id stringlengths 4 10 | text stringlengths 4 2.14M | source stringclasses 2
values | created timestamp[s]date 2001-05-16 21:05:09 2025-01-01 03:38:30 | added stringdate 2025-04-01 04:05:38 2025-04-01 07:14:06 | metadata dict |
|---|---|---|---|---|---|
1366402594 | Emit warning for deprecated fields in v1beta1
Changes
[WIP]This commit adds warnings when a user creates a CRD with a deprecated field.
Fixes: #5373
/kind feature
Submitter Checklist
As the author of this PR, please check off the items in this checklist:
[x] Has Docs included if any changes are user facing
[x] Has Tests included if any functionality added or changed
[x] Follows the commit message standard
[x] Meets the Tekton contributor standards (including
functionality, content, code)
[x] Has a kind label. You can add one by adding a comment on this PR that contains /kind <type>. Valid types are bug, cleanup, design, documentation, feature, flake, misc, question, tep
[x] Release notes block below has been updated with any user facing changes (API changes, bug fixes, changes requiring upgrade notices or deprecation warnings)
[x] Release notes contains the string "action required" if the change requires additional action from users switching to the new release
Release Notes
NONE
/assign @lbernick
| gharchive/pull-request | 2022-09-08T14:02:50 | 2025-04-01T06:45:57.260272 | {
"authors": [
"JeromeJu"
],
"repo": "tektoncd/pipeline",
"url": "https://github.com/tektoncd/pipeline/pull/5457",
"license": "apache-2.0",
"license_type": "permissive",
"license_source": "bigquery"
} |
439176211 | Fix TestStorageBucketPipelineRun to actually, y'know, run.
Changes
It was using the UpdateConfigMap function from Knative test, but
that assumes that configMap.Data is already a non-nil map. Since in
a normal test scenario with the default config-artifact-bucket.yaml
in config/, the relevant configMap.Data is in fact nil, the test
as written will just panic all the time.
Mind you, the test will still fail, but that'll be due to #819.
We haven't caught this, or #819, due to not running the bucket-related
tests in CI!
/assign @bobcatfish
/assign @vdemeester
/assign @dlorenc
/assign @dwnusbaum
Submitter Checklist
These are the criteria that every PR should meet, please check them off as you
review them:
[x] Includes tests (if functionality changed/added)
[x] Includes docs (if user facing)
[x] Commit messages follow commit message best practices
See the contribution guide
for more details.
Release Notes
n/a
@abayer just checking my understanding: the test still won't actually run in CI, but I assume you verified this fix manually?
Yup, in order to reproduce #819.
| gharchive/pull-request | 2019-05-01T14:06:45 | 2025-04-01T06:45:57.265851 | {
"authors": [
"abayer",
"bobcatfish"
],
"repo": "tektoncd/pipeline",
"url": "https://github.com/tektoncd/pipeline/pull/820",
"license": "apache-2.0",
"license_type": "permissive",
"license_source": "bigquery"
} |
1670957368 | fully functional send page
Fixes #223
also Fixes #174 presented in this draft PR
also Fixes #253 solved in this PR currently merged
Description
In order to fulfill the requirement of having a fully functional "send page", three largely independent parts needed to be completed:
(#253) The implementation of new notification banners for success and error messages.
(#174) The visual design of the send page, including the HTML and CSS.
(#223) Adding support for token sending in the new library, which can be further divided into three parts:
Retrieving balances for each ERC20 or native token.
Obtaining the gas price and estimating the cost of execution.
Actual sending of the ERC20 or native token.
Test scenarios
goto this link
login on EVM using an account with at least 1 liquid TLOS and a positive balance of any other ERC20 token
goto Send Page
you should see the send tokens form
TLOS should be selected by default
the estimated fee should be low but not zero (in TLOS)
view token link should not be visible
the whole balance should be set in the amount's input.
the input should show the amount followed by a semi-transparent symbol and the end
the symbol should not affect the input content and should not be editable or even selected
the available amount should show the total token balance
the fiat balance should be shown in the footer of the input field
clean the amount field and press the available amount link
the whole balance should be set in the amount's input.
click the fiat balance
the footer balance and the input balance should be interchanged
the available amount should show the total fiat balance.
the input should show the USD symbol and then the input field amount (not editable or selectable)
change the token
the view token contract link should be shown in the token selector footer
the available balance should show the total balance for the new token selected
if no price is available for that token, then the footers for the amount input are not shown.
the estimated fee should be higher than the system token sending gas
prepare an invalid form (no address, not enough balance, or non-positive amount)
the send button should be disabled
prepare a valid form using any token and press send
The Metamask should present the sending confirmation with the correct information, confirm!!
If no errors a success notification should be shown for at least 5 sec
if you press the see transaction link you should be redirected to Teloscan to see the transaction
if an error occurs you should see an error notification with the error info.
Checklist:
[x] I have performed a self-review of my own code
[x] I have commented my code, particularly in hard-to-understand areas
[x] I have cleaned up the code in the areas my change touches
[x] My changes generate no new warnings
[x] Any dependent changes have been merged and published in downstream modules
[x] I have checked my code and corrected any misspellings
[x] I have removed any unnecessary console messages
[x] I have included all english text to the translation file
[x] I have created a new issue with the required translations for the currently supported languages
[ ] I have added appropriate test coverage
symbol is being shown twice
fiat value should be 2 decimal places
there should be an error when the user has entered too many decimal places for the token i think. in this case pressing send doesnt work, but there is no feedback to the user that it's because there are too many decimal places
at mobile the layout breaks. lets move the token picker to a new line on on XS devices. this will mean the available text label will need to be moved in the markup too it seems
also there should be some validation on the address field. you can use this regex to check if the input has a valid ethereum address:
const addressRegex = /^0x\d{40}$/;
const isValid = addressRegex.test(address);
if the user does not enter a valid regex, there should be some error text in my opinion. you may also want to add placeholder text like
:placeholder=`e.g. 0x${'0'.repeat(40)}`
sending fails if i try to send STLOS :(
there is also a huge error message that takes up the whole screen (cant get a picture because it goes too fast), but basically it fails because it cannot estimate gas. error starts with:
nnot estimate gas; transaction may fail or may require manual gas limit [ See: https://links.ethers.org/v5-errors-UNPREDICTABLE_GAS_LIMIT ]
i think maybe we don't want to show the user the actual error message, maybe either show something generic and they can check the console if they want, or cut off the message after a certain number of characters
I am still seeing an error when trying to send STLOS. printing the entire error leads to this:
maybe we can parse the error message to get an error code, then display a message like "if error code = -32603, error mesage = "failed to estimate gas"'
note: this error is actually handled in teloscan, it may help you debug:
https://github.com/telosnetwork/teloscan/blob/dev/src/components/LoginModal.vue#L278
@Viterbo double 'back' button
| gharchive/pull-request | 2023-04-17T11:22:09 | 2025-04-01T06:45:57.411116 | {
"authors": [
"EJSG",
"Viterbo",
"donnyquixotic"
],
"repo": "telosnetwork/telos-wallet",
"url": "https://github.com/telosnetwork/telos-wallet/pull/257",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
1864045457 | 🛑 Secret Site2 is down
In 5c0479f, Secret Site2 ($SECRET_SITE_2) was down:
HTTP code: 404
Response time: 80 ms
Resolved: Secret Site2 is back up in 4d4ef0f after 59 days, 14 hours, 42 minutes.
| gharchive/issue | 2023-08-23T21:33:54 | 2025-04-01T06:45:57.426952 | {
"authors": [
"templain"
],
"repo": "templain/mywatcher",
"url": "https://github.com/templain/mywatcher/issues/1327",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
2050064918 | 🛑 QRCODE VIEWER is down
In b1b8d9a, QRCODE VIEWER (https://qrcode-viewer.onrender.com/qrcode-viewer/) was down:
HTTP code: 0
Response time: 0 ms
Resolved: QRCODE VIEWER is back up in 1681703 after 9 minutes.
| gharchive/issue | 2023-12-20T08:16:23 | 2025-04-01T06:45:57.429456 | {
"authors": [
"templain"
],
"repo": "templain/mywatcher",
"url": "https://github.com/templain/mywatcher/issues/3024",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
1825998752 | 🛑 Secret Site2 is down
In 84eec6c, Secret Site2 ($SECRET_SITE_2) was down:
HTTP code: 404
Response time: 84 ms
Resolved: Secret Site2 is back up in d60ca94.
| gharchive/issue | 2023-07-28T08:50:07 | 2025-04-01T06:45:57.431612 | {
"authors": [
"templain"
],
"repo": "templain/mywatcher",
"url": "https://github.com/templain/mywatcher/issues/645",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
300165685 | 部分安卓手机uploadFile方法直接返回{"readyState":0,"responseText":"","status":0,"statusText":"error"}
部分安卓手机uploadFile方法直接返回{"readyState":0,"responseText":"","status":0,"statusText":"error"}，
uploading... curr progress is NaN
如果是部分机型出现的错误，可以尝试配置 CORS AllowHeaders: *
如果还是不行，提供一下请求返回的 RequestId
AllowHeaders已配置为*，目前只发现oppo r9跟锤子有问题，在successCallback返回的只有{"readyState":0,"responseText":"","status":0,"statusText":"error"}
返回的 header 里有个 x-cos-request-id 提供一下？
{
"code": -121,
"message": "ERROR_CMD_CORSRULE_NOT_MATCH",
"request_id": "NWE5M2ViODhfZDgyNzVkNjRfZDk1OF8yOTA5OTc="
}
ERROR_CMD_CORSRULE_NOT_MATCH 这个就是 CORS 配置有误
请检查请求参数是不是搞错了，导致请求到别的 bucket 去，然后检查你 bucket 的 CORS 是否正确。
如果还不行发一下你的 appid 和 bucket 看看
这个是公用的方法，其他机型都能正常上传，只有oppo r9 跟锤子会报这个错误，bucket确认是正确的
一般这个表现是因为某些浏览器请求的时候会带有特定的 Access-Control-Request-Headers: origin,accept,content-type
你再次确认下 CORS 配置：AllowHeaders: *
如果还不行，请贴上 appid 和 bucket 我检查下，或者加我 QQ:459452372
抱歉，刚去检查了下配置，AllowHeaders没有配上导致的，耽误您时间了，实在抱歉，现在好了
ok
| gharchive/issue | 2018-02-26T09:35:05 | 2025-04-01T06:45:57.486373 | {
"authors": [
"carsonxu",
"warrior-bing"
],
"repo": "tencentyun/cos-js-sdk-v4",
"url": "https://github.com/tencentyun/cos-js-sdk-v4/issues/30",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
1141512594 | Do we support tf.nn.bidirectional_dynamic_rnn ?
Hi:
I only see CudnnRNN ,the project has not testcase for it,I not know if we support tf.nn.bidirectional_dynamic_rnn or normal simple rnn?
thank you
I don't think we do support out-of-the-box RNN ops, most in TensorFlow has been also deprecated in favor to Keras RNN cells and layers, so I guess this support will also as we port the Keras API into our framework.
I don't think we do support out-of-the-box RNN ops, most in TensorFlow has been also deprecated in favor to Keras RNN cells and layers, so I guess this support will also as we port the Keras API into our framework.
wow, when this framework will wrapper keras api?
This is a own project on its own, leaded by @JimClarke5 , a lot of work as already been done by porting the optimizers, metrics, losses, regularizers and activations of Keras to Java. The plumbing for layers and models are coming on soon and from there it would be interesting to tackle the support for RNNs.
If you are interested to know more about it @mullerhai and if you can, I suggest that you join the next SIG meeting where we discuss various topics related to TF Java.
| gharchive/issue | 2022-02-17T15:45:29 | 2025-04-01T06:45:57.603213 | {
"authors": [
"karllessard",
"mullerhai"
],
"repo": "tensorflow/java",
"url": "https://github.com/tensorflow/java/issues/421",
"license": "apache-2.0",
"license_type": "permissive",
"license_source": "bigquery"
} |
352573335 | padding='causal' is in document but cannot be used with tf.keras.layers.Conv1D
System information
Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
Yes
OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
Linux Ubuntu 16.04
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
TensorFlow installed from (source or binary):
I use docker tensorflow/tensorflow:1.10.0-devel-gpu-py3
TensorFlow version (use command below):
1.10.0
Python version:
Python 3.5.2
Bazel version (if compiling from source):
GCC/Compiler version (if compiling from source):
CUDA/cuDNN version:
GPU model and memory:
Exact command to reproduce:
see my gist below
Describe the problem
In the document, we can use causal option for padding. But causal option causes error in r1.10. We should remove causal from the document or support causal. There are related issues, #14933, #15000 and #15037. But all of them are closed. I think they should be reopen.
Source code / logs
https://gist.github.com/dhgrs/ca552f5804ddfb4db9669f9189eba76f
Nagging Assignee @drpngx: It has been 14 days with no activity and this issue has an assignee. Please update the label and/or status accordingly.
Nagging Assignee @drpngx: It has been 29 days with no activity and this issue has an assignee. Please update the label and/or status accordingly.
This is fixed now in the latest nightly version, please pip install tf-nightly (or pip install tf-nightly-gpu for GPU support)
| gharchive/issue | 2018-08-21T14:39:34 | 2025-04-01T06:45:57.711287 | {
"authors": [
"dhgrs",
"omalleyt12",
"tensorflowbutler"
],
"repo": "tensorflow/tensorflow",
"url": "https://github.com/tensorflow/tensorflow/issues/21763",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
384407988 | Save/Load problem with keras.layers.ReLU
Running this example
x = tf.keras.layers.Input([1])
y = tf.keras.layers.ReLU()(x)
mdl = tf.keras.models.Model(x, y)
tf.keras.models.save_model(mdl, "./keras_model_tmp.hdf5", overwrite=True)
tf.keras.models.load_model("./keras_model_tmp.hdf5")
returns trackback
/data/virtualenv/venv2/lib/python2.7/site-packages/tensorflow/python/keras/engine/saving.pyc in load_model(filepath, custom_objects, compile)
228 raise ValueError('No model found in config file.')
229 model_config = json.loads(model_config.decode('utf-8'))
--> 230 model = model_from_config(model_config, custom_objects=custom_objects)
231
232 # set weights
/data/virtualenv/venv2/lib/python2.7/site-packages/tensorflow/python/keras/engine/saving.pyc in model_from_config(config, custom_objects)
308 '`Sequential.from_config(config)`?')
309 from tensorflow.python.keras.layers import deserialize # pylint: disable=g-import-not-at-top
--> 310 return deserialize(config, custom_objects=custom_objects)
311
312
/data/virtualenv/venv2/lib/python2.7/site-packages/tensorflow/python/keras/layers/serialization.pyc in deserialize(config, custom_objects)
62 module_objects=globs,
63 custom_objects=custom_objects,
---> 64 printable_module_name='layer')
/data/virtualenv/venv2/lib/python2.7/site-packages/tensorflow/python/keras/utils/generic_utils.pyc in deserialize_keras_object(identifier, module_objects, custom_objects, printable_module_name)
171 custom_objects=dict(
172 list(_GLOBAL_CUSTOM_OBJECTS.items()) +
--> 173 list(custom_objects.items())))
174 with CustomObjectScope(custom_objects):
175 return cls.from_config(config['config'])
/data/virtualenv/venv2/lib/python2.7/site-packages/tensorflow/python/keras/engine/network.pyc in from_config(cls, config, custom_objects)
1291 for layer_data in config['layers']:
1292 process_layer(layer_data)
-> 1293 # Then we process nodes in order of layer depth.
1294 # Nodes that cannot yet be processed (if the inbound node
1295 # does not yet exist) are re-enqueued, and the process
/data/virtualenv/venv2/lib/python2.7/site-packages/tensorflow/python/keras/engine/network.pyc in process_layer(layer_data)
1276 from tensorflow.python.keras.layers import deserialize as deserialize_layer # pylint: disable=g-import-not-at-top
1277
-> 1278 layer = deserialize_layer(layer_data, custom_objects=custom_objects)
1279 created_layers[layer_name] = layer
1280
/data/virtualenv/venv2/lib/python2.7/site-packages/tensorflow/python/keras/layers/serialization.pyc in deserialize(config, custom_objects)
62 module_objects=globs,
63 custom_objects=custom_objects,
---> 64 printable_module_name='layer')
/data/virtualenv/venv2/lib/python2.7/site-packages/tensorflow/python/keras/utils/generic_utils.pyc in deserialize_keras_object(identifier, module_objects, custom_objects, printable_module_name)
173 list(custom_objects.items())))
174 with CustomObjectScope(custom_objects):
--> 175 return cls.from_config(config['config'])
176 else:
177 # Then `cls` may be a function returning a class.
/data/virtualenv/venv2/lib/python2.7/site-packages/tensorflow/python/keras/engine/base_layer.pyc in from_config(cls, config)
1604 A layer instance.
1605 """
-> 1606 return cls(**config)
1607
1608
/data/virtualenv/venv2/lib/python2.7/site-packages/tensorflow/python/keras/layers/advanced_activations.py in __init__(self, max_value, negative_slope, threshold, **kwargs)
319 self.max_value = max_value
320 self.negative_slope = K.cast_to_floatx(negative_slope)
--> 321 self.threshold = K.cast_to_floatx(threshold)
322
323 def call(self, inputs):
/data/virtualenv/venv2/lib/python2.7/site-packages/tensorflow/python/keras/backend.pyc in cast_to_floatx(x)
231 ```
232 """
--> 233 return np.asarray(x, dtype=_FLOATX)
234
235
/data/virtualenv/venv2/lib/python2.7/site-packages/numpy/core/numeric.pyc in asarray(a, dtype, order)
499
500 """
--> 501 return array(a, dtype, copy=False, order=order)
502
503
TypeError: float() argument must be a string or a number
I temporally fixed it in tensorflow/python/keras/layers/advanced_activations.py by changing get_config
from
def get_config(self):
config = {
'max_value': self.max_value,
'negative_slope': self.negative_slope,
'threshold': self.threshold
}
base_config = super(ReLU, self).get_config()
return dict(list(base_config.items()) + list(config.items()))
to
def get_config(self):
config = {
'max_value': self.max_value,
'negative_slope': float(self.negative_slope),
'threshold': float(self.threshold)
}
base_config = super(ReLU, self).get_config()
return dict(list(base_config.items()) + list(config.items()))
However, the problem might be somewhere in deserialize_layer, as for a some reason negative_slope is a dictionary, not a numpy.ndarray
@cataclysmus I am able to reproduce with tf 1.12.0, but not with tf-nightly. Can you try with tf-nightly and see if the issue still exist?
Thanks @yongtang for taking a look. Previously I failed to check with nightly version. However I checked with TF nightly version : '1.13.0-dev20181108' now and the issue seems to be fixed. Will wait for @cataclysmus confirmation.
@yongtang @ymodak Checked. No bug at the build 1.13.0-dev20181128
Are you satisfied with the resolution of your issue?
Yes
No
| gharchive/issue | 2018-11-26T16:24:54 | 2025-04-01T06:45:57.717122 | {
"authors": [
"cataclysmus",
"ymodak",
"yongtang"
],
"repo": "tensorflow/tensorflow",
"url": "https://github.com/tensorflow/tensorflow/issues/23979",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
404187660 | tf.contrib.opt.ScipyOptimizerInterface error
Hello.
I tried to use tf.contrib.opt.ScipyOptimizerInterface with an example code from your documentation.
vector = tf.Variable([7., 7.], 'vector')
loss = tf.reduce_sum(tf.square(vector))
optimizer = tf.contrib.opt.ScipyOptimizerInterface(loss, options={'maxiter': 100})
with tf.Session() as session:
---->optimizer.minimize(session).
I am getting the following error: Tensors in list passed to 'values' of 'ConcatV2' Op have types [int32, float32, float32, float32, float32, float32, float32, float32, float32, float32, int32, float32, float32, float32, float32, int32, int32, float32, float32, float32, float32] that don't all match.
OS Platform and Distribution: Ubuntu 18.04.1
TensorFlow installed from: source
TensorFlow version: 1.12.0
Python version: 3.6
Bazel version: 0.21.0
GCC version: 7.3.0
CUDA and GPU: no running on GPU, because I don't have GPU.
Thank you!
ScipyOptimizer is moving from contrib to tensorflow/addons in #3 . I'm afraid that it would be a while, at least, before we could look into the issue. cc @seanpmorgan
@facaiy is correct it will take some time before we're in a position to accept questions for addons ExternalOptimizers. As part of the moving and upgrading code from contrib to addons, we also need to step through the code and make sure we understand exactly how it works.
In the mean time, I'll try to some troubleshooting -- but can not give any concrete time estimates.
Contrib has been depreciated here in Tensorflow repo and moved to tensorflow/addons , please reopen the issue in https://github.com/tensorflow/addons/issues if this exists in latest version. Thank you
| gharchive/issue | 2019-01-29T09:07:32 | 2025-04-01T06:45:57.722560 | {
"authors": [
"ciprianmihai94",
"facaiy",
"rthadur",
"seanpmorgan"
],
"repo": "tensorflow/tensorflow",
"url": "https://github.com/tensorflow/tensorflow/issues/25279",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
419645948 | tensorflow lite: error while converting frozen model to lite format
System information
Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
No
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Win 10 pro
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device: NA
TensorFlow installed from (source or binary): Using Anaconda navigator
TensorFlow version (use command below): v1.12.0-9901-gf380d8b8e5 1.14.1-dev20190309
Python version: Python 3.6.8
Bazel version (if compiling from source): NA
GCC/Compiler version (if compiling from source): NA
CUDA/cuDNN version: using cpu version
GPU model and memory: na
You can collect some of this information using our environment capture script
You can also obtain the TensorFlow version with
python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"
Describe the current behavior
I am trying to quantize a model that is made using tfslim library. I froze it using graph_util.convert_variables_to_constants function and tried to convert it to tflite formate for quantization. I am using win 10 and tf-nighlty. the following error appears:
TOCO failed. See console for info.
2019-03-12 00:20:27.142300: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before Removing unused ops: 221 operators, 366 arrays (0 quantized)
2019-03-12 00:20:27.147170: I tensorflow/lite/toco/graph_transformations/graph_transformations.cc:39] Before general graph transformations: 221 operators, 366 arrays (0 quantized)
2019-03-12 00:20:27.243872: F tensorflow/lite/toco/graph_transformations/propagate_fixed_sizes.cc:722] Check failed: start_array.data_type == ArrayDataType::kInt32 Range op inputs must be int32.
Fatal Python error: Aborted
Current thread 0x00001f44 (most recent call first):
File "c:\anaconda3\lib\site-packages\tensorflow\lite\toco\python\toco_from_protos.py", line 33 in execute
File "c:\anaconda3\lib\site-packages\absl\app.py", line 251 in run_main
File "c:\anaconda3\lib\site-packages\absl\app.py", line 300 in run
File "c:\anaconda3\lib\site-packages\tensorflow\python\platform\app.py", line 40 in run
File "c:\anaconda3\lib\site-packages\tensorflow\lite\toco\python\toco_from_protos.py", line 59 in main
File "C:\anaconda3\Scripts\toco_from_protos.exe_main.py", line 9 in
File "c:\anaconda3\lib\runpy.py", line 85 in _run_code
File "c:\anaconda3\lib\runpy.py", line 193 in _run_module_as_main
Describe the expected behavior
Should convert frozen pb file to tflite with int8 quantization
Code to reproduce the issue
Provide a reproducible test case that is the bare minimum necessary to generate the problem.
pb file in the below link
https://drive.google.com/open?id=1Ba6aEuv2VTGD_bct24UBiMh7MFe_jkOr
graph_def_file = "frozen_model_yolov3-tiny.pb"
input_arrays = ["input_to_model"]
output_arrays = ["concat_1"]
converter = tf.lite.TFLiteConverter.from_frozen_graph(
graph_def_file, input_arrays, output_arrays)
tflite_model = converter.convert()
open("converted_tiny_model.tflite", "wb").write(tflite_model)
Other info / logs
Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached.
Thank you for your post. We noticed you have not filled out the fields in the issue template. Could you update them if they are relevant in your case, or leave them as N/A? Along with the template, please provide as many details as possible to find the root cause of the issue.
Thank you for your post. We noticed you have not filled out the fields in the issue template. Could you update them if they are relevant in your case, or leave them as N/A? Along with the template, please provide as many details as possible to find the root cause of the issue.
Ive updated the post. please have a look
Thank you for your post. We noticed you have not filled out the fields in the issue template. Could you update them if they are relevant in your case, or leave them as N/A? Along with the template, please provide as many details as possible to find the root cause of the issue.
Ive updated the post. please have a look
@haozha111 Could you help to take a look at the model?
I think this requires broadening supported types of Range, in both converter and runtime
I downloaded your model, but I can't reproduce your issue. I used virtualenv and tf-nightly.
(tensorflow_venv) haoliang@haoliang0:~/tensorflow_venv/bin$ python test.py
2019-03-19 16:37:17.875562: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-03-19 16:37:17.905232: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3492135000 Hz
2019-03-19 16:37:17.906497: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55a21cc6c070 executing computations on platform Host. Devices:
2019-03-19 16:37:17.906550: I tensorflow/compiler/xla/service/service.cc:175] StreamExecutor device (0): ,
2019-03-19 16:37:18.050999: I tensorflow/core/grappler/devices.cc:53] Number of eligible GPUs (core count >= 8): 0 (Note: TensorFlow was not compiled with CUDA support)
2019-03-19 16:37:18.051125: I tensorflow/core/grappler/clusters/single_machine.cc:359] Starting new session
2019-03-19 16:37:18.283008: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:666] Optimization results for grappler item: graph_to_optimize
2019-03-19 16:37:18.283043: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:668] model_pruner: Graph size after: 236 nodes (-63), 253 edges (-63), time = 1.355ms.
2019-03-19 16:37:18.283054: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:668] implementation_selector: Graph size after: 236 nodes (0), 253 edges (0), time = 0.397ms.
2019-03-19 16:37:18.283071: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:668] function_optimizer: Graph size after: 236 nodes (0), 253 edges (0), time = 0.306ms.
2019-03-19 16:37:18.283078: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:668] constant folding: Graph size after: 158 nodes (-78), 173 edges (-80), time = 25.045ms.
2019-03-19 16:37:18.283084: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:668] shape_optimizer: Graph size after: 158 nodes (0), 173 edges (0), time = 0.505ms.
2019-03-19 16:37:18.283090: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:668] arithmetic_optimizer: Graph size after: 152 nodes (-6), 175 edges (2), time = 100.996ms.
2019-03-19 16:37:18.283096: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:668] loop_optimizer: Graph size after: 152 nodes (0), 175 edges (0), time = 0.661ms.
2019-03-19 16:37:18.283102: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:668] dependency_optimizer: Graph size after: 151 nodes (-1), 173 edges (-2), time = 1.329ms.
2019-03-19 16:37:18.283110: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:668] layout: Graph size after: 151 nodes (0), 173 edges (0), time = 0.286ms.
2019-03-19 16:37:18.283119: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:668] memory_optimizer: Graph size after: 151 nodes (0), 173 edges (0), time = 9.367ms.
2019-03-19 16:37:18.283125: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:668] model_pruner: Graph size after: 151 nodes (0), 173 edges (0), time = 0.983ms.
2019-03-19 16:37:18.283130: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:668] implementation_selector: Graph size after: 151 nodes (0), 173 edges (0), time = 0.257ms.
2019-03-19 16:37:18.283135: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:668] function_optimizer: Graph size after: 151 nodes (0), 173 edges (0), time = 0.254ms.
2019-03-19 16:37:18.283140: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:668] constant folding: Graph size after: 149 nodes (-2), 171 edges (-2), time = 12.494ms.
2019-03-19 16:37:18.283146: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:668] shape_optimizer: Graph size after: 149 nodes (0), 171 edges (0), time = 0.503ms.
2019-03-19 16:37:18.283152: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:668] arithmetic_optimizer: Graph size after: 149 nodes (0), 171 edges (0), time = 37.109ms.
2019-03-19 16:37:18.283160: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:668] dependency_optimizer: Graph size after: 149 nodes (0), 171 edges (0), time = 1.423ms.
Could you check what version of Tensorflow you are using?
@haozha111
will this snippet trigger the error?
graph_def_file = "frozen_model_yolov3-tiny.pb"
input_arrays = ["input_to_model"]
output_arrays = ["concat_1"]
converter = tf.lite.TFLiteConverter.from_frozen_graph(graph_def_file, input_arrays, output_arrays)
converter.inference_type = tf.lite.constants.QUANTIZED_UINT8
input_arrays = converter.get_input_arrays()
converter.quantized_input_stats = {input_arrays[0] : (0., 1.)} # mean, std_dev
tflite_model = converter.convert()
open("converted_tiny_model.tflite", "wb").write(tflite_model)
I tried the same, unfortunately got exactly the same error.
I'm using virtualenv and tf-nightly ('1.14.1-dev20190410')
Thanks Mark. Now I can reproduce that exact same error. I think this will only fail when quantization is enabled.
See the comments here[1], it looks like range op currently doesn't support quantization. So the check will fail when the input is not int32 or float32. I will transfer this issue to Pulkit since he is planning to support quantization for range op.
[1]https://github.com/tensorflow/tensorflow/blob/c238fc4a25c71c71e1bfdbb6eac750c64aed52ad/tensorflow/lite/kernels/range.cc#L89
Thanks Mark. Now I can reproduce that exact same error. I think this will only fail when quantization is enabled.
See the comments here[1], it looks like range op currently doesn't support quantization. So the check will fail when the input is not int32 or float32. I will transfer this issue to Pulkit since he is planning to support quantization for range op.
[1]https://github.com/tensorflow/tensorflow/blob/c238fc4a25c71c71e1bfdbb6eac750c64aed52ad/tensorflow/lite/kernels/range.cc#L89
@gjraza did you solve this ?
@nutsiepully @haozha111 , When will you support quantization for range op
| gharchive/issue | 2019-03-11T19:33:27 | 2025-04-01T06:45:57.753893 | {
"authors": [
"Rachel07",
"devimonica",
"gjraza",
"haozha111",
"jvishnuvardhan",
"marksunpeng",
"miaout17"
],
"repo": "tensorflow/tensorflow",
"url": "https://github.com/tensorflow/tensorflow/issues/26586",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
436361739 | Windows Build working with cuda 10.1 and vs2019
I am only writing this as an issue as I got tensorflow with win 10 building with cuda 10.1 and vs2019 .
I am not sure if my changes can be general, they seem to work for me and I can train MNIST on GPU. The cuda changes could be relevant, the others might be working only for my system config.
Please make sure that this is a build/installation issue. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:build_template
System information
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Windows 10
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
TensorFlow installed from (source or binary): source
TensorFlow version: 2.0a
Python version: 3.6.5
Installed using virtualenv? pip? conda?: pip
Bazel version (if compiling from source): 20
GCC/Compiler version (if compiling from source): visual studo 2019
CUDA/cuDNN version: 10.1/7
GPU model and memory: gtx 1080 ti , 4gv
Describe the problem
Cannot compile tensorflow 2.0 alpha on windows with cuda 10.1, and visual studio 2019
Provide the exact sequence of commands / steps that you executed before running into the problem
Hardlinked visual studio 2019 as 2017 with mklink
modified bazel scripts and stream operators as in : https://github.com/atemysemicolon/tensorflow/commit/54faf06d5c10e8875b9ce36b941004aceb44c8b9
Compiles
Any other info / logs
Visual 2019 does not seem to be supported by older versions of Bazel. Bazel 24.1 causes compilation issues using nvcc. However, cheating bazel into thinking 2019 is 2017 is good enough - by hardlinking the 2019 folder to 2017 in C:\Program Files\Microsoft Visual Studio..
I had to modify bazel to not generate workspaces for mac and linux,
The most important one seems to be the modification in cuda_10_0.inc in tensorflow/stream_executer/cuda/...
TensorFlow supports CUDA 10.0 (TensorFlow >= 1.13.0). Please refer this link and let us know in case of any clarification. Thanks!
This guide is for 10.1 , not 10
Unfortunately, none of the TensorFlow versions officially support CUDA 10.1. As of now we have to build TensorFlow version>=1.13.0 using CUDA 10.0. Thanks!
Automatically closing due to lack of recent activity. Please update the issue when new information becomes available, and we will reopen the issue. Thanks!
I thought only when someone builds it , it could be officially supported xd
| gharchive/issue | 2019-04-23T19:54:28 | 2025-04-01T06:45:57.763251 | {
"authors": [
"achandraa",
"atemysemicolon"
],
"repo": "tensorflow/tensorflow",
"url": "https://github.com/tensorflow/tensorflow/issues/28086",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
461299150 | ERROR: Cannot uninstall 'wrapt'. during upgrade
System information
OS Platform and Distribution (e.g., Linux Ubuntu 19.04 on Sony notebook):
TensorFlow version:
python
Python 3.6.3 |Anaconda, Inc.| (default, Oct 13 2017, 12:02:49)
[GCC 7.2.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
/home/ronald/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
from ._conv import register_converters as _register_converters
>>> print(tf.__version__)
2.0.0-alpha0
Describe the problem
I try to upgrade to beta1 with:
install tensorflow==2.0.0-beta1
at the end I get:
Installing collected packages: wrapt, tensorflow
Found existing installation: wrapt 1.10.11
ERROR: Cannot uninstall 'wrapt'. It is a distutils installed project and thus we cannot accurately determine which files belong to it which would lead to only a partial uninstall.
How to fix it?
I fixed it by:
conda update --all
pip install --upgrade tensorflow==2.0.0-beta1
It didn't work for me. Still getting that error.
it work for me. Thank you
I fixed it by:
conda update --all
pip install --upgrade tensorflow==2.0.0-beta1
It work for me. Thank you
Works for me, thanks!
It didn't work for me. Still getting that error.
I fixed it by:
conda update --all
pip install --upgrade tensorflow==2.0.0-beta1
It worked for me also.
conda update --all
pip install tensorflow
It didn't work for me. Still getting that error.
try
conda update wrapt
conda update --all
pip install tensorflow
this worked for me!!!!
PS: I got a reboot after the first line was done.
I have windows 10.
Above solutions are not worked for me. So I remove the `wrapt' by conda operation.
conda remove wrapt
And, it worked.
pip install tensorflow
it work for me. Thank you
I fixed it by:
conda update --all
pip install --upgrade tensorflow==2.0.0-beta1
It work for me. Thank you
agreed!
None of the solutions worked for me.
I am always getting ERROR: Cannot uninstall 'wrapt'. It is a distutils installed project and thus we cannot accurately determine which files belong to it which would lead to only a partial uninstall.
and with conda remove wrapt I get RemoveError: 'setuptools' is a dependency of conda and cannot be removed from conda's operating environment.
env: Mac OS 10.14.5
Above solutions are not worked for me. So I remove the `wrapt' by conda operation.
conda remove wrapt
And, it worked.
pip install tensorflow
Env: Windows 10
This worked for me.
Tensorflow seems to have trouble being friendly with other packages. The following worked for me, starting from a clean conda environment:
pip install --upgrade pip
pip install six>=1.12.0
pip install httplib2==0.12.0
pip uninstall -y setuptools
pip install setuptools>=41.0.0
pip install tensorflow==1.14.0
pip install tfx
pip install pylint
This sequence gets rid of wrapt as well as tensorboard warnings and google-apitools failures.
This worked for me. I am using Jupyter notebook (OD: Ubuntu 16.0) all the commands running from the notebook:
At the time of installing tensor flow I got following two errors. The errors and solutions are:
ERROR 1: Cannot uninstall 'wrapt'. It is a distutils installed project and thus we cannot accurately determine which files belong to it which would lead to only a partial uninstall.
Solution: run following command
!conda remove wrapt --yes
ERROR 2: tensorboard 1.14.0 has requirement setuptools>=41.0.0
Solution: run following command to solve this error
!pip uninstall -y setuptools
!pip install setuptools>=41.0.0
Now install tensorflow:
!pip install tensorflow
dist-packages cannot be uninstalled or removed by pip, so you have to go manually delete the wrapt folder.
Where is that wrapt folder?- It can be seen in the terminal from where it is picking the wrapt.
in my case, the wrapt folder was in root/usr/lib/python3/
hope it works for you too.
ps. (you can start by deleting all wrapt folders by just searching them)
This worked for me:
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
This worked for me:
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
This worked for me:
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
It works for me. Thanks.
conda update --all
pip install tensorflow
It works for me. thank you.
It didn't work for me. Still getting that error.
try
conda update wrapt
It didn't work for me. Still getting that error.
try
conda update wrapt
It works for me. Thank you.
It didn't work for me. Still getting that error.
try
conda update wrapt
It worked for me. Thanks a lot.
Above solutions are not worked for me. So I remove the `wrapt' by conda operation.
conda remove wrapt
And, it worked.
pip install tensorflow
Env: Windows 10
Thanks @NoSyu this work me
This worked for me
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
This worked for me
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
This worked for me too.
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
This worked for me too，Thanks.
Worked like charm
Above solutions are not worked for me. So I remove the `wrapt' by conda operation.
conda remove wrapt
And, it worked.
pip install tensorflow
Env: Windows 10
it works for me, thanks very much!
I fixed it by:
conda update --all
pip install --upgrade tensorflow==2.0.0-beta1
I fixed it by:
conda update --all
pip install --upgrade tensorflow==2.0.0-beta1
Thanks..It worked for me.
I fixed it by:
conda update --all
pip install --upgrade tensorflow==2.0.0-beta1
works for me too!!!!
I fixed it by:
conda update --all
pip install --upgrade tensorflow==2.0.0-beta1
Worked for me too
It didn't work for me. Still getting that error.
Edit: Fixed it by installing tensorflow 1.14 first then updating it to version 2.0
This is is the only thing that worked for me. Thanks.
Tried removing 'wrapt' and installing tensorflow v2.0 and then numpy threw a similar error.
This worked for me:
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
it worked for me as well , thanks.
This worked for me:
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
@rickykim93 you are awesome... I love you...
This worked for me:
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
Hi, I had this problem in Raspberry Pi and your procedure worked for me.
Thank you.
Above solutions are not worked for me. So I remove the wrapt' by conda operation. conda remove wraptAnd, it worked.pip install tensorflow`
Env: Windows 10
This worked for me.
This also worked for me. Env: Mac OS 10.14.6
System information
OS Platform and Distribution (e.g., Linux Ubuntu 19.04 on Sony notebook):
TensorFlow version:
python
Python 3.6.3 |Anaconda, Inc.| (default, Oct 13 2017, 12:02:49)
[GCC 7.2.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
/home/ronald/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
from ._conv import register_converters as _register_converters
>>> print(tf.__version__)
2.0.0-alpha0
Describe the problem
I try to upgrade to beta1 with:
install tensorflow==2.0.0-beta1
at the end I get:
Installing collected packages: wrapt, tensorflow
Found existing installation: wrapt 1.10.11
ERROR: Cannot uninstall 'wrapt'. It is a distutils installed project and thus we cannot accurately determine which files belong to it which would lead to only a partial uninstall.
How to fix it?
if "pip install tensorflow" command won't work...
try to "update conda --upgrade all"
then "conda install tensorflow" this will definitely work.
This worked for me:
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
Great fix.
This worked for me:
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
Thanks alot,
it works for me and able to installed TensorFlow and keras
This worked for me:
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
it worked for me. thanks.
This worked for me:
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
Works for me, thanks :)
它对我有用。谢谢
我通过以下方式修复它：
conda update --all
pip install --upgrade tensorflow==2.0.0-beta1
它对我有用。谢谢
me too
I fixed it by:
conda update --all
pip install --upgrade tensorflow==2.0.0-beta1
This works for me, thanks!
I fixed it by:
conda update --all
pip install --upgrade tensorflow==2.0.0-beta1
worked...great..thanks
This worked for me:
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
This works for my Windows 8.1
However, I was asked to consider upgrade the pip.
And I did it first of all, using:
python -m pip install --upgrade pip
Thanks!
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
This worked for me:
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
This worked for me too in my mac，Thanks.
This worked for me:
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
Thanks so much! This saved me.
I fixed it by:
conda update --all
pip install --upgrade tensorflow==2.0.0-beta1
This worked for me
conda update --all
pip install tensorflow
This worked for me
Env: Mac OS 10.14.6
try conda from anaconda prompt or else it doesnt work
This worked for me on a mac OS 10.14. Running in the terminal.
pip install wrapt --upgrade --ignore-installed
pip install tensorflow --upgrade
I also fixed it by simply running
conda update wrapt
I think this avoids other unwanted upgrades by conda
This worked for me:
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
@rickykim93 you are awesome... I love you...
That worked for me too. Fantastic !!!
This worked for me:
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
this worked for me.
thanks a lot to the genius developers
From all the solutions named here. This one is the only one that worked for me:
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
This worked for me:
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
This worked in Mac
This worked for me:
pip install wrapt --upgrade --ignore-installed
pip install tensorflow
I tried this and the tensorflow was successfully installed, but I had error when tired to use it. Than I tried
pip install --upgrade tensorflow==2.0.0-beta1
and after this, it works well!
That works for me
conda uninstall wrapt
pip install tensorflow
Thank you man, this worked for me!
Worked for Ubuntu 16.04 x86_64
When I perform the command "pip install tensorflow-gpu==1.15", I encounter the error "Found existing installation: wrapt 1.10.11 ERROR: Cannot uninstall 'wrapt'".
my solution:
perform "pip install wrapt --upgrade --ignore-installed", upgrade wrapt 1.10.11 to wrapt-1.12.0
perform "pip install tensorflow-gpu==1.15"
if you cannot perform "pip install tensorflow-gpu==1.15" successfully. Maybe you firstly need to upgrade pip-18.1 to pip-20.0 using "python -m pip install --upgrade pip setuptools".
This worked for me. I am using Jupyter notebook (OD: Ubuntu 16.0) all the commands running from the notebook:
At the time of installing tensor flow I got following two errors. The errors and solutions are:
ERROR 1: Cannot uninstall 'wrapt'. It is a distutils installed project and thus we cannot accurately determine which files belong to it which would lead to only a partial uninstall.
Solution: run following command
!conda remove wrapt --yes
ERROR 2: tensorboard 1.14.0 has requirement setuptools>=41.0.0
Solution: run following command to solve this error
!pip uninstall -y setuptools
!pip install setuptools>=41.0.0
Now install tensorflow:
!pip install tensorflow
It worked for me ，thank you!
This worked for me. I am using Jupyter notebook (OD: Ubuntu 16.0) all the commands running from the notebook:
At the time of installing tensor flow I got following two errors. The errors and solutions are:
ERROR 1: Cannot uninstall 'wrapt'. It is a distutils installed project and thus we cannot accurately determine which files belong to it which would lead to only a partial uninstall.
Solution: run following command
!conda remove wrapt --yes
ERROR 2: tensorboard 1.14.0 has requirement setuptools>=41.0.0
Solution: run following command to solve this error
!pip uninstall -y setuptools
!pip install setuptools>=41.0.0
Now install tensorflow:
!pip install tensorflow
It worked for me ，thank you!
Above solutions are not worked for me. So I remove the `wrapt' by conda operation.
conda remove wrapt
And, it worked.
pip install tensorflow
Env: Windows 10
It worked for me, thank you!
This worked for me. I am using Jupyter notebook (OD: Ubuntu 16.0) all the commands running from the notebook:
At the time of installing tensor flow I got following two errors. The errors and solutions are:
ERROR 1: Cannot uninstall 'wrapt'. It is a distutils installed project and thus we cannot accurately determine which files belong to it which would lead to only a partial uninstall.
Solution: run following command
!conda remove wrapt --yes
ERROR 2: tensorboard 1.14.0 has requirement setuptools>=41.0.0
Solution: run following command to solve this error
!pip uninstall -y setuptools
!pip install setuptools>=41.0.0
Now install tensorflow:
!pip install tensorflow
It worked for me , thank you
It's worked for me as well. Really appreciated for providing such details. However, could you please provide more details regarding the problem? Why we are not able to uninstall "wrapt" without upgrading all the packages and libraries? @Elmit2015
Locking conversation to prevent a stream of "it works"
| gharchive/issue | 2019-06-27T03:51:28 | 2025-04-01T06:45:57.822542 | {
"authors": [
"BhavishyaDiggiwal",
"Boyombo1",
"Devinmathew",
"Elmit2015",
"HaikunHuang",
"Jingciii",
"JuanYan",
"KishaRenee",
"MonsieurWave",
"Neowy",
"NoSyu",
"PrasadSiri",
"RealPolitiX",
"RegaipKURT",
"VRHaritha",
"XiaoqianSun0104",
"Yogeshnaik1190",
"ajourney1",
"atoyissan",
"back-p",
"bamwani",
"bhabani-shankar",
"chikum",
"christophgm",
"congee524",
"deepeshguru",
"eleprocha",
"eric-0x72",
"fabio11c",
"fabriciofsantana",
"gitvimalhub",
"hi-im-ryanli",
"houchengbin",
"hridaydutta123",
"hysunflower",
"imoisharma",
"javiervg",
"jliu1235",
"jmeile",
"kentaroy47",
"kurkutesa",
"liangsun-ponyai",
"lkfrota",
"mihaimaruseac",
"mikeyEcology",
"moloudshahbazi",
"nahidalam",
"primrose3128",
"qingxuantang",
"rickykim93",
"robertlugg",
"scaler2017",
"seyedmohammadmortaji",
"ssusie",
"sumiting",
"tahwaru",
"turinglife",
"xiejunyu0531",
"yangyang945",
"zeineb12",
"zung"
],
"repo": "tensorflow/tensorflow",
"url": "https://github.com/tensorflow/tensorflow/issues/30191",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
798591502 | floating point exception in tf.nn.avg_pool3d and tf.nn.max_pool3dwhen ksize=0
System information
Have I written custom code (as opposed to using a stock example script provided in TensorFlow): No
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Ubuntu 18.04
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device: N/A
TensorFlow installed from (source or binary): binary
TensorFlow version (use command below):2.1.0
Python version:3.7.6
Bazel version (if compiling from source):N/A
GCC/Compiler version (if compiling from source):N/A
CUDA/cuDNN version:N/A
GPU model and memory:N/A
Describe the current behavior
floating point exception in tf.nn.avg_pool3d and tf.nn.max_pool3d when ksize=0
Describe the expected behavior
expect no crash
Standalone code to reproduce the issue
The code crashes in nightly version too. Check out the gist
tf.nn.avg_pool3d(input=tf.ones((1,1,1,1,1)), strides=1, ksize=0, padding='VALID')
tf.nn.max_pool3d(input=tf.ones((1,1,1,1,1)), strides=1, ksize=0, padding='VALID')
Output:
Floating point exception (core dumped)
@ravikyram I have created a pull request to solve this issue , which will help raise FloatingPoitnError when ksize = 0
I have tried in colab with TF version 2.4, nightly version(2.5.0-dev20210201) and was able to reproduce the issue.Please, find the gist here. Thanks!
| gharchive/issue | 2021-02-01T18:12:40 | 2025-04-01T06:45:57.829912 | {
"authors": [
"DNXie",
"around-star",
"ravikyram"
],
"repo": "tensorflow/tensorflow",
"url": "https://github.com/tensorflow/tensorflow/issues/46834",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
181759336 | Android Demo build error
The error I saw is as follows, don't quit know how this permission error occurs
ERROR: /home/toxido/.cache/bazel/_bazel_root/e7444205eb7a78f2fb0f6da55e24d78b/external/androidsdk/BUILD:5:1: Executing genrule @androidsdk//:aapt_runner failed: linux-sandbox failed: error executing command /home/toxido/.cache/bazel/_bazel_root/e7444205eb7a78f2fb0f6da55e24d78b/execroot/tensorflow/_bin/linux-sandbox ... (remaining 5 argument(s) skipped).
src/main/tools/linux-sandbox-pid1.cc:233: "mount(/, /home/toxido/.cache/bazel/_bazel_root/e7444205eb7a78f2fb0f6da55e24d78b/bazel-sandbox/28d014be-3643-4295-b588-2ed7789511a4-1/tmp, NULL, MS_BIND | MS_REC, NULL)": Permission denied
Target //tensorflow/examples/android:tensorflow_demo failed to build
Use --verbose_failures to see the command lines of failed build steps.
@ToxidoLiu Please fill out the following information, which was the default template when you clicked on the green "New issue" button. Also include the exact command-line that you ran, that causes the error.
What related GitHub issues or StackOverflow threads have you found by searching the web for your problem?
Environment info
Operating System:
Installed version of CUDA and cuDNN:
(please attach the output of ls -l /path/to/cuda/lib/libcud*):
If installed from binary pip package, provide:
A link to the pip package you installed:
The output from python -c "import tensorflow; print(tensorflow.__version__)".
If installed from source, provide
The commit hash (git rev-parse HEAD)
The output of bazel version
If possible, provide a minimal reproducible example (We usually don't have time to read hundreds of lines of your code)
What other attempted solutions have you tried?
Logs or other output that would be helpful
(If logs are large, please upload as attachment or provide link).
@tatatodd
OS & Environment : Ubuntu 16.04 LTS , Android Studio v2.2
tensorflow version : 0.8.0
bazel version: 0.3.2
Android SDK version: 24.0.3
NDK version: 13.0.3315539
The above error occured when I tried to do
'$ bazel build //tensorflow/examples/android:tensorflow_demo'
as instructed here:
https://github.com/tensorflow/tensorflow/tree/master/tensorflow/examples/android
Thanks!
@ToxidoLiu Please try the latest version of TensorFlow 0.11, since 0.8 is quite old at this point:
https://www.tensorflow.org/versions/r0.11/get_started/os_setup.html#download-and-setup
@toxidoliu Have you checked that relevant binaries all have the execute bit set? If you're still having issues after you upgrade TF can you paste the error log running with --verbose_failures?
Closing automatically due to lack of recent activity. Please reopen when further information becomes available. Thank you.
| gharchive/issue | 2016-10-07T20:21:08 | 2025-04-01T06:45:57.837675 | {
"authors": [
"ToxidoLiu",
"andrewharp",
"aselle",
"tatatodd"
],
"repo": "tensorflow/tensorflow",
"url": "https://github.com/tensorflow/tensorflow/issues/4832",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
876408178 | Dynamic Input support for TFLite models
Hello Tensors
I have a TF model with (None,None,100) input dims and its converted into TFLite too.
But when I do inference, it gives error-
RuntimeError: tensorflow/lite/kernels/reshape.cc:58 stretch_dim != -1 (0 != -1)Node number 72 (RESHAPE) failed to prepare.
System information
TensorFlow version (you are using): 2.4.1.
Describe the feature and the current behavior/state.
Currently, 0th index can be dynamic(None or -1).
Will this change the current api? How?
Other indexs of model input can be dynamic(None or -1)
Who will benefit with this feature?
Generally, Vision models have 0th index dynamic but NLP models have other dimensions as dynamic.
@ichuang
@neso613 Please share simple stand alone code such that we can replicate the issue faced or if possible share a colab gist.
FYI, both TF and TFLite supports multiple dimensions but the Reshape operator does not only allow two dynamic dimensions in the shape argument.
@neso613 Please share simple stand alone code such that we can replicate the issue faced or if possible share a colab gist.
FYI, both TF and TFLite supports multiple dimensions but the Reshape operator does not only allow two dynamic dimensions in the shape argument.
Thats the Question.
TFLite supports dynamic input shape.
[{'name': 'input_1', 'index': 0, 'shape': array([ 1, 1, 40], dtype=int32), 'shape_signature': array([-1, -1, 40], dtype=int32), 'dtype': <class 'numpy.float32'>, 'quantization': (0.0, 0), 'quantization_parameters': {'scales': array([], dtype=float32), 'zero_points': array([], dtype=int32), 'quantized_dimension': 0}, 'sparsity_parameters': {}}]
When I do inference, my input can be of any shape, so I have to resize using
interpreter.resize_tensor_input(input_details[0]['index'],data_test.shape)
That is an intended behavior since the input tensors should be fixed through the resize_tensor_input method when the given model has dynamic inpiuts. You can resize input tensors again when the model should handle the different size in the following tasks.
That is an intended behavior since the input tensors should be fixed through the resize_tensor_input method when the given model has dynamic inpiuts. You can resize input tensors again when the model should handle a different size in the following tasks.
This is the code, I am using
interpreter.resize_tensor_input(input_details[0]['index'],data_test.shape) interpreter.allocate_tensors() interpreter.set_tensor(input_details[0]['index'], data_test) interpreter.invoke() output_data = interpreter.get_tensor(output_details[0]['index'])
@neso613 Please share simple stand alone code such that we can replicate the issue faced or if possible share a colab gist. It is really impossible to reproduce your problem at our end and please consider the latest TF version from the conversion stage to the inference stage.
I have gotten a very similar error when converting models with TFLite and running with TensorFlow 2.4. TensorFlow versions 2.3 and 2.5 pre-release work for me, I'd recommend trying these versions.
It is running now, but with Flex dependecny. Any solution for this flex issue?
Please file a feature request for the Select TF ops by adding a new issue. Thanks.
| gharchive/issue | 2021-05-05T12:40:56 | 2025-04-01T06:45:57.846196 | {
"authors": [
"abattery",
"gcervantes8",
"neso613"
],
"repo": "tensorflow/tensorflow",
"url": "https://github.com/tensorflow/tensorflow/issues/48915",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
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| gharchive/issue | 2024-11-30T08:42:51 | 2025-04-01T06:45:57.894507 | {
"authors": [
"amiraufaa",
"jayasanka009",
"lailihasan6",
"mismebasu"
],
"repo": "tensorflow/tensorflow",
"url": "https://github.com/tensorflow/tensorflow/issues/81411",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
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𝖨𝗇 𝗍𝗁𝖾 𝖾𝗏𝖾𝗋 𝖾𝗏𝗈𝗅𝗏𝗂𝗇𝗍𝗈 𝗅𝖺𝗇𝖽𝗈𝗌𝖼𝖺𝗉𝖾 𝗈𝖿 𝖼𝖾𝗅𝖾𝖻𝗋𝗂𝗍𝗒 𝖼𝗎𝗅𝗍𝗎𝗋𝖾, 𝗍𝗁𝖾 𝖨𝗌𝗁𝗈𝗐𝗌𝗉𝖾𝖾𝖽𝗌𝖼𝖺𝗇𝖽𝖺𝗅 𝗎𝗇𝖽𝖾𝗋𝗌𝖼𝗈𝗋𝖾𝗌 𝗍𝗁𝖾 𝗋𝖾𝗅𝖾𝗇𝗍𝗅𝖾𝗌𝗌 𝗉𝗎𝗋𝗌𝗎𝗂𝗍𝗈 𝗌𝖾𝗇𝗌𝖺𝗍𝗂𝗈𝗇𝖺𝗅𝗂𝗌𝗆𝗈, 𝖺 𝗉𝗎𝗋𝗌𝗎𝗂𝗍 𝗍𝗁𝖺𝗍 𝗈𝖿𝗍𝖾𝗇 𝖼𝗈𝗆𝖾𝗌 𝖺𝗍 𝗍𝗁𝖾 𝖾𝗑𝗉𝖾𝗇𝗌𝖾 𝗈𝖿 𝗍𝗋𝗎𝗍𝗁 𝖺𝗇𝖽𝖺 𝖽𝗂𝗀𝗇𝗂𝗍𝗒. 𝖠𝗌 𝗐𝖾 𝗇𝖺𝗏𝗂𝗀𝖺𝗍𝖾 𝗍𝗁𝖾 𝖼𝗈𝗆𝗉𝗅𝖾𝗑𝗂𝗍𝗂𝖾𝗌 𝗈𝖿 𝗍𝗁𝖾 𝖽𝗂𝗀𝗂𝗍𝖺𝗅 𝖺𝗀𝖾, 𝗍𝗁𝖾 𝗅𝗂𝗇𝖾 El programa de fidelización de veteranos de guerra de 2018 está en marcha.
𝖠𝗌 𝗔𝗻 𝗹𝗶𝗻𝗲𝗻 𝗲𝗻 𝗹𝗮 𝗽𝗮𝗿𝗮 ...�𝗼𝗺𝗽𝗮𝗿𝗮 El programa de fidelización de veteranos de la Segunda Guerra Mundial está en marcha. Yo estaba en el hospital y estaba muy ocupado con mis tareas, así que, 𝗌𝗀𝗶𝗻 𝗲𝗻 𝗹𝗮 𝗽𝗮𝗿𝗮 𝗹𝗮 𝗽𝗮𝗿𝗮 𝗹𝗮 𝗽𝗮𝗿𝗮 𝗹𝗮 𝗽𝗮𝗿𝗮 𝗽𝗮𝗿𝗮 𝗹𝗮 𝗽𝗮𝗿𝗮 𝗹𝗮 𝗽𝗮𝗿𝗮 𝗽𝗮𝗿𝗮 𝗹𝗮 𝗽𝗮𝗿𝗮 𝗽𝗮𝗿𝗮 𝗹𝗮 𝗗𝗘 𝗖𝗜𝗡𝗜𝗢 𝗗𝗘 𝗗𝗘 𝗖𝗜𝗢𝗡𝗖𝗜Ó𝗡 𝗗𝗘 𝗔𝗡𝗧𝗘𝗥𝗖𝗜Ó𝗡 𝗗𝗘 𝗔𝗡𝗧𝗘𝗥𝗧𝗘𝗦 𝗗𝗘 𝗉𝗋𝗂𝗏𝖺𝗼𝗒 𝗗𝗘 𝗔𝗡𝗧𝗘𝗥𝗧𝗘𝗦.
cvcv
| gharchive/issue | 2024-12-01T14:23:15 | 2025-04-01T06:45:57.898223 | {
"authors": [
"ba05251670",
"semolisk"
],
"repo": "tensorflow/tensorflow",
"url": "https://github.com/tensorflow/tensorflow/issues/81811",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
347565992 | fix var type issue which breaks crf_decode
CRF decode can fail when default type of "0" (as viewed by math_ops.maximum) does not match the type of sequence_length.
This change is parallel in motivation and solution to the fix in https://github.com/tensorflow/tensorflow/commit/c0f1080188c5c6955cfa3b3c086ac262b1e5ec02, for crf_log_norm()=>_multi_seq_fn().
Just modified one of the a couple of the CRF tests to presumably(?) provide better coverage of different var types for sequence_length settings.
| gharchive/pull-request | 2018-08-03T23:58:47 | 2025-04-01T06:45:57.901462 | {
"authors": [
"cbockman"
],
"repo": "tensorflow/tensorflow",
"url": "https://github.com/tensorflow/tensorflow/pull/21371",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
2296978713 | Fix ConcreteFunction when called with structured outputs.
ConcreteFunction properly flattens structured inputs (e.g. composite tensors) when called, but it does not pack/un-flatten the outputs. When ConcreteFunction outputs are structured, they must be packed back into their structured form to match the function signature.
Hi @james-choncholas Can you please sign the CLA? Thank you!
Force-pushed to update the commits email address to the one associated with my Google contributor CLA.
Hi @rohan100jain Any update on this PR? Please. Thank you!
Hi @rohan100jain Any update on this PR? Please. Thank you!
Hi @rohan100jain Any update on this PR? Please. Thank you!
Hi @rohan100jain Any update on this PR? Please. Thank you!
Hi @rohan100jain, Any update on this PR? Please. Thank you!
Hi @rohan100jain, Any update on this PR? Please. Thank you!
Hi @rohan100jain, Any update on this PR? Please. Thank you!
Hi @rohan100jain, Any update on this PR? Please. Thank you!
| gharchive/pull-request | 2024-05-15T06:29:19 | 2025-04-01T06:45:57.904903 | {
"authors": [
"gbaned",
"james-choncholas",
"keerthanakadiri"
],
"repo": "tensorflow/tensorflow",
"url": "https://github.com/tensorflow/tensorflow/pull/67612",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
222313675 | Explicitly delete Estimator before copying output_dir
Hopefully this fixes #9185 by releasing some stray file handle.
I triggered http://ci.tensorflow.org/job/tensorflow-pr-win-bazel/3/console
I hope the setup is the same as tf-master-win-bzl.
@meteorcloudy FYI.
@martinwicke I tested on my local machine as well, it doesn't seem to fix the problem.
But I found shutil.copytree(model_dir1, model_dir2) works, can we use this instead of os.rename?
The problem with that would be that this does not delete the old tree. This test is to ensure that no absolute paths creep in anywhere, so this would defang the test.
I cannot see what hangs on to a file handle.
Perhaps the easiest approach would be to install the current nightly on one of our Windows test VMs, run a modified version of estimator_test.py that blocks before the rename, and apply https://technet.microsoft.com/en-us/sysinternals/processexplorer.aspx to the Python interpreter to see what handles are open?
@mrry It shows this file is in use by python
c:/tmp/tmp3y2vhvzi/model_dir1/events.out.tfevents.1492671112.TENSORFLOW-JENK
Thanks for tracking that down, Yun! Then I think we have a smoking gun: the tf.summary.FileWriter is holding open a file handle after est1.train() returns.
It looks like this happens deep in the MonitoredTrainingSession... and there seems to be a cache(!!) involved:
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/summary/writer/writer_cache.py#L27
As a hack, you might try invoking FileWriterCache.clear() before the rename, but I'm not sure that that's sufficient because deleting a FileWriter doesn't appear to close() it, so you might need to add a writer.close() call somewhere (or maybe add it to the destructor?).
@mrry Thanks for the hint, Derek!
I tested adding writer_cache.FileWriterCache._cache[model_dir1].close() before rename also solves the problem. Does this sounds good to you?
That'll fix the test, but I'm wondering whether we can get put that line (or some equivalent) somewhere were it will be called automatically when the Estimator owning the model_dir is deleted?
I'm even wondering whether we should even keep the cache live when any of train(), eval(), predict() exit. They're all meant to be long running and ideally shouldn't leave open file handles hanging around.
@martinwicke Yes, I totally agree! But I am lack of knowledge how these function works. Can someone with more experience look into this?
Jenkins, test this please.
Triggered another Windows build: http://ci.tensorflow.org/job/tensorflow-pr-win-bazel/4/
I edited FileWriterCache to close() all caches it has, and call that in the test. Cleaner than closing the cache directly.
I'll merge to fix build.
| gharchive/pull-request | 2017-04-18T06:19:07 | 2025-04-01T06:45:57.913619 | {
"authors": [
"martinwicke",
"meteorcloudy",
"mrry"
],
"repo": "tensorflow/tensorflow",
"url": "https://github.com/tensorflow/tensorflow/pull/9281",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
309426689 | Starter Project links broken
Starter project links at homepage are broken
https://deeplearnjs.org/index.html#demos
https://github.com/PAIR-code/deeplearnjs/tree/master/starter/es6/
https://github.com/PAIR-code/deeplearnjs/tree/master/starter/typescript/
Apologies, we're in the middle of moving some code to other repositories. We'll send an update on Friday with where all the code now lives!
Hi @kriptontr We are moving demos/starter projects to a new repo with the launch of https://js.tensorflow.org/ See https://github.com/tensorflow/tfjs-examples for the things start off from. With this we are removing starter projects from the main repository.
We are keeping up the old site for a while to make the transition easier but it is essentially deprecated.
| gharchive/issue | 2018-03-28T15:51:30 | 2025-04-01T06:45:57.917020 | {
"authors": [
"kriptontr",
"nsthorat",
"tafsiri"
],
"repo": "tensorflow/tfjs-core",
"url": "https://github.com/tensorflow/tfjs-core/issues/906",
"license": "apache-2.0",
"license_type": "permissive",
"license_source": "bigquery"
} |
2123778609 | Consumer core gives different NoC dst for matmul
To reproduce:
go to yugao/wh_block_matmul_hang_consumer
run pytest tests/tt_eager/python_api_testing/unit_testing/test_bert_ops.py
In tt_metal/impl/dispatch/kernels/command_queue_consumer.hpp, I added DPRINT info for command_ptr[3], noc_x_start, noc_y_start, noc_x_end, noc_y_end. The command_ptr[3] should contain the NoC dst.
The branch is based on the yugao/wh_block_matmul_hang, so it will han after running the test for around 100 iterations.
Machine IP: 172.27.44.23, harvested X2
@yugaoTT is this a blocker?
@davorchap no I was debugging the matmul_hang, and saw the consumer is mcasting go signal to a NoC dst of (1,3),(9,9) for matmul, while for interleaved_to_sharded the consumer is mcasting to (1,2),(9,9), which is a grid of 8x7.
I looked into this, and for matmul, given it is broken into two kernel groups, it is correct that Yu would see two GO signal mcasts. One potential bug we did catch though is that there is nothing stalling the dispatcher on sending the GO signals in the case where we have multiple kernel groups. That means it is possible for semaphores to not arrive to one group before another group gets its GO signal. Apparently this is not done for this matmul kernel, but it seems like a general problem. Ideally, we'd want to stall sending the GO signal before binaries/semaphores have arrived in cases where we have two kernel groups. @pgkeller @davorchap FYI.
Closing this as a non-issue, will spin up another issue for the race that Yu and I caught.
| gharchive/issue | 2024-02-07T20:02:24 | 2025-04-01T06:45:58.140811 | {
"authors": [
"DrJessop",
"davorchap",
"yugaoTT"
],
"repo": "tenstorrent-metal/tt-metal",
"url": "https://github.com/tenstorrent-metal/tt-metal/issues/5189",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
2226546240 | FD2: PrefetchQ possible corruption
Running Finish stress test we see:
prefetch q is all zeros
host writes an entry
device sees the entry but also sees the prior entry get re-written
Things to try:
add sfence after each write to fetchQ
StrictOrdering on TLB
16B fetchQ entry
make L1 uncachable
@davorchap @imatosevic @tt-aho @tooniz @abhullar-tt @ubcheema @aliuTT
Additional note is this was seen on a single GS machine. Typically this would occur under ~2 million loops.
Tried on a WH on a T3000 machine and didn't see an issue after ~5 million iterations before stopping it. Can retry on WH as well to confirm.
Additional note is this was seen on a single GS machine. Typically this would occur under ~2 million loops.
Tried on a WH on a T3000 machine and didn't see an issue after ~5 million iterations before stopping it. Can retry on WH as well to confirm.
How long does 2 million loops take?
Yes, maybe run it over night.
| gharchive/issue | 2024-04-04T21:25:52 | 2025-04-01T06:45:58.144508 | {
"authors": [
"pgkeller",
"tt-aho"
],
"repo": "tenstorrent-metal/tt-metal",
"url": "https://github.com/tenstorrent-metal/tt-metal/issues/7136",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
2070828301 | Adding interface to assign dispatch kernels to dispatch functionality and adding kernel to service remote command queue
Host changes
create dispatch core assigner interface to track which dispatch cores are assigned to which dispatch functionalities because with multi-chip fast dispatch we have more dispatch functionality than just cq producer and cq consumer (defined in dispatch_core_manager.hpp)
update SendDispatchKernelsToDevice to program remote cq interface cores as well as mmio dispatch cores when initializing mmio device
update CQ interface apis to account for hugepage channel offsets (each device has a hugepage in different channel)
Device changes
added remote_issue_queue_interface kernel to pull commands from remote command queue. In this PR that kernel doesn't do anything but @aliuTT is working on integrating it to the ethernet core
Passing post commit test suite
| gharchive/pull-request | 2024-01-08T16:34:33 | 2025-04-01T06:45:58.147478 | {
"authors": [
"abhullar-tt"
],
"repo": "tenstorrent-metal/tt-metal",
"url": "https://github.com/tenstorrent-metal/tt-metal/pull/4615",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
2103706984 | #0: Fix dprint server lock not being released before throw
Manually verified that the test fails on my BM before this fix, and that is passes after this fix
lgtm
@aliuTT has a PR that includes this, will close this one without merging
| gharchive/pull-request | 2024-01-27T18:14:36 | 2025-04-01T06:45:58.148642 | {
"authors": [
"aliuTT",
"tt-dma"
],
"repo": "tenstorrent-metal/tt-metal",
"url": "https://github.com/tenstorrent-metal/tt-metal/pull/4992",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
2267658366 | #7919: fix barriers in s2i writers and add read_one_packet for row-ma…
…jor wormhole case
I see. I dunno about all cases but it did help cases in RN50. (From 100k
cycles to 80k cycles). Ill put the barriers back and investigate this more
throughly in a separate PR.
On Mon, Apr 29, 2024 at 09:08 Austin Ho @.***> wrote:
@tarafdarTT https://github.com/tarafdarTT do you have profiling data
that moving the barriers has improved perf in all cases? When this op was
originally brought up, then having the barrier outside the inner loop was
sometimes suboptimal due to noc congestion
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You are receiving this because you were mentioned.Message ID:
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I used the default vim formatter.
On Mon, Apr 29, 2024 at 09:15 Austin Ho @.***> wrote:
@.**** commented on this pull request.
In
tt_eager/tt_dnn/op_library/sharded/kernels/dataflow/reader_unary_stick_layout_sharded_blocks_interleaved_start_id.cpp
https://github.com/tenstorrent/tt-metal/pull/7920#discussion_r1583070950
:
@@ -7,57 +7,83 @@
void kernel_main() {
const uint32_t src_addr = get_arg_val<uint32_t>(0);
What kind of code formatter did you use on these kernel files? We normally
use clang-format if we format code and this doesn't seem to match.
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.
You are receiving this because you were mentioned.Message ID:
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I used the default vim formatter.
…
On Mon, Apr 29, 2024 at 09:15 Austin Ho @.> wrote: @.* commented on this pull request. ------------------------------ In tt_eager/tt_dnn/op_library/sharded/kernels/dataflow/reader_unary_stick_layout_sharded_blocks_interleaved_start_id.cpp <#7920 (comment)> : > @@ -7,57 +7,83 @@ void kernel_main() { - const uint32_t src_addr = get_arg_val<uint32_t>(0); What kind of code formatter did you use on these kernel files? We normally use clang-format if we format code and this doesn't seem to match. — Reply to this email directly, view it on GitHub <#7920 (review)>, or unsubscribe https://github.com/notifications/unsubscribe-auth/BAK3IA2FWSTUATLMQGNEF7LY7ZBWXAVCNFSM6AAAAABG5C4CBGVHI2DSMVQWIX3LMV43YUDVNRWFEZLROVSXG5CSMV3GSZLXHMZDAMRYGQ4DGMBZHA . You are receiving this because you were mentioned.Message ID: @.***>
Could you either revert the formatting or use clang-format? The vim formatting does not match our style guide
| gharchive/pull-request | 2024-04-28T16:08:46 | 2025-04-01T06:45:58.161505 | {
"authors": [
"tarafdarTT",
"tt-aho"
],
"repo": "tenstorrent/tt-metal",
"url": "https://github.com/tenstorrent/tt-metal/pull/7920",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
2275177048 | #7956: Fix addc like ttnn ops doc
Fix issue #7956
Add supported dtypes and layouts and skipped that are unsupported
Reflect the same in documentation
Sweep Test Results:
addcdiv.csv
addcmul.csv
All post commit test : https://github.com/tenstorrent/tt-metal/actions/runs/8922478405
Fix merged to main
| gharchive/pull-request | 2024-05-02T10:35:26 | 2025-04-01T06:45:58.164109 | {
"authors": [
"Aswinmcw"
],
"repo": "tenstorrent/tt-metal",
"url": "https://github.com/tenstorrent/tt-metal/pull/8045",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
2278084992 | #0: umd bump
BH support in UMD is coming soon, so we'll need to bump sometime in the near future
This is a test to see if anything broke
???
| gharchive/pull-request | 2024-05-03T17:02:59 | 2025-04-01T06:45:58.165072 | {
"authors": [
"TT-billteng",
"tt-rkim"
],
"repo": "tenstorrent/tt-metal",
"url": "https://github.com/tenstorrent/tt-metal/pull/8104",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
2352217688 | #8482: Trace on remote chips
Ticket
https://github.com/tenstorrent/tt-metal/issues/8482
Problem description
Trace is not working on remote chips.
What's changed
Changes from @pgkeller:
Fix host completion write ptr in test_prefetcher
Was clobbering cmds.
This enables more prefetcher test configs w/ exec_buf
Rework split prefetch exec_buf sync mechanism
prefetch_h now stalls itself at the start of exec_buf by taking away its
downstream page credits. After sending the exec_buf, it unstalls the
prefetch_q so that it can continue to do prefetch work. dispatch restores
prefetch_h credits at exec_buf_end.
Increase test_prefetcher exec_buf test coverage
cq_prefetch changes:
Modify detection of exec_buf command. Prefetcher no longer looks at the cmd_id, since exec_buf command is not the first command in the Fetch Q. Instead rely on stall flag.
prefetch_h should not offset exec_buf command by preamble size, since it belongs to the same entry as a previously offset command (due to barrier_and_stall)
Account for wrap in barrier and stall
Add T3K trace tests.
Checklist
[x] Post commit CI passes
[ ] Model regression CI testing passes (if applicable)
[x] New/Existing tests provide coverage for changes
can you run the t3k frequent tests pipeline to test your changes?
can you run the t3k frequent tests pipeline on your branch to test your changes? will approve if the specific test suite in t3k frequent CI pipeline tests pass
Done, trace stress tests were passing
| gharchive/pull-request | 2024-06-13T23:36:09 | 2025-04-01T06:45:58.171156 | {
"authors": [
"tt-asaigal",
"ttmchiou"
],
"repo": "tenstorrent/tt-metal",
"url": "https://github.com/tenstorrent/tt-metal/pull/9433",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
1253633676 | Add Internal Load Balancer
This change wraps the VAST server task in a load balancer into a service and adds a network load balancer in front. This allows us to:
expose the server on a pre-defined local IP, removing the need to dynamically resolve it through the Fargate API
automatically restart the VAST server when it crashes
It requires a few extra resources to be initiated:
in terms of code complexity, this is offset-ed by the fact we can remove all the logic for the dynamic IP resolution
in terms of cost, the extra network load balancer adds a fix cost of ~$0.03 / hour to the stack
:memo: Checklist
[ ] All user-facing changes have changelog entries.
[ ] The changes are reflected on docs.tenzir.com/vast, if necessary.
[x] The PR description contains instructions for the reviewer, if necessary.
:dart: Review Instructions
Add a service and a load balancer resource in the fargate module
The task now being wrapped in a service, we use desiredCount to start / stop the server instead of start-task / stop-task API calls (for stopping, we keep stop-task to speed up the process)
Also did some minor changes in the tagging of the network resources because they were detected as perpetual changes by Terraform
simplified the integration tests to avoid having to do long cleanups of the EFS drive
Needs to be rebased once https://github.com/tenzir/vast/pull/2315 is merged before
I changed the resource naming strategy a bit because they were sometimes too long, integration tests should now pass: https://github.com/rdettai/vast/runs/6774453785
Note that this PR should go with some minor updates of the setup README, but we have batched them into https://github.com/tenzir/vast/pull/2322 instead.
I think this is ready to merge @dispanser !
| gharchive/pull-request | 2022-05-31T10:03:29 | 2025-04-01T06:45:58.180164 | {
"authors": [
"rdettai"
],
"repo": "tenzir/vast",
"url": "https://github.com/tenzir/vast/pull/2319",
"license": "BSD-3-Clause",
"license_type": "permissive",
"license_source": "github-api"
} |
1414466839 | Add a --web-root option to the web plugin
:memo: Reviewer Checklist
Review this pull request by ensuring the following items:
[ ] All user-facing changes have changelog entries
[ ] User-facing changes are reflected on vast.io
Also, that CORS error should go away with this patch
diff --git a/src/routes/status/+page.svelte b/src/routes/status/+page.svelte
index 9bbed5b..07c081d 100644
--- a/src/routes/status/+page.svelte
+++ b/src/routes/status/+page.svelte
@@ -14,7 +14,7 @@
const getStatus = async () => {
try {
- const API_BASE = 'http://localhost:42001/api/v0';
+ const API_BASE = 'http://127.0.0.1:42001/api/v0';
const url = `${API_BASE}/status?verbosity=detailed`;
const response = await fetch(url);
Historically, the "web root" is the place where a web server places its file, so --web-root to me feels like a well-known thing. I have no strong opinions on calling it differently though.
My mistake. I thought web/docs, web/blog and plugins/web/ui are at the same level, and are also served from the CLI - so I wanted to disambiguate. But since that is not the case, --web-root is perfectly fine.
I changed it to just --root for now, since that's what nginx also uses in their configuration and there doesn't seem to be consensus between "document root" and "web root" between different web servers.
I "merged" this manually by rebasing and pushing onto the base branch, to keep the commit graph a bit simpler by avoiding multiple merge bases.
| gharchive/pull-request | 2022-10-19T07:39:57 | 2025-04-01T06:45:58.184259 | {
"authors": [
"dit7ya",
"lava",
"mavam"
],
"repo": "tenzir/vast",
"url": "https://github.com/tenzir/vast/pull/2641",
"license": "BSD-3-Clause",
"license_type": "permissive",
"license_source": "github-api"
} |
1503688569 | Fix UB in order(...) for floating point numbers
The coder unit tests using the order(...) function on floating point numbers started failing for release builds on Debian after the CAF 0.18 bump, but the unit test suite wasn't touched since 2016, and the code itself not since 2018, so it was pretty like to be undefined behavior that we ran into. That turned out be rather easy to spot looking at the function.
But do you need to launder the pointer?
Laundering suffices if you are no longer using x afterwards. We do use it again in the unit tests, though. Bitcasting is defined in terms of memcpy, which then all compilers in practice elide, so that will never have this issue.
Btw, I confirmed the issue to work using our Dockerfile, slightly modified to build and run vast-test rather than vast. I reproduced the issue on msater, and was unable to with this fix.
| gharchive/pull-request | 2022-12-19T22:15:28 | 2025-04-01T06:45:58.186441 | {
"authors": [
"dominiklohmann"
],
"repo": "tenzir/vast",
"url": "https://github.com/tenzir/vast/pull/2814",
"license": "BSD-3-Clause",
"license_type": "permissive",
"license_source": "github-api"
} |
1154887732 | fix: Errors on ignore_desired_capacity_changes = true with mixed_instances_policy
Description
fix: Errors on ignore_desired_capacity_changes = true with mixed_instances_policy
Motivation and Context
Configured the mixed_instances_policy object just like the example shows,
but encounterd the following errors while applying an autoscaling group with ignore_desired_capacity_changes = true.
```
Error: Invalid function argument
on .terraform/modules/asg/main.tf line 468, in resource "aws_autoscaling_group" "idc":
468: instance_type = lookup(override.value, "instance_type", null)
├────────────────
│ override.value is tuple with 6 elements
Invalid value for "inputMap" parameter: lookup() requires a map as the first argument.
Error: Invalid function argument
on .terraform/modules/asg/main.tf line 469, in resource "aws_autoscaling_group" "idc":
469: weighted_capacity = lookup(override.value, "weighted_capacity", null)
├────────────────
│ override.value is tuple with 6 elements
Invalid value for "inputMap" parameter: lookup() requires a map as the first argument.
```
If you set ignore_desired_capacity_changes = false with the same mixed_instance_policy, then terraform apply does not report these errors.
Breaking Changes
There are no breaking changes. It is a bug fix.
How Has This Been Tested?
[x] I have tested and validated these changes using the mixed_instance module in the provided examples/complete project (with ignore_desired_capacity_changes = true set)
Tested with Terraform v1.1.4
@bryantbiggs
This MR is not proceeding for 2weeks.
Can you suggest me any actions missing from me?
@smaruy30 we'll need a reproduction showing the issue and then that will most likely get added as a test case so we can validate and sure functionality is maintained going forward
This issue has been resolved in version 6.0.0 :tada:
@antonbabenko Thanks for the update!
| gharchive/pull-request | 2022-03-01T05:23:53 | 2025-04-01T06:45:58.326379 | {
"authors": [
"antonbabenko",
"bryantbiggs",
"smaruy30"
],
"repo": "terraform-aws-modules/terraform-aws-autoscaling",
"url": "https://github.com/terraform-aws-modules/terraform-aws-autoscaling/pull/183",
"license": "apache-2.0",
"license_type": "permissive",
"license_source": "bigquery"
} |
2524383883 | [add]: multiple service connect services
Description
I changed a line to allow the dynamic block to take an entier list instead of one element
Motivation and Context
Breaking Changes
How Has This Been Tested?
[ ] I have updated at least one of the examples/* to demonstrate and validate my change(s)
[x] I have tested and validated these changes using one or more of the provided examples/* projects
[ ] I have executed pre-commit run -a on my pull request
closing in favor of #217
| gharchive/pull-request | 2024-09-13T09:41:02 | 2025-04-01T06:45:58.329497 | {
"authors": [
"bryantbiggs",
"mathias-mrsn"
],
"repo": "terraform-aws-modules/terraform-aws-ecs",
"url": "https://github.com/terraform-aws-modules/terraform-aws-ecs/pull/229",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
731626834 | Usage Example breaks during cluster upgrades
I have issues
I'm submitting a...
[x] bug report
[ ] feature request
[ ] support request - read the FAQ first!
[ ] kudos, thank you, warm fuzzy
What is the current behavior?
Resources that use the Kubernetes provider from the example (including the aws-auth configmap in the module) will fail to be modified after a control plane upgrade with the following (or similar) error:
Error: Failed to update Config Map: Unauthorized
Right now, the recommended/example way to set use this module per the README is as follows:
data "aws_eks_cluster" "cluster" {
name = module.my-cluster.cluster_id
}
data "aws_eks_cluster_auth" "cluster" {
name = module.my-cluster.cluster_id
}
provider "kubernetes" {
host = data.aws_eks_cluster.cluster.endpoint
cluster_ca_certificate = base64decode(data.aws_eks_cluster.cluster.certificate_authority.0.data)
token = data.aws_eks_cluster_auth.cluster.token
load_config_file = false
version = "~> 1.9"
}
module "my-cluster" {
source = "terraform-aws-modules/eks/aws"
cluster_name = "my-cluster"
cluster_version = "1.17"
}
Note that the two data sources are dependent on outputs from the module. During the first creation of the module, the dependency chain will look something like this:
After the first creation of the module, that output is well-known and does not change during a cluster upgrade, so it seems like Terraform will allow the data sources to be read/updated before the cluster upgrade happens. That results in a graph that looks more like the following
The problem that seems to be twofold:
When a cluster upgrade does occur, it looks like tokens generated against the old control plane are no longer valid. I tested this by requesting and storing a token locally, then modifying a copy of the kubeconfig to use it explicitly. With time still left before the expiration, I received You must be logged in to the server (Unauthorized) when trying to access the cluster after the control plane was upgraded. I'm not sure if this is a bug with EKS/AWS.
Since a cluster upgrade takes an extraordinarily long time (30m+), the token that was fetched in the datasource would have expired since they seem to have a lifetime of ~15m. That means that even in the absence of the problem described above, modifying the config map would still fail.
If this is a bug, how to reproduce? Please include a code sample if relevant.
Create a kubernetes cluster following the example, then upgrade the control plane while modifying the aws-auth configmap to add a role. Observe that the configmap modification fails with the following error:
Error: Failed to update Config Map: Unauthorized
What's the expected behavior?
The ConfigMap should be updated.
Are you able to fix this problem and submit a PR? Link here if you have already.
Environment details
Affected module version: 12.1.0
OS: OSX
Terraform version: 0.12.29
Any other relevant info
My current workaround that I just implemented is the following, though it creates a dependency on the aws cli:
provider "kubernetes" {
host = data.aws_eks_cluster.cluster.endpoint
cluster_ca_certificate = base64decode(data.aws_eks_cluster.cluster.certificate_authority.0.data)
load_config_file = false
exec {
api_version = "client.authentication.k8s.io/v1alpha1"
command = "aws"
args = ["eks", "get-token", "--cluster-name", "${module.eks.cluster_id}"]
}
}
@dcherman I have the same issue and it seems that after update some autoscaling node groups cannot connect to the cluster due to authorization error (((. Also terraform is trying to create new aws_auth kubernetes resource. It happens always after update, i am going to increase duration_seconds for cluster IAM roles but I am not sure , that the problem is here(
@dzirg44 Are you using managed nodegroups? If so, I've experienced similar problems.
Are you experiencing this with the latest version of this module or with v12.2.0 ?
@barryib In my case, v12.1.0, however in looking at the example I believe the latest version would have this issue as well. I haven't upgraded yet since I think I had a problem w/ cycles last time I tried; haven't revisited that yet.
In v12.2.0 we improved dependences management for managed node group https://github.com/terraform-aws-modules/terraform-aws-eks/pull/867. I was wondering if this solves your issue.
| gharchive/issue | 2020-10-28T17:01:02 | 2025-04-01T06:45:58.340665 | {
"authors": [
"barryib",
"dcherman",
"dzirg44"
],
"repo": "terraform-aws-modules/terraform-aws-eks",
"url": "https://github.com/terraform-aws-modules/terraform-aws-eks/issues/1072",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
2525490203 | feat: Allow passing in custom instance profile role
Description
Allows passing in a custom instance profile role and custom autoscaling role to the service pass role policy.
Also includes minor provider version upgrade https://github.com/hashicorp/terraform-provider-aws/pull/37740.
Motivation and Context
Closes: https://github.com/terraform-aws-modules/terraform-aws-emr/issues/26
Breaking Changes
No.
How Has This Been Tested?
[x] I have updated at least one of the examples/* to demonstrate and validate my change(s)
[x] I have tested and validated these changes using one or more of the provided examples/* projects
[x] I have executed pre-commit run -a on my pull request
This PR is included in version 2.3.0 :tada:
| gharchive/pull-request | 2024-09-13T19:07:38 | 2025-04-01T06:45:58.344959 | {
"authors": [
"antonbabenko",
"magreenbaum"
],
"repo": "terraform-aws-modules/terraform-aws-emr",
"url": "https://github.com/terraform-aws-modules/terraform-aws-emr/pull/30",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
1331740645 | Wrong url has been occurred while running terraform apply.
╷
│ Error: failed to create kubernetes rest client for read of resource: Get "https://localhost/api?timeout=32s": x509: certificate is valid for *.dev.tappy.stage-codal.net, dev.tappy.stage-codal.net, not localhost
│
│ with module.cert_manager.kubectl_manifest.cluster_issuer[0],
│ on .terraform/modules/cert_manager/main.tf line 42, in resource "kubectl_manifest" "cluster_issuer":
│ 42: resource "kubectl_manifest" "cluster_issuer" {
│
Working fine in local machine where kubectl, helm, kubectl config and providers are configured.
Not working in jenkins server where only kubectl command is installed.
Hello, terraform providers settings are incorrect
Hello, terraform providers settings are incorrect
Kubernetes and helm resources through terraform are being created.
Just this one throws error
What about kubectl provider ?
https://github.com/terraform-iaac/terraform-kubernetes-cert-manager#you-should-to-add-into-your-terraform-kubectl--helm--provider-configuration
jenkins@ip-172-31-11-15:~/workspace/Dev-Terraform-Deployment/infra/terraform-resources/configs$ cat kubernetes.tf | head -n25
provider "helm" {
kubernetes {
host = module.eks.cluster_endpoint
cluster_ca_certificate = base64decode(module.eks.cluster_certificate_authority_data)
token = data.aws_eks_cluster_auth.eks_cluster.token
}
experiments {
manifest = true
}
}
provider "kubernetes" {
host = module.eks.cluster_endpoint
cluster_ca_certificate = base64decode(module.eks.cluster_certificate_authority_data)
token = data.aws_eks_cluster_auth.eks_cluster.token
}
provider "kubectl" {
host = module.eks.cluster_endpoint
cluster_ca_certificate = base64decode(module.eks.cluster_certificate_authority_data)
token = data.aws_eks_cluster_auth.eks_cluster.token
}
pls chk above
I cannot understand how it is getting "https://localhost/api?timeout=32s"?
please try to add this into kubectl provider
provider "kubectl" {
host = module.eks.cluster_endpoint
cluster_ca_certificate = base64decode(module.eks.cluster_certificate_authority_data)
token = data.aws_eks_cluster_auth.eks_cluster.token
load_config_file = false
}
@bohdantverdyi Thank you.
It has been resolved.
| gharchive/issue | 2022-08-08T11:35:43 | 2025-04-01T06:45:58.377396 | {
"authors": [
"bohdantverdyi",
"codal-jayesh"
],
"repo": "terraform-iaac/terraform-kubernetes-cert-manager",
"url": "https://github.com/terraform-iaac/terraform-kubernetes-cert-manager/issues/16",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
1800693323 | fix(deps): update dependency gitpython to v3.1.32
This PR contains the following updates:
Package
Update
Change
gitpython
patch
==3.1.31 -> ==3.1.32
Release Notes
gitpython-developers/GitPython (gitpython)
v3.1.32: - with another security update
Compare Source
What's Changed
Bump cygwin/cygwin-install-action from 3 to 4 by @dependabot in https://github.com/gitpython-developers/GitPython/pull/1572
Fix up the commit trailers functionality by @itsluketwist in https://github.com/gitpython-developers/GitPython/pull/1576
Name top-level exceptions as private variables by @Hawk777 in https://github.com/gitpython-developers/GitPython/pull/1590
fix pypi long description by @eUgEntOptIc44 in https://github.com/gitpython-developers/GitPython/pull/1603
Don't rely on del by @r-darwish in https://github.com/gitpython-developers/GitPython/pull/1606
Block insecure non-multi options in clone/clone_from by @Beuc in https://github.com/gitpython-developers/GitPython/pull/1609
New Contributors
@Hawk777 made their first contribution in https://github.com/gitpython-developers/GitPython/pull/1590
@eUgEntOptIc44 made their first contribution in https://github.com/gitpython-developers/GitPython/pull/1603
@r-darwish made their first contribution in https://github.com/gitpython-developers/GitPython/pull/1606
@Beuc made their first contribution in https://github.com/gitpython-developers/GitPython/pull/1609
Full Changelog: https://github.com/gitpython-developers/GitPython/compare/3.1.31...3.1.32
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2128093053 | chore(deps): update common-dev-assets digest to 3324eff
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| gharchive/pull-request | 2024-02-10T04:43:03 | 2025-04-01T06:45:58.401608 | {
"authors": [
"terraform-ibm-modules-dev",
"terraform-ibm-modules-ops"
],
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2498556996 | chore(deps): update ci dependencies
This PR contains the following updates:
Package
Type
Update
Change
common-dev-assets
digest
0b1411f -> 5b96dd7
github.com/terraform-ibm-modules/ibmcloud-terratest-wrapper
require
minor
v1.37.2 -> v1.38.1
Release Notes
terraform-ibm-modules/ibmcloud-terratest-wrapper (github.com/terraform-ibm-modules/ibmcloud-terratest-wrapper)
v1.38.1
Compare Source
Bug Fixes
deps: update gomod (#857) (87710ff)
v1.38.0
Compare Source
Features
add function to check ingress health status of a cluster (#751) - Added new function testhelper.CheckClusterIngressHealthy() which can be used in Terraform tests to validate the status of an OpenShift cluster (801dd27)
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Details:
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v0.67.0 -> v0.68.1
github.com/gruntwork-io/terratest
v0.47.0 -> v0.47.1
github.com/hashicorp/go-getter
v1.7.5 -> v1.7.6
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| gharchive/pull-request | 2024-08-31T02:12:01 | 2025-04-01T06:45:58.415932 | {
"authors": [
"terraform-ibm-modules-dev",
"terraform-ibm-modules-ops"
],
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2290489016 | fix(deps): update terraform ibm to latest for the deployable architecture solution
This PR contains the following updates:
Package
Type
Update
Change
ibm (source)
required_provider
minor
1.64.2 -> 1.65.0
Release Notes
IBM-Cloud/terraform-provider-ibm (ibm)
v1.65.0
Compare Source
Features
Support for VMware as a Service API
Datasources
ibm_vmaas_vdc
Resources
ibm_vmaas_vdc
Support for PowerVS
Datasources
ibm_pi_networks
Enhancements
align Projects terraform provider to latest API spec (5252)
Add power edge details to workspace data source (5205)
feat(tekton): add locked properties (5274)
Added support for IBM Cloud Logs atracker targets (5270)
Deprecate vtl attributes in data source/resource (5265)
Update PI Image import/export and capture cos region doc (5273)
CBR typeset change for cbr rule/zone and adding CBR retries (5246)
Fix data assignment APIs (5306)
feat: wrap provider to create new error structure (5278)
ODF workerpool support (5283)
fix(Cloud Databases):Incorporate new client-error-toolchain in datasources (5320)
Added IAM fields in enterprise create child account response (5313)
ODF 4.15 Templates for add-on and satellite (5316)
Added support for snapshot service tags (5326)
BugFixes
Fix deleting instances with replicant attribute set (5176)
fix access group resource: recreate ag when it is deleted outside terraform (5304)
fix(docs): fixed documents for network acl and rules (5302)
add fix for timeouts for observe logging resource (5300)
Produce error when selecting invalid region in toolchain service (5297)
Fix instance policy drift (5308)
fix access group members resource: recreate ag members when it is deleted outside terraform (5317)
updated host_flavor id docs (5323)
fix(docs): Fix bm initialization doc titile (5330)
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"authors": [
"terraform-ibm-modules-dev",
"terraform-ibm-modules-ops"
],
"repo": "terraform-ibm-modules/terraform-ibm-icd-elasticsearch",
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2663487691 | chore(deps): update ci dependencies
This PR contains the following updates:
Package
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Change
common-dev-assets
digest
95f6c1e -> 81754c2
github.com/terraform-ibm-modules/ibmcloud-terratest-wrapper
require
patch
v1.41.4 -> v1.41.5
Release Notes
terraform-ibm-modules/ibmcloud-terratest-wrapper (github.com/terraform-ibm-modules/ibmcloud-terratest-wrapper)
v1.41.5
Compare Source
Bug Fixes
deps: update module github.com/ibm/vpc-go-sdk to v0.62.0 (#896) (f84c9e7)
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| gharchive/pull-request | 2024-11-15T23:39:39 | 2025-04-01T06:45:58.463449 | {
"authors": [
"terraform-ibm-modules-dev",
"terraform-ibm-modules-ops"
],
"repo": "terraform-ibm-modules/terraform-ibm-icd-postgresql",
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1638784985 | chore(deps): update common-dev-assets digest to 8039123
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2034463873 | chore(deps): update common-dev-assets digest to dfefa07
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2277447930 | Customise some input variables in ibm_catalog.json
Review all your input variables in https://github.com/terraform-ibm-modules/terraform-ibm-mas/blob/main/solutions/existing-cluster/variables.tf and for any that can be customised (e.g. dropdown pickers) please add them into the ibm_catalog.json with the customisations.
As an example, you might wish to convert the region input variable into a dropdown like was done for landing zone here.
And maybe add a custom dropdown list for deployment_flavour that only shows core and manage in the dropdown. For example of custom dropdown, see this.
Re-opening, the PR is now yet merged
PR is now merged - closing
| gharchive/issue | 2024-05-03T11:05:17 | 2025-04-01T06:45:58.478243 | {
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1772536041 | chore(deps): update common-dev-assets digest to 0b2bca3
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2229489834 | chore(deps): update common-dev-assets digest to 2285d99
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1761648181 | chore(deps): update module github.com/terraform-ibm-modules/ibmcloud-terratest-wrapper to v1.10.5
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github.com/terraform-ibm-modules/ibmcloud-terratest-wrapper
require
patch
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terraform-ibm-modules/ibmcloud-terratest-wrapper
v1.10.5
Compare Source
Bug Fixes
deps: update module golang.org/x/crypto to v0.10.0 (#566) (5e52db4)
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2447281454 | fix(deps): update terraform ibm to latest for the deployable architecture solution
This PR contains the following updates:
Package
Type
Update
Change
ibm (source)
required_provider
minor
1.67.1 -> 1.68.0
Release Notes
IBM-Cloud/terraform-provider-ibm (ibm)
v1.68.0
Compare Source
Features
Support CBR
Datasources
ibm_cbr_zone_addresses
Resources
ibm_cbr_zone_addresses
Support CIS
Datasources
ibm_cis_origin_certificates
Resources
ibm_cis_advanced_certificate_pack_order
ibm_cis_origin_certificate_order
Support VPC
Resources
ibm_is_bare_metal_server_initialization
Enhancements
Add dhcp network support for stratos (5503)
IAM Policy Assignment: S2S Policy Assignments (5499)
Code Engine Provider and Documentation Update (5347)
move wait_till logic into function, integrate it into vpc_cluster datasource (5476)
Remove hardcoded values for private and direct cos config endpoint (5484)
feat(bm-dynamic-bandwidth): Support for bandwidth in bare metal (5493)
Doc update for ODF (5454)
feat(fs-cross-account): Support for file share cross account access (5510)
feat Bm firmware update (5519)
Changing the documentation for SCC (5456)
feat(lb-parameterized-redirect): Update doc to specify parameterized url redirect (5521)
chore(Cloud-Databases): Remove Datastax (5511)
feat(ResourceController): Added onetime_credentials to ResourceInstance and ResourceKey read schemas (5532)
Add PhysicalAddress and CapabilitiesManagedBySatellite to Terraform SatelliteLocation (5530)
Added support for bm reinitialization (5520)
BugFixes
fix(CIS): updating managed ruleset documents (5488)
fix(ins-keys): Make VSI keys optional (5518)
fix(is-volume): Set catalogoffering computed attribute empty list (5514)
add import_on_create param to ibm_container_vpc_worker_pool doc (5506)
[Doc]Update Doc for E1080 Support (5536)
Fix(iam-identity):trusted profile templates (5440)
S2S documentation note for ibm_kms_key and minor linting fixes (5529)
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2229496346 | chore(deps): update common-dev-assets digest to 2285d99
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"repo": "terraform-ibm-modules/terraform-ibm-scc-da",
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2739427643 | fix(deps): update required_provider to latest for deployable architectures
This PR contains the following updates:
Package
Type
Update
Change
ibm (source)
required_provider
minor
1.71.3 -> 1.72.2
kubernetes (source)
required_provider
minor
2.33.0 -> 2.35.0
Release Notes
IBM-Cloud/terraform-provider-ibm (ibm)
v1.72.2
Compare Source
BugFixes
Fix the issue of loading IAM endpoints either for stage or file (5866)
v1.72.1
Compare Source
BugFixes
Breaking change fix Revert "Add version validation (5859)
v1.72.0
Compare Source
Features
Support for Db2 SaaS
Resources
ibm_db2
Datasources
ibm_db2
Support for IAM
Datasources
ibm_iam_effective_account_settings
Support for MQaaS
-Resources
- ibm_mqcloud_virtual_private_endpoint_gateway
Datasources
ibm_mqcloud_virtual_private_endpoint_gateway
ibm_mqcloud_virtual_private_endpoint_gateways
Support for VPC
Datasources
ibm_is_cluster_network
ibm_is_cluster_networks
ibm_is_cluster_network_interface
ibm_is_cluster_network_interfaces
ibm_is_cluster_network_profile
ibm_is_cluster_network_profiles
ibm_is_cluster_network_subnet
ibm_is_cluster_network_subnets
ibm_is_cluster_network_subnet_reserved_ip
ibm_is_cluster_network_subnet_reserved_ips
ibm_is_instance_cluster_network_attachment
ibm_is_instance_cluster_network_attachments
Resources
ibm_is_cluster_network_interface
ibm_is_cluster_network_subnet_reserved_ip
ibm_is_cluster_network_subnet
ibm_is_cluster_network
ibm_is_instance_cluster_network_attachment
Support for Power System
Datasources
ibm_pi_network_peers
Enhancements
Add version validation (5791)
Refactor shared-processor-pool resource (5796)
Refactor Cloud Connection Network Attach (5781)
Import a resource provisioned with key_protect_id and key_protect_instance attributes set (5798)
enable commit while creating template/version (5797)
ListClassicWorkers => ListAllWorkers (5784)
chore: update mirroring example doc (5767)
Update resource_instance.html.markdown (5806)
fix(cloud-databases): Refactor tests Part 1 (5810)
feat(BM-Reservations-Automatic-Attachment): Baremetal Server Reservations and Reservations Automatic Attachment (5805)
Support enable secure-by-default (5751)
Added support for volume_prototypes on ibm_is_instance resource (5777)
ODF 4.16 terraform support (5789)
Add Chenai to the doc (5813)
ibm_pag_instance should force a new instance when parameters_json are updated (5807)
Add power private datacenter capabilities (5833)
fixed instance, instance template documents, alignment (5850)
fix: instance cluster network attachment update (5853)
Custom Diff User Tags (5844)
added primary_ip refernce to nac for consistency (5847)
BugFixes
ICD: Promote read replicas (5738)
docs(pps): Remove SA notes fpr private path service gateway feature (5788)
Fix sap profile datasource warning (5779)
fixed documents for is datasources (5782)
fix: eventstreams sarama clientid (5802)
fix(ibm_is_image): 404 error fix on datasource (5769)
fix(ibm_is_share): 404 error fix on datasource (5770)
fix(ibm_is_snapshot): 404 error fix on datasource (5771)
vol fix for snapshot crn (5815)
fix: adjust validation for Code Engine application scale_concurrency_target (5792)
hashicorp/terraform-provider-kubernetes (kubernetes)
v2.35.0
Compare Source
FEATURES:
resources_kubernetes_daemon_set_v1 : Added max_surge argument for to rolling_update block. [GH-2630]
v2.34.0
Compare Source
ENHANCEMENTS:
Added conditions attribute to kubernetes_nodes data source, which will provide detailed node health and status information [GH-2612]
Adding the kubernetes_secret_v1_data resource to the kubernetes provider. This resource will allow users to manage kubernetes secrets [GH-2604]
Properly handle Kubernetes Jobs with ttl_seconds_after_finished = 0 to prevent unnecessary recreation. [GH-2596]
FEATURES:
New ephemeral resource: kubernetes_certificate_signing_request_v1 [GH-2628]
New ephemeral resource: kubernetes_token_request_v1 [GH-2628]
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| gharchive/pull-request | 2024-12-14T01:14:12 | 2025-04-01T06:45:58.571054 | {
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"terraform-ibm-modules-ops"
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"repo": "terraform-ibm-modules/terraform-ibm-scc-workload-protection-agent",
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2746415045 | chore(deps): update common-dev-assets digest to 5f5fd35
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| gharchive/pull-request | 2024-12-18T00:27:08 | 2025-04-01T06:45:58.576458 | {
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"terraform-ibm-modules-ops"
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"repo": "terraform-ibm-modules/terraform-ibm-secrets-manager-public-cert",
"url": "https://github.com/terraform-ibm-modules/terraform-ibm-secrets-manager-public-cert/pull/140",
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1679258847 | chore(deps): update module github.com/terraform-ibm-modules/ibmcloud-terratest-wrapper to v1.8.9
This PR contains the following updates:
Package
Type
Update
Change
github.com/terraform-ibm-modules/ibmcloud-terratest-wrapper
require
patch
v1.8.8 -> v1.8.9
Release Notes
terraform-ibm-modules/ibmcloud-terratest-wrapper
v1.8.9
Compare Source
Bug Fixes
deps: update module github.com/ibm/platform-services-go-sdk to v0.36.0 (#528) (f4a94b5)
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1619791709 | chore(deps): update common-dev-assets digest to 04de466
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"authors": [
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"repo": "terraform-ibm-modules/terraform-ibm-transit-gateway",
"url": "https://github.com/terraform-ibm-modules/terraform-ibm-transit-gateway/pull/205",
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2512085749 | chore(deps): update terraform-module
This PR contains the following updates:
Package
Type
Update
Change
github.com/terraform-ibm-modules/terraform-ibm-landing-zone
module
patch
v5.31.1 -> v5.31.2
terraform-ibm-modules/base-ocp-vpc/ibm (source)
module
patch
3.30.0 -> 3.30.1
Release Notes
terraform-ibm-modules/terraform-ibm-landing-zone (github.com/terraform-ibm-modules/terraform-ibm-landing-zone)
v5.31.2
Compare Source
Bug Fixes
added outputs for workload/management cluster names (#875) (a6b3f6e)
terraform-ibm-modules/terraform-ibm-base-ocp-vpc (terraform-ibm-modules/base-ocp-vpc/ibm)
v3.30.1
Compare Source
Bug Fixes
deps: update terraform-module (#512) (3aecbb6)
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@ocofaigh
we need to add the same change on TestRunSLZExample test
adding it
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:tada: This PR is included in version 1.4.25 :tada:
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| gharchive/pull-request | 2024-09-07T21:33:47 | 2025-04-01T06:45:58.605176 | {
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466404712 | Kayrus optional parameters
Addressing #230, #205, and #190 where GITHUB_TOKEN should not be required for all data sources.
Before fix:
Error: GET https://api.github.com/users/hashibot: 401 Bad credentials []
on /var/folders/nj/n5hr70hd2dx45qb__6wl10nc0000gp/T/tf-test353694711/main.tf line 6:
(source code not available)
FAIL
After fix:
== RUN TestProvider_anonymous
--- PASS: TestProvider_anonymous (1.04s)
PASS
@megan07 when are you going to make the release with this feature?
| gharchive/pull-request | 2019-07-10T16:24:55 | 2025-04-01T06:45:58.689090 | {
"authors": [
"kayrus",
"megan07"
],
"repo": "terraform-providers/terraform-provider-github",
"url": "https://github.com/terraform-providers/terraform-provider-github/pull/255",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
2064240440 | V1.5.0 release changes
Update Changelog
Change Examples links to use v1.5.0 tag
/lgtm
/approve
| gharchive/pull-request | 2024-01-03T15:38:45 | 2025-04-01T06:45:58.740086 | {
"authors": [
"bardielle",
"nirarg"
],
"repo": "terraform-redhat/terraform-provider-rhcs",
"url": "https://github.com/terraform-redhat/terraform-provider-rhcs/pull/487",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
1045438669 | Remove file name checks when reading in RIPL data.
Remove check for number of files and file names when reading the RIPL data into the nuclide bases. This check was found to be incorrect for the latest version of RIPL (from 7/12/2020) where the file names were no longer labeled as z000.dat to z117.dat. Instead they were changed to z001.dat to z118.dat.
On balance, it seems like a clear, easy-to-understand change. The obvious questions I have are:
Now that we have removed this check, what if one or more files are missing? Will the user know why their run failed?
Why not add in a simpler check to make sure that there are >= 118 files named *.dat? (That does mostly the same thing, but is a bit more future proof.)
Hi @john-science -
These are good questions and I will add the responses here on the PR so we can track them:
The original implementation was to make sure that this was checked, but the way that this functions now is that the nuclideBases will be populated based on the zXXX.dat files. There are missing zXXX.dat files then some of the nuclideBases may not be initialized and therefore the if some client code needs that nuclide then a KeyError exception will be thrown.
We could check the number of files, but that may not be future proof. I could add at least 118 files possibly, if that helps?
| gharchive/pull-request | 2021-11-05T04:16:21 | 2025-04-01T06:45:58.752975 | {
"authors": [
"jakehader",
"john-science"
],
"repo": "terrapower/armi",
"url": "https://github.com/terrapower/armi/pull/462",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
1608403614 | default threads=1?
currently 8, but that's probably not an appropriate default.
Pros:
avoids users needing to remember to set the number of threads; in most cases, we can expect that they'll want multi-threaded indexing and retrieval
nearly free speedup
Cons:
Easy for folks to mistakenly measure query throughput, rather than latency
8 threads will rarely be optimal, machines will often have more threads that should be used. Or users may have multiple processes going at once without realising that Pisa is multi-threaded, causing thrashing
fixed
| gharchive/issue | 2023-03-03T10:46:42 | 2025-04-01T06:45:58.756280 | {
"authors": [
"seanmacavaney"
],
"repo": "terrierteam/pyterrier_pisa",
"url": "https://github.com/terrierteam/pyterrier_pisa/issues/17",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
2104419923 | 똥피하기게임_신준원
A,D / <-, -> - 좌우 이동
스페이스바 - 총 쏘기
설명 추가
| gharchive/pull-request | 2024-01-29T00:18:09 | 2025-04-01T06:45:58.778285 | {
"authors": [
"tesia102"
],
"repo": "tesia102/Avoid_Ddong_And_Shoot",
"url": "https://github.com/tesia102/Avoid_Ddong_And_Shoot/pull/1",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
1480024461 | 🛑 racl.kr is down
In f5d9781, racl.kr (https://racl.kr) was down:
HTTP code: 500
Response time: 3265 ms
Resolved: racl.kr is back up in 9a25d27.
| gharchive/issue | 2022-12-06T19:45:42 | 2025-04-01T06:45:58.782980 | {
"authors": [
"teslamint"
],
"repo": "teslamint/uptime",
"url": "https://github.com/teslamint/uptime/issues/179",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
468028488 | Adding confidential threshold on output
Where can I obtain the degree of confidence that every word tesseract recognized?
I'm dealing with important messages that would better be left as blank than mistakenly translated. I want to set up a threshold to let tesseract output "?" if the degree of confidence for a given word/character is low. Is it possible?
Environment
Tesseract 4.0
ubuntu 64-bit
Please respect guidelines for posting issue: use tesseract user forum for asking questions/support.
| gharchive/issue | 2019-07-15T09:32:30 | 2025-04-01T06:45:58.788550 | {
"authors": [
"zdenop",
"zguoguo"
],
"repo": "tesseract-ocr/tesseract",
"url": "https://github.com/tesseract-ocr/tesseract/issues/2566",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
2397758314 | [Bug]: Finalizing JUnit 5 test case with Kafka Streams and Spring Boot takes several minutes
Module
Kafka
Testcontainers version
1.19.8
Using the latest Testcontainers version?
Yes
Host OS
MacOS, Linux, Windows
Host Arch
ARM, x86
Docker version
This is my local setup with Podman. In the pipeline we use Docker and other colleagues use Docker Desktop where the issue also happens.
Client: Docker Engine - Community
Version: 27.0.3
API version: 1.41 (downgraded from 1.46)
Go version: go1.22.4
Git commit: 7d4bcd863a
Built: Fri Jun 28 14:56:30 2024
OS/Arch: darwin/arm64
Context: default
Server: linux/arm64/fedora-40
Podman Engine:
Version: 5.0.3
APIVersion: 5.0.3
Arch: arm64
BuildTime: 2024-05-10T02:00:00+02:00
Experimental: false
GitCommit:
GoVersion: go1.22.2
KernelVersion: 6.8.8-300.fc40.aarch64
MinAPIVersion: 4.0.0
Os: linux
Conmon:
Version: conmon version 2.1.10, commit:
Package: conmon-2.1.10-1.fc40.aarch64
OCI Runtime (crun):
Version: crun version 1.14.4
commit: a220ca661ce078f2c37b38c92e66cf66c012d9c1
rundir: /run/crun
spec: 1.0.0
+SYSTEMD +SELINUX +APPARMOR +CAP +SECCOMP +EBPF +CRIU +LIBKRUN +WASM:wasmedge +YAJL
Package: crun-1.14.4-1.fc40.aarch64
Engine:
Version: 5.0.3
API version: 1.41 (minimum version 1.24)
Go version: go1.22.2
Git commit:
Built: Fri May 10 02:00:00 2024
OS/Arch: linux/arm64
Experimental: false
What happened?
We're running a Spring Boot project with Kafka Streams. We have one integration test (using @SpringBootTest and @Testcontainers) that sometimes takes several minutes to complete after all tests successfully ran. Lots of Kafka "no connection to node" and "Node 1 disconnected" are printed in the logs repeatedly.
It seems like the Kafka container is stopped before the Spring context is shutdown. And the Spring Context is waiting for Kafka to become available before shutting down.
Relevant log output
### The following 20 lines are printed repeatedly for several minutes
[11:00:35.147] [INFO] [org.apache.kafka.clients.NetworkClient] - [Consumer clientId=<our-consumer-group>-StreamThread-1-consumer, groupId=streams.notification-report-selector.notification-repartitioner] Node 1 disconnected.
[11:00:35.147] [WARN] [org.apache.kafka.clients.NetworkClient] - [Consumer clientId=<our-consumer-group>-StreamThread-1-consumer, groupId=streams.notification-report-selector.notification-repartitioner] Connection to node 1 (localhost/127.0.0.1:32772) could not be established. Node may not be available.
[11:00:35.218] [INFO] [org.apache.kafka.clients.NetworkClient] - [AdminClient clientId=<our-consumer-group>-admin] Node 1 disconnected.
[11:00:35.218] [WARN] [org.apache.kafka.clients.NetworkClient] - [AdminClient clientId=<our-consumer-group>-admin] Connection to node 1 (localhost/127.0.0.1:32772) could not be established. Node may not be available.
[11:00:35.350] [INFO] [org.apache.kafka.clients.NetworkClient] - [Producer clientId=producer-3] Node 1 disconnected.
[11:00:35.350] [WARN] [org.apache.kafka.clients.NetworkClient] - [Producer clientId=producer-3] Connection to node 1 (localhost/127.0.0.1:32772) could not be established. Node may not be available.
[11:00:35.591] [INFO] [org.apache.kafka.clients.NetworkClient] - [Producer clientId=<our-consumer-group>-StreamThread-1-producer] Node 1 disconnected.
[11:00:35.591] [WARN] [org.apache.kafka.clients.NetworkClient] - [Producer clientId=<our-consumer-group>-StreamThread-1-producer] Connection to node 1 (localhost/127.0.0.1:32772) could not be established. Node may not be available.
[11:00:35.782] [INFO] [org.apache.kafka.clients.NetworkClient] - [Producer clientId=producer-1] Node 1 disconnected.
[11:00:35.782] [WARN] [org.apache.kafka.clients.NetworkClient] - [Producer clientId=producer-1] Connection to node 1 (localhost/127.0.0.1:32772) could not be established. Node may not be available.
[11:00:36.072] [INFO] [org.apache.kafka.clients.NetworkClient] - [Producer clientId=producer-2] Node 1 disconnected.
[11:00:36.072] [WARN] [org.apache.kafka.clients.NetworkClient] - [Producer clientId=producer-2] Connection to node 1 (localhost/127.0.0.1:32772) could not be established. Node may not be available.
[11:00:36.148] [INFO] [org.apache.kafka.clients.NetworkClient] - [Consumer clientId=<our-consumer-group>-StreamThread-1-consumer, groupId=[<our-consumer-group>]] Node 1 disconnected.
[11:00:36.148] [WARN] [org.apache.kafka.clients.NetworkClient] - [Consumer clientId=<our-consumer-group>-StreamThread-1-consumer, groupId=[<our-consumer-group>]] Connection to node 1 (localhost/127.0.0.1:32772) could not be established. Node may not be available.
[11:00:36.221] [INFO] [org.apache.kafka.clients.NetworkClient] - [AdminClient clientId=<our-consumer-group>-admin] Node 1 disconnected.
[11:00:36.221] [WARN] [org.apache.kafka.clients.NetworkClient] - [AdminClient clientId=<our-consumer-group>-admin] Connection to node 1 (localhost/127.0.0.1:32772) could not be established. Node may not be available.
[11:00:36.370] [INFO] [org.apache.kafka.clients.NetworkClient] - [Producer clientId=producer-3] Node 1 disconnected.
[11:00:36.371] [WARN] [org.apache.kafka.clients.NetworkClient] - [Producer clientId=producer-3] Connection to node 1 (localhost/127.0.0.1:32772) could not be established. Node may not be available.
[11:00:36.544] [INFO] [org.apache.kafka.clients.NetworkClient] - [Producer clientId=<our-consumer-group>-StreamThread-1-producer] Node 1 disconnected.
[11:00:36.544] [WARN] [org.apache.kafka.clients.NetworkClient] - [Producer clientId=<our-consumer-group>-StreamThread-1-producer] Connection to node 1 (localhost/127.0.0.1:32772) could not be established. Node may not be available.
[11:00:36.731] [INFO] [org.apache.kafka.clients.admin.internals.AdminMetadataManager] - [AdminClient clientId=<our-consumer-group>-admin] Metadata update failed
org.apache.kafka.common.errors.TimeoutException: Timed out waiting for a node assignment. Call: fetchMetadata
[11:00:36.804] [INFO] [org.apache.kafka.clients.NetworkClient] - [Producer clientId=producer-1] Node 1 disconnected.
[11:00:36.804] [WARN] [org.apache.kafka.clients.NetworkClient] - [Producer clientId=producer-1] Connection to node 1 (localhost/127.0.0.1:32772) could not be established. Node may not be available.
[11:00:36.925] [INFO] [org.apache.kafka.clients.NetworkClient] - [Producer clientId=producer-2] Node 1 disconnected.
[11:00:36.925] [WARN] [org.apache.kafka.clients.NetworkClient] - [Producer clientId=producer-2] Connection to node 1 (localhost/127.0.0.1:32772) could not be established. Node may not be available.
### The following log lines are only printed once at when the tests are finalized
Error: 1:00:36.961] [ERROR] [org.apache.kafka.streams.processor.internals.TaskExecutor] - stream-thread [<our-consumer-group>-StreamThread-1] Committing task(s) 0_1 failed.
org.apache.kafka.common.errors.TimeoutException: Timeout of 60000ms expired before successfully committing offsets {notification.managed-1=OffsetAndMetadata{offset=5, leaderEpoch=null, metadata='AgAAAZCWstBN'}}
Error: 1:00:36.961] [ERROR] [org.apache.kafka.streams.processor.internals.TaskManager] - stream-thread [<our-consumer-group>-StreamThread-1] Exception caught while committing tasks [TaskId: 0_1
ProcessorTopology:
Notifications:
topics: [notification.managed]
children: [Event-Type-Filter]
Event-Type-Filter:
children: [Key-Selector]
Key-Selector:
children: [Notifications-By-Id]
Notifications-By-Id:
topic: StaticTopicNameExtractor(notification.by-id)
Partitions [notification.managed-1]
]
org.apache.kafka.common.errors.TimeoutException: Timeout of 60000ms expired before successfully committing offsets {notification.managed-1=OffsetAndMetadata{offset=5, leaderEpoch=null, metadata='AgAAAZCWstBN'}}
[11:00:36.961] [INFO] [org.apache.kafka.streams.processor.internals.StreamTask] - stream-thread [<our-consumer-group>-StreamThread-1] task [0_0] Suspended from RUNNING
[11:00:36.962] [INFO] [org.apache.kafka.streams.processor.internals.RecordCollectorImpl] - stream-thread [<our-consumer-group>-StreamThread-1] stream-task [0_0] Closing record collector dirty
[11:00:36.962] [INFO] [org.apache.kafka.streams.processor.internals.StreamTask] - stream-thread [<our-consumer-group>-StreamThread-1] task [0_0] Closed dirty
[11:00:36.962] [INFO] [org.apache.kafka.streams.processor.internals.StreamTask] - stream-thread [<our-consumer-group>-StreamThread-1] task [0_1] Suspended from RUNNING
[11:00:36.963] [INFO] [org.apache.kafka.streams.processor.internals.RecordCollectorImpl] - stream-thread [<our-consumer-group>-StreamThread-1] stream-task [0_1] Closing record collector dirty
[11:00:36.963] [INFO] [org.apache.kafka.streams.processor.internals.StreamTask] - stream-thread [<our-consumer-group>-StreamThread-1] task [0_1] Closed dirty
[11:00:36.963] [INFO] [org.apache.kafka.clients.producer.KafkaProducer] - [Producer clientId=<our-consumer-group>-StreamThread-1-producer] Closing the Kafka producer with timeoutMillis = 9223372036854775807 ms.
[11:00:36.966] [INFO] [org.apache.kafka.common.metrics.Metrics] - Metrics scheduler closed
[11:00:36.966] [INFO] [org.apache.kafka.common.metrics.Metrics] - Closing reporter org.apache.kafka.common.metrics.JmxReporter
[11:00:36.966] [INFO] [org.apache.kafka.common.metrics.Metrics] - Closing reporter org.apache.kafka.common.telemetry.internals.ClientTelemetryReporter
[11:00:36.966] [INFO] [org.apache.kafka.common.metrics.Metrics] - Metrics reporters closed
[11:00:36.967] [INFO] [org.apache.kafka.common.utils.AppInfoParser] - App info kafka.producer for <our-consumer-group>-StreamThread-1-producer unregistered
Error: 1:00:36.967] [ERROR] [org.apache.kafka.streams.processor.internals.StreamThread] - stream-thread [<our-consumer-group>-StreamThread-1] Failed to close task manager due to the following error:
org.apache.kafka.common.errors.TimeoutException: Timeout of 60000ms expired before successfully committing offsets {notification.managed-1=OffsetAndMetadata{offset=5, leaderEpoch=null, metadata='AgAAAZCWstBN'}}
[11:00:36.967] [INFO] [org.apache.kafka.clients.consumer.internals.LegacyKafkaConsumer] - [Consumer clientId=<our-consumer-group>-StreamThread-1-restore-consumer, groupId=null] Unsubscribed all topics or patterns and assigned partitions
[11:00:36.967] [INFO] [org.apache.kafka.common.metrics.Metrics] - Metrics scheduler closed
[11:00:36.967] [INFO] [org.apache.kafka.common.metrics.Metrics] - Closing reporter org.apache.kafka.common.metrics.JmxReporter
[11:00:36.967] [INFO] [org.apache.kafka.common.metrics.Metrics] - Closing reporter org.apache.kafka.common.telemetry.internals.ClientTelemetryReporter
[11:00:36.967] [INFO] [org.apache.kafka.common.metrics.Metrics] - Metrics reporters closed
[11:00:36.970] [INFO] [org.apache.kafka.common.utils.AppInfoParser] - App info kafka.consumer for <our-consumer-group>-StreamThread-1-consumer unregistered
[11:00:36.970] [INFO] [org.apache.kafka.common.metrics.Metrics] - Metrics scheduler closed
[11:00:36.970] [INFO] [org.apache.kafka.common.metrics.Metrics] - Closing reporter org.apache.kafka.common.metrics.JmxReporter
[11:00:36.970] [INFO] [org.apache.kafka.common.metrics.Metrics] - Closing reporter org.apache.kafka.common.telemetry.internals.ClientTelemetryReporter
[11:00:36.970] [INFO] [org.apache.kafka.common.metrics.Metrics] - Metrics reporters closed
[11:00:36.972] [INFO] [org.apache.kafka.common.utils.AppInfoParser] - App info kafka.consumer for <our-consumer-group>-StreamThread-1-restore-consumer unregistered
[11:00:36.973] [INFO] [org.apache.kafka.streams.processor.internals.StreamThread] - stream-thread [<our-consumer-group>-StreamThread-1] State transition from PENDING_SHUTDOWN to DEAD
[11:00:36.973] [INFO] [org.apache.kafka.streams.processor.internals.StreamThread] - stream-thread [<our-consumer-group>-StreamThread-1] Shutdown complete
[11:00:36.973] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Shutdown 1 stream threads complete
[11:00:36.973] [INFO] [org.apache.kafka.common.utils.AppInfoParser] - App info kafka.admin.client for <our-consumer-group>-admin unregistered
[11:00:36.973] [INFO] [org.apache.kafka.clients.admin.internals.AdminMetadataManager] - [AdminClient clientId=<our-consumer-group>-admin] Metadata update failed
org.apache.kafka.common.errors.TimeoutException: The AdminClient thread has exited. Call: fetchMetadata
[11:00:36.973] [INFO] [org.apache.kafka.clients.admin.KafkaAdminClient] - [AdminClient clientId=<our-consumer-group>-admin] Timed out 1 remaining operation(s) during close.
[11:00:36.984] [INFO] [org.apache.kafka.common.metrics.Metrics] - Metrics scheduler closed
[11:00:36.984] [INFO] [org.apache.kafka.common.metrics.Metrics] - Closing reporter org.apache.kafka.common.metrics.JmxReporter
[11:00:36.984] [INFO] [org.apache.kafka.common.metrics.Metrics] - Metrics reporters closed
[11:00:36.984] [INFO] [org.apache.kafka.common.metrics.Metrics] - Metrics scheduler closed
[11:00:36.984] [INFO] [org.apache.kafka.common.metrics.Metrics] - Closing reporter org.apache.kafka.common.metrics.JmxReporter
[11:00:36.984] [INFO] [org.apache.kafka.common.metrics.Metrics] - Metrics reporters closed
[11:00:36.985] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] State transition from PENDING_SHUTDOWN to NOT_RUNNING
[11:00:36.985] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client stopped completely
[11:00:37.006] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal NOT_RUNNING state, all resources are closed and the client has stopped.
[11:00:37.007] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal NOT_RUNNING state, all resources are closed and the client has stopped.
[11:00:37.007] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal NOT_RUNNING state, all resources are closed and the client has stopped.
[11:00:37.007] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal NOT_RUNNING state, all resources are closed and the client has stopped.
[11:00:37.011] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal ERROR state, all resources are closed and the client has stopped.
[11:00:37.011] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal ERROR state, all resources are closed and the client has stopped.
[11:00:37.011] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal ERROR state, all resources are closed and the client has stopped.
[11:00:37.011] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal ERROR state, all resources are closed and the client has stopped.
[11:00:37.016] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal ERROR state, all resources are closed and the client has stopped.
[11:00:37.016] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal ERROR state, all resources are closed and the client has stopped.
[11:00:37.016] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal ERROR state, all resources are closed and the client has stopped.
[11:00:37.016] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal ERROR state, all resources are closed and the client has stopped.
[11:00:37.028] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal ERROR state, all resources are closed and the client has stopped.
[11:00:37.028] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal ERROR state, all resources are closed and the client has stopped.
[11:00:37.029] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal ERROR state, all resources are closed and the client has stopped.
[11:00:37.029] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal ERROR state, all resources are closed and the client has stopped.
[11:00:37.044] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal ERROR state, all resources are closed and the client has stopped.
[11:00:37.044] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal ERROR state, all resources are closed and the client has stopped.
[11:00:37.044] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal ERROR state, all resources are closed and the client has stopped.
[11:00:37.044] [INFO] [org.apache.kafka.streams.KafkaStreams] - stream-client [<our-consumer-group>] Streams client is already in the terminal ERROR state, all resources are closed and the client has stopped.
Additional Information
The issue seems to be mitigated to some extend (we wait < 10 seconds for the test to finalize) if we start the container manually in the @BeforeAll method, instead of using the @Testcontainers and @Container annotations.
Does anyone have a clue why this can happen? Or how I can investigate further?
Hi, do you a project to reproduce it?
I'll try to provide you with a minimal example today.
Sorry for the slow response. Here is the example repo: https://github.com/MarvinVaillant/demo-long-kafka-streams-teardown/tree/main
Here you'll also find a short video that shows the issue:
https://github.com/user-attachments/assets/535847ac-cbbc-4f72-b6c9-a09e682bf84e
@MarvinVaillant thanks for providing the example but I am not able to run the project. It fails because of Mapped port can only be obtained after the container is started. I can make some changes but I can not see the behavior described.
i'm really sorry. I was fiddeling around with the code to get some more insights. Could you please pull the latest commits?
Thanks for updating it. I'm moving this to a discussion because It is not an issue itself. Testcontainers is creating, running the container and killing it. However, in order to close the context you should call close explicitly or rather use @DirtiesContext. I do not have much experience on Kafka Streams but others can help on how to handle this.
| gharchive/issue | 2024-07-09T10:12:50 | 2025-04-01T06:45:58.954098 | {
"authors": [
"MarvinVaillant",
"eddumelendez"
],
"repo": "testcontainers/testcontainers-java",
"url": "https://github.com/testcontainers/testcontainers-java/issues/8867",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
1588646833 | Add windows build.
Adding a windows build as in #309 is not currently possible because windows-latest does not support running linux-based images (cf. https://github.com/actions/runner-images/issues/1143). The same seems to be true for CircleCI (see https://circleci.com/docs/using-windows/#known-issues-and-limitations) and Travis (see https://travis-ci.community/t/hyper-v-support-in-windows/2605/3). Once it is feasible, running automated tests could help address #303, #108, #101, and #99.
seems like this is fixed in #345?
| gharchive/issue | 2023-02-17T02:09:31 | 2025-04-01T06:45:58.957477 | {
"authors": [
"alexanderankin",
"tillahoffmann"
],
"repo": "testcontainers/testcontainers-python",
"url": "https://github.com/testcontainers/testcontainers-python/issues/310",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
2149424897 | Exception while running typefuzz on the remote server
Bug Description
While trying to use typefuzz on Ubuntu Linux
Linux mantella 5.4.0-159-generic #176-Ubuntu SMP Mon Aug 14 12:04:20 UTC 2023 x86_64 x86_64 x86_64 GNU/Linux
It returns an error, trying to iterate on argument of type "Term"
Note
Possibly it is due to the command, as cvc5 is not installed on the machine, and I try to provide it by giving the executable path in the command:
./bin/typefuzz "z3 model_validate=true;../cvc5/build/bin/cvc5 --check-models -m -i -q" ../opensmt/regression/QF_UF/NEQ004_size4.smt│2
Hi @wintered, thanks for the quick response.
I tried to run it with QF_LIA, but stubled into a different error
Any ideas what could have caused it?
| gharchive/issue | 2024-02-22T16:12:12 | 2025-04-01T06:45:59.011308 | {
"authors": [
"BritikovKI"
],
"repo": "testsmt/yinyang",
"url": "https://github.com/testsmt/yinyang/issues/66",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
2238370297 | [Feature Request] feedback after setting volume
If i set the volume in Home Assistant, ideally it would blink the volume indicators on the device. Right now there is no feedback at all.
Also Google has the device "click" as sort of a "volume preview" when you turn it up or down. It should do that when setting the volume, regardless of manner.
Due to the mutex limitation in ESPHome, the click might not be possible when listening for wake word.
However, I agree it would be a nice thing to temporarily flash the volume LED configuration even when the volume is changed off-device.
| gharchive/issue | 2024-04-11T19:00:51 | 2025-04-01T06:45:59.012796 | {
"authors": [
"jherby2k",
"tetele"
],
"repo": "tetele/onju-voice-satellite",
"url": "https://github.com/tetele/onju-voice-satellite/issues/28",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
142066910 | docs(txtnode): Update document about TxtNode/TxtAST
Reflect update from "Compliances tests for TxtNode #141"
This update only reflect current status. It don't change anything.
Rename TxtSyntax to TxtAST https://github.com/textlint/textlint/blob/master/docs/txtnode.d.ts
Split TxtNodeto ParentNode(block) and TextNode(inline)
Define value property to TextNode
Add Compliance tests tool https://github.com/textlint/textlint-ast-test
Add note about https://github.com/wooorm/unist
Add notice for Processor plugin creator
@homu r+
:pushpin: Commit c05803a has been approved by azu
:zap: Test exempted - status
| gharchive/pull-request | 2016-03-19T14:34:07 | 2025-04-01T06:45:59.034139 | {
"authors": [
"azu",
"homu"
],
"repo": "textlint/textlint",
"url": "https://github.com/textlint/textlint/pull/170",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
593367224 | Musicalypse don't load library when starting
Hello!
I use Musicalypse with snap on Gallium OS.
The music folder has been added in settings (it's an external hard drive : /mnt...)
The first scan was OK
But after reboot, Musicalypse don't load this folder. He just memorizes the last song played.
How to fix it please?
(and : thanks for this beautiful design)
Hello,
Please try installing Musicalypse through the available AppImage directly. This might fix your issue.
It's what I did:
I downloaded the Musicalypse-1.0.0-x64.AppImage
Gave perrmissions
Set the external drive as source for music
Launch the first scan (the library filled with folders)
But when I quit and launch again Musicalype, the library looks empty.
(dommage, cette appli est classe ! :)
On launch, Musicalypse scans the library directory and removes any file that has been deleted or that it doesn't have access to anymore. I guess in your case the external drive might be unavailable on application start, hence the whole library is cleared. So you should make sure the external drive is indeed available whenever you launch Musicalypse.
To check this assertion maybe try to use a local folder with some music and see if the problem persists.
(Merci! ;)
Yes, that's it: Musicalypse remembers the local music folder.
Thanks!
(Et continuez : cette appli est vraiment très bien !)
| gharchive/issue | 2020-04-03T13:03:34 | 2025-04-01T06:45:59.121073 | {
"authors": [
"StephaneDeVannes",
"tgambet"
],
"repo": "tgambet/musicalypse",
"url": "https://github.com/tgambet/musicalypse/issues/8",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
121507485 | Why cant I save a related collection?
return new respond.Responses([{
response: 'response one.',
created_by: 'TestUser'
}, {
response: 'response two.',
created_by: 'TestUser'
}, {
response: 'response three.',
created_by: 'TestUser'
}]).invokeThen('save')
.then(function(responses) {
// This works, one at a time though
// return responses[0].related('triggers').create({
// trigger: 'trigger one',
// chance: 0.03,
// created_by: 'TestUser2'
// });
// This doesnt work
// ERROR
// Unhandled rejection Error: SQLITE_CONSTRAINT: NOT NULL constraint failed: trigger.response_id
responses[0].related('triggers').add([{
trigger: 'trigger one',
chance: 0.03,
created_by: 'TestUser2'
}, {
trigger: 'trigger two',
chance: 0.08,
created_by: 'TestUser2'
}]).invokeThen('save');
return;
})
var bookshelf = require('bookshelf')(knexContext);
var Response = bookshelf.Model.extend({
tableName: 'response',
hasTimestamps: true,
triggers: function() {
return this.hasMany(Trigger);
}
});
var Trigger = bookshelf.Model.extend({
tableName: 'trigger',
hasTimestamps: true,
respond: function() {
return this.belongsTo(Response);
}
})
var Responses = bookshelf.Collection.extend({
model: Response
});
var Triggers = bookshelf.Collection.extend({
model: Trigger
});
Setting response_id explicitly works for me:
var dbFile = './test.sqlite';
var knex = require('knex')({
client: 'sqlite3',
connection: {
filename: dbFile
}
});
var bookshelf = require('bookshelf')(knex);
var fs = require('fs');
if (fs.existsSync(dbFile)) {
fs.unlinkSync(dbFile);
}
var Response = bookshelf.Model.extend({
tableName: 'response',
hasTimestamps: true,
triggers: function() {
return this.hasMany(Trigger);
}
});
var Trigger = bookshelf.Model.extend({
tableName: 'trigger',
hasTimestamps: true,
respond: function() {
return this.belongsTo(Response);
}
});
var Responses = bookshelf.Collection.extend({
model: Response
});
var Triggers = bookshelf.Collection.extend({
model: Trigger
});
return knex.schema.createTable('response', function (table) {
table.increments();
table.string('response');
table.string('created_by');
table.timestamps();
})
.then(function () {
return knex.schema.createTable('trigger', function (table) {
table.increments();
table.integer('response_id').notNullable();
table.string('trigger');
table.float('chance');
table.string('created_by');
table.timestamps();
});
})
.then(function () {
return new Responses([{
response: 'response one.',
created_by: 'TestUser'
}, {
response: 'response two.',
created_by: 'TestUser'
}, {
response: 'response three.',
created_by: 'TestUser'
}])
.invokeThen('save')
.then(function(responses) {
return responses[0].related('triggers').add([{
response_id: responses[0].id,
trigger: 'trigger one',
chance: 0.03,
created_by: 'TestUser2'
}, {
response_id: responses[0].id,
trigger: 'trigger two',
chance: 0.08,
created_by: 'TestUser2'
}])
.invokeThen('save');
});
})
.then(function () {
return Response.fetchAll({ withRelated: 'triggers' })
.then(function (responses) {
console.log(require('util').inspect(responses.toJSON(), { depth: null }));
});
})
.finally(function () {
return knex.destroy();
});
$ node index.js
[ { id: 1,
response: 'response one.',
created_by: 'TestUser',
created_at: 1449775827903,
updated_at: 1449775827903,
triggers:
[ { id: 1,
response_id: 1,
trigger: 'trigger one',
chance: 0.03,
created_by: 'TestUser2',
created_at: 1449775827925,
updated_at: 1449775827925 },
{ id: 2,
response_id: 1,
trigger: 'trigger two',
chance: 0.08,
created_by: 'TestUser2',
created_at: 1449775827925,
updated_at: 1449775827925 } ] },
{ id: 2,
response: 'response two.',
created_by: 'TestUser',
created_at: 1449775827904,
updated_at: 1449775827904,
triggers: [] },
{ id: 3,
response: 'response three.',
created_by: 'TestUser',
created_at: 1449775827904,
updated_at: 1449775827904,
triggers: [] } ]
So why does create just figure
| gharchive/issue | 2015-12-10T15:11:51 | 2025-04-01T06:45:59.124230 | {
"authors": [
"LordWingZero",
"blah238"
],
"repo": "tgriesser/bookshelf",
"url": "https://github.com/tgriesser/bookshelf/issues/1060",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
2499650370 | 🛑 DDoS-Relay US-E-nyc1-01 is down
In 5aa2c7a, DDoS-Relay US-E-nyc1-01 (http://178.128.157.126:42069/;csv) was down:
HTTP code: 0
Response time: 0 ms
Resolved: DDoS-Relay US-E-nyc1-01 is back up in 6b2dc92 after 5 minutes.
| gharchive/issue | 2024-09-01T19:42:19 | 2025-04-01T06:45:59.127552 | {
"authors": [
"tgstation-server"
],
"repo": "tgstation-operations/status",
"url": "https://github.com/tgstation-operations/status/issues/582",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
996854505 | Replace/revamp master branch
[x] make npm the default branch
[ ] rename npm to (e.g.) release
[ ] check in with @layik re. unpublished commits on master
[ ] delete master
This is mainly to keep using GH functionality such as automatic issue closing etc.
The npm development is the way forward. ~However, the original fork is useful for people who might want to use it the way the original work was done.~ Now is the time for a new master/main branch.
Imported from #96:
For clarification, the branch was the main dev repo for eAtlas/TGVE and has now grown out of its purpose.
master branch is now way behind branch npm
branch npm is the most important part, npm-dev is where I do work and create PRs on npm.
Wiki is the main docs for "the project"
Dockerfile is based on "old" approach of building the front-end using JS tools (npm)
Must be done:
README to serve as pointer to Wiki/docs and other repo docs etc
master branch => npm branch?
etc
Consider doing:
??
#92
Closing #92 as a duplicate of this. Importing comment from that issue by @layik:
Thanks @LydiaFrance and @rolyp.
One thing that is prevented/preventing me from making my mind up is tgve/eatlas-template and tgve/full-template in terms of what a master branch should look like. Say we rename this repo as tgvejs (i.e this repository becomes the "source of truth"), then we would either keep those repositories or move them into an "example" folder in the same tgvejs repo and possibly build those as the GH pages output.
If we do keep them, and so far I am inclined towards this, as they are now, then maybe I need to just propose to rename master as master-old and rename npm as master. The importance of those two repositories can be documented, if not already, with their reasons.
Any thoughts on this would be great for me. Thanks
@layik Ah, there seem to be commits on master that haven't yet been published to npm, so things aren't straightforward. In particular README.md is quite different on the two branches. Need to discuss.
Indeed!
@layik Btw, I will (occasionally) work weird hours, e.g. at weekends. Please ignore any comments that come your way during those unusual hours (unless you wish to respond, of course)!
That makes two of us, glad you gave the warning first.
@layik I'll reopen this until we're able to delete old.
OK, I have pushed "old" = "master" to private repo for backup only.
| gharchive/issue | 2021-09-15T09:22:23 | 2025-04-01T06:45:59.330129 | {
"authors": [
"layik",
"rolyp"
],
"repo": "tgve/eAtlas",
"url": "https://github.com/tgve/eAtlas/issues/64",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
1289673049 | 🛑 SoundHound is down
In 30fc83c, SoundHound (https://www.soundhound.com) was down:
HTTP code: 403
Response time: 97 ms
Resolved: SoundHound is back up in c5487a9.
| gharchive/issue | 2022-06-30T06:43:06 | 2025-04-01T06:45:59.339440 | {
"authors": [
"thaaai"
],
"repo": "thaaai/upptime",
"url": "https://github.com/thaaai/upptime/issues/5",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
168414342 | Answer what Tomi was doing with the reserved value for the change counter
I've decided to check in 720 since it is passing tests. But I still need you to get an answer to this question.
change counter is used to determine if we should update peer properties. if old change counter!= new change counter or old peer properties==null android bluetooth lib will update peer properties.
org.thaliproject.p2p.btconnectorlib.utils.PeerModel#addOrUpdateDiscoveredPeer . So if it's new peer properties (with any value of change counter) it will be updated. Or if old change counter == 255 and new change counter ==0 .
| gharchive/issue | 2016-07-29T21:06:06 | 2025-04-01T06:45:59.360938 | {
"authors": [
"vasilevskayaem",
"yaronyg"
],
"repo": "thaliproject/Thali_CordovaPlugin",
"url": "https://github.com/thaliproject/Thali_CordovaPlugin/issues/810",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
2280253635 | [Bug] Non-proficient with shields not being triggered
Shields should have the same disadvantages as armor when it comes to non-proficiency.
Armor Proficiency. Anyone can put on a suit of armor or strap a shield to an arm. Only those proficient in the armor's use know how to wear it effectively, however. Your class gives you proficiency with certain types of armor. If you wear armor that you lack proficiency with, you have disadvantage on any ability check, saving throw, or attack roll that involves Strength or Dexterity, and you can't cast spells.
Tested with different shields, and armor. All armor worked as intended, no shields cause the disadvantage.
Shield Proficiency is obtained from Class Features, or the Moderately Armored feat.
Foundry - 11.315
DnD5e - 3.1.2
Good point. I haven't added Shields in the mix to be honest, cause I didn't think about it.
I will put it in the next release.
Thanks for that.
| gharchive/issue | 2024-05-06T07:40:44 | 2025-04-01T06:45:59.381527 | {
"authors": [
"glitchies",
"thatlonelybugbear"
],
"repo": "thatlonelybugbear/automated-conditions-5e",
"url": "https://github.com/thatlonelybugbear/automated-conditions-5e/issues/125",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
668423806 | Wrong compat bounds
Please don't have compat bounds like https://github.com/thautwarm/NameResolution.jl/blob/e0d52d57f6487faba685517ee88ff9fbbfcc707d/Project.toml#L13. You just broke my package which is three links down the depency chain with https://github.com/thautwarm/PrettyPrint.jl/releases/tag/v0.2.0. With that release, it's no longer possible to load this package and therefore also not possible to load any of the 14 packages that depend on this package.
Ref https://github.com/JuliaRegistries/General/pull/18713
| gharchive/issue | 2020-07-30T06:47:31 | 2025-04-01T06:45:59.383538 | {
"authors": [
"andreasnoack"
],
"repo": "thautwarm/NameResolution.jl",
"url": "https://github.com/thautwarm/NameResolution.jl/issues/3",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
475160614 | ReleaseNewVersion
does not work as a user command.
Fixed
| gharchive/issue | 2019-07-31T13:56:20 | 2025-04-01T06:45:59.391017 | {
"authors": [
"PaulMansour"
],
"repo": "the-carlisle-group/AcreTools",
"url": "https://github.com/the-carlisle-group/AcreTools/issues/10",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
253723900 | Question?
The next release will be for Laravel 5.5, or for both versions 5.4 & 5.5?
And please dont forget that many dependencies doesn't support Laravel 5.5(If you suggest migrating from 5.4 to 5.5) for now and dont forget your old users of Voyager to have new cool stuf
The new version of Voyager (1.0) will support Laravel 5.3, 5.4, and 5.5. It will not require any specific version to run, so it will not affect your project or its other dependencies.
Super @fletch3555 why did not I write earlier)))))))
| gharchive/issue | 2017-08-29T16:18:20 | 2025-04-01T06:45:59.396704 | {
"authors": [
"davodavodavo3",
"fletch3555"
],
"repo": "the-control-group/voyager",
"url": "https://github.com/the-control-group/voyager/issues/1614",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
256201972 | Permissions and menu items
Laravel Version: 5.5
Voyager Version: 1.0 dev
PHP Version: 7.1.1
Database Driver & Version: MySQL 5.6.12
Description:
Some items in the sidebar menu are not hidden, as they should according to the permissions I defined in the Roles page.
I noticed this problem for the Tools dropdown (if empty, it is visible but empty) and the Settings and Hooks pages.
Steps To Reproduce:
From a fresh installation, go to roles and edit permissions for any of them: uncheck Browse Database, Browse Compass, Menus, Settings and Admin/Browse Hooks permissions.
After signing in with a user having this edited role, the Tools dropdown, Settings and Hooks items are still visible.
Laravel Version: 5.5
Voyager Version: 1.0 dev
PHP Version: 7.1.5
Database Driver & Version: MySQL 5.7.17
I have same problem.
@fletch3555 , @jeremyargoud Looks like I've fixed the problem. But the code that checks the permissions must refactor to a fuction in package. I dont know where can i put it. So i dont send pull request.
File: vendor/tcg/voyager/resources/views/menu/admin_menu.blade.php
`
@php
if (Voyager::translatable($items)) {
$items = $items->load('translations');
}
@endphp
@foreach ($items as $item)
@php
$originalItem = $item;
if (Voyager::translatable($item)) {
$item = $item->translate($options->locale);
}
// TODO - still a bit ugly - can move some of this stuff off to a helper in the future.
$listItemClass = [];
$styles = null;
$linkAttributes = null;
if(url($item->link()) == url()->current())
{
array_push($listItemClass,'active');
}
//If have children, default false. we will check childs permissions!
if(!$originalItem->children->isEmpty()) {
$show_menu_item = false;
} else {
$show_menu_item = true;
}
// With Children Attributes
if(!$originalItem->children->isEmpty())
{
foreach($originalItem->children as $children)
{
if(url($children->link()) == url()->current())
{
array_push($listItemClass,'active');
}
// Childrens Permission Checker
$self_prefix = str_replace('/', '\/', $options->user->prefix);
$slug = str_replace('/', '', preg_replace('/^\/'.$self_prefix.'/', '', $children->link()));
if ($slug != '') {
// Get dataType using slug
$dataType = $options->user->dataTypes->first(function ($value) use ($slug) {
return $value->slug == $slug;
});
if ($dataType) {
// Check if datatype permission exist
$exist = $options->user->permissions->first(function ($value) use ($dataType) {
return $value->key == 'browse_'.$dataType->name;
});
} else {
// Check if admin permission exists
$exist = $options->user->permissions->first(function ($value) use ($slug) {
return $value->key == 'browse_'.$slug;
});
}
if ($exist) {
if (in_array($exist->key, $options->user->user_permissions)) {
$show_menu_item = true;
}
}
}
}
$linkAttributes = 'href="#' . str_slug($item->title, '-') .'-dropdown-element" data-toggle="collapse" aria-expanded="'. (in_array('active', $listItemClass) ? 'true' : 'false').'"';
array_push($listItemClass, 'dropdown');
}
else
{
$linkAttributes = 'href="' . url($item->link()) .'"';
}
// Permission Checker
$self_prefix = str_replace('/', '\/', $options->user->prefix);
$slug = str_replace('/', '', preg_replace('/^\/'.$self_prefix.'/', '', $item->link()));
if ($slug != '') {
// Get dataType using slug
$dataType = $options->user->dataTypes->first(function ($value) use ($slug) {
return $value->slug == $slug;
});
if ($dataType) {
// Check if datatype permission exist
$exist = $options->user->permissions->first(function ($value) use ($dataType) {
return $value->key == 'browse_'.$dataType->name;
});
} else {
// Check if admin permission exists
$exist = $options->user->permissions->first(function ($value) use ($slug) {
return $value->key == 'browse_'.$slug;
});
}
if ($exist) {
// Check if current user has access
if (!in_array($exist->key, $options->user->user_permissions)) {
continue;
}
}
}
@endphp
@if($show_menu_item)
<li class="{{ implode(" ", $listItemClass) }}">
<a {!! $linkAttributes !!} target="{{ $item->target }}">
<span class="icon {{ $item->icon_class }}"></span>
<span class="title">{{ $item->title }}</span>
</a>
@if(!$originalItem->children->isEmpty())
<div id="{{ str_slug($originalItem->title, '-') }}-dropdown-element" class="panel-collapse collapse {{ (in_array('active', $listItemClass) ? 'in' : '') }}">
<div class="panel-body">
@include('voyager::menu.admin_menu', ['items' => $originalItem->children, 'options' => $options, 'innerLoop' => true])
</div>
</div>
@endif
</li>
@endif
@endforeach
`
No need to post the whole file.... Please only post the suggested changes, or better yet, open a PR with the changes for us to review
@fletch3555 Thank you for fast feed back. PR for you to review.
https://github.com/the-control-group/voyager/pull/1783
| gharchive/issue | 2017-09-08T09:56:28 | 2025-04-01T06:45:59.405879 | {
"authors": [
"evrend",
"fletch3555",
"jeremyargoud"
],
"repo": "the-control-group/voyager",
"url": "https://github.com/the-control-group/voyager/issues/1684",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
285046603 | MacOS new features.
translate English to other languages
save notes
create files
Great going!
Fix the typos in activities.md
If I am not wrong Mac has Pages,Keynote and Numbers for the Microsoft equivalents, right?
yeah ! sorry , dint check those .
Great!
| gharchive/pull-request | 2017-12-29T07:23:27 | 2025-04-01T06:45:59.408398 | {
"authors": [
"Snehal-Reddy",
"the-ethan-hunt"
],
"repo": "the-ethan-hunt/B.E.N.J.I.",
"url": "https://github.com/the-ethan-hunt/B.E.N.J.I./pull/96",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
1599689462 | Add translation of PIDINST schema to pydantic
This PR simply adds a pydantic model for instruments that is a direct translation of the RDA PIDINST schema https://github.com/rdawg-pidinst/schema/blob/master/schema.rst.
They themselves provide two versions that includes a translation to DataCite's format. It's not clear how they expect this data to be reused.
I don't like the resource layout (it is very XML-y) so think we should use this as an example for having our own internally schema but being able to map out to others. I may offer to contribute this file back upstream to PIDINST (maybe as LinkML yaml instead) and see what they say.
Superseded by #531
| gharchive/pull-request | 2023-02-25T12:10:12 | 2025-04-01T06:45:59.412455 | {
"authors": [
"ml-evs"
],
"repo": "the-grey-group/datalab",
"url": "https://github.com/the-grey-group/datalab/pull/304",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
2054770436 | fix price of gpu shown on btc farm cost page
Used to show the GPU sell price, now properly shows the GPU buy price.
.deploy
.deploy
.deploy
.deploy
.deploy
.deploy
| gharchive/pull-request | 2023-12-23T12:14:17 | 2025-04-01T06:45:59.414177 | {
"authors": [
"Razzmatazzz"
],
"repo": "the-hideout/tarkov-dev",
"url": "https://github.com/the-hideout/tarkov-dev/pull/792",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
2368226298 | 1.21 Update
No rush, I know the version just came out. Just a nudge. It's been a godsend on my server in 1.20.6 and I'd be honored to have it in the server for 1.21 :)
Done.
Done.
| gharchive/issue | 2024-06-23T04:27:12 | 2025-04-01T06:45:59.430394 | {
"authors": [
"Proxi2",
"the-sh4d0w"
],
"repo": "the-sh4d0w/too-cheap",
"url": "https://github.com/the-sh4d0w/too-cheap/issues/3",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
2628096289 | 🛑 glance-probe is down
In 14512a4, glance-probe (https://glance.api.sjc3.rackspacecloud.com) was down:
HTTP code: 502
Response time: 9511 ms
Resolved: glance-probe is back up in b22cf93 after 1 hour, 33 minutes.
| gharchive/issue | 2024-11-01T01:06:02 | 2025-04-01T06:45:59.439012 | {
"authors": [
"the2hill"
],
"repo": "the2hill/rs-flex-uptime",
"url": "https://github.com/the2hill/rs-flex-uptime/issues/5",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
206084194 | Add Database Setup
Changes
Add docker postgres start and stop scripts
Add database migrations
Please Review: @sagersmith8
+1 looks pretty good, could we maybe put them in their own folder though?
Design Database
| gharchive/pull-request | 2017-02-08T03:15:37 | 2025-04-01T06:45:59.449129 | {
"authors": [
"Kuroshii",
"sagersmith8"
],
"repo": "theVite/vite_server",
"url": "https://github.com/theVite/vite_server/pull/18",
"license": "apache-2.0",
"license_type": "permissive",
"license_source": "bigquery"
} |
119724448 | Use with Apache Phoenix
I would like to output events from logstash to HBase, via Apache Phoenix:
https://phoenix.apache.org
My output configuration:
jdbc
{
connection_string => 'jdbc:phoenix://hbase'
statement => [ "upsert into test values (2,'World!')"]
}
I can see JAR is loaded because duplicate SLF4J errors:
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/opt/logstash/vendor/bundle/jruby/1.9/gems/logstash-output-jdbc-0.2.1/vendor/jar-dependencies/runtime-jars/slf4j-nop-1.7.13.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/opt/logstash/vendor/jar/jdbc/phoenix-4.6.0-HBase-1.1-client.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.helpers.NOPLoggerFactory]
Error:
{
: outgoing_count=>1,
: exception=>"Java::JavaLang::RuntimeException",
: backtrace=>[
"com.zaxxer.hikari.util.DriverDataSource.<init>(com/zaxxer/hikari/util/DriverDataSource.java:88)",
"com.zaxxer.hikari.pool.PoolBase.initializeDataSource(com/zaxxer/hikari/pool/PoolBase.java:296)",
"com.zaxxer.hikari.pool.PoolBase.<init>(com/zaxxer/hikari/pool/PoolBase.java:84)",
"com.zaxxer.hikari.pool.HikariPool.<init>(com/zaxxer/hikari/pool/HikariPool.java:103)",
"com.zaxxer.hikari.HikariDataSource.getConnection(com/zaxxer/hikari/HikariDataSource.java:94)",
"java.lang.reflect.Method.invoke(java/lang/reflect/Method.java:497)",
"LogStash::Outputs::Jdbc.safe_flush(/opt/logstash/vendor/bundle/jruby/1.9/gems/logstash-output-jdbc-0.2.1/lib/logstash/outputs/jdbc.rb:168)",
"LogStash::Outputs::Jdbc.safe_flush(/opt/logstash/vendor/bundle/jruby/1.9/gems/logstash-output-jdbc-0.2.1/lib/logstash/outputs/jdbc.rb:168)",
"LogStash::Outputs::Jdbc.flush(/opt/logstash/vendor/bundle/jruby/1.9/gems/logstash-output-jdbc-0.2.1/lib/logstash/outputs/jdbc.rb:116)",
"LogStash::Outputs::Jdbc.flush(/opt/logstash/vendor/bundle/jruby/1.9/gems/logstash-output-jdbc-0.2.1/lib/logstash/outputs/jdbc.rb:116)",
"Stud::Buffer.buffer_flush(/opt/logstash/vendor/bundle/jruby/1.9/gems/stud-0.0.22/lib/stud/buffer.rb:219)",
"Stud::Buffer.buffer_flush(/opt/logstash/vendor/bundle/jruby/1.9/gems/stud-0.0.22/lib/stud/buffer.rb:219)",
"org.jruby.RubyHash.each(org/jruby/RubyHash.java:1342)",
"Stud::Buffer.buffer_flush(/opt/logstash/vendor/bundle/jruby/1.9/gems/stud-0.0.22/lib/stud/buffer.rb:216)",
"Stud::Buffer.buffer_flush(/opt/logstash/vendor/bundle/jruby/1.9/gems/stud-0.0.22/lib/stud/buffer.rb:216)",
"Stud::Buffer.buffer_flush(/opt/logstash/vendor/bundle/jruby/1.9/gems/stud-0.0.22/lib/stud/buffer.rb:193)",
"Stud::Buffer.buffer_flush(/opt/logstash/vendor/bundle/jruby/1.9/gems/stud-0.0.22/lib/stud/buffer.rb:193)",
"RUBY.buffer_receive(/opt/logstash/vendor/bundle/jruby/1.9/gems/stud-0.0.22/lib/stud/buffer.rb:159)",
"RUBY.receive(/opt/logstash/vendor/bundle/jruby/1.9/gems/logstash-output-jdbc-0.2.1/lib/logstash/outputs/jdbc.rb:109)",
"RUBY.handle(/opt/logstash/vendor/bundle/jruby/1.9/gems/logstash-core-2.1.0-java/lib/logstash/outputs/base.rb:81)",
"RUBY.output_func((eval):323)",
"RUBY.outputworker(/opt/logstash/vendor/bundle/jruby/1.9/gems/logstash-core-2.1.0-java/lib/logstash/pipeline.rb:276)",
"RUBY.start_outputs(/opt/logstash/vendor/bundle/jruby/1.9/gems/logstash-core-2.1.0-java/lib/logstash/pipeline.rb:193)",
"java.lang.Thread.run(java/lang/Thread.java:745)"
],
: level=>: warn
}
Any idea? Thanks,
The SLF4J warning isn't ideal, but I don't think it's should actually be causing a problem. That said, I can't stand up a hbase instance to check today though :disappointed:
Couple of questions:
Does the error happen when logstash starts, or when an event is tried to be sent?
Looking at https://phoenix.apache.org/ the example connection strings don't include the preceding slashes before the hostname. I won't pretend to have ever looked at phoenix before - but have you tried without them? I don't know if phoenix is perhaps touchy about them?
Looks like connection string jdbc:phoenix:hbase:/hbase works actually !
I am not getting errors any more.
I keep you posted if it's working, that could mean you wrote a very nice plugin to output to HBase!
I'd love to know if it does or doesn't work :+1: If you have problems, let me know and I'll see what I can do.
If it does work if you could put together a sample configuration that would be amazing :smile:
Haaa
https://github.com/theangryangel/logstash-output-jdbc/blob/master/lib/logstash/outputs/jdbc.rb#L173
Took me some hours to figure out this! So with statements it's working fine! data are inserted into HBase, cool!
Thanks,
Ah sorry about that @ebuildy. I clearly didn't look at your example configuration very well :(
The code does assume that you're actually passing in some event data, which is why it has that check.
Would it have been helpful if we output a warning before skipping the event? Or do you have a use case where you wouldnt actually insert any event data (other than testing)? :)
Nop, was just for testing.
But a warning could save some lives in the futur ;-)
Added in 529c98aadb91dcb6e8a3db8ae976ad543178e8b8
| gharchive/issue | 2015-12-01T14:09:52 | 2025-04-01T06:45:59.509830 | {
"authors": [
"ebuildy",
"theangryangel"
],
"repo": "theangryangel/logstash-output-jdbc",
"url": "https://github.com/theangryangel/logstash-output-jdbc/issues/22",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
937191589 | typescript d.ts 和导入误报错
1.克隆任何一个 typescript 源码库，文件中的导入都会报错找不到模块。
2.d.ts 中 declare namespace cc 会报错 duplicate identifier cc
以上两个问题在 vscode 是正常的
3.应用里显示的是3.7.4，是否只是显示错误
4.下次大版本更新是否能更新到typescript 4.3，增加了 override ，很有用
感谢这么快速地更新到了4.2
这个有关多文件的支持，需要透过未来更新支援。目前编辑器只会分析已经开启的档案。
应该是bug，会尽快修复
对的，只是显示错误。编辑器的TypeScript版本需要透过app更新，但terminal内的tsc 可以用npm install -g typescript自行更新
4. 会的
感谢，比较致命的问题是第一点，导致现在我就算只是想在 ipad 上用 codeapp 预览一下代码都不太实用，希望能解决
明白，会尽量改善这问题。
能否进一步更新ts版本，我的项目使用了moduleResolution: NodeNext，目前完全不能正常使用。
我对 ios 开发很不熟悉，所以我没找到 TS 的引入位置，希望能够尽快得到支持（顺便改进了一下中文本地化）
我不认为这个问题被修复了，如果你觉得你已经不存在原问题，计划关闭的话，那我就新开一个。
@bummoblizard 感谢，请问有计划更新一下内置的ts版本么？不太清楚有什么困难，但至少ts不应该有ios适配方面的问题。
能够在ipad上临时应急改个项目还是不错的，（虽然已经有vscode.dev了）
@Mister-Hope 上游 Monaco Editor 仍在4.5.5。如果你真的需要，我可以手动更新它。
https://github.com/microsoft/monaco-editor/blob/f20e0c8d472bababab79108dff951ae09460c4ed/src/language/typescript/lib/typescriptServicesMetadata.ts#L5
恩恩，还是建议更新一下吧😅因为我在使用一些新版本的特性。
恩恩，还是建议更新一下吧😅因为我在使用一些新版本的特性。
懒得跟进了，作者有空就加吧
| gharchive/issue | 2021-07-05T15:21:32 | 2025-04-01T06:45:59.552865 | {
"authors": [
"Mister-Hope",
"TheSmallMain",
"bummoblizard",
"smallmain"
],
"repo": "thebaselab/codeapp",
"url": "https://github.com/thebaselab/codeapp/issues/179",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
1025031378 | Impossible to track events on iOS
🐛 Bug Report
I'm trying to log events from my app, but the events are not shown correctly in the events manager dashboard of Facebook.
I'm using all the settings from the Setup / Installation, i'm using the same FB account on the test device ( iPhone XR, iOS 15 ) and the only events that i can see are "fb_mobile_login_method_start" and "fb_mobile_login_start".
To Reproduce / Code Example
This is the javascript function that i'm calling for test.
After loading the main screen
Settings.initializeSDK();
await Settings.setAdvertiserTrackingEnabled(true);
By pressing one button
AppEventsLogger.logPurchase(Math.random(999), 'EUR', {
[AppEventsLogger.AppEventParams.ContentID]: `order-${Math.random(
9999,
).toString()}`,
});
Expected Behavior
The strange thing is that with the account of a colleague , the events are being tracked.
Environment
OS: macOS 11.6
CPU: (8) x64 Apple M1
Memory: 20.29 MB / 16.00 GB
Shell: 5.8 - /bin/zsh
Binaries:
Node: 15.6.0 - ~/.nvm/versions/node/v15.6.0/bin/node
Yarn: 1.22.15 - /usr/local/bin/yarn
npm: 7.4.0 - ~/.nvm/versions/node/v15.6.0/bin/npm
Watchman: 2021.10.04.00 - /usr/local/bin/watchman
Managers:
CocoaPods: 1.11.2 - /usr/local/bin/pod
SDKs:
iOS SDK:
Platforms: iOS 15.0, DriverKit 20.4, macOS 11.3, tvOS 15.0, watchOS 8.0
Android SDK: Not Found
IDEs:
Android Studio: 2020.3 AI-203.7717.56.2031.7678000
Xcode: 13.0/13A233 - /usr/bin/xcodebuild
Languages:
Java: Not Found
npmPackages:
@react-native-community/cli: Not Found
react: 17.0.2 => 17.0.2
react-native: 0.65.1 => 0.65.1
react-native-macos: Not Found
npmGlobalPackages:
*react-native*: Not Found
This is not actionable without some sort of reproducible example, apologies https://stackoverflow.com/help/minimal-reproducible-example
We are about to release with a bump of underlying ios sdk from 9 to 11, maybe that helps
if not we must have an example that reproducibly fails for anyone to offer any help
| gharchive/issue | 2021-10-13T09:50:40 | 2025-04-01T06:45:59.559086 | {
"authors": [
"Derewith",
"mikehardy"
],
"repo": "thebergamo/react-native-fbsdk-next",
"url": "https://github.com/thebergamo/react-native-fbsdk-next/issues/114",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
2614138646 | Minor error handing and tracing improvements
Rename update to get_line_value
Add specific exceptions when hub is not online and user is using the switches
Remove the duplicate update_lines call in the cover case
@thecode can you take a look again? I added another submit with README changes.
| gharchive/pull-request | 2024-10-25T13:38:39 | 2025-04-01T06:45:59.578792 | {
"authors": [
"tomer-w"
],
"repo": "thecode/ha-rpi_gpio",
"url": "https://github.com/thecode/ha-rpi_gpio/pull/308",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
347265678 | Docker swarm machine
I have created a Swarm and consule. After that i tried to do below comment but i am having doubt that what is a and b in the comment mentioned.
"Now we can configure our new Swarm agents on each host a and b:
$ docker run -d --restart=always --name swarm-agent-consul swarm:1.0.0 join --advertise $(curl http://169.254.169.254/latest/meta-data/public-ipv4):2376 consul://192.169.0.1:8500"
Also when i used this command i am getting error as mentioned below:
Hi @Ajith-AK!
Thank you for reaching out, there are a few things to note here.
This repository is not being maintained as The {code} Team dissolved in March 2018, see https://blog.thecodeteam.com/2018/02/22/final-thank-code-team/.
I believe you meant to create an issue, not issue a pull request. The pull request includes a great number of changes from @nikolaia and @mastoj from years ago, unfortunately none of which has been sent back to the main repository (I wish they had been, the changes look really great).
This workshop is ~3 years old, so things will most likely not work exactly as they did during that time.
Final thought, your command includes an IP address that's not private, 192.169.0.1, you should be using a private block such as 192.168.0.0 - 192.168.255.255 when seeing up your environment.
Best of luck!
Thanks
| gharchive/pull-request | 2018-08-03T05:39:04 | 2025-04-01T06:45:59.583668 | {
"authors": [
"Ajith-AK",
"jonasrosland"
],
"repo": "thecodeteam/training",
"url": "https://github.com/thecodeteam/training/pull/60",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
433838714 | Adding Deferred types support
We should add support for Webonyx Deferred types in order to offer a way to avoid the N+1 issues.
Implementation should be as easy as possible on the user side.
Current proposal:
Consider a request where a user attached to a post must be returned.
{
posts {
id
user {
id
}
}
}
/**
* @Type
*/
class PostType {
/**
* @Field(prefetchMethod="prefetchUsers")
* @param Post $post
* @param mixed $prefetchedUsers
* @return User
*/
public function getUser(Post $post, $prefetchedUsers): User
{
// This method will receive the $prefetchedUsers as second argument. This is the return value of the "prefetchUsers" method below.
// Using this prefetched list, it should be easy to map it to the post
}
/**
* @param Post[] $posts
* @return mixed
*/
public function prefetchUsers(iterable $posts)
{
// This function is called only once per GraphQL request
// with the list of posts. You can fetch the list of users
// associated with this posts in a single request,
// for instance using a "IN" query in SQL or a multi-fetch
// in your cache back-end.
}
}
When the "prefetchMethod" attribute is detected in the "@Field" annotation, the method is called automatically. The first argument of the method is an iterable over the instances of the main type.
The "prefetchMethod" can return absolutely anything (mixed). The return value will be passed as the second parameter of the "@Field" annotated method.
Important: field arguments can be set either on the @Field annotated method OR/AND on the prefetchMethod.
For instance:
/**
* @Type
*/
class PostType {
/**
* @Field(prefetchMethod="prefetchComments")
* @param Post $post
* @param mixed $prefetchedComments
* @return Comment[]
*/
public function getComments(Post $post, $prefetchedComments): array
{
// ...
}
/**
* @param Post[] $posts
* @return mixed
*/
public function prefetchComments(iterable $posts, bool $hideSpam, int $filterByScore)
{
// Parameters passed after the first parameter (hideSpam, filterByScore...) are automatically exposed as GraphQL arguments for the "comments" field.
}
}
The prefetch method MUST be in the same class as the @Field-annotated method and MUST be public.
Note: the "prefetchMethod" argument CANNOT be applied on @Query and @Mutation annotations. We will need a different kind of attribute for this.
Note to self: implementation warning! A GraphQL query can contain many different calls with different arguments for a same field. For instance:
{
posts {
id
legitComments: comments(hideSpam: true) {
id
}
spamComments: comments(hideSpam: false) {
id
}
}
}
With the example above, we will have to call the prefetch method twice! Once with the "hideSpam" set to true, and once with the "hideSpam" set to false.
To be honest, this format seems a little bit off. What happened with the original where getComments(Post $post): array would actually be getComments(array $posts): array?
Maybe I just don't see exactly how does it work, but let me try though:
<?php
/**
* @Type
*/
class PostType {
/**
* @Field(prefetchMethod="eagerLoadComments")
* @return Comment[]
*/
public function getComments(Post $post, $promisedData): array
{
return array_filter($promisedData, function ($comment) use ($post) {
return $post->getId() === $comment['post_id'];
});
}
/**
* @param Post[] $posts
* @return array
*/
public function eagerLoadComments(iterable $posts, bool $hideSpam, int $filterByScore)
{
return [
[
'post_id' => 1,
'comment' => 'Hello world',
],
[
'post_id' => 1,
'comment' => 'Hello world2',
],
[
'post_id' => 2,
'comment' => 'Hello world3',
],
];
}
}
Is this what you wanted to achieve?
Hey @golaod ,
Your example is perfect, you got it right.
Indeed, the idea we first talked about was different. My first idea was something like:
/**
* @Type
*/
class PostType {
/**
* @BatchField()
* @param Post[] $posts
* @return Comment[][]
*/
public function getComments(array $posts): array
{
// ...
}
}
I've been talking with @homersimpsons for quite some time about it. He convinced me this is a somewhat better alternative.
Here are the main points:
Regarding method signature
/**
* @Field(prefetchMethod="eagerLoadComments")
* @return Comment[]
*/
public function getComments(Post $post, $promisedData): array
This method signature is quite similar to the usual way we create fields. It is easier to understand (it is obvious that the field "comments" is of type "Comment[]".
Compare this to:
/**
* @BatchField()
* @param Post[] $posts
* @return Comment[][]
*/
public function getComments(array $posts): array
{
// ...
}
The return type ("Comment[][]") will map to Comment[] in GraphQL. It is obvious to both of us, but it could cause problems to beginners.
Regarding implementation
With this signature:
public function getComments(array $posts): array
the keys of the returned array must match the keys of the $posts array (otherwise, GraphQLite cannot know by itself what comments are linked to what posts).
Doing the matching on the keys of the arrays is error-prone. Also, what is GraphQLite supposed to return if some keys are missing or if there are some additional keys passed by the developer? Should it trigger an error?
Compare this to the solution proposed by @homersimpsons:
/**
* @Field(prefetchMethod="eagerLoadComments")
* @return Comment[]
*/
public function getComments(Post $post, $promisedData): array
Here, there is absolutely no possible doubt. The returned comments are matching the "$post" passed in argument. The method signature is way more strict than in the other solution and less things can go awkward.
Does it make sense? Or do you think another way of doing things we did not think about?
How does it now about $promisedData? Asking because the field can still have inputs
/**
* @Field(prefetchMethod="eagerLoadComments")
* @return Comment[]
*/
public function getComments(Post $post, $promisedData): array
GraphQLite will detect the prefetchMethod attribute in the @Field annotation. If the prefetchMethod attribute is present, the 2nd argument of the method MUST be the promisedData (returned by the prefetch method).
Input arguments come either in third position and afterwards, or in the prefetch method:
/**
* @Type
*/
class PostType {
/**
* @Field(prefetchMethod="prefetchComments")
* @param Post $post
* @param mixed $prefetchedComments
* @return Comment[]
*/
public function getComments(Post $post, $prefetchedComments, int $maxCommentLength): array
{
// In this sample, the input arguments of the comments field are:
// - maxCommentLength: Int
// - hideSpam: Bool
// - filterByScore: Int
}
/**
* @param Post[] $posts
* @return mixed
*/
public function prefetchComments(iterable $posts, bool $hideSpam, int $filterByScore)
{
// Parameters passed after the first parameter (hideSpam, filterByScore...) are automatically exposed as GraphQL arguments for the "comments" field.
}
}
:+1:
| gharchive/issue | 2019-04-16T15:16:49 | 2025-04-01T06:45:59.598772 | {
"authors": [
"golaod",
"moufmouf"
],
"repo": "thecodingmachine/graphqlite",
"url": "https://github.com/thecodingmachine/graphqlite/issues/42",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
180847627 | Change licence text in README to match LICENSE/metadata
The commit history shows the module has always been under the ASL-2.0,
and that the README text was an inconsistency in 999eb91 where the
LICENSE document was added and README.md was extended (probably from a
template).
Updated the main LICENSE document to include the full text, not only the
boilerplate copyright statement.
Fixes GH-66
Thanks!
| gharchive/pull-request | 2016-10-04T09:40:53 | 2025-04-01T06:45:59.714399 | {
"authors": [
"domcleal",
"ekohl"
],
"repo": "theforeman/puppet-dns",
"url": "https://github.com/theforeman/puppet-dns/pull/69",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
372293068 | AbstractDataSource methods access level
Methods in AbstractDataSource are not open so in case we need to change / add something to current implementation, we can't. I wanted to ask what's the reason for such decision? Can I make PR with open methods?
I agree this could be required. Do you have the reason/use-case for it so I am sure this is required?
I needed to call method on table view's instance every time cellForRowAtIndexPath: is called. However, I realized it's not good at all and found different solution.
I decided to close this issue because I can't think of any other scenario when we might need these public methods to be open.
Thank you
I'm sorry for late reply. I haven't received notification.
OK, thanks for the information.
| gharchive/issue | 2018-10-21T08:50:17 | 2025-04-01T06:45:59.730407 | {
"authors": [
"adam-leitgeb",
"mkj-is"
],
"repo": "thefuntasty/CellKit",
"url": "https://github.com/thefuntasty/CellKit/issues/14",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
1580995242 | Does this Action support something like: "feat(whatever): Issue-Name (#ISSUE-IDENTIFIER)"?
Does this action support this linting?
For Example:
"feat(authentication): Creating Login UI + Logic(#GGG-2)" or "test: Implement Unit tests for Authentication(#GG-5)"
If you can figure out a regex for it, it should
@thehanimo Alright. So that is my regex:
(fix|feat|build|chore|ci|docs|style|refactor|test)(\(([^)]+)\))?:\s.*\s\(#\w{1,3}-\d+\)
How should my json look like because I already set the prefixes at another point of the config or is that optional?
prefixes is optional so you can either delete it or pass in an empty array.
Your regexp field under CHECKS would look like this:
"regexp": "(fix|feat|build|chore|ci|docs|style|refactor|test)(\\(([^)]+)\\))?:\\s.*\\(#\\w{1,3}-\\d+\\)"
Notice how double backslashes are required to put literal \ characters in the string.
Also, I noticed a bug in your regexp where you have an extra \s before (#ISSUE-IDENTIFIER) but I'm not sure if you meant that. If you did, then your examples given above wouldn't work.
Alright, I'll take a look and let you know :)
One more question: What is the property regexpFlags and is it optional? Is ignoreLabels also optional?
I just tried it and it works perfectly. Thanks for the great tool.
Yes, regexpFlags and ignoreLabels are both optional. You can find more about the flags here.
| gharchive/issue | 2023-02-11T20:00:57 | 2025-04-01T06:45:59.739734 | {
"authors": [
"NicoMarksman",
"thehanimo"
],
"repo": "thehanimo/pr-title-checker",
"url": "https://github.com/thehanimo/pr-title-checker/issues/35",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
415211547 | Unable to slice with non-categorical obs index
import anndata
import numpy as np
import pandas as pd
adata = anndata.AnnData(X=np.array([[1,2], [1,2], [1,2]]), obs=pd.DataFrame(index=[0,1,2]), var=['a','b'])
subset = adata[:,0]
'Don’t call _normalize_index with non-categorical/string names'
AssertionError: Don’t call _normalize_index with non-categorical/string names
I am getting the same error when attempting to slice with the string var name as well.
subset = adata[:,'a']
subset = adata[:,adata.var_names[0]]
subset = adata[:,'0']
all throw the same error
Hi, i will check.
Thanks, Sergei! The main problem here is that AnnData is in an invalid state and we should have thrown errors in the first place. I'll take care of it.
Closing this, since it's an unsupported use case.
what the heck this was a use case in your official tutorial
| gharchive/issue | 2019-02-27T16:26:06 | 2025-04-01T06:45:59.761631 | {
"authors": [
"Koncopd",
"cryptovec",
"falexwolf",
"ivirshup",
"joshua-gould",
"snyquist2"
],
"repo": "theislab/anndata",
"url": "https://github.com/theislab/anndata/issues/120",
"license": "bsd-3-clause",
"license_type": "permissive",
"license_source": "bigquery"
} |
598872828 | Error in read seurat loom object in scanpy
Hello,
I converted a Seurat object into a .loom file and tried to read it into Scanpy using the read_loom() function. But I got this error:
OSError Traceback (most recent call last)
~/anaconda3/lib/python3.7/site-packages/h5py/_hl/files.py in make_fid(name, mode, userblock_size, fapl, fcpl, swmr)
198 try:
--> 199 fid = h5f.open(name, h5f.ACC_RDWR, fapl=fapl)
200 except IOError:
h5py/_objects.pyx in h5py._objects.with_phil.wrapper()
h5py/_objects.pyx in h5py._objects.with_phil.wrapper()
h5py/h5f.pyx in h5py.h5f.open()
OSError: Unable to open file (unable to lock file, errno = 11, error message = 'Resource temporarily unavailable')
During handling of the above exception, another exception occurred:
OSError Traceback (most recent call last)
~/anaconda3/lib/python3.7/site-packages/h5py/_hl/files.py in make_fid(name, mode, userblock_size, fapl, fcpl, swmr)
201 try:
--> 202 fid = h5f.open(name, h5f.ACC_RDONLY, fapl=fapl)
203 except IOError:
h5py/_objects.pyx in h5py._objects.with_phil.wrapper()
h5py/_objects.pyx in h5py._objects.with_phil.wrapper()
h5py/h5f.pyx in h5py.h5f.open()
OSError: Unable to open file (unable to lock file, errno = 11, error message = 'Resource temporarily unavailable')
During handling of the above exception, another exception occurred:
OSError Traceback (most recent call last)
<ipython-input-13-9ead8199ac42> in <module>
----> 1 adata=sc.read_loom("/home/user/Data/pseudo_time/data/5ns+5s/seurat_5ns_5s_sae.loom")
~/anaconda3/lib/python3.7/site-packages/anndata/_io/read.py in read_loom(filename, sparse, cleanup, X_name, obs_names, obsm_names, var_names, varm_names, dtype, **kwargs)
189 from loompy import connect
190
--> 191 with connect(filename, "r", **kwargs) as lc:
192 if X_name not in lc.layers.keys():
193 X_name = ""
~/anaconda3/lib/python3.7/site-packages/loompy/loompy.py in connect(filename, mode, validate, spec_version)
1147 Note: if validation is requested, an exception is raised if validation fails.
1148 """
-> 1149 return LoomConnection(filename, mode, validate=validate, spec_version=spec_version)
~/anaconda3/lib/python3.7/site-packages/loompy/loompy.py in __init__(self, filename, mode, validate, spec_version)
82 if validate:
83 lv = loompy.LoomValidator(version=spec_version)
---> 84 if not lv.validate(filename):
85 raise ValueError("\n".join(lv.errors) + f"\n{filename} does not appead to be a valid Loom file according to Loom spec version '{spec_version}'")
86
~/anaconda3/lib/python3.7/site-packages/loompy/loom_validator.py in validate(self, path, strictness)
46 """
47 valid1 = True
---> 48 with h5py.File(path) as f:
49 valid1 = self.validate_spec(f)
50 if not valid1:
~/anaconda3/lib/python3.7/site-packages/h5py/_hl/files.py in __init__(self, name, mode, driver, libver, userblock_size, swmr, rdcc_nslots, rdcc_nbytes, rdcc_w0, track_order, **kwds)
406 fid = make_fid(name, mode, userblock_size,
407 fapl, fcpl=make_fcpl(track_order=track_order),
--> 408 swmr=swmr)
409
410 if isinstance(libver, tuple):
~/anaconda3/lib/python3.7/site-packages/h5py/_hl/files.py in make_fid(name, mode, userblock_size, fapl, fcpl, swmr)
202 fid = h5f.open(name, h5f.ACC_RDONLY, fapl=fapl)
203 except IOError:
--> 204 fid = h5f.create(name, h5f.ACC_EXCL, fapl=fapl, fcpl=fcpl)
205 else:
206 raise ValueError("Invalid mode; must be one of r, r+, w, w-, x, a")
h5py/_objects.pyx in h5py._objects.with_phil.wrapper()
h5py/_objects.pyx in h5py._objects.with_phil.wrapper()
h5py/h5f.pyx in h5py.h5f.create()
OSError: Unable to create file (unable to open file: name = '/home/user/Data/pseudo_time/data/5ns+5s/seurat_5ns_5s_sae.loom', errno = 17, error message = 'File exists', flags = 15, o_flags = c2)
It looks like that file was open from another process while you were trying to read it. Try making sure that nothing else was trying to access the file when you read it. IIRC, a common cause for this error is needing to close the r session that wrote the file.
Updating your version of loompy might work too.
@ivirshup Thank you for your help. By closing R, it works fine now
https://satijalab.org/loomr/loomr_tutorial
It looks like that file was open from another process while you were trying to read it. Try making sure that nothing else was trying to access the file when you read it. IIRC, a common cause for this error is needing to close the r session that wrote the file.
If closing the R session doesn't work, I found that the "close_all()" function works. For example "loom_file$close_all()"
Source: https://satijalab.org/loomr/loomr_tutorial
| gharchive/issue | 2020-04-13T12:53:23 | 2025-04-01T06:45:59.766660 | {
"authors": [
"colinmcgovern",
"ivirshup",
"roofya"
],
"repo": "theislab/anndata",
"url": "https://github.com/theislab/anndata/issues/354",
"license": "bsd-3-clause",
"license_type": "permissive",
"license_source": "bigquery"
} |
152968152 | revise zh-Hans translation
There is no such idiom as "昨日黄花". The correct word should be "明日黄花".
See: https://github.com/thejameskyle/babel-handbook/blob/master/CONTRIBUTING.md#translating-the-handbook
| gharchive/pull-request | 2016-05-04T09:24:54 | 2025-04-01T06:45:59.812150 | {
"authors": [
"ArlenKou",
"thejameskyle"
],
"repo": "thejameskyle/babel-handbook",
"url": "https://github.com/thejameskyle/babel-handbook/pull/76",
"license": "CC-BY-4.0",
"license_type": "permissive",
"license_source": "github-api"
} |
381648504 | Class 'Kordy\Ticketit\TicketitServiceProvider' not found
i have pasted Kordy\Ticketit\TicketitServiceProvider::class, ni my config/app.php but when i rust url to install its giving following error.
Class 'Kordy\Ticketit\TicketitServiceProvider' not found
Was the composer install successful? You could also try composer dump-autoload
yes i tried composer dump-autoloadbut not worked
What version of ticketit did you install? (You can find the version number in composer.lock)
| gharchive/issue | 2018-11-16T15:34:57 | 2025-04-01T06:45:59.816067 | {
"authors": [
"balping",
"waqarali09"
],
"repo": "thekordy/ticketit",
"url": "https://github.com/thekordy/ticketit/issues/504",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
186483606 | demo is included in installed package
The demo package gets included into the installed package (i.e. into site-packages) since the packages clause doesn't tell the tooling not to include it.
I think that's not optimal :)
Could you submit a merge request to have it not part of the package?
Done deal, @bufke. Sorry it took me a while to get back to doing that.
| gharchive/issue | 2016-11-01T08:38:22 | 2025-04-01T06:45:59.818018 | {
"authors": [
"akx",
"bufke"
],
"repo": "thelabnyc/wagtail_blog",
"url": "https://github.com/thelabnyc/wagtail_blog/issues/33",
"license": "apache-2.0",
"license_type": "permissive",
"license_source": "bigquery"
} |
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