f4334277
 Hu Chunming
提交3rdparty
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def tokenize(s):
tokens = []
token = ""
isString = False
isComment = False
for symbol in s:
isComment = (isComment and symbol != '\n') or (not isString and symbol == '#')
if isComment:
continue
if symbol == ' ' or symbol == '\t' or symbol == '\r' or symbol == '\'' or \
symbol == '\n' or symbol == ':' or symbol == '\"' or symbol == ';' or \
symbol == ',':
if (symbol == '\"' or symbol == '\'') and isString:
tokens.append(token)
token = ""
else:
if isString:
token += symbol
elif token:
tokens.append(token)
token = ""
isString = (symbol == '\"' or symbol == '\'') ^ isString
elif symbol == '{' or symbol == '}' or symbol == '[' or symbol == ']':
if token:
tokens.append(token)
token = ""
tokens.append(symbol)
else:
token += symbol
if token:
tokens.append(token)
return tokens
def parseMessage(tokens, idx):
msg = {}
assert(tokens[idx] == '{')
isArray = False
while True:
if not isArray:
idx += 1
if idx < len(tokens):
fieldName = tokens[idx]
else:
return None
if fieldName == '}':
break
idx += 1
fieldValue = tokens[idx]
if fieldValue == '{':
embeddedMsg, idx = parseMessage(tokens, idx)
if fieldName in msg:
msg[fieldName].append(embeddedMsg)
else:
msg[fieldName] = [embeddedMsg]
elif fieldValue == '[':
isArray = True
elif fieldValue == ']':
isArray = False
else:
if fieldName in msg:
msg[fieldName].append(fieldValue)
else:
msg[fieldName] = [fieldValue]
return msg, idx
def readTextMessage(filePath):
if not filePath:
return {}
with open(filePath, 'rt') as f:
content = f.read()
tokens = tokenize('{' + content + '}')
msg = parseMessage(tokens, 0)
return msg[0] if msg else {}
def listToTensor(values):
if all([isinstance(v, float) for v in values]):
dtype = 'DT_FLOAT'
field = 'float_val'
elif all([isinstance(v, int) for v in values]):
dtype = 'DT_INT32'
field = 'int_val'
else:
raise Exception('Wrong values types')
msg = {
'tensor': {
'dtype': dtype,
'tensor_shape': {
'dim': {
'size': len(values)
}
}
}
}
msg['tensor'][field] = values
return msg
def addConstNode(name, values, graph_def):
node = NodeDef()
node.name = name
node.op = 'Const'
node.addAttr('value', values)
graph_def.node.extend([node])
def addSlice(inp, out, begins, sizes, graph_def):
beginsNode = NodeDef()
beginsNode.name = out + '/begins'
beginsNode.op = 'Const'
beginsNode.addAttr('value', begins)
graph_def.node.extend([beginsNode])
sizesNode = NodeDef()
sizesNode.name = out + '/sizes'
sizesNode.op = 'Const'
sizesNode.addAttr('value', sizes)
graph_def.node.extend([sizesNode])
sliced = NodeDef()
sliced.name = out
sliced.op = 'Slice'
sliced.input.append(inp)
sliced.input.append(beginsNode.name)
sliced.input.append(sizesNode.name)
graph_def.node.extend([sliced])
def addReshape(inp, out, shape, graph_def):
shapeNode = NodeDef()
shapeNode.name = out + '/shape'
shapeNode.op = 'Const'
shapeNode.addAttr('value', shape)
graph_def.node.extend([shapeNode])
reshape = NodeDef()
reshape.name = out
reshape.op = 'Reshape'
reshape.input.append(inp)
reshape.input.append(shapeNode.name)
graph_def.node.extend([reshape])
def addSoftMax(inp, out, graph_def):
softmax = NodeDef()
softmax.name = out
softmax.op = 'Softmax'
softmax.addAttr('axis', -1)
softmax.input.append(inp)
graph_def.node.extend([softmax])
def addFlatten(inp, out, graph_def):
flatten = NodeDef()
flatten.name = out
flatten.op = 'Flatten'
flatten.input.append(inp)
graph_def.node.extend([flatten])
class NodeDef:
def __init__(self):
self.input = []
self.name = ""
self.op = ""
self.attr = {}
def addAttr(self, key, value):
assert(not key in self.attr)
if isinstance(value, bool):
self.attr[key] = {'b': value}
elif isinstance(value, int):
self.attr[key] = {'i': value}
elif isinstance(value, float):
self.attr[key] = {'f': value}
elif isinstance(value, str):
self.attr[key] = {'s': value}
elif isinstance(value, list):
self.attr[key] = listToTensor(value)
else:
raise Exception('Unknown type of attribute ' + key)
def Clear(self):
self.input = []
self.name = ""
self.op = ""
self.attr = {}
class GraphDef:
def __init__(self):
self.node = []
def save(self, filePath):
with open(filePath, 'wt') as f:
def printAttr(d, indent):
indent = ' ' * indent
for key, value in sorted(d.items(), key=lambda x:x[0].lower()):
value = value if isinstance(value, list) else [value]
for v in value:
if isinstance(v, dict):
f.write(indent + key + ' {\n')
printAttr(v, len(indent) + 2)
f.write(indent + '}\n')
else:
isString = False
if isinstance(v, str) and not v.startswith('DT_'):
try:
float(v)
except:
isString = True
if isinstance(v, bool):
printed = 'true' if v else 'false'
elif v == 'true' or v == 'false':
printed = 'true' if v == 'true' else 'false'
elif isString:
printed = '\"%s\"' % v
else:
printed = str(v)
f.write(indent + key + ': ' + printed + '\n')
for node in self.node:
f.write('node {\n')
f.write(' name: \"%s\"\n' % node.name)
f.write(' op: \"%s\"\n' % node.op)
for inp in node.input:
f.write(' input: \"%s\"\n' % inp)
for key, value in sorted(node.attr.items(), key=lambda x:x[0].lower()):
f.write(' attr {\n')
f.write(' key: \"%s\"\n' % key)
f.write(' value {\n')
printAttr(value, 6)
f.write(' }\n')
f.write(' }\n')
f.write('}\n')
def parseTextGraph(filePath):
msg = readTextMessage(filePath)
graph = GraphDef()
for node in msg['node']:
graphNode = NodeDef()
graphNode.name = node['name'][0]
graphNode.op = node['op'][0]
graphNode.input = node['input'] if 'input' in node else []
if 'attr' in node:
for attr in node['attr']:
graphNode.attr[attr['key'][0]] = attr['value'][0]
graph.node.append(graphNode)
return graph
# Removes Identity nodes
def removeIdentity(graph_def):
identities = {}
for node in graph_def.node:
if node.op == 'Identity' or node.op == 'IdentityN':
inp = node.input[0]
if inp in identities:
identities[node.name] = identities[inp]
else:
identities[node.name] = inp
graph_def.node.remove(node)
for node in graph_def.node:
for i in range(len(node.input)):
if node.input[i] in identities:
node.input[i] = identities[node.input[i]]
def removeUnusedNodesAndAttrs(to_remove, graph_def):
unusedAttrs = ['T', 'Tshape', 'N', 'Tidx', 'Tdim', 'use_cudnn_on_gpu',
'Index', 'Tperm', 'is_training', 'Tpaddings']
removedNodes = []
for i in reversed(range(len(graph_def.node))):
op = graph_def.node[i].op
name = graph_def.node[i].name
if to_remove(name, op):
if op != 'Const':
removedNodes.append(name)
del graph_def.node[i]
else:
for attr in unusedAttrs:
if attr in graph_def.node[i].attr:
del graph_def.node[i].attr[attr]
# Remove references to removed nodes except Const nodes.
for node in graph_def.node:
for i in reversed(range(len(node.input))):
if node.input[i] in removedNodes:
del node.input[i]
def writeTextGraph(modelPath, outputPath, outNodes):
try:
import cv2 as cv
cv.dnn.writeTextGraph(modelPath, outputPath)
except:
import tensorflow as tf
from tensorflow.tools.graph_transforms import TransformGraph
with tf.gfile.FastGFile(modelPath, 'rb') as f:
graph_def = tf.GraphDef()
graph_def.ParseFromString(f.read())
graph_def = TransformGraph(graph_def, ['image_tensor'], outNodes, ['sort_by_execution_order'])
for node in graph_def.node:
if node.op == 'Const':
if 'value' in node.attr and node.attr['value'].tensor.tensor_content:
node.attr['value'].tensor.tensor_content = b''
tf.train.write_graph(graph_def, "", outputPath, as_text=True)
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