70 lines
1.8 KiB
Python
70 lines
1.8 KiB
Python
import sys
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from typing import Any
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import torch
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from torch._logging import LazyString
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def lazy_format_graph_code(
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name: str, gm: torch.fx.GraphModule, maybe_id: int | None = None, **kwargs: Any
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) -> LazyString:
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"""
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Returns a LazyString that formats the graph code.
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"""
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def format_name() -> str:
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if maybe_id is not None:
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return f"{name} {maybe_id}"
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else:
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return name
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if "print_output" not in kwargs:
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kwargs["print_output"] = False
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if "colored" in kwargs:
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try:
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if not sys.stdout.isatty():
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kwargs["colored"] = False
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except AttributeError:
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kwargs["colored"] = False
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return LazyString(
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lambda: _format_graph_code(
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f"===== {format_name()} =====\n",
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gm.forward.__code__.co_filename,
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gm.print_readable(**kwargs),
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)
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)
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def _format_graph_code(name: str, filename: str, graph_str: str) -> str:
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"""
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Returns a string that formats the graph code.
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"""
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return f"TRACED GRAPH\n {name} {filename} {graph_str}\n"
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def first_call_function_nn_module_stack(graph: torch.fx.Graph) -> dict[str, Any] | None:
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"""
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Returns the nn_module_stack of the first call_function node.
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"""
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for node in graph.nodes:
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if node.op == "call_function" and "nn_module_stack" in node.meta:
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return node.meta["nn_module_stack"]
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return None
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def get_node_context(node: torch.fx.Node, num_nodes: int = 2) -> str:
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"""
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Returns a string of the last num_nodes nodes in the graph.
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"""
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node_contexts = []
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cur = node
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for _ in range(num_nodes):
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# cast to str to handle None return value
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node_contexts.append(str(cur.format_node()))
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if cur.op == "root":
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break
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cur = cur.prev
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return "\n".join(node_contexts[::-1])
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