I am following the wildml blog on text classification using tensorflow. I have changed the code to save graph def as follows :
tf.train.write_graph(sess.graph_def,'./DeepLearn/model/','train.pb', as_text=False)
Later in a separate file i am restoring the graph as follows :
with tf.gfile.FastGFile(os.path.join('./DeepLearn/model/','train.pb'), 'rb') as f:
graph_def = tf.GraphDef()
graph_def.ParseFromString(f.read())
_ = tf.import_graph_def(graph_def, name='')
with tf.Session() as sess:
t = sess.graph.get_tensor_by_name('embedding/W:0')
sess.run(t)
When i try to run the tensor and get its value, i am getting the following error :
tensorflow.python.framework.errors.FailedPreconditionError: Attempting to use uninitialized value embedding/W
What could be the possible reason for this error. The tensor should have been initialized as i am restoring it from the saved graph.
Thanks Alexandre!
Yes, i need to load both the graph (from .pb file) and weights (from checkpoints file.). Used the following sample code (taken from a blog) and it worked for me.
with tf.Session() as persisted_sess:
print("load graph")
with gfile.FastGFile("/tmp/load/test.pb",'rb') as f:
graph_def = tf.GraphDef()
graph_def.ParseFromString(f.read())
persisted_sess.graph.as_default()
tf.import_graph_def(graph_def, name='')
persisted_result = persisted_sess.graph.get_tensor_by_name("saved_result:0")
tf.add_to_collection(tf.GraphKeys.VARIABLES,persisted_result)
try:
saver = tf.train.Saver(tf.all_variables())
except:pass
print("load data")
saver.restore(persisted_sess, "checkpoint.data") # now OK
print(persisted_result.eval())
print("DONE")
Related
I am following an Agents.jl tutorial (https://juliadynamics.github.io/Agents.jl/stable/examples/schelling/) and get the following error when executing this piece of code. Any ideas why?
using Agents
using InteractiveDynamics
using CairoMakie
groupColor(a) = a.group == 1 ? :blue : :green
groupMarker(a) = a.group == 1 ? :circle : :rect
fig, _ = abm_plot(model, ac = groupColor, am = groupMarker, as = 10)
#Note that abm_plot is a function from InteractiveDynamics.jl which uses makie
#and model is an AgentBasedModel obj created from Agents.jl
#Out >
No backend available (GLMakie, CairoMakie, WGLMakie)!
Maybe you imported GLMakie but it didn't build correctly.
In that case, try `]build GLMakie` and watch out for any warnings.
If that's not the case, make sure to explicitely import any of the mentioned backends.
Had to update InteractiveDynamics package from 0.14.6 to 0.15.1. The answer to this problem can be found in the following thread.
https://discourse.julialang.org/t/no-backend-available-glmakie-cairomakie-wglmakie/62984/6
I would like to test GQ-CNN which is network in Dex-Net on tensorRT.
I successfully converted tflite file to uff file but when I tried to inference with that network, there is an error I couldn't figure out.
[TensorRT] ERROR: Parameter check failed at: ../builder/Network.cpp::addLRN::149, condition: lrnWindow & 0x1
python3: uff/orders.cpp:330: void UffParser::addTranspose(ParserLayer&, std::vector<int>): Assertion `outputs.size() == 1' failed.
The error is appeared when building model.
I tried to find clue from google but there are no codes and no references.
There's only different thing compare with example code that works well.
(I wrote captions which codes I added. If I remove that codes and replace model file to single input network, it works well.)
I registered input twice like below code because GQ-CNN has multiple input.
So I guess that registering multiple input using uffparser could be the main reason of that error.
class ModelData(object):
MODEL_FILE = "./gqcnn.uff"
INPUT_NAME_1 = "Placeholder"
INPUT_SHAPE_1 = (1, 32, 32)
INPUT_NAME_2 = "Placeholder_1"
INPUT_SHAPE_2 = (2,)
OUTPUT_NAME = "softmax/Softmax"
def build_engine(model_file):
# For more information on TRT basics, refer to the introductory samples.
with trt.Builder(TRT_LOGGER) as builder, builder.create_network() as network, trt.UffParser() as parser:
builder.max_workspace_size = common.GiB(1)
builder.fp16_mode = True
#builder.int8_mode = True
# Parse the Uff Network
parser.register_input(ModelData.INPUT_NAME_1, ModelData.INPUT_SHAPE_1)
parser.register_input(ModelData.INPUT_NAME_2, ModelData.INPUT_SHAPE_2) # added code
parser.register_output(ModelData.OUTPUT_NAME)
parser.parse(model_file, network)
# Build and return an engine.
return builder.build_cuda_engine(network)
# do inference
with build_engine(ModelData.MODEL_FILE) as engine:
# Build an engine, allocate buffers and create a stream.
# For more information on buffer allocation, refer to the introductory samples.
inputs, outputs, bindings, stream = common.allocate_buffers(engine)
with engine.create_execution_context() as context:
for idx in range(len(val_images)) :
start = time.time()
val_image = val_images[idx]
val_pose = val_poses[idx] # added code
np.copyto(inputs[0].host, val_image)
np.copyto(inputs[1].host, val_pose) # added code
[prediction] = common.do_inference(context, bindings=bindings, inputs=inputs, outputs=outputs, stream=stream)
Is there anyone who succeeded to inference with multiple input model?
I try to search a string in multiple files, my code works fine but for big text files it takes a few minutes.
wrd = b'my_word'
path = 'C:\path\to\files'
#### opens the path where all of .txt files are ####
for f in os.listdir(path):
if f.strip().endswith('.txt'):
with open(os.path.join(path, f), 'rb') as ofile:
#### loops through every line in the file comparing the strings ####
for line in ofile:
if wrd in line:
try:
sendMail(...)
logging.warning('There is an error {} in this file : {}'.format(line, f))
sys.exit(0)
except IOError as e:
logging.error('Operation failed: {}' .format(e.strerror))
sys.exit(0)
I found this topic : Python finds a string in multiple files recursively and returns the file path
but it does not answer my question..
Do you have an idea how to make it faster ?
Am using python3.4 on windows server 2003.
Thx ;)
My files are generated from an oracle application and if there is an error, i log it and stop generation my files.
So i search my string by reading the files from the end, because the string am looking for is an Oracle error and is at the end of the files.
wrd = b'ORA-'
path = 'C:\path\to\files'
#### opens the path where all of .txt files are ####
for f in os.listdir(path):
if f.strip().endswith('.txt'):
with open(os.path.join(path, f), 'r') as ofile:
try:
ofile.seek (0, 2) # Seek a end of file
fsize = ofile.tell() # Get Size
ofile.seek (max (fsize-1024, 0), 0) # Set pos a last n chars
lines = ofile.readlines() # Read to end
lines = lines[-10:] # Get last 10 lines
for line in lines:
if string in line:
sendMail(.....)
logging.error('There is an error {} in this file : {}'.format(line, f))
sys.exit(0)
except IOError as e:
logging.error('Operation failed: {}'.format(e.strerror))
sys.exit(0)
I'm trying to write a quick script to open a family document, change the parameter group of 2 specified parameters, and then close and save the document. I've done multiple tests and I am able to change the parameter groups of the specified parameters, but the changes of the groups don't save back to the family file. When I open the newly saved family, the parameter groups revert back to their original group.
This is with Revit 2017.2.
The same script, when run in RPS in Revit 2018 will do as desired.
import clr
import os
clr.AddReference('RevitAPI')
clr.AddReference('RevitAPIUI')
from Autodesk.Revit.DB import *
from Autodesk.Revit.UI import UIApplication
from System.IO import Directory, SearchOption
searchstring = "*.rfa"
dir = r"C:\Users\dboghean\Desktop\vanity\2017"
docs = []
if Directory.Exists(dir):
files = Directory.GetFiles(dir, searchstring, SearchOption.AllDirectories)
for f in files:
name, extension = os.path.splitext(f)
name2, extension2 = os.path.splitext(name)
if extension2:
os.remove(f)
else:
docs.append(f)
else:
print("Directory does not exist")
doc = __revit__.ActiveUIDocument.Document
app = __revit__.Application
uiapp = UIApplication(app)
currentPath = doc.PathName
pgGroup = BuiltInParameterGroup.PG_GRAPHICS
for i in docs:
doc = app.OpenDocumentFile(i)
paramList = [i for i in doc.FamilyManager.Parameters]
t = Transaction(doc, "test")
t.Start()
for i in paramList:
if i.Definition.Name in ["Right Sidesplash Edge line", "Left Sidesplash Edge line"]:
i.Definition.ParameterGroup = pgGroup
t.Commit()
doc.Close(True)
Any ideas?
Thanks!
I can confirm that this happens in Revit 2017. Strange!
A simple way around it is to arbitrarily rename the parameter using doc.FamilyManager.RenameParameter, then rename it back to the original name.
So in your case this would be three additional lines of code after changing the Parameter group:
originalName = i.Definition.Name
doc.FamilyManager.RenameParameter(i, "temp")
doc.FamilyManager.RenameParameter(i, originalName)
Doesnt get to the root problem, but works around it
I often have to define many similar devices in sip.conf like this:
[device](!)
; setting some parameters
[device01](device)
callerid=dev01 <01>
[device02](device)
callerid=dev02 <02>
; ...
[deviceXX](device)
callerid=devXX <XX>
The question is perhaps I could avoid setting device-name specific parameters by using some variable like following?
[device](!)
callerid=dev${DEVICE_NAME:-2} <${DEVICE_NAME:-2}>
; setting some parameters
[device01](device)
[device02](device)
; ...
[deviceXX](device)
P.S.
It would be perfect, if there was some device constructor, so I could reduce the script to following, but, I think, that is not possible in Asterisk.
[device](!)
callerid=dev${DEVICE_NAME:-2} <${DEVICE_NAME:-2}>
; setting some parameters
;[device${MAGIC_LOOP(1,XX,leading_zeroes)}](device)
I've had good results writing a small program that takes care of it. It checks for a line saying something like
------- Automatically generated -------
and whatever is after that line, it's going to be regenerated as soon as it detects that there are new values for it (it could be from a database or from a text file). Then, I run it with supervisor and it checks every XX seconds if there are changes.
If there are changes, it issues a sip reload command after updating the sip.conf file
I wrote it in python, but whatever language you feel comfortable with should work just fine.
That's how I managed that and has been working fine so far (after a couple of months). I'd be extremely interested in learning about other approaches though. It's basically this (called from another script with supervisor):
users = get_users_logic()
#get the data that will me used on the sip.conf file
data_to_be_hashed = reduce(lambda x, y: x + y, map(lambda x: x['username'] + x['password'] + x['company_prefix'], users))
m = hashlib.md5()
m.update(str(data_to_be_hashed).encode("ascii"))
new_md5 = m.hexdigest()
last_md5 = None
try:
file = open(os.path.dirname(os.path.realpath(__file__)) + '/lastMd5.txt', 'r')
last_md5 = file.read().rstrip()
file.close()
except:
pass
# if it changed...
if new_md5 != last_md5:
#needs update
with open(settings['asterisk']['path_to_sip_conf'], 'r') as file:
sip_content = file.read().rstrip()
parts = sip_content.split(";-------------- BEYOND THIS POINT IT IS AUTO GENERATED --------------;")
sip_content = parts[0].rstrip()
sip_content += "\n\n;-------------- BEYOND THIS POINT IT IS AUTO GENERATED --------------;\n\n"
for user in users:
m = hashlib.md5()
m.update(("%s:sip.ellauri.it:%s" % (user['username'], user['password'])).encode("ascii"))
md5secret = m.hexdigest()
sip_content += "[%s]\ntype = friend\ncontext = %sLocal\nmd5secret = %s\nhost = dynamic\n\n" % (
user['username'], user['company_prefix'], md5secret)
#write the sip.conf file
f = open(settings['asterisk']['path_to_sip_conf'], 'w')
print(sip_content, file=f)
f.close()
subprocess.call('asterisk -x "sip reload"', shell=True)
#write the new md5
f = open(os.path.dirname(os.path.realpath(__file__)) + '/lastMd5.txt', 'w')
print(new_md5, file=f)
f.close()