I followed this link to doc to create environment of my own.
But when i run this
from mlagents_envs.environment import UnityEnvironment
env = UnityEnvironment(file_name="v1-ball-cube-game.x86_64")
env.reset()
behavior_names = env.behavior_spec.keys()
print(behavior_names)
Game window pop up and then terminal show error saying
Traceback (most recent call last):
File "index.py", line 6, in <module>
behavior_names = env.behavior_spec.keys()
AttributeError: 'UnityEnvironment' object has no attribute 'behavior_spec'
despite the fact that this is the exact snippet as shown in the documentation.
I created environment by following this (it make without brain) and i was able to train the model by .conf file. Now i wanted to connect to python API.
You need to use stable documents and stable repo( RELEASE_TAGS ) to achieve stable results. Unity ML Agents changes it's syntax every few months so that is problem if you are following master branch.
env.get_behavior_spec(behavior_name: str)
Should solve your problem.
https://github.com/Unity-Technologies/ml-agents/blob/release_2/docs/Python-API.md
Related
I am doing initial exploration in the SoCo module which is a Python API for Sonos. Following the tutorial I do
>>> speakers = soco.discover()
>>> speaker = speakers.pop()
>>> speaker.player_name
'Portable'
>>> speaker.ip_address
'192.168.0.11'
>>> speaker.get_current_transport_info()['current_transport_state']
'STOPPED'
So far, so good. Now, still following the documentation, I do
>>> speaker.music_library.list_library_shares()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'MusicLibrary' object has no attribute 'list_library_shares'
and, sure enough, dir(speaker.music_library) confirms there is no such method.
But the documentation for this class says:
Listing and deleting music library shares
Music library shares are the local network drive shares connected to Sonos, which host the
audio content in the Sonos Music Library.
To list the shares connected to Sonos, use the list_library_shares()
method as follows:
››› device.music_library.list_library_shares()
['//share_host_01/music', '//share_host_02/music']
The result is a
list of network share locations.
Now either the documentation is badly out of step with the version I just downloaded (0.18.1; it says not), or I need another pair of eyes to point out what I am doing wrong.
I asked this question also on the SoCo Google group and this is the answer I got:
This function is not included in v0.18.1, but will be in the upcoming
v0.19 release. It's unintuitive but you need to look at the v0.18.1
documentation at:
http://docs.python-soco.com/en/v0.18.1/api/soco.music_library.html
... not the 'latest' version of the documentation.
I forbear to remark on the wisdom of pointing readers of the Getting Started page in the wrong direction.
I have taken over a project which was using Yocto Fido version from 2015. I need to update this to the latest stable version Thud.
I have cloned the Poky-Thud repository and cloned the latest layers which are required by our customized layer such as meta-openembedded etc. and added our customized layer back to it.
Now, I wasn't expecting this to build straight away without issues by any means, but the below errors I'm getting with the new layers, I just don't understand. There are more errors like this relating to not enough values, but posted below is one.
There is an interface issue in meta/classes/sanity.bbclass. I can't just revert to the older version of meta to solve this, nor I don't think it makes sense to modify the code myself? Any ideas why this is and how to solve it?
ERROR: Execution of event handler 'config_reparse_eventhandler' failed
Traceback (most recent call last):
File "/home/ubuntu/new-repo/poky-thud/build-
bbgw/../meta/classes/sanity.bbclass", line 971, in
config_reparse_eventhandler(e=<bb.event.ConfigParsed object at
0x7ff4103bf3c8>):
python config_reparse_eventhandler() {
> sanity_check_conffiles(e.data)
}
File "/home/ubuntu/new-repo/poky-thud/build-
bbgw/../meta/classes/sanity.bbclass", line 572, in sanity_check_conffiles(d=
<bb.data_smart.DataSmart object at 0x7ff4108d35c0>):
for func in funcs:
> conffile, current_version, required_version, func =
func.split(":")
if check_conf_exists(conffile, d) and d.getVar(current_version)
is not None and \
ValueError: not enough values to unpack (expected 4, got 1)
I am currently attempting to change the value of input as it goes through data process in Azure ML. However, I cannot find a clue about how to access to the input data with python.
For example, if you were to use python, you can access to the column of data with
print(dataframe1["Hello World"])
I tried to change the name of Web Service Input and tried to do it like how I did for other dataframe (e.g. sample)
print(dataframe["sample"])
But it returns an error with no luck, and from what I read from an error, it's not compatible to dataframe:
object of type 'NoneType' has no len()
I tried to look up a solution with Nonetype error, but there is no good solution.
The whole error message:
requestId = 1f0f621f1d8841baa7862d5c05154942 errorComponent=Module. taskStatusCode=400. {"Exception":{"ErrorId":"FailedToEvaluateScript","ErrorCode":"0085","ExceptionType":"ModuleException","Message":"Error 0085: The following error occurred during script evaluation, please view the output log for more information:\r\n---------- Start of error message from Python interpreter ----------\r\nCaught exception while executing function: Traceback (most recent call last):\r\n File \"C:\\server\\invokepy.py\", line 211, in batch\r\n xdrutils.XDRUtils.DataFrameToRFile(outlist[i], outfiles[i], True)\r\n File \"C:\\server\\XDRReader\\xdrutils.py\", line 51, in DataFrameToRFile\r\n attributes = XDRBridge.DataFrameToRObject(dataframe)\r\n File \"C:\\server\\XDRReader\\xdrbridge.py\", line 40, in DataFrameToRObject\r\n if (len(dataframe) == 1 and type(dataframe[0]) is pd.DataFrame):\r\nTypeError: object of type 'NoneType' has no len()\r\nProcess returned with non-zero exit code 1\r\n\r\n---------- End of error message from Python interpreter ----------"}}Error: Error 0085: The following error occurred during script evaluation, please view the output log for more information:---------- Start of error message from Python interpreter ----------Caught exception while executing function: Traceback (most recent call last): File "C:\server\invokepy.py", line 211, in batch xdrutils.XDRUtils.DataFrameToRFile(outlist[i], outfiles[i], True) File "C:\server\XDRReader\xdrutils.py", line 51, in DataFrameToRFile attributes = XDRBridge.DataFrameToRObject(dataframe) File "C:\server\XDRReader\xdrbridge.py", line 40, in DataFrameToRObject if (len(dataframe) == 1 and type(dataframe[0]) is pd.DataFrame):TypeError: object of type 'NoneType' has no len()Process returned with non-zero exit code 1---------- End of error message from Python interpreter ---------- Process exited with error code -2
I have also tried to a way to pass python script in data, but it is not able to make any change to Web Service Input value as I want it to be.
I have tried to look on forums like msdn or SO, but it's been difficult to find any information about it. Please let me know if you need any more information if needed. I would greatly appreciate your help!
tl;dr; You need to also link the dataset you used for training to the same port you link the Web service input, so that the Execute Python Script has something to work on - see the image below for how this should look.
You need to keep in mind that the Predictive experiment has some conventions that need to be followed (or learned the hard way :) ). One of them is that in order to use the Web service input, you need to pair it with an actual dataset, which Azure ML Studio can then use to infer structure and to provide you with some data while testing your predictive experiment. You can see it as some sort of 'ghost' module that doesn't do anything by itself.
Hope this helps.
I am using the w2v_server_googlenews code from the word2vec HTTP server running at https://rare-technologies.com/word2vec-tutorial/#bonus_app. I changed the loaded file to a file of vectors trained with the original C version of word2vec. I load the file with
gensim.models.KeyedVectors.load_word2vec_format(fname, binary=True)
and it seems to load without problems. But when I test the HTTP service with, let's say
curl 'http://127.0.0.1/most_similar?positive%5B%5D=woman&positive%5B%5D=king&negative%5B%5D=man'
I got an empty result with only the execution time.
{"taken": 0.0003361701965332031, "similars": [], "success": 1}
I put a traceback.print_exc() on the except part of the related method, which is in this case def most_similar(self, *args, **kwargs): and I got:
Traceback (most recent call last):
File "./w2v_server.py", line 114, in most_similar
topn=5)
File "/usr/local/lib/python2.7/dist-packages/gensim/models/keyedvectors.py", line 304, in most_similar
self.init_sims()
File "/usr/local/lib/python2.7/dist-packages/gensim/models/keyedvectors.py", line 817, in init_sims
self.syn0norm = (self.syn0 / sqrt((self.syn0 ** 2).sum(-1))[..., newaxis]).astype(REAL)
AttributeError: 'KeyedVectors' object has no attribute 'syn0'
Any idea on why this might happens?
Note: I use python 2.7 and I installed gensim using pip, which gave me gensim 2.1.0.
FYI that demo code was baed on gensim 0.12.3 (from 2015, as listed in its requirements.txt), and would need updating to work with the latest gensim.
It might be sufficient to add a line to w2v_server.py at line 70 (just after the load_word2vec_format()), to force the creation of the needed syn0norm property (which in older gensims was auto-created on load), before deleting the raw syn0 values. Specifically:
self.model.init_sims(replace=True)
(You would leave out the replace=True if you were going to be doing operations other than most_similar(), that might require raw vectors.)
If this works to fix the problem for you, a pull-request to the w2v_server_googlenews repo would be favorably received!
I used Model Builder to convert feature classes within a geodatabase into shapefiles into a preexisting folder. It ran successfully. However, when i exported the Model into a Python Script and ran it in Python, I get an error saying:
Traceback (most recent call last):
File "C:\Users\Mark.Novicio\Desktop\New folder\FSA_Counties_delivered_by_GISO\Updated_Iterators.py", line 13, in
arcpy.ImportToolbox("Model Functions")
The python script is attached in the image:
ArcPy code exported from ModelBuilder often needs a lot of tweaking, although it can be a moderately useful starting point.
IterateFeatureClasses_mb is the python-code of a ModelBuilder only tool.
This tool is intended for use in ModelBuilder and not in Python scripting.
Since you want to use Python instead, you need to use a normal iterator (generally, a for loop running through a list of feature classes). You can automatically build the list with arcpy.ListFeatureClasses, and then just loop:
# set the workspace
arcpy.env.workspace = Test_gdb
# get a list of feature classes in arcpy.env.workspace
listFC = arcpy.ListFeatureClasses()
# iterate
for fc in listFC:
#
# code to do to fc
#
If you're only planning to use that list of feature classes once, call ListFeatureClasses in the for loop:
for fc in arcpy.ListFeatureClasses():
In either case, you'll need to look at FeatureClassToFeatureClass for outputting a shapefile once you get your loop working :)