forked from tinygrad/tinygrad
move image to post coalese (#16749)
* move image to post coalese
* fix types
* dv2
* work
* load_store_indexing
* lsi
* simplify indexing
* always simplify
* more
* whitespace
* no simplify
* no early opt
* fix linter
* exit early without valid
* always simplify
* relax ir3
* no gep
* Revert "no gep"
This reverts commit 3fa4dd6dfa.
* shapes in ctx
* disable IR3
This commit is contained in:
George Hotz
@@ -314,8 +314,9 @@ jobs:
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run: BENCHMARK_LOG=openpilot_0_11_0_vision PYTHONPATH="." ASSERT_MIN_STEP_TIME=17 DEV=QCOM FLOAT16=1 IMAGE=1 NOLOCALS=1 taskset -c 4-7 python3 examples/openpilot/compile3.py https://github.com/commaai/openpilot/raw/v0.11.0/selfdrive/modeld/models/driving_vision.onnx
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- name: openpilot compile3 0.11.0 driving_vision (from pickle)
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run: BENCHMARK_LOG=openpilot_0_11_0_vision_run_pickle RUN_PICKLE=1 PYTHONPATH="." ASSERT_MIN_STEP_TIME=17 DEV=QCOM taskset -c 4-7 python3 examples/openpilot/compile3.py
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- name: IR3 openpilot compile3 0.11.0 driving_vision
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run: BENCHMARK_LOG=ir3_openpilot_0_11_0_vision PYTHONPATH="." ASSERT_MIN_STEP_TIME=17 DEV=QCOM:IR3 FLOAT16=1 IMAGE=1 NOLOCALS=1 taskset -c 4-7 python3 examples/openpilot/compile3.py https://github.com/commaai/openpilot/raw/v0.11.0/selfdrive/modeld/models/driving_vision.onnx
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# this is broken
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#- name: IR3 openpilot compile3 0.11.0 driving_vision
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# run: BENCHMARK_LOG=ir3_openpilot_0_11_0_vision PYTHONPATH="." ASSERT_MIN_STEP_TIME=17 DEV=QCOM:IR3 FLOAT16=1 IMAGE=1 NOLOCALS=1 taskset -c 4-7 python3 examples/openpilot/compile3.py https://github.com/commaai/openpilot/raw/v0.11.0/selfdrive/modeld/models/driving_vision.onnx
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- name: openpilot compile3 0.11.0 driving_policy
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run: BENCHMARK_LOG=openpilot_0_11_0_policy PYTHONPATH="." ASSERT_MIN_STEP_TIME=3.2 DEV=QCOM FLOAT16=1 IMAGE=1 NOLOCALS=1 taskset -c 4-7 python3 examples/openpilot/compile3.py https://github.com/commaai/openpilot/raw/v0.11.0/selfdrive/modeld/models/driving_policy.onnx
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- name: openpilot compile3 0.11.0 dmonitoring
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@@ -42,7 +42,7 @@ def compile(onnx_file):
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kernel_calls = [u for u in run_onnx_jit.captured.linear.toposort(gate=lambda x: x.op not in kernel_asts)
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if u.op is Ops.CALL and u.src[0].op in kernel_asts]
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print(f"captured {len(kernel_calls)} kernels")
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np.testing.assert_equal(test_val, ret, "JIT run failed")
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if getenv("TEST", 1): np.testing.assert_equal(test_val, ret, "JIT run failed")
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print("jit run validated")
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# check gated read_image usage
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@@ -17,14 +17,14 @@ from tinygrad.codegen.decomp.op import get_late_rewrite_patterns, get_simplifyin
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from tinygrad.codegen.decomp.transcendental import get_transcendental_patterns
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from tinygrad.codegen.late.expander import expander, pm_pre_expander, pm_group_for_reduce
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from tinygrad.codegen.late.devectorizer import load_store_folding, indexing_simplify, devectorize_buf_and_index, devectorize_alu, pm_reduce, \
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ReduceContext, correct_load_store, pm_render, pm_add_loads, pm_make_images
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ReduceContext, correct_load_store, pm_render, pm_add_loads
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from tinygrad.codegen.opt.postrange import apply_opts
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from tinygrad.codegen.late.gater import pm_move_gates_from_index
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from tinygrad.codegen.simplify import pm_simplify_ranges, pm_flatten_range, pm_split_ranges, pm_load_collapse
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from tinygrad.schedule.rangeify import pm_add_buffers_local, rangeify_codegen, pm_mops, pm_syntactic_sugar, pm_store_ranges
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from tinygrad.codegen.late.linearizer import CFGContext, pm_split_ends, pm_add_control_flow, linearize
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from tinygrad.codegen.late.regalloc import LinearScanRegallocContext, pm_regalloc_rewrite
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from tinygrad.codegen.late.coalese import memory_coalesing
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from tinygrad.codegen.late.coalese import memory_coalesing, pm_simplify_add_image
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pm_remove_vec_dtypes = PatternMatcher([
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# rewrite PARAM to non pointer
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@@ -97,10 +97,6 @@ def full_rewrite_to_sink(ast:UOp, ren:Renderer, optimize:bool=True) -> UOp:
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# add loads and remove invalids
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sink = graph_rewrite(sink, pm_add_loads+pm_remove_invalid, name="** add loads (code)")
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# create image buffers
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if IMAGE and ren.target.device in {"QCOM", "CL", "PYTHON", "NULL"}:
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sink = graph_rewrite(sink, pm_make_images, name="create image buffers", bottom_up=True, ctx=ren.target.arch)
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# devectorize
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sink = graph_rewrite(sink, sym+devectorize_alu+devectorize_buf_and_index+load_store_folding+correct_load_store, ctx=ren, name="devectorize")
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@@ -113,6 +109,7 @@ def full_rewrite_to_sink(ast:UOp, ren:Renderer, optimize:bool=True) -> UOp:
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# do memory coalesing (late)
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sink = memory_coalesing(sink, ren)
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sink = graph_rewrite(sink, pm_simplify_add_image, name="add images", ctx=({}, ren), bottom_up=True)
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# extra symbolic before decomp. crashes without this?
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sink = graph_rewrite(sink, symbolic, name="extra symbolic")
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@@ -2,9 +2,58 @@ from typing import Any
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import itertools
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from collections import defaultdict
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from tinygrad.dtype import dtypes, AddrSpace, Invalid, ImageDType
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from tinygrad.uop.ops import UOp, Ops
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from tinygrad.helpers import getenv
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from tinygrad.uop.ops import UOp, Ops, PatternMatcher, UPat, GroupOp
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from tinygrad.helpers import getenv, IMAGE, all_same
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from tinygrad.renderer import Renderer
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from tinygrad.uop.symbolic import symbolic_simple
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from tinygrad.codegen.late.devectorizer import image_valid_dims, _drop_valid_stmts, uop_given_valid
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def do_devectorize(b:UOp):
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if b.shape == (): return None
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# broadcasting needs to be already unpacked
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if not all_same([x.shape for x in b.src]): return None
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src = []
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for idx in itertools.product(*[range(x) for x in b.shape]):
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idx_c = [UOp.const(dtypes.weakint, i) for i in idx]
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src.append(b.replace(src=tuple([x.index(*idx_c) for x in b.src])))
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return UOp._stack(*src).reshape(b.shape) if b.op is not Ops.STORE else UOp.group(*src)
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devectorizer2 = PatternMatcher([
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# unpack broadcasting
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(UPat(GroupOp.Elementwise, name="b"), do_devectorize),
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])
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def transform_to_image(ctx, buf:UOp, x:UOp) -> UOp|None:
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shapes, ren = ctx
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if not IMAGE or ren.target.device not in {"QCOM", "CL", "PYTHON", "NULL"}: return None
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valid = UOp.const(dtypes.bool, True)
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if x.op == Ops.WHERE and x.src[2].op == Ops.CONST and x.src[2].arg == Invalid: valid,x,_= x.src
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# search for dims that drop the most valid statements
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best_drop, cands = -1, []
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for ch, cw in [shapes[buf.arg.slot]] if buf.arg.slot in shapes else image_valid_dims(buf.dtype.base, buf.max_numel(), ren.target.arch):
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cidx = uop_given_valid(valid, UOp.vectorize((x//4)%cw, x//(4*cw)))
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dropped = len(_drop_valid_stmts(valid, cidx, ch, cw))
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if dropped > best_drop: best_drop, cands = dropped, [(ch, cw, cidx)]
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elif dropped == best_drop: cands.append((ch, cw, cidx))
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# if no candidates, we don't rewrite
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if len(cands) == 0: return None
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# and tiebreak with indexing complexity (ie. number of nodes)
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h, w, cidx = cands[0] if len(cands) == 1 else min(cands, key=lambda cand: len(cand[2].gep(1).simplify().backward_slice))
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buf = buf.replace(dtype=(dtypes.imageh if buf.dtype.itemsize == 2 else dtypes.imagef)((h, w, 4)))
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shapes[buf.arg.slot] = (h, w)
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if valid.op is not Ops.CONST or valid.arg is not True:
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return buf.index(valid.where(cidx.src[1], cidx.src[1].const_like(Invalid)),
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valid.where(cidx.src[0], cidx.src[0].const_like(Invalid)))
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else:
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return buf.index(cidx.src[1], cidx.src[0])
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pm_simplify_add_image = PatternMatcher([
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(UPat(Ops.SHRINK, src=(UPat(Ops.PARAM, name="buf"), UPat(name="x"), UPat(arg=4))), transform_to_image),
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# image load/store is always float
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(UPat(Ops.INDEX, dtype=dtypes.float, name="x").load(dtype=dtypes.half), lambda x: x.load().cast(dtypes.half)),
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(UPat(Ops.INDEX, dtype=dtypes.float, name="x").store(UPat(name="d", dtype=dtypes.half)), lambda x,d: x.store(d.cast(dtypes.float))),
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(UPat.var("x", dtype=dtypes.float).cast(dtypes.half).cast(dtypes.float), lambda x: x),
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])+devectorizer2+symbolic_simple
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def memory_coalesing(sink:UOp, ctx:Renderer) -> UOp:
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if getenv("DMC"): return sink
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@@ -169,11 +169,8 @@ def split_load_store(ctx:Renderer|None, ls:UOp, idx:UOp):
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buf = idx.src[0]
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# determine fold lengths
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lengths = []
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lengths = [1]
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must_divide = True
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# TODO: this belongs in coalese
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if isinstance(buf.dtype, ImageDType): lengths = [4]
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lengths.append(1) # worst case, it's not folded
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# filter fold lengths that don't divide
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offset, mask = idx.src[1].get_idx(), idx.src[1].get_valid()
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