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Author SHA1 Message Date
geohot 29262a7543 fine for ptx 2025-08-05 18:26:06 -07:00
geohot dcc6ddf0eb that hack broke things 2025-08-05 18:24:58 -07:00
geohot d1d935242b Revert "fix tests"
This reverts commit a27019383d.
2025-08-05 18:06:27 -07:00
geohot 6b330f302d remote metal was flaky 2025-08-05 17:50:14 -07:00
geohot a27019383d fix tests 2025-08-05 17:45:35 -07:00
geohot 8b285e193a move those to fix_kernel_ops 2025-08-05 17:07:12 -07:00
geohot f0c9b11b9e early meta ops 2025-08-05 17:00:49 -07:00
geohot 1902a85ac1 early load buffer 2025-08-05 16:56:10 -07:00
geohot b2fc111e3f cleanup fix_kernel 2025-08-05 16:46:13 -07:00
George HotzandGitHub 067daee5be pin torch to 2.7.1 (#11519) 2025-08-05 15:58:57 -07:00
George HotzandGitHub b39f43c46a optimize in rewrite, try 2 (#11518)
* changes

* fix test uops

* optimize in rewrite, try 2
2025-08-05 15:52:53 -07:00
geohot 07b0df0d86 hotfix: test tensor dims start at 1 2025-08-05 15:40:24 -07:00
George HotzandGitHub 4dabdf7c6d Revert "optimize in rewrite (#11516)" (#11517)
This reverts commit 3b777a9e05.
2025-08-05 15:39:07 -07:00
George HotzandGitHub 3b777a9e05 optimize in rewrite (#11516)
* changes

* fix test uops

* dim shouldn't be 0

* huh, why did that one not save
2025-08-05 15:33:26 -07:00
nimlgenandGitHub ec676eddfa nv: move base address higher (#11514) 2025-08-05 22:42:53 +03:00
qazalandGitHub 7703f8b805 viz: skip flops info if estimates is symbolic (#11513) 2025-08-05 22:12:52 +03:00
12 changed files with 70 additions and 56 deletions
+23 -23
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@@ -870,29 +870,29 @@ jobs:
- name: Test ONNX Runner (WEBGPU)
run: WEBGPU=1 PYTHONPATH=. python3 test/external/external_test_onnx_runner.py
osxremote:
name: MacOS (remote metal)
runs-on: macos-15
timeout-minutes: 10
env:
REMOTE: 1
REMOTEDEV: METAL
steps:
- name: Checkout Code
uses: actions/checkout@v4
- name: Setup Environment
uses: ./.github/actions/setup-tinygrad
with:
key: macos-remote
deps: testing_minimal
- name: Check Device.DEFAULT and print some source
run: |
python -c "from tinygrad import Device; assert Device.DEFAULT == 'REMOTE', Device.DEFAULT"
python -c "from tinygrad import Device; assert Device.default.properties.real_device == 'METAL', Device.default.properties.real_device"
DEBUG=4 python3 test/test_tiny.py TestTiny.test_plus
- name: Run REMOTE=1 Test
run: |
python3 -m pytest test/test_tiny.py test/test_jit.py test/test_subbuffer.py test/test_graph.py test/test_multitensor.py test/test_tensor_variable.py
#osxremote:
# name: MacOS (remote metal)
# runs-on: macos-15
# timeout-minutes: 10
# env:
# REMOTE: 1
# REMOTEDEV: METAL
# steps:
# - name: Checkout Code
# uses: actions/checkout@v4
# - name: Setup Environment
# uses: ./.github/actions/setup-tinygrad
# with:
# key: macos-remote
# deps: testing_minimal
# - name: Check Device.DEFAULT and print some source
# run: |
# python -c "from tinygrad import Device; assert Device.DEFAULT == 'REMOTE', Device.DEFAULT"
# python -c "from tinygrad import Device; assert Device.default.properties.real_device == 'METAL', Device.default.properties.real_device"
# DEBUG=4 python3 test/test_tiny.py TestTiny.test_plus
# - name: Run REMOTE=1 Test
# run: |
# python3 -m pytest test/test_tiny.py test/test_jit.py test/test_subbuffer.py test/test_graph.py test/test_multitensor.py test/test_tensor_variable.py
amdremote:
name: Linux (remote)
+1 -1
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@@ -9,7 +9,7 @@ with open(directory / 'README.md', encoding='utf-8') as f:
testing_minimal = [
"numpy",
"torch",
"torch==2.7.1",
"pytest",
"pytest-xdist",
"hypothesis",
+3 -3
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@@ -892,13 +892,13 @@ class TestIdxUpcast(unittest.TestCase):
@unittest.skipUnless(is_dtype_supported(dtypes.long), "int64 is supported")
def test_overflow_sym(self):
self.do_op_then_assert(dtypes.long, 2048, 2048, UOp.variable("dim3", 0, 2048).bind(32))
self.do_op_then_assert(dtypes.long, 2048, 2048, UOp.variable("dim3", 1, 2048).bind(32))
def test_regular(self):
self.do_op_then_assert(dtypes.int, 64, 64, 64)
def test_regular_sym(self):
self.do_op_then_assert(dtypes.int, 2048, 2048, UOp.variable("dim3", 0, 64).bind(32))
self.do_op_then_assert(dtypes.int, 2048, 2048, UOp.variable("dim3", 1, 64).bind(32))
@unittest.skipIf(PTX, "PTX always convert Ops.INDEX to int64")
def test_symfold(self):
@@ -910,7 +910,7 @@ class TestIdxUpcast(unittest.TestCase):
@unittest.skipIf(is_dtype_supported(dtypes.long), "int64 is supported")
def test_int64_unsupported_overflow_sym(self):
with self.assertRaises(KeyError):
self.do_op_then_assert(dtypes.long, 2048, 2048, UOp.variable("dim3", 0, 2048).bind(32))
self.do_op_then_assert(dtypes.long, 2048, 2048, UOp.variable("dim3", 1, 2048).bind(32))
@unittest.skipIf(is_dtype_supported(dtypes.long), "int64 is supported")
def test_int64_unsupported_overflow(self):
+5
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@@ -16,6 +16,7 @@ from tinygrad.codegen.devectorizer import load_store_folding, load_store_indexin
ReduceContext, correct_load_store, pm_render
from tinygrad.codegen.optional import get_late_rewrite_patterns
from tinygrad.codegen.linearize import block_create, pm_blockend_merge, block_merge, pm_finalize, BlockContext
from tinygrad.opt import pm_optimize
@dataclass
class RewriteStep:
@@ -42,6 +43,10 @@ def get_rewrites_for_renderer(opts:Renderer, linearizer:bool=True) -> list[Rewri
def _get_rewrites_for_renderer(opts:Renderer, linearizer:bool, _QUANTIZE, _DEVECTORIZE, _TRANSCENDENTAL) -> list[RewriteStep]:
# ** lowerer (rewrite_shapetracker_with_index) **
ret: list[RewriteStep] = []
# this is kernel.py
ret.append(RewriteStep(pm_optimize, ctx=lambda _: opts, name="optimize ast"))
if _QUANTIZE and opts.device in {"CPU", "DSP"}: ret.append(RewriteStep(pm_quant, name="quantize"))
ret.append(RewriteStep(pm_lowerer, get_index, name="lowerer", bottom_up=True))
+1 -6
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@@ -7,9 +7,7 @@ from tinygrad.uop.ops import Ops, PatternMatcher, UOp, UPat, Variable, sym_infer
from tinygrad.device import Device, Buffer
from tinygrad.renderer import Renderer, ProgramSpec, Estimates
from tinygrad.engine.schedule import ScheduleItem
from tinygrad.opt import get_optimized_ast
from tinygrad.codegen import full_rewrite
from tinygrad.uop.spec import type_verify
# **************** Program Creation ****************
@@ -27,16 +25,13 @@ def get_program(ast:UOp, renderer:Renderer) -> ProgramSpec:
"""
if getenv("VIZ"): graph_rewrite(ast, PatternMatcher([]), name="View Base AST")
modified_ast = get_optimized_ast(ast, renderer) if ast.arg is None or ast.arg.opts_to_apply is not None else ast
if __debug__: type_verify(list(modified_ast.toposort()))
# linearize
try:
uops = full_rewrite(modified_ast, renderer)
uops = full_rewrite(ast, renderer)
except RuntimeError:
print("***** LINEARIZE FAILURE *****")
print(f"ast = {ast}")
print(f"opts = {modified_ast.arg.applied_opts}")
raise
assert uops[-1].op is Ops.SINK, "last uop must be sink"
+10 -2
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@@ -2,9 +2,10 @@
from tinygrad.opt.kernel import Kernel
from tinygrad.opt.heuristic import hand_coded_optimizations
from tinygrad.uop.ops import UOp
from tinygrad.uop.ops import UOp, PatternMatcher, UPat, Ops
from tinygrad.helpers import NOOPT, BEAM, USE_TC, getenv
from tinygrad.renderer import Renderer
from tinygrad.uop.spec import type_verify
def get_optimized_ast(ast:UOp, renderer:Renderer) -> UOp:
"""
@@ -27,4 +28,11 @@ def get_optimized_ast(ast:UOp, renderer:Renderer) -> UOp:
kb = Kernel(ast, opts=renderer)
rawbufs = bufs_from_lin(kb, allocate=False)
k = beam_search(kb, rawbufs, BEAM.value, bool(getenv("BEAM_ESTIMATE", 1)))
return k.get_optimized_ast()
ret = k.get_optimized_ast()
if __debug__: type_verify(list(ret.toposort()))
return ret
pm_optimize = PatternMatcher([
(UPat(Ops.SINK, name="ast"), lambda ctx,ast:
get_optimized_ast(ast, ctx) if (ast.arg is None or ast.arg.opts_to_apply is not None) and ast.src[0].st is not None else None),
])
+1 -1
View File
@@ -95,7 +95,7 @@ view_right = merge_views+PatternMatcher([
# apply view after reduceops
(UPat(Ops.REDUCE_AXIS, src=(UPat(Ops.VIEW, src=(UPat(GroupOp.All-ALWAYS_CONTIGUOUS, name="src"),), name="v"),), name="r"), reduceop_view_right),
# apply view after elementwise ops
(UPat(GroupOp.All-{Ops.SINK, Ops.REDUCE_AXIS}, name="root"), elementwise_view_right),
(UPat(GroupOp.All-{Ops.SINK, Ops.REDUCE_AXIS, Ops.LOAD, Ops.STORE}, name="root"), elementwise_view_right),
# merge axes for double reduce (invert of SPLIT_REDUCEOP=1)
(UPat(Ops.REDUCE_AXIS, src=(UPat(Ops.REDUCE_AXIS, name="r1"),), name="r2"),
lambda r1,r2: r1.replace(arg=(r1.arg[0], r2.arg[1]+r1.arg[1])) if r1.arg[0] is r2.arg[0] else None),
+1 -1
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@@ -66,7 +66,7 @@ class NVPageTableEntry:
return self.read_fields(entry_id)[f'address{small}{sys}'] << 12
class NVMemoryManager(MemoryManager):
va_allocator = TLSFAllocator((1 << 44), base=1 << 30) # global for all devices.
va_allocator = TLSFAllocator((1 << 44), base=0x1000000000) # global for all devices.
def on_range_mapped(self): self.dev.NV_VIRTUAL_FUNCTION_PRIV_MMU_INVALIDATE.write((1 << 0) | (1 << 1) | (1 << 6) | (1 << 31))
+1 -1
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@@ -3,7 +3,7 @@ from tinygrad.helpers import all_int, prod, unwrap, dedup, DONT_REALIZE_EXPAND,
from tinygrad.shape.shapetracker import ShapeTracker
ALWAYS_CONTIGUOUS = {Ops.CONTIGUOUS, Ops.ASSIGN, Ops.COPY, Ops.BUFFER, Ops.BUFFER_VIEW,
Ops.CONST, Ops.BIND, Ops.DEVICE, Ops.MSELECT, Ops.MSTACK}
Ops.CONST, Ops.BIND, Ops.DEVICE, Ops.MSELECT, Ops.MSTACK, Ops.DEFINE_GLOBAL}
# **** Grouper decides which of the UOps realize
+20 -15
View File
@@ -150,18 +150,11 @@ create_kernels = PatternMatcher([
# **** fix kernel AST
add_buffer_ops = PatternMatcher([
early_buffer_ops = PatternMatcher([
# LOAD
(UPat(Ops.BUFFER, name="x"), lambda ctx,x: UOp.load(UOp(Ops.DEFINE_GLOBAL, x.dtype.ptr(x.size), (), ctx.index(x)).view(x.st),)),
# STORE (except for meta ops)
(UPat(Ops.BUFFER, name="x"), lambda ctx,x: UOp(Ops.DEFINE_GLOBAL, x.dtype.ptr(x.size), (), ctx.index(x), tag=1)),
# no SINK for meta ops
(UPat(Ops.SINK, src=(UPat(Ops.CONTIGUOUS, src=(UPat(GroupOp.Meta, name="x"),),))), lambda x:x),
(UPat(Ops.SINK, src=UPat(GroupOp.All-{Ops.STORE}), name="sink"), lambda ctx,sink:
UOp.sink(*[UOp.store(UOp(Ops.DEFINE_GLOBAL, (s:=x.base).dtype.ptr(ctx[i].size), (), i).view(s.st), s) for i,x in enumerate(sink.src)])),
# passthrough ASSIGN
(UPat(Ops.ASSIGN, name="x"), lambda x: x.src[1]),
# VALID
(UPat(Ops.VIEW, src=(UPat.cvar(),), name="self"),
lambda self: UOp.where(UOp(Ops.VALID, dtypes.bool, (UOp(Ops.VIEW, arg=self.st),)), self.const_like(self.base.arg), 0)),
])
def check_load_st(glbl:UOp, view:UOp):
@@ -175,6 +168,16 @@ def check_load_st(glbl:UOp, view:UOp):
+colored(" - a += a.T\n", "red")+colored(" + a += a.T.contiguous()", "green"))
fix_kernel_ops = PatternMatcher([
# add the LOAD
(UPat(Ops.DEFINE_GLOBAL, name="x"), lambda x: x.replace(tag=None).view(x.st).load() if x.tag is not None else None),
# STORE (except for meta ops)
(UPat(Ops.SINK, src=UPat(GroupOp.All-{Ops.STORE}), name="sink"), lambda sink:
UOp.sink(*[UOp.store(UOp(Ops.DEFINE_GLOBAL, (s:=x.base).dtype.ptr(s.st.real_size()), (), i).view(s.st), s) for i,x in enumerate(sink.src)])),
# passthrough ASSIGN
(UPat(Ops.ASSIGN, name="x"), lambda x: x.src[1]),
# VALID
(UPat(Ops.VIEW, src=(UPat.cvar(),), name="self"),
lambda self: UOp.where(UOp(Ops.VALID, dtypes.bool, (UOp(Ops.VIEW, arg=self.st),)), self.const_like(self.base.arg), 0)),
# remove CONTIGUOUS/DEVICE from kernel AST
(UPat((Ops.CONTIGUOUS, Ops.MSELECT), src=(UPat.var("x"),)), lambda x: x),
(UPat(Ops.VIEW, src=(UPat(Ops.DEVICE),), name="view"), lambda view: view.replace(src=())),
@@ -193,10 +196,6 @@ replace_globals = PatternMatcher([
def fix_kernel_ast(k:UOp) -> UOp|None:
if k.arg.ast.op in GroupOp.Meta or all(s.op is Ops.STORE for s in k.arg.ast.src): return None
# replace global memory ops with the BUFFER they write to
ast = graph_rewrite(k.arg.ast, replace_globals, bottom_up=True, name="replace globals")
# push views to edges
ast = graph_rewrite(graph_rewrite(ast, view_left, name="Main View Left"), view_right, name="Main View Right")
# replace buffer with define_global + add load/store last
bufs = []
for s in k.src:
@@ -204,9 +203,15 @@ def fix_kernel_ast(k:UOp) -> UOp|None:
# traverse back through MSELECT and MSTACK. HACK: 0 branch of MSTACK only
while s.op in {Ops.MSELECT, Ops.MSTACK}: s = s.src[0]
bufs.append(s)
ast = graph_rewrite(ast, view_left+add_buffer_ops+fix_kernel_ops, bufs, bottom_up=True, name="replace buffer")
# replace global memory ops with the BUFFER they write to
ast = graph_rewrite(k.arg.ast, replace_globals, bottom_up=True, name="replace globals")
ast = graph_rewrite(ast, early_buffer_ops, bufs, bottom_up=True, name="replace buffer early")
if ast.op is Ops.SINK and not all_same([x.device for x in k.src]):
raise RuntimeError(f"all buffers must be on the same device: {tuple(b.buf_uop.buffer for b in k.src)}")
# TODO: move these to codegen
ast = graph_rewrite(ast, view_left, name="Main View Left")
ast = graph_rewrite(ast, view_right, name="Main View Right")
ast = graph_rewrite(ast, view_left+fix_kernel_ops, bottom_up=True, name="replace buffer")
return k.replace(arg=Kernel(ast, k.arg.metadata))
create_ast = PatternMatcher([(UPat(Ops.KERNEL, name="k"), fix_kernel_ast),])
+2 -2
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@@ -154,8 +154,8 @@ class UOp(MathTrait, metaclass=UOpMetaClass):
sz = cast(PtrDType, self.dtype).size
return ShapeTracker.from_shape((sz,)) if sz > 0 else None
# hack for PTX, CASTing the ptr loses the shape
if self.op is Ops.CAST and self.src[0].op is Ops.DEFINE_GLOBAL: return None
# hack for PTX, CASTing the ptr loses the shape. even worse hack with tag
if self.op is Ops.CAST and self.src[0].op is Ops.DEFINE_GLOBAL and self.src[0].tag is None: return None
# otherwise we get the shape from sources
if not (src_sts := [x.st for x in self.src if x.st is not None]): return None
+2 -1
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@@ -132,7 +132,8 @@ def timeline_layout(events:list[tuple[int, int, float, DevEvent]]) -> dict:
name, cat, info = e.name, None, None
if (ref:=ref_map.get(name)) is not None:
name = ctxs[ref]["name"]
if isinstance(p:=contexts[0][ref].ret, ProgramSpec):
# TODO: support symbolic by capturing var_vals in profile events
if isinstance(p:=contexts[0][ref].ret, ProgramSpec) and all(isinstance(es,int) for es in [p.estimates.ops, p.estimates.mem, p.estimates.lds]):
info = f"{p.estimates.ops/(t:=dur*1e3):.2f} GFLOPS {p.estimates.mem/t:4.1f}|{p.estimates.lds/t:.1f} GB/s"
elif isinstance(e.name, TracingKey):
name, cat = e.name.display_name, e.name.cat