tinygrad/extra/to_movement_ops.py

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from tqdm import tqdm
import itertools
from collections import defaultdict
from typing import List, Tuple, DefaultDict
from extra.optimization.helpers import load_worlds, ast_str_to_ast
from tinygrad.ops import MovementOps, BufferOps, LazyOp
from tinygrad.helpers import prod
from tinygrad.shape.shapetracker import ShapeTracker
from tinygrad.shape.symbolic import sym_infer, Node
def apply_mop(st: ShapeTracker, mop_arg: Tuple[MovementOps, Tuple]) -> ShapeTracker:
mop, arg = mop_arg
if mop == MovementOps.RESHAPE:
# shapetracker doesn't allow flattening with -1 but required for MovementOps.RESHAPE
if arg == (-1,): return st.reshape((prod(st.views[-1].shape),))
return st.reshape(arg)
if mop == MovementOps.PERMUTE: return st.permute(arg)
if mop == MovementOps.EXPAND:
if len(arg) != len(st.shape): st = st.reshape((1,*st.shape))
return st.expand(arg)
if mop == MovementOps.PAD: return st.pad(arg)
if mop == MovementOps.SHRINK: return st.shrink(arg)
if mop == MovementOps.STRIDE: return st.stride(arg)
raise ValueError("invalid mop")
def make_scratch_st(st: ShapeTracker) -> ShapeTracker:
return ShapeTracker.from_shape((get_buffer_size(st.views[0].shape, st.views[0].strides, st.views[0].offset, st.views[0].mask),))
# ShapeTracker to an equivalent series of MovementOps (https://github.com/tinygrad/tinygrad/pull/2216)
def to_movement_ops(st: ShapeTracker) -> List[Tuple[MovementOps, Tuple]]:
to_apply:List[Tuple[MovementOps, Tuple]] = []
for i, v in enumerate(st.views):
real_shape = tuple(y-x for x,y in v.mask) if v.mask else v.shape
offset = v.offset + sum(st*(s-1) for s,st in zip(real_shape, v.strides) if st<0)
real_offset = offset + (sum(x*st for (x,_),st in zip(v.mask, v.strides)) if v.mask else 0)
real_real_shape = [s for s,st in zip(real_shape, v.strides) if st]
strides: List[Node|int] = [abs(st) if isinstance(st,int) else st for st in v.strides if st]
buffer_size = sum((s-1)*st for s,st in zip(real_real_shape,strides)) + 1
if i: buffer_size = prod(st.views[i-1].shape) - real_offset
def sort_by_strides(shape, strides): return sorted(zip(shape, strides), key=lambda k: (k[1],-k[0]), reverse=True), sorted(range(len(strides)), key=lambda k: (strides[k],-real_real_shape[k]), reverse=True)
ordered_shape_strides, order = sort_by_strides(real_real_shape, strides)
to_apply.extend([(MovementOps.RESHAPE, (-1,)), (MovementOps.SHRINK, ((real_offset, real_offset+buffer_size),))])
if strides:
if (ordered_shape_strides[0][0]*ordered_shape_strides[0][1])-buffer_size>0: to_apply.append((MovementOps.PAD, ((0, (ordered_shape_strides[0][0] * ordered_shape_strides[0][1]) - buffer_size),)))
for i, shape_stride in enumerate(ordered_shape_strides):
if i<len(ordered_shape_strides)-1 and shape_stride[1] < ordered_shape_strides[i+1][0]*ordered_shape_strides[i+1][1]:
remaining_buffer = ordered_shape_strides[i-1][1] if i>0 else buffer_size
to_apply.append((MovementOps.EXPAND, (shape_stride[0], *(s[0] for s in ordered_shape_strides[:i]), remaining_buffer)))
to_apply.append((MovementOps.PERMUTE, (*range(1,i+1), 0, i+1)))
to_apply.append((MovementOps.RESHAPE, (*(s[0] for s in ordered_shape_strides[:i]), shape_stride[0]*remaining_buffer)))
to_apply.append((MovementOps.PAD, (*((0,0) for _ in range(i)), (0, shape_stride[0]*shape_stride[1]))))
to_apply.append((MovementOps.RESHAPE, (*(s[0] for s in ordered_shape_strides[:i+1]), remaining_buffer+shape_stride[1])))
ordered_shape_strides[i] = (ordered_shape_strides[i][0], remaining_buffer+shape_stride[1])
else:
to_apply.append((MovementOps.SHRINK, (*((0, s[0]) for s in ordered_shape_strides[:i]), (0, shape_stride[0]*shape_stride[1]))))
to_apply.append((MovementOps.RESHAPE, (*[s[0] for s in ordered_shape_strides[:i+1]], shape_stride[1])))
to_apply.extend([(MovementOps.SHRINK, (*[(0, s[0]) for s in ordered_shape_strides], (0,1))), (MovementOps.RESHAPE, tuple(s[0] for s in ordered_shape_strides))])
if order != list(range(len(order))): to_apply.append((MovementOps.PERMUTE, tuple(order.index(i) for i in range(len(strides)))))
to_apply.append((MovementOps.RESHAPE, tuple(s if st else 1 for s,st in zip(real_shape, v.strides))))
if any(i<0 for i in v.strides): to_apply.append((MovementOps.STRIDE, tuple(-1 if st<0 else 1 for st in v.strides)))
# then, we apply pre expand pads
if v.mask is not None:
pre_expand_pads = tuple((x,s-y) if st != 0 else (0,0) for (x,y),s,st in zip(v.mask, v.shape, v.strides))
post_expand_pads = tuple((x,s-y) if st == 0 else (0,0) for (x,y),s,st in zip(v.mask, v.shape, v.strides))
if any(x != (0,0) for x in pre_expand_pads):
to_apply.append((MovementOps.PAD, pre_expand_pads))
real_shape = tuple(x+s[0]+s[1] for x,s in zip(real_shape, pre_expand_pads))
# then, we do any expands
if any(s != 1 and st == 0 for s,st in zip(real_shape, v.strides)): to_apply.append((MovementOps.EXPAND, real_shape))
# lastly, we apply post expand pads
if v.mask is not None and any(x != (0,0) for x in post_expand_pads): to_apply.append((MovementOps.PAD, post_expand_pads))
scratch_st = make_scratch_st(st)
ret = []
for mop_arg in to_apply:
st = apply_mop(scratch_st, mop_arg)
if st != scratch_st:
ret.append(mop_arg)
scratch_st = st
return ret
def get_real_view(shape, strides, offset, mask):
real_shape = tuple(y-x for x,y in mask) if mask else shape
offset = offset + sum(st * (s-1) for s,st in zip(real_shape, strides) if st<0)
real_offset = offset + (sum(x*st for (x,_),st in zip(mask, strides)) if mask else 0)
real_real_shape = [s for s,st in zip(real_shape, strides) if st]
strides = [abs(st) if isinstance(st,int) else st for st in strides if st]
return real_real_shape, strides, real_offset
def get_buffer_size(shape, strides, offset, mask):
real_real_shape, strides, real_offset = get_real_view(shape, strides, offset, mask)
return real_offset + sum((s-1)*st for s, st in zip(real_real_shape,strides)) + 1
def st_equivalent(st1: ShapeTracker, st2: ShapeTracker):
if (idxs1:=st1.expr_idxs()) == (idxs2:=st2.expr_idxs()): return True
idx1, valid1 = idxs1
idx2, valid2 = idxs2
# always invalid
if valid1 == 0 and valid2 == 0: return True
var1 = idx1.vars() | valid1.vars()
var2 = idx2.vars() | valid2.vars()
# Maybe there are cases that vars are different yet the sts are the same?
if var1 != var2: return False
# brute force over the vars range
vs = list(var1)
for i, ranges in enumerate(itertools.product(*[range(v.min, v.max+1) for v in vs])):
if i > 1000:
print("WARNING: did not search all possible combinations")
# not happening for now
break
var_vals = {k:v for k,v in zip(vs, ranges)}
r1 = sym_infer(idx1, var_vals) if sym_infer(valid1, var_vals) else 0
r2 = sym_infer(idx2, var_vals) if sym_infer(valid2, var_vals) else 0
if r1 != r2: return False
return True
c: DefaultDict[int,int] = defaultdict(int)
def test_rebuild(st: ShapeTracker):
rebuilt_st = make_scratch_st(st)
mops = to_movement_ops(st)
c[len(mops)] += 1
for mop_arg in mops: rebuilt_st = apply_mop(rebuilt_st, mop_arg)
rebuilt_st = rebuilt_st.simplify()
assert st_equivalent(st, rebuilt_st)
last_v1 = st.views[-1]
last_v2 = rebuilt_st.views[-1]
assert last_v1.shape == last_v2.shape, f"{last_v1.shape} != {last_v2.shape}"
def test_interpret_ast(ast:LazyOp):
if ast.op in BufferOps:
test_rebuild(ast.arg.st)
else:
for src in ast.src: test_interpret_ast(src)
if __name__ == "__main__":
ast_strs = load_worlds(False, False, True)[:4000]
for ast_str in tqdm(ast_strs):
test_interpret_ast(ast_str_to_ast(ast_str))
print(f"avg length of mop = {sum(k*v for k,v in c.items()) / sum(c.values()):.2f}")