
-  mjson: List[Dict] = []
-  actors: Dict[Union[str, Tuple[str, str]], int] = {}
-
-  def __init__(self): self.events, self.deps, ProfileLogger.writers = [], [], ProfileLogger.writers + 1
-
-  def add_event(self, ev_name, ev_start, ev_end, actor, subactor=None, args=None): self.events += [(ev_name, ev_start, ev_end, actor, subactor, args)]
-
-  def _ensure_actor(self, actor_name, subactor_name):
-    if actor_name not in self.actors:
-      self.actors[actor_name] = (pid:=len(self.actors))
-      self.mjson.append({"name": "process_name", "ph": "M", "pid": pid, "args": {"name": actor_name}})
-
-    if (subactor_key:=(actor_name,subactor_name)) not in self.actors:
-      self.actors[subactor_key] = (tid:=len(self.actors))
-      self.mjson.append({"name": "thread_name", "ph": "M", "pid": self.actors[actor_name], "tid":tid, "args": {"name": subactor_name}})
-
-    return self.actors[actor_name], self.actors.get(subactor_key, -1)
-
-  def __del__(self):
-    # perfetto json docs: https://docs.google.com/document/d/1CvAClvFfyA5R-PhYUmn5OOQtYMH4h6I0nSsKchNAySU/preview
-    for name, st, et, actor_name, subactor_name, args in self.events:
-      pid, tid = self._ensure_actor(actor_name,subactor_name)
-      args = {k: (v if v.__class__ is str else v(et-st)) for k, v in args.items()} if args is not None else None
-      self.mjson.append({"name": name, "ph": "X", "pid": pid, "tid": tid, "ts": st, "dur": et-st, "args": args})
-
-    for en,st,dep_actor_name,dep_subactor_name,actor_name,subactor_name in self.deps:
-      dep_pid, dep_tid = self._ensure_actor(dep_actor_name,dep_subactor_name)
-      pid, tid = self._ensure_actor(actor_name,subactor_name)
-      self.mjson.append({"ph": "s", "pid": dep_pid, "tid": dep_tid, "id": len(self.mjson), "ts": en, "bp": "e"})
-      self.mjson.append({"ph": "f", "pid": pid, "tid": tid, "id": len(self.mjson)-1, "ts": st, "bp": "e"})
-
-    ProfileLogger.writers -= 1
-    if ProfileLogger.writers == 0 and len(self.mjson) > 0:
-      with open(PROFILEPATH.value, "w") as f: f.write(json.dumps({"traceEvents": self.mjson}))
-      print(f"Saved profile to {PROFILEPATH.value}. Use https://ui.perfetto.dev/ to open it.")
-
 # *** universal database cache ***
 
 _cache_dir: str = getenv("XDG_CACHE_HOME", os.path.expanduser("~/Library/Caches" if OSX else "~/.cache"))
@@ -363,16 +309,6 @@ class tqdm:
 class trange(tqdm):
   def __init__(self, n:int, **kwargs): super().__init__(iterable=range(n), total=n, **kwargs)
 
-def pretty_print(x:Any, rep:Callable, srcfn=lambda x: x.src, cache=None, d=0)->str:
-  def dfs(x:Any, cache:dict):
-    for s in srcfn(x) or []:
-      cache.setdefault(s, [len(cache), 0, False])[1] += 1
-      if cache[s][1] == 1: dfs(s, cache)
-  if cache is None: dfs(x, cache:={})
-  if (cx:=cache.setdefault(x, [0,0,False]))[2]: return f"{' '*d} x{cx[0]}"
-  cx[2], srcs = True, ('None' if srcfn(x) is None else ''.join(f'\n{pretty_print(s, rep, srcfn, cache, d+2)},' for s in srcfn(x)))
-  return f"{' '*d}{f'x{cx[0]}:=' * (cx[1]>1)}{rep(x)}" % srcs
-
 # *** universal support for code object pickling
 
 def _reconstruct_code(*args): return types.CodeType(*args)

tinygrad/ops.py

@@ -6,7 +6,7 @@ from enum import auto, IntEnum, Enum
 from dataclasses import dataclass, field
 from weakref import WeakValueDictionary
 from tinygrad.dtype import ConstType, ImageDType, PtrDType, dtypes, DType, truncate
-from tinygrad.helpers import ContextVar, pretty_print, prod, getenv, all_same
+from tinygrad.helpers import ContextVar, prod, getenv, all_same
 if TYPE_CHECKING:
   from tinygrad.shape.symbolic import Variable, sint
   from tinygrad.shape.shapetracker import ShapeTracker
@@ -159,6 +159,17 @@ def resolve(x, default:bool=True):
 def smax(lst): return max(lst, key=lambda x: x if isinstance(x, int) else x.vmax)
 def ssimplify(uop): return uop.ssimplify() if isinstance(uop, UOp) else uop
 
+# used for UOp and UPat
+def pretty_print(x:Any, rep:Callable, srcfn=lambda x: x.src, cache=None, d=0)->str:
+  def dfs(x:Any, cache:dict):
+    for s in srcfn(x) or []:
+      cache.setdefault(s, [len(cache), 0, False])[1] += 1
+      if cache[s][1] == 1: dfs(s, cache)
+  if cache is None: dfs(x, cache:={})
+  if (cx:=cache.setdefault(x, [0,0,False]))[2]: return f"{' '*d} x{cx[0]}"
+  cx[2], srcs = True, ('None' if srcfn(x) is None else ''.join(f'\n{pretty_print(s, rep, srcfn, cache, d+2)},' for s in srcfn(x)))
+  return f"{' '*d}{f'x{cx[0]}:=' * (cx[1]>1)}{rep(x)}" % srcs
+
 ucache:WeakValueDictionary[Tuple, UOp] = WeakValueDictionary()
 class UOp(MathTrait):
   def __reduce__(self): return UOp, (self.op, self.dtype, self.src, self.arg)

tinygrad/tensor.py

@@ -6,7 +6,7 @@ from typing import List, Tuple, Callable, Optional, ClassVar, Type, Union, Seque
 from collections import defaultdict
 
 from tinygrad.dtype import DType, DTypeLike, dtypes, ImageDType, ConstType, least_upper_float, least_upper_dtype, sum_acc_dtype, to_dtype
-from tinygrad.helpers import argfix, make_pair, flatten, prod, all_int, round_up, merge_dicts, argsort, getenv, get_shape, fully_flatten, dedup
+from tinygrad.helpers import argfix, make_pair, flatten, prod, all_int, round_up, merge_dicts, argsort, getenv, all_same, fully_flatten, dedup
 from tinygrad.helpers import IMAGE, DEBUG, WINO, _METADATA, Metadata, TRACEMETA
 from tinygrad.lazy import LazyBuffer
 from tinygrad.multi import MultiLazyBuffer
@@ -57,6 +57,14 @@ def _fromnp(x: 'np.ndarray') -> LazyBuffer:  # type: ignore [name-defined] # noq
   del ret.srcs
   return ret
 
+def get_shape(x) -> Tuple[int, ...]:
+  if not hasattr(x, "__len__") or not hasattr(x, "__getitem__") or isinstance(x, str): return ()
+  if (aapi := (hasattr(x, "shape") and x.shape == ())): return ()
+  subs = [get_shape(xi) for xi in x]
+  if not all_same(subs): raise ValueError(f"inhomogeneous shape from {x}")
+  slen = 1 if aapi else len(subs)
+  return (slen,) + (subs[0] if subs else ())
+
 def _frompy(x:Union[List, Tuple, bytes], dtype:DType) -> LazyBuffer:
   if isinstance(x, bytes): ret, data = LazyBuffer.metaop(MetaOps.EMPTY, (len(x)//dtype.itemsize,), dtype, "PYTHON"), x
   else: