Problem with gcloud local prediction. about cloudml-samples

[andrewferlitsch]

@dizcology please take a look

[gogasca]

@Mustufain is this a model in our samples? Take a look at: https://stackoverflow.com/questions/49172710/what-does-google-cloud-ml-engine-do-when-a-json-request-contains-bytes-or-b6 if not a model please open issue in StackOverflow for visibility of the community

[Grandmother]

I've met the same problem and found out that ml_engine/local_utils.py uses python to run ml_engine/local_predict.pyc that is built for python2.7.
My python is python3, so when ml_engine/local_utils.py tries to run ml_engine/local_predict.pyc using python (actually python3), it fails with error:

RuntimeError: Bad magic number in .pyc file

Solution 1:

You can just make python2 as default one in system.

Solution 2:

I changed ml_engine/local_utils.py with such patch:

83c83
<   python_executables = files.SearchForExecutableOnPath("python")
---
>   python_executables = files.SearchForExecutableOnPath("python2")
114a115
>   log.debug(args)
124,126c125,130
<   for instance in instances:
<     proc.stdin.write((json.dumps(instance) + "\n").encode("utf-8"))
<   proc.stdin.flush()
---
>   try:
>     for instance in instances:
>       proc.stdin.write((json.dumps(instance) + "\n").encode("utf-8"))
>     proc.stdin.flush()
>   except:
>     pass

* log.degub(args) needed to see what we are running.
** try-catch needed to make script able to read and print an error ocurred while running ml_engine/local_predict.pyc.

[Grandmother]

Here is a patch in unified format:

--- /usr/lib/google-cloud-sdk/lib/googlecloudsdk/command_lib/ml_engine/local_utils_orig.py      2020-05-14 10:18:40.389442573 +0300
+++ /usr/lib/google-cloud-sdk/lib/googlecloudsdk/command_lib/ml_engine/local_utils.py   2020-05-14 12:28:41.053351849 +0300
@@ -80,7 +80,7 @@
     encoding.SetEncodedValue(env, "CLOUDSDK_ROOT", sdk_root)
     # We want to use whatever the user's Python was, before the Cloud SDK started
     # changing the PATH. That's where Tensorflow is installed.
-    python_executables = files.SearchForExecutableOnPath("python")
+    python_executables = files.SearchForExecutableOnPath("python2")
     # Need to ensure that ml_sdk is in PYTHONPATH for the import in
     # local_predict to succeed.
 
@@ -112,6 +112,7 @@
         for a in ([python_executable, local_predict.__file__] + predict_args)
     ]
 
+    log.debug(args)
     proc = subprocess.Popen(
         args,
         stdin=subprocess.PIPE,
@@ -121,9 +122,12 @@
     )
 
     # Pass the instances to the process that actually runs local prediction.
-    for instance in instances:
-        proc.stdin.write((json.dumps(instance) + "\n").encode("utf-8"))
-    proc.stdin.flush()
+    try:
+        for instance in instances:
+            proc.stdin.write((json.dumps(instance) + "\n").encode("utf-8"))
+        proc.stdin.flush()
+    except:
+        pass
 
     # Get the results for the local prediction.
     output, err = proc.communicate()

[kweinmeister]

It looks like this issue is about the AI Platform itself, not sample code in this repo. The best path forward is to contact Google Cloud Support. I will go ahead and close this issue. Please feel free to reopen if you have any questions about the sample code in this repo.