ModuleNotFoundError: No module named 'tensorflow'

After
conda install tensorflow
and
conda activate tensorflow_env
while running code
import tensorflow as tf
Error
ModuleNotFoundError                       Traceback (most recent call last)
 in
----> 1 import tensorflow as tf
ModuleNotFoundError: No module named 'tensorflow'

Hi, I think there might be mainly two reasons for this. The most probable reasons and their solutions are described below:

If you are using Python 2.7, then Tensroflow might not work. Upgrade it to Python 3.5 and above.
For this open the conda prompt and type:
conda install python = 3.5
Then type the commands to get tensorflow
You might be already having Python in your Program Data. To check if the paths are not the same:
i) Open command prompt and :-
>>>python
>>>import sys
>>>print(sys.executable)
Note down the path.
ii) Open conda prompt and type the same commands. If the paths are not the same then,
uninstall both (or all) the python packages you have. Install anaconda package and make sure to
check the "add to path" option.

@georgevettathu
Which version of tensorflow you are using?
Can you please go through this link ?Thanks!

Thanks. I have installed through the command
conda install tensorflow
Ialso activitate invirinment also ok
but on call import tensorflow as tf
error message: as given below.
ModuleNotFoundError                       Traceback (most recent call
last) in ----> 1 import
tensorflow as tf
ModuleNotFoundError: No module named 'tensorflow'
Can you please help me to install tensorflow properely
my system is windows 7 and pythen 3.7.2
Dr. George Mathew
On Tue, Sep 3, 2019 at 11:45 AM ravikyram<EMAIL_ADDRESS>wrote:

@georgevettathu https://github.com/georgevettathu
Which version of tensorflow you are using?
Can you please go through this link
https://www.tensorflow.org/install/pip ?Thanks!
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.

again installed through the command
pip install tensorflow==2.0.0-rc0
no onstallation errors but on call:
Import tensorflow
import tensorflow as tf
Initialize two constants
x1 = tf.constant([1,2,3,4])
x2 = tf.constant([5,6,7,8])
Multiply
result = tf.multiply(x1, x2)
Print the result
print(result)
Error as given below:
ERROR:root:Internal Python error in the inspect module.
Below is the traceback from this internal error.
Traceback (most recent call last):
File "C:\ProgramData\Anaconda37\lib\site-packages\IPython\core\interactiveshell.py",
line 3325, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "", line 5, in
x1 = tf.constant([1,2,3,4])
AttributeError: module 'tensorflow' has no attribute 'constant'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\ProgramData\Anaconda37\lib\site-packages\IPython\core\interactiveshell.py",
line 2039, in showtraceback
stb = value.render_traceback()
AttributeError: 'AttributeError' object has no attribute 'render_traceback'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\ProgramData\Anaconda37\lib\site-packages\tensorflow_core\python\pywrap_tensorflow.py",
line 58, in
from tensorflow.python.pywrap_tensorflow_internal import *
File "C:\ProgramData\Anaconda37\lib\site-packages\tensorflow_core\python\pywrap_tensorflow_internal.py",
line 28, in
_pywrap_tensorflow_internal = swig_import_helper()
File "C:\ProgramData\Anaconda37\lib\site-packages\tensorflow_core\python\pywrap_tensorflow_internal.py",
line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp,
pathname, description)
File "C:\ProgramData\Anaconda37\lib\imp.py", line 242, in load_module
return load_dynamic(name, filename, file)
File "C:\ProgramData\Anaconda37\lib\imp.py", line 342, in load_dynamic
return _load(spec)
ImportError: DLL load failed with error code -1073741795
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\ProgramData\Anaconda37\lib\site-packages\IPython\core\ultratb.py",
line 1101, in get_records
return _fixed_getinnerframes(etb, number_of_lines_of_context, tb_offset)
File "C:\ProgramData\Anaconda37\lib\site-packages\IPython\core\ultratb.py",
line 319, in wrapped
return f(*args, **kwargs)
File "C:\ProgramData\Anaconda37\lib\site-packages\IPython\core\ultratb.py",
line 353, in fixed_getinnerframes
records = fix_frame_records_filenames(inspect.getinnerframes(etb, context))
File "C:\ProgramData\Anaconda37\lib\inspect.py", line 1502, in getinnerframes
frameinfo = (tb.tb_frame,) + getframeinfo(tb, context)
File "C:\ProgramData\Anaconda37\lib\inspect.py", line 1460, in getframeinfo
filename = getsourcefile(frame) or getfile(frame)
File "C:\ProgramData\Anaconda37\lib\inspect.py", line 696, in getsourcefile
if getattr(getmodule(object, filename), 'loader', None) is not None:
File "C:\ProgramData\Anaconda37\lib\inspect.py", line 733, in getmodule
if ismodule(module) and hasattr(module, 'file'):
File "C:\ProgramData\Anaconda37\lib\site-packages\tensorflow_init.py",
line 50, in getattr
module = self.load()
File "C:\ProgramData\Anaconda37\lib\site-packages\tensorflow_init.py",
line 44, in _load
module = importlib.import_module(self.name)
File "C:\ProgramData\Anaconda37\lib\importlib_init.py", line
127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "", line 1006, in _gcd_import
File "", line 983, in _find_and_load
File "", line 953, in _find_and_load_unlocked
File "", line 219, in _call_with_frames_removed
File "", line 1006, in _gcd_import
File "", line 983, in _find_and_load
File "", line 967, in _find_and_load_unlocked
File "", line 677, in _load_unlocked
File "", line 728, in exec_module
File "", line 219, in call_with_frames_removed
File "C:\ProgramData\Anaconda37\lib\site-packages\tensorflow_core_init.py",
line 42, in
from tensorflow.api.v2 import audio
File "C:\ProgramData\Anaconda37\lib\site-packages\tensorflow_core_api\v2\audio_init.py",
line 10, in
from tensorflow.python.ops.gen_audio_ops import decode_wav
File "C:\ProgramData\Anaconda37\lib\site-packages\tensorflow_core\python\ops\gen_audio_ops.py",
line 9, in
from tensorflow.python import pywrap_tensorflow as pywrap_tensorflow
File "C:\ProgramData\Anaconda37\lib\site-packages\tensorflow_init.py",
line 50, in getattr
module = self.load()
File "C:\ProgramData\Anaconda37\lib\site-packages\tensorflow_init.py",
line 44, in _load
module = importlib.import_module(self.name)
File "C:\ProgramData\Anaconda37\lib\importlib_init.py", line
127, in import_module
return _bootstrap.gcd_import(name[level:], package, level)
File "C:\ProgramData\Anaconda37\lib\site-packages\tensorflow_core\python_init.py",
line 49, in
from tensorflow.python import pywrap_tensorflow
File "C:\ProgramData\Anaconda37\lib\site-packages\tensorflow_core\python\pywrap_tensorflow.py",
line 74, in
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "C:\ProgramData\Anaconda37\lib\site-packages\IPython\core\interactiveshell.py",
line 3325, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "", line 5, in
x1 = tf.constant([1,2,3,4])
AttributeError: module 'tensorflow' has no attribute 'constant'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\ProgramData\Anaconda37\lib\site-packages\IPython\core\interactiveshell.py",
line 2039, in showtraceback
stb = value.render_traceback()
AttributeError: 'AttributeError' object has no attribute 'render_traceback'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\ProgramData\Anaconda37\lib\site-packages\tensorflow_core\python\pywrap_tensorflow.py",
line 58, in
from tensorflow.python.pywrap_tensorflow_internal import *
File "C:\ProgramData\Anaconda37\lib\site-packages\tensorflow_core\python\pywrap_tensorflow_internal.py",
line 28, in
_pywrap_tensorflow_internal = swig_import_helper()
File "C:\ProgramData\Anaconda37\lib\site-packages\tensorflow_core\python\pywrap_tensorflow_internal.py",
line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp,
pathname, description)
File "C:\ProgramData\Anaconda37\lib\imp.py", line 242, in load_module
return load_dynamic(name, filename, file)
File "C:\ProgramData\Anaconda37\lib\imp.py", line 342, in load_dynamic
return _load(spec)
ImportError: DLL load failed with error code -1073741795
Failed to load the native TensorFlow runtime.
See https://www.tensorflow.org/install/errors
for some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.
can you please suggest any solution to this problem
Thanking you
Dr. George Mathew
On Tue, Sep 3, 2019 at 12:56 PM George Mathew<EMAIL_ADDRESS>wrote:

Thanks. I have installed through the command
conda install tensorflow
Ialso activitate invirinment also ok
but on call import tensorflow as tf
error message: as given below.
ModuleNotFoundError                       Traceback (most recent call last) in ----> 1 import tensorflow as tf
ModuleNotFoundError: No module named 'tensorflow'
Can you please help me to install tensorflow properely
my system is windows 7 and pythen 3.7.2
Dr. George Mathew
On Tue, Sep 3, 2019 at 11:45 AM ravikyram<EMAIL_ADDRESS>wrote:

@georgevettathu https://github.com/georgevettathu
Which version of tensorflow you are using?
Can you please go through this link
https://www.tensorflow.org/install/pip ?Thanks!
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
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or mute the thread
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.

@georgevettathu
Request you to uninstall python and tensorflow .Please, install it again and see if the problem still persists.Thanks!

Apologies for the delay in response. I suspect that your cpu does not support AVX instructtion sets.
See Hardware Requirements
Can you please confirm?

See also #19584

Is this still an issue?

Most likely its because of your cpu does not support AVX instruction sets. Feel free to reopen this issue if otherwise. Thanks!

Dear Yasir,
Thank you so much for your suggestions. My CPU is:
Intel (R) Core(TM)2 Duo CPU E7200 @ 2.53GHz
Whether it support AVX instruction sets. What is the solution?
Can you help me. I could install tensorflow but not working while calling.
George Mathew
On Thu, Oct 3, 2019 at 11:33 PM Yasir Modak<EMAIL_ADDRESS>wrote:

Most likely its because of your cpu does not support AVX instruction sets.
Feel free to reopen this issue if otherwise. Thanks!
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub
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My python is Python 3.7.2
I checked the path as you suggested.
) Open command prompt and :-

python
import sys
print(sys.executable)
Note down the path.
ii) Open conda prompt and type the same commands.
I got the path as
C:\ProgramData\Anaconda37\python.exe
in both cases
My CPU is:
Intel (R) Core(TM)2 Duo CPU E7200 @ 2.53GHz
Whether it support AVX instruction sets. What is the solution?
Thanking you
George Mathew

Plese check if AVX is supported.
If it is not, the only options are either compiling from source or #19584

Unfortunately your model does not support AVX instruction sets.
See https://ark.intel.com/content/www/us/en/ark/products/35348/intel-core-2-duo-processor-e7200-3m-cache-2-53-ghz-1066-mhz-fsb.html

Thank you so much Mr. Yasir Modak
Dr. George Mathew
On Fri, Oct 4, 2019 at 10:50 PM Yasir Modak<EMAIL_ADDRESS>wrote:

Unfortunately your model does not support AVX instruction sets.
See
https://ark.intel.com/content/www/us/en/ark/products/35348/intel-core-2-duo-processor-e7200-3m-cache-2-53-ghz-1066-mhz-fsb.html
—
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when i start training using this command
python train.py --logtostderr --train_dir=training/ --pipeline_config_path=training/faster_rcnn_resnet101_voc07.config
and get respond something like this
2020-03-01 23:00:07.833275: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
Traceback (most recent call last):
File "train.py", line 48, in
from tensorflow.contrib import framework as contrib_framework
File "C:\Users\Lab Visual I\Anaconda3\envs\tensorflow_gpu\lib\site-packages\tensorflow\contrib_init_.py", line 27, in
from tensorflow.contrib import checkpoint
File "C:\Users\Lab Visual I\Anaconda3\envs\tensorflow_gpu\lib\site-packages\tensorflow\contrib\checkpoint_init_.py", line 37, in
from tensorflow.contrib.checkpoint.python.containers import UniqueNameTracker
File "C:\Users\Lab Visual I\Anaconda3\envs\tensorflow_gpu\lib\site-packages\tensorflow\contrib\checkpoint\python\containers.py", line 20, in
from tensorflow.python.training.checkpointable import base as checkpointable_lib
ModuleNotFoundError: No module named 'tensorflow.python.training.checkpointable'
Description of the issue (what needs to be changed):
i really dont know how to fix it, i had searched on github and got nothing.

let {PythonShell} = require('python-shell')
var myPythonScriptPath = 'tacotron-master/eval.py';
var options = {
mode: 'text',
args: [' --checkpoint ~/tacotron/logs-tacotron/model.ckpt', '-185000']
};
PythonShell.run('tacotron-master/eval.py', options, function (err, results) {
if (err) throw err;
// results is an array consisting of messages collected during execution
console.log('results: %j', results);
});
i wrote this code to run this command "python3 eval.py --checkpoint ~/tacotron/logs-tacotron/model.ckpt-185000"
and gives me error
No module named 'tensorflow'
wich is in another script.py that eval call import tensor flow
what should i do to run this pre-trained model

Thanks. I have installed through the command conda install tensorflow Ialso activitate invirinment also ok but on call import tensorflow as tf error message: as given below. ModuleNotFoundError Traceback (most recent call last) in ----> 1 import tensorflow as tf ModuleNotFoundError: No module named 'tensorflow' Can you please help me to install tensorflow properely my system is windows 7 and pythen 3.7.2 Dr. George Mathew
…
On Tue, Sep 3, 2019 at 11:45 AM ravikyram @.***> wrote: @georgevettathu https://github.com/georgevettathu Which version of tensorflow you are using? Can you please go through this link https://www.tensorflow.org/install/pip ?Thanks! — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#32147?email_source=notifications&email_token=ALSVGJTILAB3DPRDWNERRTTQHX6IVA5CNFSM4ISZNKY2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOD5XDW3Y#issuecomment-527317871>, or mute the thread https://github.com/notifications/unsubscribe-auth/ALSVGJUKTVZEWBJMK2VAYRTQHX6IVANCNFSM4ISZNKYQ .

pip install tensorflow==2.0.0a0

Python 3.7.5 (default, Oct 31 2019, 15:18:51) [MSC v.1916 64 bit (AMD64)] :: Anaconda, Inc. on win32
Type "help", "copyright", "credits" or "license" for more information.

import tensorflow
Traceback (most recent call last):
File "C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorflow_core\python\pywrap_tensorflow.py", line 58, in
from tensorflow.python.pywrap_tensorflow_internal import *
File "C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorflow_core\python\pywrap_tensorflow_internal.py", line 28, in
_pywrap_tensorflow_internal = swig_import_helper()
File "C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorflow_core\python\pywrap_tensorflow_internal.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
File "C:\Users\rosha.conda\envs\MachineLEarning\lib\imp.py", line 242, in load_module
return load_dynamic(name, filename, file)
File "C:\Users\rosha.conda\envs\MachineLEarning\lib\imp.py", line 342, in load_dynamic
return _load(spec)
ImportError: DLL load failed: The specified module could not be found.

During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "", line 1, in
File "C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorflow_init_.py", line 101, in
from tensorflow_core import *
File "C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorflow_core_init_.py", line 40, in
from tensorflow.python.tools import module_util as module_util
File "C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorflow_init.py", line 50, in getattr
module = self.load()
File "C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorflow_init.py", line 44, in _load
module = importlib.import_module(self.name)
File "C:\Users\rosha.conda\envs\MachineLEarning\lib\importlib_init.py", line 127, in import_module
return _bootstrap.gcd_import(name[level:], package, level)
File "C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorflow_core\python_init.py", line 49, in
from tensorflow.python import pywrap_tensorflow
File "C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorflow_core\python\pywrap_tensorflow.py", line 74, in
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorflow_core\python\pywrap_tensorflow.py", line 58, in
from tensorflow.python.pywrap_tensorflow_internal import *
File "C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorflow_core\python\pywrap_tensorflow_internal.py", line 28, in
_pywrap_tensorflow_internal = swig_import_helper()
File "C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorflow_core\python\pywrap_tensorflow_internal.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
File "C:\Users\rosha.conda\envs\MachineLEarning\lib\imp.py", line 242, in load_module
return load_dynamic(name, filename, file)
File "C:\Users\rosha.conda\envs\MachineLEarning\lib\imp.py", line 342, in load_dynamic
return _load(spec)
ImportError: DLL load failed: The specified module could not be found.
Failed to load the native TensorFlow runtime.
See https://www.tensorflow.org/install/errors
for some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.

exit()

(MachineLEarning) C:\Users\rosha\Downloads\Documents\Python\DMProject>pip install tensorflow==2.0.0a0
Collecting tensorflow==2.0.0a0
Downloading https://files.pythonhosted.org/packages/c7/90/cf5e7fbf4a3c14b314e1ed6571eae1f9ad3b5e32a4e24b2b817466435a21/tensorflow-2.0.0a0-cp37-cp37m-win_amd64.whl (49.4MB)
|████████████████████████████████| 49.5MB 139kB/s
Requirement already satisfied: termcolor>=1.1.0 in c:\users\rosha.conda\envs\machinelearning\lib\site-packages (from tensorflow==2.0.0a0) (1.1.0)
Requirement already satisfied: numpy<2.0,>=1.14.5 in c:\users\rosha.conda\envs\machinelearning\lib\site-packages (from tensorflow==2.0.0a0) (1.18.2)
Requirement already satisfied: google-pasta>=0.1.2 in c:\users\rosha.conda\envs\machinelearning\lib\site-packages (from tensorflow==2.0.0a0) (0.2.0)
Requirement already satisfied: gast>=0.2.0 in c:\users\rosha.conda\envs\machinelearning\lib\site-packages (from tensorflow==2.0.0a0) (0.2.2)
Collecting tb-nightly<1.14.0a20190302,>=1.14.0a20190301
Downloading https://files.pythonhosted.org/packages/a9/51/aa1d756644bf4624c03844115e4ac4058eff77acd786b26315f051a4b195/tb_nightly-1.14.0a20190301-py3-none-any.whl (3.0MB)
|████████████████████████████████| 3.0MB 156kB/s
Requirement already satisfied: wheel>=0.26 in c:\users\rosha.conda\envs\machinelearning\lib\site-packages (from tensorflow==2.0.0a0) (0.34.2)
Requirement already satisfied: protobuf>=3.6.1 in c:\users\rosha.conda\envs\machinelearning\lib\site-packages (from tensorflow==2.0.0a0) (3.11.3)
Requirement already satisfied: absl-py>=0.7.0 in c:\users\rosha.conda\envs\machinelearning\lib\site-packages (from tensorflow==2.0.0a0) (0.9.0)
Requirement already satisfied: six>=1.10.0 in c:\users\rosha.conda\envs\machinelearning\lib\site-packages (from tensorflow==2.0.0a0) (1.14.0)
Requirement already satisfied: keras-preprocessing>=1.0.5 in c:\users\rosha.conda\envs\machinelearning\lib\site-packages (from tensorflow==2.0.0a0) (1.1.0)
Requirement already satisfied: astor>=0.6.0 in c:\users\rosha.conda\envs\machinelearning\lib\site-packages (from tensorflow==2.0.0a0) (0.8.1)
Requirement already satisfied: keras-applications>=1.0.6 in c:\users\rosha.conda\envs\machinelearning\lib\site-packages (from tensorflow==2.0.0a0) (1.0.8)
Requirement already satisfied: grpcio>=1.8.6 in c:\users\rosha.conda\envs\machinelearning\lib\site-packages (from tensorflow==2.0.0a0) (1.28.1)
Collecting tf-estimator-nightly<1.14.0.dev2019030116,>=1.14.0.dev2019030115
Downloading https://files.pythonhosted.org/packages/13/82/f16063b4eed210dc2ab057930ac1da4fbe1e91b7b051a6c8370b401e6ae7/tf_estimator_nightly-1.14.0.dev2019030115-py2.py3-none-any.whl (411kB)
|████████████████████████████████| 419kB 182kB/s
Requirement already satisfied: werkzeug>=0.11.15 in c:\users\rosha.conda\envs\machinelearning\lib\site-packages (from tb-nightly<1.14.0a20190302,>=1.14.0a20190301->tensorflow==2.0.0a0) (1.0.1)
Requirement already satisfied: markdown>=2.6.8 in c:\users\rosha.conda\envs\machinelearning\lib\site-packages (from tb-nightly<1.14.0a20190302,>=1.14.0a20190301->tensorflow==2.0.0a0) (3.2.1)
Requirement already satisfied: setuptools in c:\users\rosha.conda\envs\machinelearning\lib\site-packages (from protobuf>=3.6.1->tensorflow==2.0.0a0) (46.1.3)
Requirement already satisfied: h5py in c:\users\rosha.conda\envs\machinelearning\lib\site-packages (from keras-applications>=1.0.6->tensorflow==2.0.0a0) (2.10.0)
Installing collected packages: tb-nightly, tf-estimator-nightly, tensorflow
Found existing installation: tensorflow 2.1.0
Uninstalling tensorflow-2.1.0:
Successfully uninstalled tensorflow-2.1.0
Successfully installed tb-nightly-1.14.0a20190301 tensorflow-2.0.0a0 tf-estimator-nightly-1.14.0.dev2019030115
(MachineLEarning) C:\Users\rosha\Downloads\Documents\Python\DMProject>python
Python 3.7.5 (default, Oct 31 2019, 15:18:51) [MSC v.1916 64 bit (AMD64)] :: Anaconda, Inc. on win32
Type "help", "copyright", "credits" or "license" for more information.

import tensorflow
C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorflow\python\framework\dtypes.py:523: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint8 = np.dtype([("qint8", np.int8, 1)])
C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorflow\python\framework\dtypes.py:524: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint8 = np.dtype([("quint8", np.uint8, 1)])
C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorflow\python\framework\dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint16 = np.dtype([("qint16", np.int16, 1)])
C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorflow\python\framework\dtypes.py:526: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint16 = np.dtype([("quint16", np.uint16, 1)])
C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorflow\python\framework\dtypes.py:527: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint32 = np.dtype([("qint32", np.int32, 1)])
C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorflow\python\framework\dtypes.py:532: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
np_resource = np.dtype([("resource", np.ubyte, 1)])
C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint8 = np.dtype([("qint8", np.int8, 1)])
C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint8 = np.dtype([("quint8", np.uint8, 1)])
C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint16 = np.dtype([("qint16", np.int16, 1)])
C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint16 = np.dtype([("quint16", np.uint16, 1)])
C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint32 = np.dtype([("qint32", np.int32, 1)])
C:\Users\rosha.conda\envs\MachineLEarning\lib\site-packages\tensorboard\compat\tensorflow_stub\dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
np_resource = np.dtype([("resource", np.ubyte, 1)])
import tensorflow as tf
import tensorflow as tf
import tensorflow
tensorflow --version
Traceback (most recent call last):
File "", line 1, in
NameError: name 'version' is not defined
tf.VERSION
Traceback (most recent call last):
File "", line 1, in
AttributeError: module 'tensorflow' has no attribute 'VERSION'
x1 = tf.constant([1,2,3,4])
2020-04-17 07:27:33.083319: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
x1 = tf.constant([1])
x2 = tf.constant([5])
result = tf.multiply(x1,x2)
print(result)
tf.Tensor([5], shape=(1,), dtype=int32)
a = tf.constant([3,4])
b = tf.constant([45,8])
print(tf.mu;tiply(a,b))
File "", line 1
print(tf.mu;tiply(a,b))
^
SyntaxError: invalid syntax
print(tf.multiply(a,b))
tf.Tensor([135  32], shape=(2,), dtype=int32)
x1 = tf.constant([1,2,3,4])
x2 = tf.constant([5,6,7,8])
result = tf.multiply(x1, x2)
print(result)
tf.Tensor([ 5 12 21 32], shape=(4,), dtype=int32)

Locking to prevent further notifications with similar errors that already have solution included in the thread


batch_size_per_gpu * grad_accumulation_steps == global steps ?

Checks

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[X] I have thoroughly reviewed the project documentation and read the related paper(s).
[X] I have searched for existing issues, including closed ones, no similar questions.
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Question details
To my understanding, if one likes to reproduce your model with a slightly different hardware, the combination of batch_size_per_gpu and grad_accumulation_steps should result in the same global batch size and gradient accumulation behaviour.
As an example:
You used 8xA100 80GB GPU's for model training, accordingly your settings are:
batch_size_per_gpu: 38400
grad_accumulation_steps: 1

If I want to use 8xA100 40GB GPU's for model training to reproduce your results, I'd use:
batch_size_per_gpu: 19200
grad_accumulation_steps: 2

Then the overall steps should be the same and also training time is roughly the same (same GPU, just half the memory).
But currently, the shown overall steps is not at all dependent from grad_accumulation_steps. Also the variable global_step in trainer.py is always updated independently from the value of grad_accumulation_steps.
This is not the case e.g. in diffusors.
The consequence is that overall number of steps in the above example is doubled, checkpoints at a certain step-time are therefore not comparable and also training seems to progress twice as fast, as now 2 steps are calculated in the same time where the 80GB A100 version needed 1 step.
It seems to me like a bug, but I am unsure because of your answer in #630.

It is the same updates to compare but not steps (in our paper)
you can find the notes in train.py (previous version)
and also https://github.com/SWivid/F5-TTS/blob/c85252f59a7b2f76bf550140b1306e56508ec6dc/src/f5_tts/configs/F5TTS_Base_train.yaml#L16 the new version using hydra

Sure welcome PR.
The epoch is the number of rounds of going through the dataset, so its concept is natively with steps, but surely someone needs to consider multiplying it according to grad_accum to maintain same update counts.

I have a similar question.
If I use a single A100 80GB GPU with batch_size_per_gpu: 38400, how can I achieve comparable results to training on 8 x A100 80GB GPUs?

Should I set grad_accumulation_steps to 8 to simulate the same global batch size?
Do I also need to scale the training steps (global steps) by 8?
Or does the number of GPUs only affect training speed without influencing the global batch size?

Thanks!

I have a similar question.
If I use a single A100 80GB GPU with batch_size_per_gpu: 38400, how can I achieve comparable results to training on 8 x A100 80GB GPUs?

Should I set grad_accumulation_steps to 8 to simulate the same global batch size?
Do I also need to scale the training steps (global steps) by 8?
Or does the number of GPUs only affect training speed without influencing the global batch size?

Thanks!

yes, set grad_accum to 8, train to 1.2M*8=9.6M steps (effectively 1.2M updates

does this also mean that if I use a single A100 with 80GB, I can use the batch size of 19200 and 16 grad_accumulation_steps to achieve comparable results


Add CMS Guides landing page

This looks great! ⚡🚀

Beautiful work, @delucis!
I think we discussed a custom ordering for these, which really only affects Storyblok, which is a larger partner. (Contentful and Butter are the other ones, but they're coincidentally already at the beginning.) I don't think this is blocking, but we might want Storyblok first eventually?
Also, just checking also with @Jutanium - is the plan to merge this WITH the Storyblok full guide draft merging? Or are we merging with the stub? If with the stub, we might want to edit the stub to say "full guide dropping soon" vs "help us create this".

Heads up that the paragraphs are looking a little long, so I'm going to take a pass at the content as a whole. Don't merge without me!!  😄

Won't merge without you! Storyblok will move up the order once it's no longer a stub after #1944.

Honestly, with Butter and Contentful being the only other two we'd want to move up, we lucked out! No other changes needed, I don't think!  😄

"wherever AND HOWEVER on your site you want to display it."  ???

@delucis - I think we're coming to the conclusion that we'd like to be able to specify a custom order for the non-stub pages!

OK, just checking in with everyone: I think this is good to go, as soon as we've merged Storyblok Guide? #1944

I’m happy!


Bumping spring-boot-starter-web to 2.7.5(latest)

Signed-off-by: tanvigour<EMAIL_ADDRESS>Description
Upgrade spring-boot-starter-web version to the latest
Issue reference
We strive to have all PR being opened based on an issue, where the problem or feature have been discussed prior to implementation.
Please reference the issue this PR will close: #782
Checklist
Please make sure you've completed the relevant tasks for this PR, out of the following list:

[ ] Code compiles correctly
[ ] Created/updated tests
[ ] Extended the documentation

Please, see failures with integration tests and samples' validation.


Quick question regarding browser support

Like what you're doing with react-autosuggest - thank you for your effort and work!
Just wanted to ask how well react-autosuggest does in terms of browser support - do you have a browser support list, especially for IE and mobile browsers?
Thanks!

@hibearpanda Thanks :)
There is no official list, but from what I know it's working in latest Chrome, Firefox, Safari, iOS, Android, and there is a known bug in IE.

Closing for no activity.

@hibearpanda Just letting you know that the IE bug I mentioned above is fixed in 3.7.2.

thanks man!


Can't use normal Netlify functions when SSR enabled

Describe the bug
When using the SSR runtime, normal Netlify (non-edge) functions are not working. Not sure if this is by design but I don't have this problem when using Next.js. Normal functions are working fine when using SSR in my Next.js apps.
angular-runtime/src/helpers/setUpEdgeFunction.js
excludedPath: ${JSON.stringify(excludedPaths)},

Shouldn't the excludedPath include .netlify and possible other internal URLs of Netlify?
Everything redirects back to the app itself. I figured that because even without any redirect rules, app works fine whereas without a /*  /index.html  200 redirect, direct access to any url should result with the Netlify's internal 404 page which it does for the non-SSR version.
To Reproduce
Example repo with a clean Angular v18 installation with SSR enabled and a single function.
It's deployed at https://vermillion-cat-89e180.netlify.app/
The function is deployed at https://vermillion-cat-89e180.netlify.app/.netlify/functions/hello but accessing it would render the app with an Error on the console that says there is no Route for the url because Angular tries to render the url.
I tried adding redirect rules but since SSR apps are not subject to redirect rules, they don't solve the problem.
--
Example repo without SSR but with exact same setup with the SSR one; Angular v18 and a single function.
The function is deployed at https://stellar-horse-4fc8e6.netlify.app/.netlify/functions/hello and works fine.
Expected behavior
I should be able to trigger normal functions when using SSR. As a workaround, I'm currently using edge functions since the ones that are defined in netlify.toml file triggered before the runtime but they are not versioned like normal functions so they are not really a replacement for normal functions.
Versions

Angular: v18.0.0
plugin: Latest, auto installed from Netlify's dashboard

If you're using the CLI to build

OS: [e.g. macOS, Windows]
netlify/cli version:

If you're using file-based installation

netlify.toml:

Good catch! I'll work on a fix for this.


Master base

:x: Validation status: errors

File
Status
Preview URL
Details

:x:Error

Details

[Error] Cannot sync git repo to specified state. Please make sure the pull request is mergeable. Details: Git merge results in conflict, repository remote url: https://github.com/OPS-E2E-Prod/azure-docs-cli-python, working directory: W:\fyr5-s, target branch: live-based, target branch commit: c76d7cf9b5f2eb3eff3ddd2214dbdf230cb3ade4, source branch: master-base, source branch commit: .

For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.


Hamburger menu should disapear after entry has been selected.

When using a smaller display (mobileView), the hamburger menu is overlapping the current page hiding it.
A common practice of behavior of a hamburger menu is usually to disappear after a choice has been made.

@vconzola, would that be ok to make the menu disappear after clicking an entry?


add deprecation notice

Description
Add deprecation notice for Log Analysis and Activity Tracker.
Also update note about not calling this module.
Release required?

[x] No release
[ ] Patch release (x.x.X)
[ ] Minor release (x.X.x)
[ ] Major release (X.x.x)

Release notes content

Run the pipeline
If the CI pipeline doesn't run when you create the PR, the PR requires a user with GitHub collaborators access to run the pipeline.
Run the CI pipeline when the PR is ready for review and you expect tests to pass. Add a comment to the PR with the following text:
/run pipeline

Checklist for reviewers

[ ] If relevant, a test for the change is included or updated with this PR.
[ ] If relevant, documentation for the change is included or updated with this PR.

For mergers

Use a conventional commit message to set the release level. Follow the guidelines.
Include information that users need to know about the PR in the commit message. The commit message becomes part of the GitHub release notes.
Use the Squash and merge option.

/run pipeline

:tada: This PR is included in version 1.12.4 :tada:
The release is available on:

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v1.12.4

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[Epic] JSON Form - Phase 2

Objective
With the new JSON form widget being launched soon, we need to consolidate the actions which are not being done right now to be done soon.
The primary objective is to allow users to discover and build faster, customise the form building experience much more.
Success Metrics *

Goal
Metric

Time taken to build a form
Customer satisfaction increases

Requirements

Requirement
User story

Crud wizard updates to use JSON form widget
As a dev, i want to build CRUD apps faster and customise them quickly.

Widget selected in the JSON Form will open the property pane for the JSON form.
As a dev, I want to navigate to the properties of the widget I am working with.

Widgets in the form can be resized and re-arranged to be in the same row. Impacts the current draggable Behavior in property pane. (Needs design)
As a dev, I want to fully customise the widgets in the JSON form so that I can build great visual forms.

Need dynamic subheadings for the nested objects
As a dev, I want to be able to add subheadings for array objects

Stretch Users can add a text and divider, which can be used for headings and subtitles
As a dev, I want to add my own ways of dividing the data in a form to make it visually clutter free

Stretch Widgets in the type dropdown should be grouped together (Needs design). Added image on how the current view looks like

Documentation

CRUD wizard should have a new video
Widget resizing will need documentation and video
If we add the text and divider widget we need to update docs

Out of Scope

Progress bar widget in the JSON form

Developer Handoff Document in Figma
RACI Matrix

Responsible

Accountable

Consulted

Informed

CC - @riodeuno @ashit-rath @somangshu @momcilo-appsmith @vasanth-appsmith

Closing till we pick up


[Event Request] codeunit 90  "Purch.-Post" - OnBeforePostInvoiceCheckCredit

Hello, would it be possible to add OnBeforePostInvoiceCheckCredit,  event to codeunit 90  "Purch.-Post", like this:
    local procedure PostInvoice(var PurchHeader: Record "Purchase Header")
...
              if PurchSetup."Ext. Doc. No. Mandatory" or (GenJnlLineExtDocNo <> '') then
                 CheckExternalDocumentNumber(VendLedgEntry, PurchHeader);

             IsHandled := false;
>             OnBeforePostInvoiceCheckCredit(PurchHeader, HideProgressWindow, Window, TotalPurchLine, TotalPurchLineLCY, GenJnlLineDocType, GenJnlLineDocNo, GenJnlLineExtDocNo, SrcCode, IsHandled);//New Event
             if not IsHandled then
                 // Post vendor entries
                 if GuiAllowed and not HideProgressWindow then
                     Window.Update(4, 1);

     [IntegrationEvent(false, false)]
     local procedure OnBeforePostInvoiceCheckCredit(var PurchHeader: Record "Purchase Header"; var HideProgressWindow: Boolean; var Window: Dialog; var TotalPurchLine: Record "Purchase Line"; var TotalPurchLineLCY: Record "Purchase Line"; var GenJnlLineDocType: Enum "Gen. Journal Document Type"; var GenJnlLineDocNo: Code[20]; var GenJnlLineExtDocNo: Code[35]; var SrcCode: Code[10]; var IsHandled: Boolean)
     begin
     end;

May I ask what is the purpose of this event and why you need this here? We cannot implement handled event here!

The purpose is to execute the following code only under certain conditions without modifying HideProgressWindow variable

I don't see how this event can help to solve this task! Can you provide full code of procedure with wanted changes? And explain how this is supposed to work?


Opt out

If I have read this page correctly, am I right in thinking that we need to opt out of the Briefing email per user and if we create new users we will have to opt out for them at the time of creation too?
There needs to be a switch to turn this off for the domain so that it's off for all existing users and any newly created mailboxes too.
Enter feedback here]

Document details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: a0a83186-6909-edb8-7de3-7a5c9307a0a1
Version Independent ID: 9ba1d4d8-60ba-1c4d-f7e8-e9a92e74727d
Content: Briefing email overview - Cortana
Content Source: Briefing/be-overview.md
Product: mya
GitHub Login: @madehmer
Microsoft Alias: madehmer

I agree, this is a total joke.  I just blacklisted<EMAIL_ADDRESS>as I hardly think I'm going to go through all of this just to block Microsoft from spamming us daily.  The one it sent me today saying "Did you miss these emails?" were all Amazon order confirmations.  Like wow real helpful.

I agree, this is a total joke. I just blacklisted<EMAIL_ADDRESS>as I hardly think I'm going to go through all of this just to block Microsoft from spamming us daily. The one it sent me today saying "Did you miss these emails?" were all Amazon order confirmations. Like wow real helpful.

I blocked that address yesterday and the email still came through. It seems like they may be bypassing the email somehow and just dropping the email into inboxes directly.
Doing a mail trace of inbound mail from<EMAIL_ADDRESS>for the past two days shows no results so that are being sneaky about it for sure.
The content of my "briefing" was basically a list of any time I have said "I will do..." in an email titled as "Tasks you may have missed" like I now have Microsoft as a micro manager nitpicking my emails.
Thanks a bunch.

You could not block MyAnalytics emails at all. They didn't route like normal emails and they were placed directly in a user's mailbox. I would not be shocked if MS is doing the same thing here.

You could not block MyAnalytics emails at all. They didn't route like normal emails and they were placed directly in a user's mailbox. I would not be shocked if MS is doing the same thing here.

Yes that seems to be what's happening here too.

Hi folks -Thank you for your feedback. We've added a tenant-level configuration, so the admin can opt in or out the entire tenant. See Tenant-level configuration for details.

Thanks for taking our feedback even though it was a bit harsh at times. Will this be available to GCC customers as well?

Hi folks -Thank you for your feedback. We've added a tenant-level configuration, so the admin can opt in or out the entire tenant. See Tenant-level configuration for details.

When will this be made available?

Worked for me earlier, go to Settings > Org Settings and then it has Briefing right there where you can turn it off.  Make sure you're in the new admin panel before doing it.
Thank you Microsoft team for making such quick changes.  I'm definitely very impressed and happy!

@martin8777 -It should be there, please try again. Thanks again for your feedback!

No it's not there. Has it been rolled out worldwide or just the US ?

No it's not there. Has it been rolled out worldwide or just the US ?

I'm in Canada and I have it.  Very strange!

We are a non profit tenant, I wonder if it's not been updated on all subscription types yet?

@martin8777 - If you have a tenant that is not part of this first release, you won’t see it as an option for that tenant yet. When the Briefing is released to your tenant, the control will be exposed prior to  the users in that tenant receiving Briefing email. Thanks for asking!

@martin8777 - If you have a tenant that is not part of this first release, you won’t see it as an option for that tenant yet. When the Briefing is released to your tenant, the control will be exposed prior to the users in that tenant receiving Briefing email. Thanks for asking!

Yeah that would make sense, except I am already receiving the briefing emails.
I've commented on them enough the past week or so!

What's the powershell command to turn it off for the tenant?

There is no PowerShell control at the tenant level. See Configure Briefing email for tenant-level configuration steps.

But the settings don't appear in our admin console so how do we turn this off?

I'm sorry to hear you're still having issues. Please contact Support for immediate assistance and/or send the team feedback about this issue, so they can follow up with you directly.

Thanks but I've tried both of those avenues and not had any success.
The 3rd party support company who responded to my ticket just repeated the published steps to disable users one by one or by using a list and then closed the support request.
I have had no response by using the feedback but then I have never had any follow up from the feedback tool so that was no surprise.

I'm surprised that Microsoft spend so much time creating something like this, which is basically scraping through Outlook, when there are already enough features to enable people to organise their day....Categories, Flags, To Do list etc.  Perhaps more energy could be expended on answering the multitudinous question/queries and suggestions for changes to existing facilities, such as 'Why can't I change the category name or colour or delete a category for a shared mailbox' - need to be a rocket surgeon to have even half a quarter of a chance of editing this.  Don't need MS Cortana micromanaging my day thanks very much.


add 'Contact Us' in README.md

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.


Web chat control on Safari and apple devices

I have a web chat control that accesses my DarlBot on the front page of my site, http://www.docandys.com. I have accessed it from Edge, FireFox, Chrome on PC, Android and windows phone and the system performs as expected, i.e. messages are correctly passed through to the Bot and it passes through it's expected sequences.
On safari on IPad the process freezes. I have not had the chance to investigate messages yet, but there is clearly a difference in behaviour.
[addition]
Looking with ApplicationInsights and setting exception handling around everything in the MessageController Post method the exception appears to be outside this and is reported as below:
15/05/2016 22:22:56 - Exception
A Task's exception(s) were not observed either by Waiting on the Task or accessing its Exception property. As a result, the unobserved exception was rethrown by the finalizer thread.
Exception type: System.NullReferenceException
Failed method: System.Web.ThreadContext.AssociateWithCurrentThread
Problem Id: System.NullReferenceException at System.Web.ThreadContext.AssociateWithCurrentThread
Severity level: Critical

That particular exception occurs when the code has an instance of a Task that was marked as "failed", but no code actually observed its Exception property before that Task instance was lost to the garbage collector, and the garbage collector's finalizer thread decided to take down the process.  (this behavior was changed in later versions of the .NET framework)
It would be interested to see where the NullReferenceException originally occurred in the code - can you break on thrown exceptions and find the call stack?

Hi Will, The .Net framework is 4.6 and the Bot connector and builder are the most recent.  I tried to set a try/catch at the outermost level of the MessagesController POST, and am not catching it in ApplicationInsights. All we get is the exception above and the uninformative contents. We've tried the web control with every variation of browser and platform we can, and everything works that is not Safari, and all Safari versions fail, whether iPhone, iPad or MacBook.

Further thoughts:
The crash happens on the second interaction. The bot is intended to demo various expert systems that illustrate our rule language and inference system. In the first screen you get to choose one of the demos. In the second the chosen expert system is loaded in the back end and a much smaller state message is passed to the bot and gets serialized. The Json for the first step is 3480 chars, the next step's json is 4001 chars. Is some size threshold for Safari being exceeded?

Maybe it's a timing issue with Safari?  It seems likely that you're spawning an asynchronous task and not waiting for its completion:
http://stackoverflow.com/a/20365859


Submit a Cloud Definition

Do NOT copy/paste a definition from somewhere else. Read about the word you want to define and come up with your own definition. Copy/Paste submissions will be closed and not added.
Fill out the JSON with your submission:
    {
    "word": "subnet",
    "content": "A subnet is the inside of a network OR a network inside of a network.",
    "learn_more_URL":"https://www.cloudflare.com/en-gb/learning/network-layer/what-is-a-subnet/",
    "tag":"networking",
    "abbreviation": "",
    "author_name":"Ella Adeka",
    "author_link": "https://github.com/ella-adeka/"
    }

Fill out the JSON below with the following.
Word (REQUIRED)
The word you are defining. Check this URL for all words we currently have.
Content (REQUIRED)
The definition. No more than 3 sentences.
learn more URL (REQUIRED)
Website where people can visit to learn more about the word.
tag (REQUIRED and select one)
Tech category the word fits in. Options:

compute
security
service
general
analytics
developer tool
web
networking
database
storage
devops
ai/ml
identity
iot
monitoring
cost management
disaster recovery

abbreviation (OPTIONAL)
If the word is commonly abbreviated, please provide it. For example, command line interface is often abbreviated as CLI.
author name (REQUIRED)
Your name.
author link (REQUIRED)
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Added, https://definethecloud.guide/subnet thank you for the submission.


Fix build

Attempt to fix build errors (#946) by removing sharp (an image optimizer)
cc @KyleAMathews

Setting the YARN_VERSION env to 1.7.0 in Netlify seems to fix it in my fork - someone with access to the main Netlify config should try updating it
@sophiebits @bvaughn one of you want to update the config?

Bummer ☹ Would be nice to get this fixed for sure.

I've set the YARN_VERSION in the build environment variables~

I'm going to retry your failed deploy now: https://app.netlify.com/sites/reactjs/deploys/5b476cb44ed62f44be89c873

Looks like the build passed 😄

Thanks for looking into this, @alexkrolick


Improve docs experience for those not running the latest beta

Is it possible to downgrade to 5.6 to make it usable for mere mortals that run latest Monterey?

The version of TSPL on Swift.org always shows the latest version of Swift that's available in Xcode or in an Xcode beta.  However, you can see both the Swift 5.6 and Swift 5.7 (beta) versions of TSPL on Apple Books:
https://books.apple.com/us/book/the-swift-programming-language-swift-5-6/id881256329
Under an older publication pipeline, we published two versions of TSPL on the web — beta and non-beta.  Maybe we sould turn this GitHub issue into a request to publish both versions again when we use DocC.

I agree with amartini51, it would be nice to have both beta and release docs available.
@ruurd, I understand you are referring to not running a beta (Ventura or Xcode), but in case you weren't aware, you can run Xcode 14 on Monterey as well (and it is now out of beta, if that was holding you back). :)

Discussed again on the forum: https://forums.swift.org/t/72375
To have it written down, we've had the following things available over time:

When TSPL was hosted on developer.apple.com, there were separate web versions of the book for beta and prerelease, separate ePUB versions in the Apple Books store for beta and prerelease, and an ePUB version on Swift.org for only the latest.
When TSPL was hosted on Swift.org using its pre-DocC toolchain, there was a single web version for the latest.  There were separate ePUB versions in the Apple Books store for beta and prerelease, and an ePUB version on Swift.org for only the latest.
Currently, with TSPL hosted on Swift.org and built using DocC, there is a single web version for the latest.  We're no longer able to build an ePUB version (see #2).


Fix oversights from 2992

Pull Request Test Coverage Report for Build<PHONE_NUMBER>
Details

0 of 1 (0.0%)  changed or added relevant line in 1 file are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 56.207%

Changes Missing Coverage
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src/SFML/Window/DRM/InputImpl.cpp
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Covered Lines:
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Adds privacy and terms in SettingsCard

Fixes https://github.com/zulip/zulip-mobile/issues/297
Added the terms and privacy policy in settings card.
@borisyankov Review.

@borisyankov  I saw slack's app. These were in the settings screen only.

Ok, then extract this to a LinkButton component. Instead of onPress pass it url.

Hello @saketkumar95, a Zulip maintainer reviewed this pull request over a week ago, but you haven't updated your pull request since. Please take a look at the requested changes and update your pull request accordingly.
Thank you for your valuable contributions to Zulip!

Another PR is merged implementing this. Closing.

Thanks for your contribution.


ask for help

when I train the generator of step 1. I find that the discriminator is powerful .the g_loss will be 1 and the d_loss will be 0. How could I do

Did you observe this behavior running Step 0 and Step 1 out of the box, or did you modify something?

Yeah I implement it in pytorch. Now I can not converge it.  In step 0 ,the accuracy of  pretrained model is 0.87. Is it right？

No, the accuracy of the model trained at Step 0 should be much lower (check the paper - Table 2, first row).


Traceback AttributeError: id

PGSync version: 1.1.7
Postgres version: 9.8
Elasticsearch version: 7.7.1
Redis version: latest
Python version: 3.7
Problem Description:
I have traceback with sync
After I see a queue in Redis, which is full. Sync works but doesn't load rows to elastic.
Error Message (if any):
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]: 2020-08-17 21:18:50.522:ERROR:pgsync.sync: Exception id
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]: Traceback (most recent call last):
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:   File "/usr/local/lib/python3.7/site-packages/sqlalchemy/util/_collections.py", line 210, in __getattr__
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:     return self._data[key]
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]: KeyError: 'id'
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]: During handling of the above exception, another exception occurred:
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]: Traceback (most recent call last):
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:   File "pgsync/sync.py", line 572, in pgsync.sync.Sync._sync
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:   File "pgsync/query_builder.py", line 804, in pgsync.query_builder.QueryBuilder.build_queries
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:   File "pgsync/query_builder.py", line 258, in pgsync.query_builder.QueryBuilder._children
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:   File "/usr/local/lib/python3.7/site-packages/sqlalchemy/util/_collections.py", line 212, in __getattr__
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:     raise AttributeError(key)
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]: AttributeError: id
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]: 2020-08-17 21:18:50.620:ERROR:pgsync.sync: Exception: id
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]: Traceback (most recent call last):
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:   File "/usr/local/lib/python3.7/site-packages/sqlalchemy/util/_collections.py", line 210, in __getattr__
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:     return self._data[key]
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]: KeyError: 'id'
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]: During handling of the above exception, another exception occurred:
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]: Traceback (most recent call last):
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:   File "pgsync/sync.py", line 644, in pgsync.sync.Sync.sync_payloads
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:   File "pgsync/elastichelper.py", line 59, in pgsync.elastichelper.ElasticHelper.bulk
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:   File "/usr/local/lib/python3.7/site-packages/elasticsearch/helpers/actions.py", line 425, in parallel_bulk
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:     actions, chunk_size, max_chunk_bytes, client.transport.serializer
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:   File "/usr/local/lib/python3.7/multiprocessing/pool.py", line 748, in next
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:     raise value
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:   File "/usr/local/lib/python3.7/multiprocessing/pool.py", line 121, in worker
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:     result = (True, func(*args, **kwds))
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:   File "/usr/local/lib/python3.7/multiprocessing/pool.py", line 140, in _helper_reraises_exception
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:     raise ex
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:   File "/usr/local/lib/python3.7/multiprocessing/pool.py", line 292, in _guarded_task_generation
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:     for i, x in enumerate(iterable):
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:   File "/usr/local/lib/python3.7/site-packages/elasticsearch/helpers/actions.py", line 128, in _chunk_actions
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:     for action, data in actions:
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:   File "pgsync/sync.py", line 575, in _sync
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:   File "pgsync/sync.py", line 572, in pgsync.sync.Sync._sync
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:   File "pgsync/query_builder.py", line 804, in pgsync.query_builder.QueryBuilder.build_queries
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:   File "pgsync/query_builder.py", line 258, in pgsync.query_builder.QueryBuilder._children
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:   File "/usr/local/lib/python3.7/site-packages/sqlalchemy/util/_collections.py", line 212, in __getattr__
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]:     raise AttributeError(key)
Aug 18 00:18:50 elastics01 sync_product_shop/product_shop[19354]: AttributeError: id

I've seen this as well, though I had not raised the issue yet.
@masterlexa  can you provide some or all of your DB schema and pg-sync schema?

I'm unable to reproduce this. Can you please share your DB and pgsync schema, please.
@masterlexa

Here's a portion of my code:
SQLAlchemy table:
surveys = Table(
    'surveys',
    metadata,
    Column('id', Integer, primary_key=True),
   # ...
}

sources = Table(
    'sources',
    metadata,
    Column('id', Integer, primary_key=True),
    Column('surveyid', Integer, ForeignKey('surveys.id')),
   # ...
)

pg-sync schema.json:
[
    {
        "database": "mydb",
        "index": "surveys",
        "nodes": [
            {
                "table": "surveys",
                "schema": "public",
                "columns": [
                    "id"
                ],
                "children": [
                    {
                        "table": "sources",
                        "schema": "public",
                        "columns": [
                            "id",
                            "surveyid"

                        ],
                        "relationship": {
                            "variant": "object",
                            "type": "one_to_many"
                        }
                    }
                ]

SQL query (trimmed for columns):
pgsync_1              | SELECT JSON_BUILD_ARRAY(anon_1._keys) AS "JSON_BUILD_ARRAY_1",
pgsync_1              |        JSON_BUILD_OBJECT('id', surveys_1.id, 'sources', anon_1.sources) AS "JSON_BUILD_OBJECT_1",
pgsync_1              |        surveys_1.id
pgsync_1              | FROM public.surveys AS surveys_1
pgsync_1              | LEFT OUTER JOIN
pgsync_1              |   (SELECT CAST(JSON_BUILD_OBJECT('sources', JSON_AGG(JSON_BUILD_OBJECT('id', JSON_BUILD_ARRAY(sources_1.id)))) AS JSONB) AS _keys,
pgsync_1              |           JSON_AGG(JSON_BUILD_OBJECT('id', sources_1.id, 'surveyid', sources_1.surveyid)) AS sources,
pgsync_1              |           sources_1.surveyid AS surveyid
pgsync_1              |    FROM public.sources AS sources_1
pgsync_1              |    GROUP BY sources_1.surveyid) AS anon_1 ON anon_1.surveyid = surveys_1.id
pgsync_1              | WHERE surveys_1.id = 202

Exception traceback:
pgsync_1              | 2020-08-19 00:11:26.308:ERROR:pgsync.sync: Exception id
pgsync_1              | Traceback (most recent call last):
pgsync_1              |   File "/usr/local/lib/python3.7/site-packages/sqlalchemy/util/_collections.py", line 210, in __getattr__
pgsync_1              |     return self._data[key]
pgsync_1              | KeyError: 'id'
pgsync_1              |
pgsync_1              | During handling of the above exception, another exception occurred:
pgsync_1              |
pgsync_1              | Traceback (most recent call last):
pgsync_1              |   File "pgsync/sync.py", line 572, in pgsync.sync.Sync._sync
pgsync_1              |   File "pgsync/query_builder.py", line 746, in pgsync.query_builder.QueryBuilder.build_queries
pgsync_1              |   File "pgsync/query_builder.py", line 252, in pgsync.query_builder.QueryBuilder._children
pgsync_1              |   File "/usr/local/lib/python3.7/site-packages/sqlalchemy/util/_collections.py", line 212, in __getattr__
pgsync_1              |     raise AttributeError(key)
pgsync_1              | AttributeError: id
pgsync_1              | 2020-08-19 00:11:26.407:ERROR:pgsync.sync: Exception: id
pgsync_1              | Traceback (most recent call last):
pgsync_1              |   File "/usr/local/lib/python3.7/site-packages/sqlalchemy/util/_collections.py", line 210, in __getattr__
pgsync_1              |     return self._data[key]
pgsync_1              | KeyError: 'id'
pgsync_1              |
pgsync_1              | During handling of the above exception, another exception occurred:
pgsync_1              |
pgsync_1              | Traceback (most recent call last):
pgsync_1              |   File "pgsync/sync.py", line 644, in pgsync.sync.Sync.sync_payloads
pgsync_1              |   File "pgsync/elastichelper.py", line 59, in pgsync.elastichelper.ElasticHelper.bulk
pgsync_1              |   File "/usr/local/lib/python3.7/site-packages/elasticsearch/helpers/actions.py", line 425, in parallel_bulk
pgsync_1              |     actions, chunk_size, max_chunk_bytes, client.transport.serializer
pgsync_1              |   File "/usr/local/lib/python3.7/multiprocessing/pool.py", line 748, in next
pgsync_1              |     raise value
pgsync_1              |   File "/usr/local/lib/python3.7/multiprocessing/pool.py", line 121, in worker
pgsync_1              |     result = (True, func(*args, **kwds))
pgsync_1              |   File "/usr/local/lib/python3.7/multiprocessing/pool.py", line 140, in _helper_reraises_exception
pgsync_1              |     raise ex
pgsync_1              |   File "/usr/local/lib/python3.7/multiprocessing/pool.py", line 292, in _guarded_task_generation
pgsync_1              |     for i, x in enumerate(iterable):
pgsync_1              |   File "/usr/local/lib/python3.7/site-packages/elasticsearch/helpers/actions.py", line 128, in _chunk_actions
pgsync_1              |     for action, data in actions:
pgsync_1              |   File "pgsync/sync.py", line 575, in _sync
pgsync_1              |   File "pgsync/sync.py", line 572, in pgsync.sync.Sync._sync
pgsync_1              |   File "pgsync/query_builder.py", line 746, in pgsync.query_builder.QueryBuilder.build_queries
pgsync_1              |   File "pgsync/query_builder.py", line 252, in pgsync.query_builder.QueryBuilder._children
pgsync_1              |   File "/usr/local/lib/python3.7/site-packages/sqlalchemy/util/_collections.py", line 212, in __getattr__
pgsync_1              |     raise AttributeError(key)
pgsync_1              | AttributeError: id

Hope that's helpful @toluaina  @masterlexa

I cant share my prod DB here, sorry, but I see the same trouble @sivy.

I see for example with the scheme
{
    "database": "my_db",
    "index": "company",
    "nodes": [
      {
        "table": "company",
        "schema": "public",
        "columns": [
          "company_name",
          "disabled",
          "image_logo",
          "image_preview",
          "inn",
          "url"
        ],
        "children": [
                    {
                        "table": "rating",
                        "schema": "public",
                        "columns": [
                          "total",
                          "comment_service",
                          "comment_actual_price",
                          "comment_actual_avail",
                          "comment_delivery",
                          "reliability"
                        ],
                        "relationship": {
                            "variant": "object",
                            "type": "one_to_one"
                        }
                    }
          ]
      }
    ]
  }

and
{
    "database": "my_db",
    "index": "product_shop",
    "nodes": [
      {
        "table": "product_shop",
        "schema": "public",
        "columns": [
          "source_id",
          "company_id",
          "name",
        ],
                "children": [{
                        "table": "offer_source",
                        "schema": "public",
                        "columns": [],
                        "relationship": {
                            "variant": "object",
                            "type": "one_to_one"
                        },
                        "children": [
                          {
                            "table": "discount",
                            "schema": "public",
                            "columns": [
                              "rate",
                              "start_at",
                              "stop_at",
                              "is_active",
                              "applicable"
                            ],
                            "relationship": {
                                "variant": "scalar",
                                "type": "one_to_one"
                            }
                          }
                        ]
        }
        ]
      }
    ]
  }

A note that I am seeing that this exception causes the data to not be indexes in Elasticsearch; After removing the child relationship the data is being indexed properly.

This should be resolved in pgsync 1.1.8. @sivy @masterlexa
I intend to expedite making the code base available

I think this issue contuniue


Make buildLocalCabal available in  haskell-ng

My apologies if it's already there and I failed to find it. I use pkgs.haskellPackages.buildLocalCabal to build a local package. It has been working fine until now, I want to use timeit, which is only available in haskell-ng. Is it possible to add buildLocalCabal to pkgs.haskellngPackages? Or is there an alternative?

I've never used buildLocalCabal nor am I entire sure of its purpose. What exactly does that function do?

From what I have seen, buildLocalCabal takes a path and a name. It then runs cabal2nix on that path, then makes a derivation out of the output, giving it the specified name. It seems to be a nice way to build stuff that I don't intend to put in nixpkgs.
Is there a better way? I'm OK with running cabal2nix and storing the output myself, but I'm not OK with having to explicitly pass build dependencies to callPackage. Would you do it differently?

Running cabal2nix with the --shell argument seems superior, IMHO. The output will be usable with nix-shell, and it's trivial to edit so that it works with nix-build, too.

Indeed, I use cabal2nix --shell and that works really well for development. However, having to modify a generated file to build (and deploy) your project doesn't sound right.
Also I notice that you didn't mention cabal2nix without --shell, does that mean it's not intended to work with the new Haskell infrastructure?

Indeed, I use cabal2nix --shell and that works really well for development. However, having to modify a generated file to build (and deploy) your project doesn't sound right.

IMHO, editing out the .env bit at the end of the generated file is not a particularly big problem. Arguably, it would be nice if cabal2nix would have a third mode to generate that kind of output directly. I just never bothered to make the necessary changes.

Also I notice that you didn't mention cabal2nix without --shell, does that mean it's not intended to
work with the new Haskell infrastructure?

cabal2nix works fine with the new infrastructure.

Uhm, then what's the intended way to use cabal2nix (without --shell) output with haskell-ng?

I'm not sure whether I understand your question. When you run cabal2nix, does it not produce valid output? What is the problem you're experiencing?

I think I confused myself too. I thought that it didn't work while it actually works. Below is the scenario.
Let's say I have a little project with this structure:

foo

Main.hs
foo.cabal

Let's assume that this works, and cabal build produces an executable foo. Now, to deploy this little project as a service:

In the shell: cabal2nix foo > foo/default.nix
In /etc/nixos/configuration.nix:

foo = pkgs.haskellngPackages.callPackage /path/to/foo/default.nix {};
systemd.service.foo.execStart = "${foo}/bin/foo"; # or something similar

For some reason I was under the impression that the callPackage didn't work, that it wanted me to pass all of foo's dependencies instead of an empty set. Apparently I made some other mistake. Everything is fine now. Thanks for staying with me @peti :)

Ah, okay. I'm glad everything turned out alright! :smile:


Extend Tr interface in sqlx/contract.go by missing methods

Thank you for the module, I use it in my Graduate Project with sqlx, and it's really helpful for me
I noticed that the trm/sqlx.Tr lacks several methods that exist in sqlx.Tx and sqlx.DB and decided to add them

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 94.015%

Totals

Change from base Build<PHONE_NUMBER>:
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Covered Lines:
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Allow admins to choose resource tag colors 🎨

More context coming soon...

This is likely a v3 feature, closing for now...


Support for set model directories

generateSwagger {
    platform.set("kotlin")
    packageName.set("com.yelp.codegen.samples")
    inputFile.set(file("./sample_specs.json"))
    outputDir.set(project.layout.buildDirectory.dir("./src/main/java/"))
}

we need something like:
generateSwagger {
    platform.set("kotlin")
    packageName.set("com.yelp.codegen.samples")
    inputFile.set(file("./sample_specs.json"))
    outputDir.set(project.layout.buildDirectory.dir("./src/main/java/"))

    requestModelsDirectory.set("models/requests")  -> default is models
    responseModelsDirectory.set("models/responses") -> default is models
}

Can you help me in that?

Related to https://github.com/Yelp/swagger-gradle-codegen/issues/146#issuecomment-759987061
I'm afraid that's not possible as models can be easily shared between responses and requests, so deciding where to place an module would be ambiguous.

Related to https://github.com/Yelp/swagger-gradle-codegen/issues/146#issuecomment-759987061
I'm afraid that's not possible as models can be easily shared between responses and requests, so deciding where to place an module would be ambiguous.

Thanks

Thanks


Handle CR as line separator

Some odd platforms (MacOS) use CR as line separator character and it is not handled correctly by ged4py, need a fix for that.

Fixed by #16


Restore math fidelity default to HiFi2 for MatmulDefaultProgramConfig

HiFi2 is most we need for bfloat16
Hifi3/hifi4 don't improve accuracy of with bfloat16 (only for fp16 which we don't use atm)
Let's set hifi2 as default

Passing pipelines (with HiFi4):

post-commit: https://github.com/tenstorrent/tt-metal/actions/runs/8991365776
post-commit models: https://github.com/tenstorrent/tt-metal/actions/runs/8991369792
device perf: https://github.com/tenstorrent/tt-metal/actions/runs/8991368620

Passing nightly fast dispatch: https://github.com/tenstorrent/tt-metal/actions/runs/8992407556


bind async property

What problem does this feature solve?
Can vuejs support binding of asynchronous properties?
What does the proposed API look like?
var data = {}
Object.defineProperty(data, 'asyncProperty', {
async get() {
// async network or database query
return true;
}
});

Duplicate of https://github.com/vuejs/vue/issues/7520


formatting jumps to top of the page

Basically:  if I make an edit, save the file, then want to undo that edit, I have to press u twice because the first press simply jumps me back to the top of the page.
Using vim version: VIM - Vi IMproved 8.0 (2016 Sep 12, compiled Oct  5 2017 19:19:02)
On commit: f68c2cc9b61728e4019bc2ce9a481c91b5d2de79
From: https://github.com/Chiel92/vim-autoformat/issues/56#issuecomment-337235379

So the formatting doesn't actually jump to the top, but undoing does?

correct, yeah. formatting stays where it is but the undo button is messed up.

This behaviour has always been in vim-autoformat, and I'm not sure yet how to fix it.

@ericlagergren I think the mechanism of vim-autoformat is generating a temp file with linter and replace the original file's all content with it. So in undo's vision, you replace all the file content with another, and this operation leads to jumping to the top. That's my thought of explanation to your problem.
So it's basically a mechanical problem, not a bug.

@dc3671 in case of eslint (and few others) you are correct about the temp file, but for the vast majority of the formatter vim-autoformat read from the stdin.
Still, that means replacing the entire buffer contents nonetheless.

Duplicate of https://github.com/Chiel92/vim-autoformat/issues/131


remove usage of non-standard string method

What is this PR for?
Recreating #1701 that was lost in refactoring.
This PR removes a non-standard string prototype method contains that can cause potential bugs in the future maintenance.
What type of PR is it?
Bug Fix
Todos

[x] - remove usage of non-standard string method contains in favor of standard indexOf

How should this be tested?
Download as csv / tsv (graph view) should work as expected

Tested it and works as expected.
But CI is fail. Could you check CI again?

I've retriggered CI a few times. Current error is
Failed tests:

  NotebookTest.testAbortParagraphStatusOnInterpreterRestart:760 expected:<ABORT> but was:<RUNNING>

obviously not related to the change. Can we ignore it and merge anyway?

LGTM and merge to master if there're no further discussions.


Simply doing a list of containers

Below are my code:
require('dotenv').config();
var ObjectStorage = require('bluemix-objectstorage').ObjectStorage;
var credentials = {
projectId: process.env.PROJECT_ID,
userId: process.env.USER_ID,
password: process.env.PASSWORD,
region: ObjectStorage.Region.DALLAS
};
var objStorage = new ObjectStorage(credentials);
objStorage.listContainers()
.then(function(containerList) {
console.log(containerList)
// containerList - an array of ObjectStorageContainers
// containerList may be empty
})
.catch(function(err) {
console.log(err);
// AuthTokenError if there was a problem refreshing authentication token
// ServerError if any unexpected status codes were returned from the request
});
I got the following error, originating from your source code.
/home/ubuntu/workspace/swift_storage/node_modules/bluemix-objectstorage/lib/HttpClient.js:51
this.authToken.expiration = body.token.expires_at;

@enkidoo my apologies for not responding. i wasn't being notified of activity. are you still having an issue here?

@abaruni @enkidoo Iam facing the same issue..Can you please let me know how to resolve this


Hydration error with Suspense > Outlet and other component outside of

Hi!
I think I found another hydration bug a bit similar to https://github.com/leptos-rs/leptos/issues/1863. This time the hydration error appears when a Suspense is outside <Routes><Routes/>.
Leptos Dependencies
Originally discovered with
leptos = { git = "https://github.com/leptos-rs/leptos.git", rev = "a3af4eb8fe09af1d7d538a660094940a17ff2285", features = ["nightly"] }
leptos_axum = { git = "https://github.com/leptos-rs/leptos.git", rev = "a3af4eb8fe09af1d7d538a660094940a17ff2285", optional = true }
leptos_meta = { git = "https://github.com/leptos-rs/leptos.git", rev = "a3af4eb8fe09af1d7d538a660094940a17ff2285", features = ["nightly"] }
leptos_router = { git = "https://github.com/leptos-rs/leptos.git", rev = "a3af4eb8fe09af1d7d538a660094940a17ff2285", features = ["nightly"] }

And then reproduced with rev = "0d6ddfb71e37a08548d938972142dbc39a0632f8"". Interestingly it doesn't occur with version = "0.5.1".
To Reproduce
use leptos::*;
use leptos_router::*;

#[server]
pub async fn get_user() -> Result<(), ServerFnError> {
    Ok(())
}

#[server]
pub async fn data() -> Result<(), ServerFnError> {
    Ok(())
}

#[component]
pub fn App() -> impl IntoView {
    view! {
        <Router>

                        <Routes>
                            <Route path="" view=LoginGuard>
                                <Route path="" view=Child/>
                            </Route>
                        </Routes>

                    //

                        <Drawer/>
                    //

                            <button on:click=move |_| leptos::logging::log!("Did I hydrate?")>"Click"</button>

        </Router>
    }
}

#[component]
pub fn Drawer() -> impl IntoView {
    let nested_data = Resource::once(data);

    view! {
        "Label"
        <Suspense>

{
                move || {
                    format!("{:?}", nested_data.get())
                }
            }

        </Suspense>
    }
}

#[component]
fn LoginGuard() -> impl IntoView {
    let guard_data = Resource::once(get_user);
    view! {
        <Suspense>
            {move || guard_data.and_then(|_| view! { <Outlet/> })}
        </Suspense>
    }
}

#[component]
pub fn Child() -> impl IntoView {
    //let nested_data = Resource::once(data);
    view! {

            "Test"

        /*<Suspense>

{
                move || {
                    format!("{:?}", nested_data.get())
                }
            }

        </Suspense>*/
    }
}

Additional context
I've been trying to identify exactly the setup causing the issue but I'm still not completely sure. In the example from the reproduce section, it looks like uncommenting the

 around the <Drawer/> component removed the hydration error, but then uncommenting the <Suspense> in <Child/> resulted again in an hydration error. This might be two different issues tho.

Makes sense, my fix for they broke this. Will look at a solution later.


Dial down expectations of things working before adding API routes

This 100% makes sense — that screenshot here is more confusing than anything. Removed, and it reads much better. Thank you!


Most of the links at the dockerfile page don't work correctly

Problem description
On the Dockerfile page, most links redirect to the getting-started page instead their intended destination.
Problem location

I saw a problem on the following URL: https://docs.docker.com/engine/reference/builder/

Closing this ticket due to its age, and the impending refactor. If you think this is in error, feel free to reopen. Thanks!


How can I read xlsx from S3 ?

Hi, I've using XToolset and love it.
I'my trying to read xlsx file from S3 not from file system.
Is it avilable to read xlsx from S3 ?
I've not found any code reading from S3 in ImporterFactory .
Should I contrinute for it?

Hi @love8587 ! Thank you for nice words ;)
Backend
As far as I know, AWS provides NodeJS client which provides getting data from S3 as a Buffer.
const buildImporterFromBuffer = (buffer) => {
  // 1. Create ExcelJS workbook instance
  const wb = new Workbook();
  // 2. Read the data from the Buffer
  await wb.xlsx.load(buffer);

  // 3. Build and return Importer
  return new Importer(wb);
}

Having this function, you are able to use it with AWS Node.js API
(code based on https://stackoverflow.com/a/16903730/4747028 )
var AWS = require('aws-sdk');
AWS.config.update(
  {
    accessKeyId: ".. your key ..",
    secretAccessKey: ".. your secret key ..",
  }
);
var s3 = new AWS.S3();
s3.getObject(
  { Bucket: "my-bucket", Key: "my-picture.jpg" },
  function (error, data) {
    if (error != null) {
      console.error("Failed to retrieve an object: " + error);
    } else {
      console.log("Loaded " + data.ContentLength + " bytes");

     // 4. Build importer
     const importer = buildImporterFromBuffer(data.Body)

     // 5. And finally, import what you need. ;-) Good luck.

    }
  }
);

Frontend
However, please keep in mind. That using accessKeyId, and secretAccessKey on the frontend is highly unsecured. 🙈 🙉 🙊
For frontend usages, I rather recommend using AWS Cloud Front which able us to publish S3 data as public resources, however, it is also an additional cost. Or write a microservice that will manage a connection with S3 and serve this file.
Additionally

We have an issue with increasing the functionality of ImporterFactory https://github.com/Siemienik/XToolset/issues/52 - any suggestions are welcome.

I would also invite you to our Gitter channel where it is able to chat in realtime, ask and answer. Additionally, this is a place where I share updates about project progress.

I hope that my answer was really helpful 😄  if yes, please left a star for this project and share XToolset with your friends and colleagues what really help promote this project, and what gets me a lot of motivation to do XToolset best.

Bonus: with a Promise support:
(I really like this one)
const importer = await s3.getObject(params)
  .promise()
  .then((data) => buildImporterFromBuffer(data.Body) )
  .catch((error) => {console.error("Failed to retrieve an object: " + error);} );

(Based on AWS official API Reference )