xref: /aosp_15_r20/external/pytorch/torch/_logging/_registrations.py (revision da0073e96a02ea20f0ac840b70461e3646d07c45) 
1# flake8: noqa: B950
2from ._internal import register_artifact, register_log
3
4
5DYNAMIC = [
6    "torch.fx.experimental.symbolic_shapes",
7    "torch.fx.experimental.sym_node",
8    "torch.fx.experimental.recording",
9]
10DISTRIBUTED = [
11    "torch.distributed",
12    "torch._dynamo.backends.distributed",
13    "torch.nn.parallel.distributed",
14]
15
16register_log("dynamo", ["torch._dynamo", *DYNAMIC])
17register_log("fake_tensor", ["torch._subclasses.fake_tensor"])
18register_log("aot", ["torch._functorch.aot_autograd", "torch._functorch._aot_autograd"])
19register_log("autograd", "torch.autograd")
20register_log("inductor", ["torch._inductor", "torch._inductor.cudagraph_trees"])
21
22register_artifact(
23    "cudagraphs",
24    "Logs information from wrapping inductor generated code with cudagraphs.",
25)
26
27register_log("dynamic", DYNAMIC)
28register_log("torch", "torch")
29register_log("distributed", DISTRIBUTED)
30register_log(
31    "c10d", ["torch.distributed.distributed_c10d", "torch.distributed.rendezvous"]
32)
33register_log(
34    "ddp", ["torch.nn.parallel.distributed", "torch._dynamo.backends.distributed"]
35)
36register_log("pp", ["torch.distributed.pipelining"])
37register_log("fsdp", ["torch.distributed.fsdp", "torch.distributed._composable.fsdp"])
38register_log("dtensor", ["torch.distributed._tensor", "torch.distributed.tensor"])
39register_log("onnx", "torch.onnx")
40register_log(
41    "export",
42    [
43        "torch._dynamo",
44        "torch.export",
45        "torch.export.dynamic_shapes",
46        *DYNAMIC,
47        "torch._export.converter",
48        "torch._export.non_strict_utils",
49    ],
50)
51
52register_artifact(
53    "guards",
54    "This prints the guards for every compiled Dynamo frame. It does not tell you where the guards come from.",
55    visible=True,
56)
57register_artifact("verbose_guards", "", off_by_default=True)
58register_artifact(
59    "bytecode",
60    "Prints the original and modified bytecode from Dynamo. Mostly useful if you're debugging our bytecode generation in Dynamo.",
61    off_by_default=True,
62)
63register_artifact(
64    "graph",
65    "Prints the dynamo traced graph (prior to AOTDispatch) in a table. If you prefer python code use `graph_code` instead. ",
66)
67register_artifact("graph_code", "Like `graph`, but gives you the Python code instead.")
68register_artifact(
69    "graph_sizes", "Prints the sizes of all FX nodes in the dynamo graph."
70)
71register_artifact(
72    "trace_source",
73    "As we execute bytecode, prints the file name / line number we are processing and the actual source code. Useful with `bytecode`",
74)
75register_artifact(
76    "trace_call",
77    "Like trace_source, but it will give you the per-expression blow-by-blow if your Python is recent enough.",
78)
79register_artifact(
80    "trace_bytecode",
81    "As we trace bytecode, prints the instruction and the current stack.",
82)
83register_artifact(
84    "aot_graphs",
85    "Prints the FX forward and backward graph generated by AOTDispatch, after partitioning. Useful to understand what's being given to Inductor",
86    visible=True,
87)
88register_artifact(
89    "aot_joint_graph",
90    "Print FX joint graph from AOTAutograd, prior to partitioning. Useful for debugging partitioning",
91)
92register_artifact(
93    "aot_graphs_effects",
94    "Prints the FX forward and backward graph generated by AOTDispatch, useful for debugging effects processing.",
95    visible=True,
96)
97register_artifact(
98    "post_grad_graphs",
99    "Prints the FX graph generated by post grad passes. Useful to understand what's being given to Inductor after post grad passes",
100)
101register_artifact(
102    "compiled_autograd",
103    "Prints various logs in compiled_autograd, including but not limited to the graphs. Useful for debugging compiled_autograd.",
104    visible=True,
105)
106register_artifact(
107    "compiled_autograd_verbose",
108    "Will affect performance. Prints compiled_autograd logs with C++ info e.g. autograd node -> fx node mapping",
109    off_by_default=True,
110)
111register_artifact(
112    "ddp_graphs",
113    "Only relevant for compiling DDP. DDP splits into multiple graphs to trigger comms early. This will print each individual graph here.",
114)
115register_artifact(
116    "recompiles",
117    "Prints the reason why we recompiled a graph. Very, very useful.",
118    visible=True,
119)
120register_artifact(
121    "recompiles_verbose",
122    "Prints all guard checks that fail during a recompilation. "
123    "At runtime, Dynamo will stop at the first failed check for each failing guard. "
124    "So not all logged failing checks are actually ran by Dynamo.",
125    visible=True,
126    off_by_default=True,
127)
128register_artifact(
129    "graph_breaks",
130    "Prints whenever Dynamo decides that it needs to graph break (i.e. create a new graph). Useful for debugging why torch.compile has poor performance",
131    visible=True,
132)
133register_artifact(
134    "not_implemented",
135    "Prints log messages whenever we return NotImplemented in a multi-dispatch, letting you trace through each object we attempted to dispatch to",
136)
137register_artifact(
138    "output_code",
139    "Prints the code that Inductor generates (either Triton or C++)",
140    off_by_default=True,
141    visible=True,
142)
143register_artifact(
144    "kernel_code",
145    "Prints the code that Inductor generates (on a per-kernel basis)",
146    off_by_default=True,
147    visible=True,
148)
149register_artifact(
150    "schedule",
151    "Inductor scheduler information. Useful if working on Inductor fusion algo",
152    off_by_default=True,
153)
154register_artifact("perf_hints", "", off_by_default=True)
155register_artifact("onnx_diagnostics", "", off_by_default=True)
156register_artifact(
157    "fusion",
158    "Detailed Inductor fusion decisions. More detailed than 'schedule'",
159    off_by_default=True,
160)
161register_artifact(
162    "loop_ordering",
163    "Logs related to loop ordering",
164    off_by_default=True,
165)
166register_artifact(
167    "overlap",
168    "Detailed Inductor compute/comm overlap decisions",
169    off_by_default=True,
170)
171register_artifact(
172    "sym_node",
173    "Logs extra info for various SymNode operations",
174    off_by_default=True,
175)
176register_artifact(
177    "trace_shape_events",
178    "Logs traces for every ShapeEnv operation that we record for replay",
179    off_by_default=True,
180)
181register_artifact(
182    "cudagraph_static_inputs",
183    "Logs static inputs handling in dynamo, AOT, and cudagraphs",
184    off_by_default=True,
185)
186register_artifact(
187    "benchmarking",
188    "Detailed Inductor benchmarking information.",
189    off_by_default=True,
190)
191
192register_artifact("custom_format_test_artifact", "Testing only", log_format="")
193