chore: import upstream snapshot with attribution

python/paddle/utils/fwd_graph_utils.py

@@ -0,0 +1,282 @@
+# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import io
+import os
+import re
+import sys
+import tempfile
+from contextlib import contextmanager
+
+import paddle
+from paddle.base.wrapped_decorator import signature_safe_contextmanager
+
+
+def _parse_tensors(input_str):
+    input_tuples = re.findall(
+        r"\(\s*(\w+)\s*,\s*(\{.*?\}|\[.*?\])\s*\)", input_str, re.DOTALL
+    )
+    tensors_list = []
+    for var_name, value_str in input_tuples:
+        # Only one Tensor
+        if value_str.startswith('{'):
+            tensor_info = _parse_tensor_info(value_str)
+            tensors_list.append((var_name, [tensor_info]))
+        # Tensor list
+        elif value_str.startswith('['):
+            list_content = value_str.strip('[]')
+            dict_strs = _split_list_elements(list_content)
+            tensor_list = []
+            for dict_str in dict_strs:
+                tensor_info = _parse_tensor_info(dict_str)
+                if tensor_info:
+                    tensor_list.append(tensor_info)
+            tensors_list.append((var_name, tensor_list))
+    return tensors_list
+
+
+def _parse_api_name(debug_str):
+    api_name_match = re.search(r"API_Name:\s*(\w+)", debug_str)
+    return api_name_match.group(1) if api_name_match else None
+
+
+def _parse_input_tensors(debug_str):
+    input_match = re.search(r"Input:\s*(\[.*?\]  )", debug_str, re.DOTALL)
+    return _parse_tensors(input_match.group(1)) if input_match else []
+
+
+def _parse_output_tensors(debug_str):
+    output_match = re.search(r"Output:\s*(\[.*?\] )", debug_str, re.DOTALL)
+    return _parse_tensors(output_match.group(1)) if output_match else []
+
+
+def _parse_tensor_info(dict_str):
+    result = {}
+    lines = dict_str.strip().split('\n')
+    for line in lines:
+        line = line.strip()
+        if line and ':' in line:
+            key, value = line.split(':', 1)
+            key = key.strip()
+            value = value.strip()
+            if key == "Place":
+                place_match = re.search(r"Place\((\w+:\d+)\)", value)
+                if place_match:
+                    value = place_match.group(1)
+            elif key == "Shape":
+                value = [int(x.strip()) for x in value.split(',') if x.strip()]
+            elif value == "None":
+                value = None
+
+            result[key] = value
+    return result
+
+
+def _split_list_elements(list_str):
+    elements = []
+    current = []
+    brace_count = 0
+
+    for char in list_str:
+        if char == '{':
+            brace_count += 1
+        elif char == '}':
+            brace_count -= 1
+
+        if char == ',' and brace_count == 0:
+            elements.append(''.join(current).strip())
+            current = []
+        else:
+            current.append(char)
+
+    if current:
+        elements.append(''.join(current).strip())
+
+    return elements
+
+
+def parse_debug_info(debug_str):
+    result = {"API_Name": None, "Input": [], "Output": []}
+
+    result["API_Name"] = _parse_api_name(debug_str)
+    result["Input"] = _parse_input_tensors(debug_str)
+    result["Output"] = _parse_output_tensors(debug_str)
+    return result
+
+
+class Edge:
+    def __init__(self, tensor_info: dict, source=""):
+        self.name = tensor_info["Name"]
+        self.shape = tensor_info["Shape"]
+        self.dtype = tensor_info["Dtype"]
+        self.source = source
+
+    def get_name(self) -> str:
+        return self.name
+
+    def get_source(self) -> str:
+        return self.source
+
+    def set_source(self, source):
+        self.source = source
+
+    def __str__(self) -> str:
+        return f"Edge(name='{self.name}', source='{self.source}',shape='{self.shape}',dtype='{self.dtype}')"
+
+    def get_edge_info(self):
+        return f"{self.name}\nshape:{self.shape}\ndtype:{self.dtype}"
+
+
+class Graph:
+    def __init__(self):
+        from graphviz import Digraph
+
+        self.dot = Digraph()
+        self.orange_box_attrs = {
+            'style': 'rounded,filled,bold',
+            'shape': 'box',
+            'color': '#FFE4B5',
+            'fillcolor': '#FFE4B5',
+            'fontcolor': '#ffffff',
+            'width': '1.3',
+            'height': '0.84',
+            'fontname': 'Arial',
+        }
+        self.grey_box_attrs = {
+            'style': 'rounded,filled,bold',
+            'shape': 'box',
+            'color': '#999999',
+            'fillcolor': '#999999',
+            'fontcolor': '#ffffff',
+            'width': '1.3',
+            'height': '0.84',
+            'fontname': 'Arial',
+        }
+
+        self.edges = {}
+        self.nodes = []
+
+    def add_node(self, name: str, node_attr=""):
+        if not node_attr:
+            node_attr = self.grey_box_attrs
+        self.dot.node(name, name, **node_attr)
+        self.nodes.append(name)
+
+    # Link the src and dst node by edge
+    def add_edge(self, dst: str, edge: Edge):
+        edge_name = edge.get_name()
+        if edge_name not in self.edges:
+            # The Edge is not stored in the graph,
+            # so the Edge's source node maybe not in the graph
+            if not edge.get_source():
+                src_name = edge.get_name() + "_SourceNode"
+                edge.set_source(src_name)
+                self.add_node(src_name, self.orange_box_attrs)
+        else:
+            edge = self.edges[edge_name]
+        src = edge.get_source()
+        self.dot.edge(src, dst, label=edge.get_edge_info())
+
+    # Store an edge, not link the src and dst node
+    def store_edge(self, edge: Edge):
+        edge_name = edge.get_name()
+        self.edges[edge_name] = edge
+
+    def render(self, file_path):
+        self.dot.render(file_path, format='svg')
+
+
+class GraphBuilder:
+    def __init__(self):
+        self.graph = Graph()
+
+    def build_graph(self, forward_debug_infos: list):
+        for info in forward_debug_infos:
+            debug_info = parse_debug_info(info)
+            api_name = debug_info['API_Name']
+            # Add a node for the API
+            self.graph.add_node(api_name)
+            # Store the Edge
+            for out_param in debug_info["Output"]:
+                var_name = out_param[0]
+                tensors = out_param[1]
+                for tensor_info in tensors:
+                    # When we do not know the edge's dst, we should  store it to the Graph
+                    edge = Edge(tensor_info, api_name)
+                    self.graph.store_edge(edge)
+            # Link the Edge
+            for input_param in debug_info["Input"]:
+                var_name = input_param[0]
+                tensors = input_param[1]
+                for tensor_info in tensors:
+                    edge = Edge(tensor_info)
+                    self.graph.add_edge(dst=api_name, edge=edge)
+
+    def save_graph(self, file_path):
+        self.graph.render(file_path)
+
+
+@contextmanager
+def capture_stderr():
+    with tempfile.TemporaryFile(mode='w+b') as temp_file:
+        original_stderr_fd = sys.stderr.fileno()
+        saved_stderr_fd = os.dup(original_stderr_fd)
+        stderr_output = io.StringIO()
+        try:
+            os.dup2(temp_file.fileno(), original_stderr_fd)
+            sys.stderr.flush()
+            yield stderr_output
+        finally:
+            sys.stderr.flush()
+            os.dup2(saved_stderr_fd, original_stderr_fd)
+            os.close(saved_stderr_fd)
+
+            temp_file.seek(0)
+            stderr_output.write(temp_file.read().decode())
+
+
+@signature_safe_contextmanager
+def capture_forward_subgraph_guard(file_path: str):
+    log = ""
+    stderr_buffer = io.StringIO()
+    origin_enable_unique_name_status = paddle.framework.get_flags(
+        "FLAGS_enable_unique_name"
+    )["FLAGS_enable_unique_name"]
+    try:
+        paddle.set_flags({"FLAGS_enable_unique_name": True})
+        # Redirect the stderr to the buffer,because the glog info will be printed to the stderr
+        with (
+            capture_stderr() as stderr_buffer,
+            paddle.base.framework.vlog_guard(3),
+        ):
+            yield
+    finally:
+        paddle.set_flags(
+            {"FLAGS_enable_unique_name": origin_enable_unique_name_status}
+        )
+        log = stderr_buffer.getvalue()
+        builder = GraphBuilder()
+
+        def get_first_indent(s):
+            match = re.match(r'^\t*', s)
+            return match.group(0)
+
+        # Find the parts describing the input and output of the API in the massive logs
+        indent = get_first_indent(log.lstrip('\n'))
+        pattern_str = r'\n' + indent + r'Forward Debug Info \{.*? ] } '
+        pattern = re.compile(pattern_str, re.DOTALL)
+        matches = pattern.findall(log)
+        # Build the forward graph
+        builder.build_graph(matches)
+        builder.save_graph(file_path)