# Owner(s): ["module: dynamo"] import copy import functools import io import json import logging import os import shutil import subprocess import tempfile import unittest.mock import torch import torch._dynamo.test_case import torch._dynamo.testing import torch._logging.structured import torch.distributed as dist import torch.fx as fx from torch._inductor.test_case import TestCase from torch._logging._internal import TorchLogsFormatter from torch.nn.parallel import DistributedDataParallel as DDP from torch.testing._internal.common_utils import find_free_port from torch.testing._internal.inductor_utils import HAS_CUDA HAS_TLPARSE = shutil.which("tlparse") is not None requires_tlparse = unittest.skipUnless(HAS_TLPARSE, "requires tlparse") requires_cuda = unittest.skipUnless(HAS_CUDA, "requires cuda") requires_distributed = functools.partial( unittest.skipIf, not dist.is_available(), "requires distributed" ) def example_fn(a): output = a.mul(torch.ones(1000, 1000)) output = output.add(torch.ones(1000, 1000)) return output def dynamo_error_fn(a): output = a.mul(torch.ones(1000, 1000)) output = output.add(torch.ones(10, 10)) return output def inductor_error_fn(a): output = torch.round(a) return output def inductor_schedule_fn(a): output = a.add(torch.ones(1000, 1000, device="cuda")) return output ARGS = (torch.ones(1000, 1000, requires_grad=True),) class StructuredTraceTestingFilter(logging.Filter): def filter(self, record): return "str" not in record.metadata class ChromiumEventFilter(logging.Filter): def filter(self, record): return "chromium_event" not in record.metadata class StructuredTraceTestingFormatter(logging.Formatter): def format(self, record): metadata = copy.deepcopy(record.metadata) # Stub out values that are not stable across runs # TODO: Check that these match schema if "has_payload" in metadata: metadata["has_payload"] = "HASH" if "dynamo_start" in metadata: metadata["dynamo_start"]["stack"] = "STACK" if "inductor_output_code" in metadata: metadata["inductor_output_code"]["filename"] = "FILENAME" if "stack" in metadata: metadata["stack"] = "STACK" if "compilation_metrics" in metadata: metadata["compilation_metrics"] = "METRICS" if "describe_storage" in metadata: metadata["describe_storage"]["describer_id"] = "ID" if "describe_tensor" in metadata: metadata["describe_tensor"]["describer_id"] = "ID" if "view_func" in metadata["describe_tensor"]: metadata["describe_tensor"]["view_func"] = "VIEW_FUNC" if "describe_source" in metadata: metadata["describe_source"]["describer_id"] = "ID" if "dump_file" in metadata: # Don't include the actually key number, that's sensitive to other # test runs metadata["dump_file"]["name"] = "" return ( json.dumps(metadata) + "\n" + "\n".join(l.rstrip() for l in record.payload.splitlines()) ) return json.dumps(metadata) trace_log = logging.getLogger("torch.__trace") chrome_event_filter = ChromiumEventFilter() def show_chrome_events(fn): """ Don't hide chrome events for this test """ @functools.wraps(fn) def wrapper(self, *args, **kwargs): self.handler.removeFilter(chrome_event_filter) return fn(self, *args, **kwargs) return wrapper class StructuredTraceTest(TestCase): def setUp(self): super().setUp() torch._dynamo.reset() torch._logging.structured.INTERN_TABLE.clear() self.buffer = io.StringIO() self.old_level = trace_log.level trace_log.setLevel(logging.DEBUG) self.handler = logging.StreamHandler(self.buffer) self.handler.setFormatter(StructuredTraceTestingFormatter()) self.handler.addFilter(StructuredTraceTestingFilter()) self.handler.addFilter(chrome_event_filter) trace_log.addHandler(self.handler) self.raw_file = tempfile.NamedTemporaryFile( mode="w", delete=True ) # set this to False to keep temporary files self.raw_handler = logging.StreamHandler(self.raw_file) self.raw_handler.setFormatter(TorchLogsFormatter(trace=True)) trace_log.addHandler(self.raw_handler) def tearDown(self): trace_log.removeHandler(self.handler) trace_log.removeHandler(self.raw_handler) self.raw_file.close() trace_log.setLevel(self.old_level) def assertParses(self): out = tempfile.mkdtemp() try: subprocess.check_call( [ "tlparse", "-o", out, "--overwrite", "--no-browser", "--strict", self.raw_file.name, ] ) finally: shutil.rmtree(out, ignore_errors=True) @requires_cuda def test_schedule(self): fn_opt = torch._dynamo.optimize("inductor")(inductor_schedule_fn) fn_opt(torch.ones(1000, 1000, device="cuda")) self.assertExpectedInline( self.buffer.getvalue(), """\ {"dynamo_start": {"stack": "STACK"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 0, "describer_id": "ID", "size": 4000000}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 0, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cuda', index=0)", "size": [1000, 1000], "is_leaf": true, "stride": [1000, 1], "storage": 0, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 0, "source": "L['a']"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"dynamo_output_graph": {"sizes": {"l_a_": [1000, 1000], "ones": [1000, 1000], "output": [1000, 1000]}}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"aot_forward_graph": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_runnable", "encoding": "string"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_post_grad_graph": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_output_code": {"filename": "FILENAME"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_cache_hash", "encoding": "json"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"dynamo_cpp_guards_str": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"compilation_metrics": "METRICS", "frame_id": 0, "frame_compile_id": 0, "attempt": 0} """, # noqa: B950 ) self.assertParses() @requires_cuda def test_cudagraphs(self): fn_opt = torch.compile(mode="reduce-overhead")(inductor_schedule_fn) fn_opt(torch.ones(1000, 1000, device="cuda")) self.assertExpectedInline( self.buffer.getvalue(), """\ {"dynamo_start": {"stack": "STACK"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 0, "describer_id": "ID", "size": 4000000}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 0, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cuda', index=0)", "size": [1000, 1000], "is_leaf": true, "stride": [1000, 1], "storage": 0, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 0, "source": "L['a']"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"dynamo_output_graph": {"sizes": {"l_a_": [1000, 1000], "ones": [1000, 1000], "output": [1000, 1000]}}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"aot_forward_graph": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_runnable", "encoding": "string"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_post_grad_graph": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_output_code": {"filename": "FILENAME"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_cache_hash", "encoding": "json"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"dynamo_cpp_guards_str": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"compilation_metrics": "METRICS", "frame_id": 0, "frame_compile_id": 0, "attempt": 0} """, # noqa: B950 ) self.assertParses() @requires_tlparse def test_recompiles(self): def fn(x, y): return torch.add(x, y) fn_opt = torch._dynamo.optimize("inductor")(fn) fn_opt(torch.ones(1000, 1000), torch.ones(1000, 1000)) fn_opt(torch.ones(1000, 1000), 1) self.assertExpectedInline( self.buffer.getvalue(), """\ {"dynamo_start": {"stack": "STACK"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 0, "describer_id": "ID", "size": 4000000}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 0, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cpu')", "size": [1000, 1000], "is_leaf": true, "stride": [1000, 1], "storage": 0, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 0, "source": "L['y']"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 1, "describer_id": "ID", "size": 4000000}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 1, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cpu')", "size": [1000, 1000], "is_leaf": true, "stride": [1000, 1], "storage": 1, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 1, "source": "L['x']"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"dynamo_output_graph": {"sizes": {"l_y_": [1000, 1000], "l_x_": [1000, 1000], "add": [1000, 1000]}}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"aot_forward_graph": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_runnable", "encoding": "string"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_post_grad_graph": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_output_code": {"filename": "FILENAME"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_cache_hash", "encoding": "json"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"dynamo_cpp_guards_str": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"compilation_metrics": "METRICS", "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"artifact": {"name": "recompile_reasons", "encoding": "json"}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0, "has_payload": "HASH"} {"dynamo_start": {"stack": "STACK"}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0} {"describe_storage": {"id": 0, "describer_id": "ID", "size": 4000000}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0} {"describe_tensor": {"id": 0, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cpu')", "size": [1000, 1000], "is_leaf": true, "stride": [1000, 1], "storage": 0, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 0, "source": "L['x']"}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0} {"dynamo_output_graph": {"sizes": {"l_x_": [1000, 1000], "add": [1000, 1000]}}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0, "has_payload": "HASH"} {"aot_forward_graph": {}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_runnable", "encoding": "string"}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0, "has_payload": "HASH"} {"inductor_post_grad_graph": {}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0, "has_payload": "HASH"} {"inductor_output_code": {"filename": "FILENAME"}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_cache_hash", "encoding": "json"}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0, "has_payload": "HASH"} {"dynamo_cpp_guards_str": {}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0, "has_payload": "HASH"} {"compilation_metrics": "METRICS", "frame_id": 0, "frame_compile_id": 1, "attempt": 0} """, # noqa: B950 ) self.assertParses() @requires_tlparse def test_example_fn(self): fn_opt = torch._dynamo.optimize("inductor")(example_fn) fn_opt(torch.ones(1000, 1000)) self.assertExpectedInline( self.buffer.getvalue(), """\ {"dynamo_start": {"stack": "STACK"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 0, "describer_id": "ID", "size": 4000000}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 0, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cpu')", "size": [1000, 1000], "is_leaf": true, "stride": [1000, 1], "storage": 0, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 0, "source": "L['a']"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"dynamo_output_graph": {"sizes": {"l_a_": [1000, 1000], "ones": [1000, 1000], "output": [1000, 1000], "ones_1": [1000, 1000], "output_1": [1000, 1000]}}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"aot_forward_graph": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_runnable", "encoding": "string"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_post_grad_graph": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_output_code": {"filename": "FILENAME"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_cache_hash", "encoding": "json"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"dynamo_cpp_guards_str": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"compilation_metrics": "METRICS", "frame_id": 0, "frame_compile_id": 0, "attempt": 0} """, # noqa: B950 ) self.assertParses() @requires_tlparse def test_dynamo_error(self): try: fn_opt = torch._dynamo.optimize("inductor")(dynamo_error_fn) fn_opt(*ARGS) except Exception: pass self.assertExpectedInline( self.buffer.getvalue(), """\ {"dynamo_start": {"stack": "STACK"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 0, "describer_id": "ID", "size": 4000000}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 0, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cpu')", "size": [1000, 1000], "is_leaf": true, "requires_grad": true, "stride": [1000, 1], "storage": 0, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 0, "source": "L['a']"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"compilation_metrics": "METRICS", "frame_id": 0, "frame_compile_id": 0, "attempt": 0} """, # noqa: B950 ) self.assertParses() @requires_tlparse def test_inductor_error(self): import torch._inductor.lowering def throw(x): raise AssertionError # inject an error in the lowerings dict_entries = {} for x in list(torch._inductor.lowering.lowerings.keys()): if "round" in x.__name__: dict_entries[x] = throw with unittest.mock.patch.dict(torch._inductor.lowering.lowerings, dict_entries): try: fn_opt = torch._dynamo.optimize("inductor")(inductor_error_fn) fn_opt(*ARGS) except Exception: pass self.assertExpectedInline( self.buffer.getvalue(), """\ {"dynamo_start": {"stack": "STACK"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 0, "describer_id": "ID", "size": 4000000}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 0, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cpu')", "size": [1000, 1000], "is_leaf": true, "requires_grad": true, "stride": [1000, 1], "storage": 0, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 0, "source": "L['a']"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"dynamo_output_graph": {"sizes": {"l_a_": [1000, 1000], "output": [1000, 1000]}}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"aot_joint_graph": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"aot_forward_graph": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"aot_backward_graph": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_runnable", "encoding": "string"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_post_grad_graph": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"compilation_metrics": "METRICS", "frame_id": 0, "frame_compile_id": 0, "attempt": 0} """, # noqa: B950 ) self.assertParses() @requires_distributed() @requires_cuda def test_ddp_graphs(self): class ToyModel(torch.nn.Module): def __init__(self) -> None: super().__init__() self.layers = torch.nn.Sequential( torch.nn.Linear(1024, 1024), torch.nn.Linear(1024, 1024), ) def forward(self, x): return self.layers(x) # TODO: this isn't safely bracketed, will leak os.environ["MASTER_ADDR"] = "localhost" os.environ["MASTER_PORT"] = str(find_free_port()) dist.init_process_group("gloo", rank=0, world_size=1) ddp_model = torch._dynamo.optimize("inductor")( DDP(ToyModel().to("cuda:0"), device_ids=[0], bucket_cap_mb=4) ) ddp_model(torch.randn(1024, 1024, device="cuda:0")) dist.destroy_process_group() if not torch._dynamo.config.inline_inbuilt_nn_modules: self.assertExpectedInline( self.buffer.getvalue(), """\ {"dynamo_start": {"stack": "STACK"}, "rank": 0, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"dynamo_cpp_guards_str": {}, "rank": 0, "frame_id": 0, "frame_compile_id": 0, "attempt": 1, "has_payload": "HASH"} {"compilation_metrics": "METRICS", "rank": 0, "frame_id": 0, "frame_compile_id": 0, "attempt": 1} {"dynamo_start": {"stack": "STACK"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 0, "describer_id": "ID", "size": 4194304}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 0, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cuda', index=0)", "size": [1024, 1024], "is_leaf": true, "stride": [1024, 1], "storage": 0, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 0, "source": "L['x']"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"dynamo_output_graph": {"sizes": {"l_x_": [1024, 1024], "l__self___layers_0": [1024, 1024], "l__self___layers_1": [1024, 1024]}}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"optimize_ddp_split_graph": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"optimize_ddp_split_child": {"name": "submod_0"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"optimize_ddp_split_child": {"name": "submod_1"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"describe_storage": {"id": 0, "describer_id": "ID", "size": 4194304}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 0, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cuda', index=0)", "size": [1024, 1024], "is_leaf": true, "stride": [1024, 1], "storage": 0, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 0, "source": "L['x']"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"aot_joint_graph": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"aot_forward_graph": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"aot_backward_graph": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_runnable", "encoding": "string"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_post_grad_graph": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_output_code": {"filename": "FILENAME"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_cache_hash", "encoding": "json"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"aot_joint_graph": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"aot_forward_graph": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"aot_backward_graph": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_runnable", "encoding": "string"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_post_grad_graph": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_output_code": {"filename": "FILENAME"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_cache_hash", "encoding": "json"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"dynamo_cpp_guards_str": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"compilation_metrics": "METRICS", "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} """, # noqa: B950 ) else: self.assertExpectedInline( self.buffer.getvalue(), """\ {"dynamo_start": {"stack": "STACK"}, "rank": 0, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"dynamo_cpp_guards_str": {}, "rank": 0, "frame_id": 0, "frame_compile_id": 0, "attempt": 1, "has_payload": "HASH"} {"compilation_metrics": "METRICS", "rank": 0, "frame_id": 0, "frame_compile_id": 0, "attempt": 1} {"dynamo_start": {"stack": "STACK"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 0, "describer_id": "ID", "size": 4194304}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 0, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cuda', index=0)", "size": [1024, 1024], "is_leaf": true, "requires_grad": true, "is_parameter": true, "stride": [1024, 1], "storage": 0, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 0, "source": "L['self']._modules['layers']._modules['0']._parameters['weight']"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 1, "describer_id": "ID", "size": 4096}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 1, "ndim": 1, "dtype": "torch.float32", "device": "device(type='cuda', index=0)", "size": [1024], "is_leaf": true, "requires_grad": true, "is_parameter": true, "stride": [1], "storage": 1, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 1, "source": "L['self']._modules['layers']._modules['0']._parameters['bias']"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 2, "describer_id": "ID", "size": 4194304}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 2, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cuda', index=0)", "size": [1024, 1024], "is_leaf": true, "stride": [1024, 1], "storage": 2, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 2, "source": "L['x']"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 3, "describer_id": "ID", "size": 4194304}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 8, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cuda', index=0)", "size": [1024, 1024], "is_leaf": true, "requires_grad": true, "is_parameter": true, "stride": [1024, 1], "storage": 3, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 8, "source": "L['self']._modules['layers']._modules['1']._parameters['weight']"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 4, "describer_id": "ID", "size": 4096}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 9, "ndim": 1, "dtype": "torch.float32", "device": "device(type='cuda', index=0)", "size": [1024], "is_leaf": true, "requires_grad": true, "is_parameter": true, "stride": [1], "storage": 4, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 9, "source": "L['self']._modules['layers']._modules['1']._parameters['bias']"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"dynamo_output_graph": {"sizes": {"l_self_modules_layers_modules_0_parameters_weight_": [1024, 1024], "l_self_modules_layers_modules_0_parameters_bias_": [1024], "l_x_": [1024, 1024], "l_self_modules_layers_modules_1_parameters_weight_": [1024, 1024], "l_self_modules_layers_modules_1_parameters_bias_": [1024], "input_1": [1024, 1024], "input_2": [1024, 1024]}}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"optimize_ddp_split_graph": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"optimize_ddp_split_child": {"name": "submod_0"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"optimize_ddp_split_child": {"name": "submod_1"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"describe_storage": {"id": 0, "describer_id": "ID", "size": 4194304}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 0, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cuda', index=0)", "size": [1024, 1024], "is_leaf": true, "stride": [1024, 1], "storage": 0, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 0, "source": "L['x']"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 1, "describer_id": "ID", "size": 4194304}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 1, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cuda', index=0)", "size": [1024, 1024], "is_leaf": true, "requires_grad": true, "is_parameter": true, "stride": [1024, 1], "storage": 1, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 1, "source": "L['self']._modules['layers']._modules['0']._parameters['weight']"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 2, "describer_id": "ID", "size": 4096}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 2, "ndim": 1, "dtype": "torch.float32", "device": "device(type='cuda', index=0)", "size": [1024], "is_leaf": true, "requires_grad": true, "is_parameter": true, "stride": [1], "storage": 2, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 2, "source": "L['self']._modules['layers']._modules['0']._parameters['bias']"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"aot_joint_graph": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"aot_forward_graph": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"aot_backward_graph": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_runnable", "encoding": "string"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_post_grad_graph": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_output_code": {"filename": "FILENAME"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_cache_hash", "encoding": "json"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"describe_storage": {"id": 16, "describer_id": "ID", "size": 4194304}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 29, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cuda', index=0)", "size": [1024, 1024], "is_leaf": true, "requires_grad": true, "is_parameter": true, "stride": [1024, 1], "storage": 16, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 29, "source": "L['self']._modules['layers']._modules['1']._parameters['weight']"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 17, "describer_id": "ID", "size": 4096}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 30, "ndim": 1, "dtype": "torch.float32", "device": "device(type='cuda', index=0)", "size": [1024], "is_leaf": true, "requires_grad": true, "is_parameter": true, "stride": [1], "storage": 17, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 30, "source": "L['self']._modules['layers']._modules['1']._parameters['bias']"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"aot_joint_graph": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"aot_forward_graph": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"aot_backward_graph": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_runnable", "encoding": "string"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_post_grad_graph": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_output_code": {"filename": "FILENAME"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_cache_hash", "encoding": "json"}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"dynamo_cpp_guards_str": {}, "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"compilation_metrics": "METRICS", "rank": 0, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} """, # noqa: B950 ) self.assertParses() @requires_tlparse def test_graph_breaks(self): @torch._dynamo.optimize("inductor") def fn(x): torch._dynamo.graph_break() return x + 1 fn(torch.ones(1)) self.assertExpectedInline( self.buffer.getvalue(), """\ {"dynamo_start": {"stack": "STACK"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"dynamo_cpp_guards_str": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 1, "has_payload": "HASH"} {"compilation_metrics": "METRICS", "frame_id": 0, "frame_compile_id": 0, "attempt": 1} {"dynamo_start": {"stack": "STACK"}, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 0, "describer_id": "ID", "size": 4}, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 0, "ndim": 1, "dtype": "torch.float32", "device": "device(type='cpu')", "size": [1], "is_leaf": true, "stride": [1], "storage": 0, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 0, "source": "L['x']"}, "frame_id": 1, "frame_compile_id": 0, "attempt": 0} {"dynamo_output_graph": {"sizes": {"l_x_": [1], "add": [1]}}, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"aot_forward_graph": {}, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_runnable", "encoding": "string"}, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_post_grad_graph": {}, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_output_code": {"filename": "FILENAME"}, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_cache_hash", "encoding": "json"}, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"dynamo_cpp_guards_str": {}, "frame_id": 1, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"compilation_metrics": "METRICS", "frame_id": 1, "frame_compile_id": 0, "attempt": 0} """, # noqa: B950 ) self.assertParses() # TODO: bring in the trace_source tests once we start emitting bytecode @requires_tlparse def test_graph_sizes_dynamic(self): def fn(a, b): return a @ b fn_opt = torch._dynamo.optimize("eager", dynamic=False)(fn) fn_opt(torch.randn(10, 20), torch.randn(20, 30)) fn_opt2 = torch._dynamo.optimize("eager", dynamic=True)(fn) fn_opt2(torch.randn(5, 10), torch.randn(10, 15)) self.assertExpectedInline( self.buffer.getvalue(), """\ {"dynamo_start": {"stack": "STACK"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 0, "describer_id": "ID", "size": 800}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 0, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cpu')", "size": [10, 20], "is_leaf": true, "stride": [20, 1], "storage": 0, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 0, "source": "L['a']"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 1, "describer_id": "ID", "size": 2400}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 1, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cpu')", "size": [20, 30], "is_leaf": true, "stride": [30, 1], "storage": 1, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 1, "source": "L['b']"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"dynamo_output_graph": {"sizes": {"l_a_": [10, 20], "l_b_": [20, 30], "matmul": [10, 30]}}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"dynamo_cpp_guards_str": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"compilation_metrics": "METRICS", "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"artifact": {"name": "recompile_reasons", "encoding": "json"}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0, "has_payload": "HASH"} {"dynamo_start": {"stack": "STACK"}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0} {"describe_storage": {"id": 0, "describer_id": "ID", "size": 200}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0} {"describe_tensor": {"id": 0, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cpu')", "size": [5, 10], "is_leaf": true, "stride": [10, 1], "storage": 0, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 0, "source": "L['a']"}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0} {"describe_storage": {"id": 1, "describer_id": "ID", "size": 600}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0} {"describe_tensor": {"id": 1, "ndim": 2, "dtype": "torch.float32", "device": "device(type='cpu')", "size": [10, 15], "is_leaf": true, "stride": [15, 1], "storage": 1, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 1, "source": "L['b']"}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0} {"dynamo_output_graph": {"sizes": {"l_a_": ["s0", "s1"], "l_b_": ["s1", "s3"], "matmul": ["s0", "s3"]}}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0, "has_payload": "HASH"} {"dynamo_cpp_guards_str": {}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0, "has_payload": "HASH"} {"compilation_metrics": "METRICS", "frame_id": 0, "frame_compile_id": 1, "attempt": 0} """, # noqa: B950 ) self.assertParses() @requires_tlparse def test_guards_recompiles(self): def fn(x, ys, zs): return inner(x, ys, zs) def inner(x, ys, zs): for y, z in zip(ys, zs): x += y * z return x ys = [1.0, 2.0] zs = [3.0] x = torch.tensor([1.0]) fn_opt = torch._dynamo.optimize("eager")(fn) fn_opt(x, ys, zs) fn_opt(x, ys[:1], zs) self.assertExpectedInline( self.buffer.getvalue(), """\ {"dynamo_start": {"stack": "STACK"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 0, "describer_id": "ID", "size": 4}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 0, "ndim": 1, "dtype": "torch.float32", "device": "device(type='cpu')", "size": [1], "is_leaf": true, "stride": [1], "storage": 0, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 0, "source": "L['x']"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"dynamo_output_graph": {"sizes": {"l_x_": [1], "x": [1]}}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"dynamo_cpp_guards_str": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"compilation_metrics": "METRICS", "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"artifact": {"name": "recompile_reasons", "encoding": "json"}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0, "has_payload": "HASH"} {"dynamo_start": {"stack": "STACK"}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0} {"describe_storage": {"id": 0, "describer_id": "ID", "size": 4}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0} {"describe_tensor": {"id": 0, "ndim": 1, "dtype": "torch.float32", "device": "device(type='cpu')", "size": [1], "is_leaf": true, "stride": [1], "storage": 0, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 0, "source": "L['x']"}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0} {"dynamo_output_graph": {"sizes": {"l_x_": [1], "x": [1]}}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0, "has_payload": "HASH"} {"dynamo_cpp_guards_str": {}, "frame_id": 0, "frame_compile_id": 1, "attempt": 0, "has_payload": "HASH"} {"compilation_metrics": "METRICS", "frame_id": 0, "frame_compile_id": 1, "attempt": 0} """, # noqa: B950 ) self.assertParses() def test_dump_file(self): def f(x, y): return x.add(y) gm = fx.symbolic_trace(f) torch.compile(gm, backend="eager")(torch.randn(3), torch.randn(3)) self.assertExpectedInline( self.buffer.getvalue(), """\ {"dynamo_start": {"stack": "STACK"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"dump_file": {"name": ""}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} def forward(self, x, y): add = x.add(y); x = y = None return add {"describe_storage": {"id": 0, "describer_id": "ID", "size": 12}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 0, "ndim": 1, "dtype": "torch.float32", "device": "device(type='cpu')", "size": [3], "is_leaf": true, "stride": [1], "storage": 0, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 0, "source": "L['x']"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 1, "describer_id": "ID", "size": 12}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 1, "ndim": 1, "dtype": "torch.float32", "device": "device(type='cpu')", "size": [3], "is_leaf": true, "stride": [1], "storage": 1, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 1, "source": "L['y']"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"dynamo_output_graph": {"sizes": {"l_x_": [3], "l_y_": [3], "add": [3]}}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"dynamo_cpp_guards_str": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"compilation_metrics": "METRICS", "frame_id": 0, "frame_compile_id": 0, "attempt": 0} """, # noqa: B950 ) @requires_tlparse @torch._inductor.config.patch("fx_graph_cache", True) def test_codecache(self): def fn(a): return a.sin() x = torch.tensor([1.0]) fn_opt = torch._dynamo.optimize("inductor")(fn) fn_opt(x) torch._dynamo.reset() # Trigger a cache hit fn_opt(x) # Should print twice, including inductor_output_code self.assertExpectedInline( self.buffer.getvalue(), """\ {"dynamo_start": {"stack": "STACK"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 0, "describer_id": "ID", "size": 4}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 0, "ndim": 1, "dtype": "torch.float32", "device": "device(type='cpu')", "size": [1], "is_leaf": true, "stride": [1], "storage": 0, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 0, "source": "L['a']"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"dynamo_output_graph": {"sizes": {"l_a_": [1], "sin": [1]}}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"aot_forward_graph": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_runnable", "encoding": "string"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_post_grad_graph": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_output_code": {"filename": "FILENAME"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_cache_hash", "encoding": "json"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"dynamo_cpp_guards_str": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"compilation_metrics": "METRICS", "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"dynamo_start": {"stack": "STACK"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_storage": {"id": 0, "describer_id": "ID", "size": 4}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_tensor": {"id": 0, "ndim": 1, "dtype": "torch.float32", "device": "device(type='cpu')", "size": [1], "is_leaf": true, "stride": [1], "storage": 0, "view_func": "VIEW_FUNC", "describer_id": "ID"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"describe_source": {"describer_id": "ID", "id": 0, "source": "L['a']"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0} {"dynamo_output_graph": {"sizes": {"l_a_": [1], "sin": [1]}}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"aot_forward_graph": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"inductor_output_code": {"filename": "FILENAME"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"artifact": {"name": "fx_graph_cache_hash", "encoding": "json"}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"dynamo_cpp_guards_str": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"} {"compilation_metrics": "METRICS", "frame_id": 0, "frame_compile_id": 0, "attempt": 0} """, # noqa: B950 ) self.assertParses() @requires_tlparse @torch._inductor.config.patch("fx_graph_cache", True) @show_chrome_events def test_chromium_event(self): def fn(a): return a.sin() x = torch.tensor([1.0]) fn_opt = torch._dynamo.optimize("inductor")(fn) fn_opt(x) torch._dynamo.reset() # Trigger a cache hit fn_opt(x) # Should print twice, including inductor_output_code self.assertParses() chromium_event = '{"chromium_event": {}, "frame_id": 0, "frame_compile_id": 0, "attempt": 0, "has_payload": "HASH"}' self.assertTrue(chromium_event in self.buffer.getvalue()) if __name__ == "__main__": from torch._dynamo.test_case import run_tests run_tests()