wehub-resource-sync
283 lines
8.9 KiB
Python
283 lines
8.9 KiB
Python
# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import io
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import os
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import re
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import sys
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import tempfile
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from contextlib import contextmanager
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import paddle
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from paddle.base.wrapped_decorator import signature_safe_contextmanager
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def _parse_tensors(input_str):
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input_tuples = re.findall(
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r"\(\s*(\w+)\s*,\s*(\{.*?\}|\[.*?\])\s*\)", input_str, re.DOTALL
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)
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tensors_list = []
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for var_name, value_str in input_tuples:
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# Only one Tensor
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if value_str.startswith('{'):
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tensor_info = _parse_tensor_info(value_str)
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tensors_list.append((var_name, [tensor_info]))
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# Tensor list
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elif value_str.startswith('['):
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list_content = value_str.strip('[]')
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dict_strs = _split_list_elements(list_content)
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tensor_list = []
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for dict_str in dict_strs:
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tensor_info = _parse_tensor_info(dict_str)
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if tensor_info:
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tensor_list.append(tensor_info)
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tensors_list.append((var_name, tensor_list))
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return tensors_list
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def _parse_api_name(debug_str):
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api_name_match = re.search(r"API_Name:\s*(\w+)", debug_str)
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return api_name_match.group(1) if api_name_match else None
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def _parse_input_tensors(debug_str):
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input_match = re.search(r"Input:\s*(\[.*?\] )", debug_str, re.DOTALL)
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return _parse_tensors(input_match.group(1)) if input_match else []
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def _parse_output_tensors(debug_str):
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output_match = re.search(r"Output:\s*(\[.*?\] )", debug_str, re.DOTALL)
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return _parse_tensors(output_match.group(1)) if output_match else []
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def _parse_tensor_info(dict_str):
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result = {}
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lines = dict_str.strip().split('\n')
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for line in lines:
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line = line.strip()
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if line and ':' in line:
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key, value = line.split(':', 1)
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key = key.strip()
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value = value.strip()
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if key == "Place":
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place_match = re.search(r"Place\((\w+:\d+)\)", value)
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if place_match:
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value = place_match.group(1)
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elif key == "Shape":
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value = [int(x.strip()) for x in value.split(',') if x.strip()]
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elif value == "None":
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value = None
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result[key] = value
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return result
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def _split_list_elements(list_str):
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elements = []
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current = []
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brace_count = 0
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for char in list_str:
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if char == '{':
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brace_count += 1
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elif char == '}':
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brace_count -= 1
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if char == ',' and brace_count == 0:
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elements.append(''.join(current).strip())
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current = []
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else:
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current.append(char)
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if current:
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elements.append(''.join(current).strip())
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return elements
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def parse_debug_info(debug_str):
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result = {"API_Name": None, "Input": [], "Output": []}
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result["API_Name"] = _parse_api_name(debug_str)
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result["Input"] = _parse_input_tensors(debug_str)
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result["Output"] = _parse_output_tensors(debug_str)
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return result
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class Edge:
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def __init__(self, tensor_info: dict, source=""):
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self.name = tensor_info["Name"]
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self.shape = tensor_info["Shape"]
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self.dtype = tensor_info["Dtype"]
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self.source = source
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def get_name(self) -> str:
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return self.name
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def get_source(self) -> str:
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return self.source
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def set_source(self, source):
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self.source = source
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def __str__(self) -> str:
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return f"Edge(name='{self.name}', source='{self.source}',shape='{self.shape}',dtype='{self.dtype}')"
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def get_edge_info(self):
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return f"{self.name}\nshape:{self.shape}\ndtype:{self.dtype}"
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class Graph:
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def __init__(self):
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from graphviz import Digraph
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self.dot = Digraph()
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self.orange_box_attrs = {
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'style': 'rounded,filled,bold',
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'shape': 'box',
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'color': '#FFE4B5',
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'fillcolor': '#FFE4B5',
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'fontcolor': '#ffffff',
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'width': '1.3',
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'height': '0.84',
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'fontname': 'Arial',
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}
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self.grey_box_attrs = {
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'style': 'rounded,filled,bold',
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'shape': 'box',
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'color': '#999999',
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'fillcolor': '#999999',
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'fontcolor': '#ffffff',
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'width': '1.3',
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'height': '0.84',
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'fontname': 'Arial',
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}
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self.edges = {}
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self.nodes = []
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def add_node(self, name: str, node_attr=""):
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if not node_attr:
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node_attr = self.grey_box_attrs
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self.dot.node(name, name, **node_attr)
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self.nodes.append(name)
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# Link the src and dst node by edge
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def add_edge(self, dst: str, edge: Edge):
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edge_name = edge.get_name()
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if edge_name not in self.edges:
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# The Edge is not stored in the graph,
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# so the Edge's source node maybe not in the graph
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if not edge.get_source():
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src_name = edge.get_name() + "_SourceNode"
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edge.set_source(src_name)
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self.add_node(src_name, self.orange_box_attrs)
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else:
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edge = self.edges[edge_name]
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src = edge.get_source()
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self.dot.edge(src, dst, label=edge.get_edge_info())
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# Store an edge, not link the src and dst node
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def store_edge(self, edge: Edge):
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edge_name = edge.get_name()
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self.edges[edge_name] = edge
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def render(self, file_path):
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self.dot.render(file_path, format='svg')
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class GraphBuilder:
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def __init__(self):
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self.graph = Graph()
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def build_graph(self, forward_debug_infos: list):
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for info in forward_debug_infos:
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debug_info = parse_debug_info(info)
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api_name = debug_info['API_Name']
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# Add a node for the API
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self.graph.add_node(api_name)
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# Store the Edge
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for out_param in debug_info["Output"]:
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var_name = out_param[0]
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tensors = out_param[1]
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for tensor_info in tensors:
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# When we do not know the edge's dst, we should store it to the Graph
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edge = Edge(tensor_info, api_name)
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self.graph.store_edge(edge)
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# Link the Edge
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for input_param in debug_info["Input"]:
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var_name = input_param[0]
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tensors = input_param[1]
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for tensor_info in tensors:
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edge = Edge(tensor_info)
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self.graph.add_edge(dst=api_name, edge=edge)
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def save_graph(self, file_path):
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self.graph.render(file_path)
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@contextmanager
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def capture_stderr():
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with tempfile.TemporaryFile(mode='w+b') as temp_file:
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original_stderr_fd = sys.stderr.fileno()
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saved_stderr_fd = os.dup(original_stderr_fd)
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stderr_output = io.StringIO()
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try:
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os.dup2(temp_file.fileno(), original_stderr_fd)
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sys.stderr.flush()
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yield stderr_output
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finally:
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sys.stderr.flush()
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os.dup2(saved_stderr_fd, original_stderr_fd)
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os.close(saved_stderr_fd)
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temp_file.seek(0)
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stderr_output.write(temp_file.read().decode())
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@signature_safe_contextmanager
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def capture_forward_subgraph_guard(file_path: str):
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log = ""
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stderr_buffer = io.StringIO()
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origin_enable_unique_name_status = paddle.framework.get_flags(
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"FLAGS_enable_unique_name"
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)["FLAGS_enable_unique_name"]
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try:
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paddle.set_flags({"FLAGS_enable_unique_name": True})
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# Redirect the stderr to the buffer,because the glog info will be printed to the stderr
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with (
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capture_stderr() as stderr_buffer,
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paddle.base.framework.vlog_guard(3),
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):
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yield
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finally:
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paddle.set_flags(
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{"FLAGS_enable_unique_name": origin_enable_unique_name_status}
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)
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log = stderr_buffer.getvalue()
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builder = GraphBuilder()
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def get_first_indent(s):
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match = re.match(r'^\t*', s)
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return match.group(0)
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# Find the parts describing the input and output of the API in the massive logs
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indent = get_first_indent(log.lstrip('\n'))
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pattern_str = r'\n' + indent + r'Forward Debug Info \{.*? ] } '
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pattern = re.compile(pattern_str, re.DOTALL)
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matches = pattern.findall(log)
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# Build the forward graph
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builder.build_graph(matches)
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builder.save_graph(file_path)
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