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dot_plot.py
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383 lines (330 loc) · 12.2 KB
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import re
from typing import Dict, Optional, Tuple
from onnx import GraphProto, ModelProto
from onnx.helper import tensor_dtype_to_string
from ..reference import to_array_extended as to_array
from ._helper import Graph, _get_shape, attributes_as_dict
def _type_to_string(dtype):
"""
Converts a type into a readable string.
"""
if dtype.HasField("tensor_type"):
ttype = dtype.tensor_type
return tensor_dtype_to_string(ttype.elem_type)
if dtype.HasField("sequence_type"):
stype = dtype.sequence_type
return f"Sequence[{type(stype.elem_type)}]"
raise ValueError(f"Unable to convert {dtype} into a string.")
def to_dot(
proto: ModelProto,
recursive: bool = False,
prefix: str = "",
use_onnx: bool = False,
add_functions: bool = True,
rt_shapes: Optional[Dict[str, Tuple[int, ...]]] = None,
**params,
) -> str:
"""
Produces a :epkg:`DOT` language string for the graph.
:param params: additional params to draw the graph
:param recursive: also show subgraphs inside operator like `Scan`
:param prefix: prefix for every node name
:param use_onnx: use :epkg:`onnx` dot format instead of this one
:param add_functions: add functions to the graph
:param rt_shapes: indicates shapes obtained from the execution or inference
:return: string
Default options for the graph are:
::
options = {
'orientation': 'portrait',
'ranksep': '0.25',
'nodesep': '0.05',
'width': '0.5',
'height': '0.1',
'size': '7',
}
One example:
.. runpython::
:showcode:
:warningout: DeprecationWarning, FutureWarning
:process:
import numpy as np # B
from onnx_array_api.npx import absolute, jit_onnx
from onnx_array_api.plotting.dot_plot import to_dot
def l1_loss(x, y):
return absolute(x - y).sum()
def l2_loss(x, y):
return ((x - y) ** 2).sum()
def myloss(x, y):
return l1_loss(x[:, 0], y[:, 0]) + l2_loss(x[:, 1], y[:, 1])
jitted_myloss = jit_onnx(myloss)
x = np.array([[0.1, 0.2], [0.3, 0.4]], dtype=np.float32)
y = np.array([[0.11, 0.22], [0.33, 0.44]], dtype=np.float32)
res = jitted_myloss(x, y)
print(res)
.. gdot::
:script: DOT-SECTION
:process:
# to_dot
import numpy as np
from onnx_array_api.npx import absolute, jit_onnx
from onnx_array_api.plotting.dot_plot import to_dot
def l1_loss(x, y):
return absolute(x - y).sum()
def l2_loss(x, y):
return ((x - y) ** 2).sum()
def myloss(x, y):
return l1_loss(x[:, 0], y[:, 0]) + l2_loss(x[:, 1], y[:, 1])
jitted_myloss = jit_onnx(myloss)
x = np.array([[0.1, 0.2], [0.3, 0.4]], dtype=np.float32)
y = np.array([[0.11, 0.22], [0.33, 0.44]], dtype=np.float32)
res = jitted_myloss(x, y)
print(to_dot(jitted_myloss.get_onnx()))
"""
clean_label_reg1 = re.compile("\\\\x\\{[0-9A-F]{1,6}\\}")
clean_label_reg2 = re.compile("\\\\p\\{[0-9P]{1,6}\\}")
def dot_name(text):
return (
text.replace("/", "_")
.replace(":", "__")
.replace(".", "_")
.replace("-", "_")
)
def dot_label(text):
if text is None:
return ""
for reg in [clean_label_reg1, clean_label_reg2]:
fall = reg.findall(text)
for f in fall:
text = text.replace(f, "_")
return text
options = {
"orientation": "portrait",
"ranksep": "0.25",
"nodesep": "0.05",
"width": "0.5",
"height": "0.1",
"size": "7",
}
options.update({k: v for k, v in params.items() if v is not None})
if use_onnx:
from onnx.tools.net_drawer import GetOpNodeProducer, GetPydotGraph
pydot_graph = GetPydotGraph(
proto.graph,
name=proto.graph.name,
rankdir=params.get("rankdir", "TB"),
node_producer=GetOpNodeProducer(
"docstring", fillcolor="orange", style="filled", shape="box"
),
)
return pydot_graph.to_string()
inter_vars = {}
exp = ["digraph{"]
for opt in {"orientation", "pad", "nodesep", "ranksep", "size"}:
if opt in options:
exp.append(f" {opt}={options[opt]};")
fontsize = 10
shapes = {}
if rt_shapes:
for name, shape in rt_shapes.items():
va = str(shape.shape)
shapes[name] = va
# inputs
exp.append("")
graph = proto.graph if isinstance(proto, ModelProto) else proto
for obj in graph.input:
if isinstance(obj, str):
exp.append(
' {2}{0} [shape=box color=red label="{0}" fontsize={1}];'
"".format(obj, fontsize, prefix)
)
inter_vars[obj] = obj
else:
sh = _get_shape(obj)
if sh:
sh = f"\\nshape={sh}"
exp.append(
' {3}{0} [shape=box color=red label="{0}\\n{1}{4}" fontsize={2}];'
"".format(
obj.name, _type_to_string(obj.type), fontsize, prefix, dot_label(sh)
)
)
inter_vars[obj.name] = obj
# outputs
exp.append("")
for obj in graph.output:
if isinstance(obj, str):
exp.append(
' {2}{0} [shape=box color=green label="{0}" fontsize={1}];'.format(
obj, fontsize, prefix
)
)
inter_vars[obj] = obj
else:
sh = _get_shape(obj)
if sh:
sh = f"\\nshape={sh}"
exp.append(
f" {prefix}{obj.name} [shape=box color=green "
f'label="{obj.name}\\n{_type_to_string(obj.type)}'
f'{dot_label(sh)}" fontsize={fontsize}];'
)
inter_vars[obj.name] = obj
# initializer
exp.append("")
if hasattr(proto, "graph"):
inits = list(proto.graph.initializer) + list(proto.graph.sparse_initializer)
for obj in inits:
val = to_array(obj)
flat = val.flatten()
if flat.shape[0] < 9:
st = str(val)
else:
st = str(val)
if len(st) > 50:
st = st[:50] + "..."
st = st.replace("\n", "\\n")
kind = ""
exp.append(
f" {prefix}{dot_name(obj.name)} "
f'[shape=box label="{dot_name(obj.name)}'
f"\\n{kind}{val.dtype}({val.shape})"
f'\\n{dot_label(st)}" fontsize={fontsize}];'
)
inter_vars[obj.name] = obj
# nodes
fill_names = {}
if hasattr(proto, "graph"):
static_inputs = [n.name for n in proto.graph.input]
static_inputs.extend(n.name for n in proto.graph.initializer)
static_inputs.extend(n.name for n in proto.graph.sparse_initializer)
nodes = list(proto.graph.node)
else:
static_inputs = list(proto.input)
nodes = proto.node
for node in nodes:
exp.append("")
for out in node.output:
if out and out not in inter_vars:
inter_vars[out] = out
sh = shapes.get(out, "")
if sh:
sh = f"\\nshape={sh}"
exp.append(
' {2}{0} [shape=box label="{0}{3}" fontsize={1}];'.format(
dot_name(out), fontsize, dot_name(prefix), dot_label(sh)
)
)
static_inputs.append(out)
if node.name.strip() == "" or node.name in fill_names:
name = node.op_type
iname = 1
while name in fill_names:
name = "%s%d" % (name, iname)
iname += 1
node.name = name
fill_names[name] = node
atts = []
node_attributes = attributes_as_dict(node)
for k, v in sorted(node_attributes.items()):
if isinstance(v, (GraphProto, Graph)):
continue
val = str(v).replace("\n", "\\n").replace('"', "'")
sl = max(30 - len(k), 10)
if len(val) > sl:
val = val[:sl] + "..."
if val is not None:
atts.append(f"{k}={val}")
satts = "" if len(atts) == 0 else ("\\n" + "\\n".join(atts))
connects = []
if recursive and node.op_type in {"Scan", "Loop", "If"}:
fields = (
["then_branch", "else_branch"] if node.op_type == "If" else ["body"]
)
for field in fields:
if field not in node_attributes:
continue
# creates the subgraph
body = node_attributes[field]
subprefix = prefix + "B_"
subdot = to_dot(
body, recursive=recursive, prefix=subprefix, rt_shapes=rt_shapes
)
lines = subdot.split("\n")
start = 0
for i, line in enumerate(lines):
if "[" in line:
start = i
break
subgraph = "\n".join(lines[start:])
# connecting the subgraph
cluster = f"cluster_{node.op_type}{id(node)}_{id(field)}"
exp.append(f" subgraph {cluster} {{")
exp.append(f' label="{node.op_type}\\n({dot_name(field)}){satts}";')
exp.append(f" fontsize={fontsize};")
exp.append(" color=black;")
exp.append("\n".join(f" {s}" for s in subgraph.split("\n")))
node0 = body.node[0]
connects.append(
(f"{dot_name(subprefix)}{dot_name(node0.name)}", cluster)
)
for inp1, inp2 in zip(node.input, body.input):
exp.append(
f" {dot_name(prefix)}{dot_name(inp1)} -> "
f"{dot_name(subprefix)}{dot_name(inp2.name)};"
)
for out1, out2 in zip(body.output, node.output):
if not out2:
# Empty output, it cannot be used.
continue
exp.append(
f" {dot_name(subprefix)}{dot_name(out1.name)} -> "
f"{dot_name(prefix)}{dot_name(out2)};"
)
else:
exp.append(
f" {dot_name(prefix)}{dot_name(node.name)} "
f'[shape=box style="filled,rounded" color=orange '
f'label="{node.op_type}{satts}" '
f"fontsize={fontsize}];"
)
if connects is not None and len(connects) > 0:
for name, cluster in connects:
exp.append(
f" {dot_name(prefix)}{dot_name(node.name)} -> "
f"{name} [lhead={cluster}];"
)
for inp in node.input:
exp.append(
f" {dot_name(prefix)}{dot_name(inp)} -> "
f"{dot_name(prefix)}{dot_name(node.name)};"
)
for out in node.output:
if not out:
# Empty output, it cannot be used.
continue
exp.append(
f" {dot_name(prefix)}{dot_name(node.name)} -> "
f"{dot_name(prefix)}{dot_name(out)};"
)
functions = getattr(proto, "function", [])
if add_functions and len(functions) > 0:
for f in functions:
dot = to_dot(
f,
recursive=recursive,
prefix=prefix + f.name,
use_onnx=use_onnx,
add_functions=False,
rt_shapes=rt_shapes,
**params,
)
spl = dot.split("\n")[1:]
exp.append("")
exp.append(" subgraph cluster_%d {" % i)
exp.append(f' label="{v.obj.name}";')
exp.append(" color=blue;")
# exp.append(' style=filled;')
exp.extend((" " + line) for line in spl)
exp.append("}")
return "\n".join(exp)