You should use certificate variables in your IoT policy and set the certificate SubjectName to the actual Thing Name of your device. This will allow you to filter based on Thing Names for Greengrass devices.
Dymola supports generating UML Diagrams, at least since 2022x. However, you should be aware that the diagram is generated by an online service, and hence the content of the image is made available to that server.
Only selecting a Field has the side-effect of the page scrolling.
If you don't want this, then you need to navigate back to the initial starting point.
To navigate back, use Range.Select(), but if you are in a (modern) comment, use Comment.Edit().
If you can serve a static HTML file, you can create a form in that HTML file that sends requests to your Gradio app. Here’s a simple example:
In this example, when users click the button, it opens the Gradio app in a new tab. You should replace http://localhost:7860/ with the actual URL of your Gradio app if it's running on a different port or domain.
The reason why you are getting as running(limited) is because one of the nodes(3rd node) is unavailable.
If you have disabled or stopped that node, intentionally then unregister it from IR, the status will get updated.
You can check that PreparedStatementSetter in your code that it's correctly setting values for multiple rows and For Cloud SQL, the JDBC URL format should be jdbc:postgresql://host:port/database. you can troubleshoot in that way once . For detailed investigation you can open a public issue tracker describing your issue and vote [+1] and Eng team will look on the Bug .
This is because you are using float for the images and cards, which doesn't automatically adapt well to responsive designs.
you should replace the float-based layout with a flexbox or grid layout
I have done a modification to modify key based on following requirements:
Excluding some keys
Using key extendedValue if data is over of 254 chars.
I have written following code on serialiser:
@model_serializer(mode="wrap")
def _serialize(self, handler):
d = handler(self)
d_attributes = list()
for k, v in self.__dict__.items():
if k not in excluded:
data = { "name": k.upper() }
if len(v) < limit:
data.update({ "value": v })
else:
data.update({ "extendedValue": v })
d_attributes.append(data)
d["attributes"] = d_attributes
return d
But I receive following error:
Error serializing to JSON: PydanticSerializationError: Error calling function `_serialize`: ValueError: Circular reference detected (id repeated)
Instead if I rollback with following code:
@model_serializer(mode="wrap")
def _serialize(self, handler):
d = handler(self)
d_attributes = list()
for k, v in self.__dict__.items():
if k not in excluded:
data = { "name": k.upper(), "value": v }
d_attributes.append(data)
d["attributes"] = d_attributes
return d
It works. Any Idea?
Reasons:
Blacklisted phrase (1): Any Idea?
RegEx Blacklisted phrase (1): I receive following error
The same thing happened to me yesterday, I thought it could be an error in the last plugins I played, so just in case I deleted them. It still doesn't work and I keep getting the same error.
Another thing I did was go to the document where the error occurs and to line 391, I tried to modify it and even delete it, but then it gave an error on another line, even in other files. I can't find a solution to the problem and I need the page for next week.
Reasons:
Blacklisted phrase (0.5): I need
RegEx Blacklisted phrase (2): It still doesn't work
RegEx Blacklisted phrase (2): I can't find a solution
RegEx Blacklisted phrase (2): can't find a solution
Docker creates a containerid for that image which can be retrieved using
docker ps -a
Export that container to a tar and then unzip the tar as follows:
docker export containerid | tar -xvf - -C /path/to/destination
After this, go to the destination folder.
Here search for the application-name.jar file, you will find it in one of the folders.
In my case it was in /home/jboss/app
Then one just needs to extract the files of the jar file
In case anyone faces similar issue, I found out why MFA selection screen keeps appearing for TOTP. The reason is that, once you select your desired MFA on orchestration step 4, using SelfAsserted-Select-MFA-Method it doesn't persist the value. It happens after, for example, if you have selected email as your MFA option, Technical Profile EmailVerifyOnSignIn used during code verification has a following reference:
UserWriteMFAMethod actually saves your value and is not being referenced by TOTP related flow.
So the fix would be following, since I want to save selected MFA method only after user has made a verification, I edited OTPVerification like this:
The reason: systemd runs its services isolated, meaning they cannot read from the env vars. so passing a docker container environment variable to a systemd process is not easy at all.
Secondly: why would you run something isolated, while it's already being run containered?
I'm on a M1 pro and the lastest combination working is Python 3.11 with tensorflow 2.15 and tensorflow-metal 1.1.0, both installable py PyPi. It has been reported that keras 3 makes no use of the GPU (at least on macos), but I have not tested this. tensorflow 2.15 ist the last version with keras 2. If this does not work for you, it could be an issue with the M2.
For those coming from Google, you probably don't have the permissions to a directory. chown user:user folder and add -R to propagate it in subdirectories.
@AirOne01 mentioned chmod but I used chown so I have the permissions.
Here is a example. I used one of your suggestions and still have a dashed line. I dont know which parameter is used to highlight the active block of code.
In sdk version 52 some arts of styles like fontSize are not supporting values like '10%' or '32em'. If you go with values like 10 and 32, it will work.
Path exploration has certain limitations, especially due to cardinality issues, which can prevent you from seeing all available paths and fully covering the data.
The most effective way to identify exits from each page is by using the Page Path dimension along with the Exits metric in a freeform report within Explore.
For the most accurate data, especially when combined with other metrics, utilizing BigQuery's raw data export is recommended.
1:1 (square): 1200 x 1200 pixels, minimum size of 200 x 200 pixels
1.91:1 (landscape): 1200 x 628 pixels, minimum size of 600 x 314 pixels
4:5 (portrait): 1200 x 1500 pixels, minimum size of 320 x 400 pixels
I know this question is old but there could be someone out there that may need help on it. I deployed a similar solution recently in one of my applications and thought I should share the script I used.
First, I needed to deploy an automated email sending script with PHPMailer and MySQL. The system is to send the emails daily to members based on their birth day and birth month. In course of my search, I came across this script from PHPMailer as seen via this link https://github.com/PHPMailer/PHPMailer/blob/master/examples/mailing_list.phps
Lastly, I know the question above do not require the use of CRON but for those that will need it, I use https://cron-job.org/en/ to schedule the process of sending the emails daily. You can watch this YouTube video to see the process of scheduling https://www.youtube.com/watch?v=8XuA_rc6lbY
I am trying to do a GET_DESCRIPTOR control transfer on USB3.0.
I have successfully done SET_ADDRESS which comes part of address device command with BSR=0. But when I try GET_DESCRIPTOR after this, I am not able to see the corresponding transfer trace in Lecroy
In MIPS, temporary registers like $t0 to $t9 are split into two groups based on who is responsible for saving their values during function calls.
Caller-Saved Registers ($t0 to $t9):
These are used for temporary data that doesn't need to be saved across function calls. When a function calls another function, it's up to the calling function (the one making the call) to save these registers if it needs their values later. The function being called (the callee) can change these registers freely, so the caller must save them if needed.
Callee-Saved Registers ($s0 to $s7):
These registers are meant for values that need to be preserved across function calls. If a function uses these registers, the called function (the callee) is responsible for saving and restoring them. This way, the calling function doesn't lose important values.
Why this split?
This split helps make function calls more efficient:
The caller only has to worry about saving temporary data if needed, which reduces the work it has to do.
The callee ensures important data stays intact, but it only has to save and restore the values that really matter.
This design helps avoid unnecessary work and keeps things running smoothly during function calls.
make sure that the following is used only one time...in my case it was being used in main and in home page
ShowCaseWidget(
builder: Builder(
builder: (_) => DashboardView(map),
),
));
to resolve this issue, you can move the configs folder from detectron2/configs to detectron2/detectron2/model_zoo/. Then, use the following line to load the configuration :cfg.merge_from_file(model_zoo.get_config_file("COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml"))
.it will work
There are two checks you need to do before putting in your redirect_URI :-
There are restrictions when it comes to adding URIs in the app registration , check here
Please check if the redirect uri that ure adding is not duplicated in any sections , for example if the redirect_uri is 'http://localhost:3000' and the platform types added are single page applications as well as web redirect urls or mobile and desktop applications and any two of them have the same URI or something similar to 'http://localhost' as the port no. doesnt matter here , the client from which ure trying to access this app registration will always pick from the top and so you will get the error "AADSTS9002326: Cross-origin token redemption is permitted only for the 'Single-Page Application' client-type" (majorly when you are using SPA React or next apps) because it will think of it as a web redirect URI and not SPA
Can you provide a bit more details, please?
Once, the SELinux policy module is loaded, do you perform a restorecon on the filesystem(s) or directory trees to make sure the binaires have the proper SELinux contexts for the processes to transition as expected in the policy?
Do you implement poly-instantiation on /tmp?
What are the AVC denials you get?
Do you switch the mongod_can_use_kerberos boolean to true?
Using the Plaid /transactions/sync API endpoint is a good approach to retrieve all historical transaction data for an account. When you use the API with cursor set as an empty string (""), you are effectively starting from the beginning of the transaction history. Plaid will return the initial batch of transactions and provide a next_cursor value, which you should use in subsequent requests to get the next batch of transactions. This process should be repeated until next_cursor is null, indicating there are no more transactions to fetch.
To handle synchronization effectively, you should process the batches in the order they are received, and always use the next_cursor from the current response to fetch the next batch. This way, you maintain the integrity and sequence of the transaction data according to how Plaid provides it.
Remember to handle edge cases, like re-synchronization if a batch fails or if there is a long delay between fetches, to ensure your local copy of the transactions remains accurate and up-to-date.
Thanks a lot for the suggestion! it was indeed much simpler to just modify the JSON Employee Vector Search and the other vector index Results
I implemented a solution that builds upon your approach while adding some additional robustness to handle different types of empty values in my Neo4j vector search results.
def filter_empty_connections(results):
"""
Filter out empty connections from vector search results across all data types
(Employee, Work, Project, WorkAllocation, WorkScheduleRule).
"""
if not results or "results" not in results:
return results
def is_empty_value(val):
"""Check if a value is considered empty."""
if isinstance(val, list):
# Check if list is empty or contains only empty/null values
return len(val) == 0 or all(is_empty_value(item) for item in val)
if isinstance(val, dict):
# Check if dict is empty or contains only empty/null values
return len(val) == 0 or all(is_empty_value(v) for v in val.values())
return val is None or val == ""
def filter_single_item(item):
"""Filter empty connections from a single item's connections array."""
if "connections" not in item:
return item
filtered_connections = []
for conn in item["connections"]:
# Skip the connection if all its non-type fields are empty
has_non_empty_value = False
for key, val in conn.items():
if key != "type" and not is_empty_value(val):
has_non_empty_value = True
break
if has_non_empty_value:
filtered_connections.append(conn)
item["connections"] = filtered_connections
return item
filtered_items = [
filter_single_item(item)
for item in results["results"]
]
return {"results": filtered_items}
Then I integrated it into my index functions like this:
This approach successfully removed empty connections like "education": [] and "has_unavailability": [] from the results while keeping the connection entries that had actual data.
Thank you again for pointing me in the right direction! This solution worked perfectly for my use case.
Yes, you could use Content Type Gallery to reuse content types in the SharePoint online.
Content types created in the Content Type Gallery, when published, will be available to all sites and libraries in your SharePoint tenant. And it supports all column types.
I do not think you can do it in that way. Instead I can suggest my project https://github.com/reagento/dishka/ which can be used in different ways (like without fastapi or directly requesting dependency)
I think that is not good idea for handle request by using Executor service. Because Embedded tomcat which is included spring-boot-starter-web dependency can handle thread pool itself. You can just configure on application properties / yaml file.
If you want to use multiple thread, use or test another use cases for example processing huge file (at least more than 2GB).
For handle requests asynchronously, I will recommend spring-boot-flux project.
If you're using Expo SDK 52, the issue is likely related to that. I recently updated from SDK 51 to 52 and experienced the same error. This update also involved upgrading the react-native-view-shot library from version 3.8.0 to 4.0.0.
Also on GitLab you need to setup your token as a Developer in order to clone the repository. The Guest role is not sufficient and will lead to a 403 error even if you have the read_repository right.
this command doesn't trigger the machine to start measuring you say?
you must use
Use PySerial Library: If you are using Python, make sure you use the pyserial library to send commands over the serial port. Here is an example of Python code to send commands using pyserial:
I've tried what you've done (and commit the new version of docker). However, I get this output:
sudo docker run --gpus all -it --rm tensorflow/tensorflow:latest-gpu python -c "import tensorflow as tf; print('Num GPUs Available:', len(tf.config.list_physical_devices('GPU')))"
2024-11-22 08:20:55.695121: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:477] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1732263655.707089 1 cuda_dnn.cc:8310] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1732263655.710704 1 cuda_blas.cc:1418] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2024-11-22 08:20:55.722395: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-11-22 08:20:57.119693: E external/local_xla/xla/stream_executor/cuda/cuda_driver.cc:152] failed call to cuInit: INTERNAL: CUDA error: Failed call to cuInit: CUDA_ERROR_COMPAT_NOT_SUPPORTED_ON_DEVICE: forward compatibility was attempted on non supported HW
2024-11-22 08:20:57.119716: I external/local_xla/xla/stream_executor/cuda/cuda_diagnostics.cc:137] retrieving CUDA diagnostic information for host: 81f8d81af78d
2024-11-22 08:20:57.119720: I external/local_xla/xla/stream_executor/cuda/cuda_diagnostics.cc:144] hostname: 81f8d81af78d
2024-11-22 08:20:57.119789: I external/local_xla/xla/stream_executor/cuda/cuda_diagnostics.cc:168] libcuda reported version is: 545.23.6
2024-11-22 08:20:57.119804: I external/local_xla/xla/stream_executor/cuda/cuda_diagnostics.cc:172] kernel reported version is: 470.256.2
2024-11-22 08:20:57.119808: E external/local_xla/xla/stream_executor/cuda/cuda_diagnostics.cc:262] kernel version 470.256.2 does not match DSO version 545.23.6 -- cannot find working devices in this configuration
Num GPUs Available: 0
Erase in odoo doesn'T really support the authentication you want. This code just isn't there.
The ode has its own authentication option. When you set "user" it turns on. It consists in the fact that you must first receive a cookie. And then in the postman already pass these cookies in the cookie header. I am sending examples of authentication and subsequent requests from my mobile app. I think it will be clear to you and you will transfer it to the postman.
next how use this cookie
So you can'T get the data in one request. First you need to get a cookie(token). And then make a request with this cookie. Also note that cookies also come in the set-cookie header By the way, there is another alternative option to create an API KEY in the user's settings and use it
For case two you can also set margin-left:auto for inner div in order to move it to the right. While text inside the inner div is already aligned to right. so this hacks works like a charm
I got something to work by just copying the values of a static array and placing them into the dynamic one like this,
void f(int r, int c, int **grid);
int main() {
int r = 3, c = 5;
int values[][5] = {
{0, 1, 2, 3, 4},
{1, 2, 4, 2, 1},
{3, 3, 3, 3, 3}
};
int **test = malloc(r*sizeof(int*));
for (int i = 0; i < r; i++) {
test[i] = malloc(c*sizeof(int));
for (int j = 0; j < c; j++) {test[i][j] = values[i][j];}
}
f(r, c, test);
return 0;
}
However I would need to specify the number of columns of the static array every time I do testing. Is there a shorter way to do this using Compound Literals and without creating a values variable? I am using GCC 6.3.0 compiler for C.
Found it, was a very dummy mistake. I did not install pykeops before running the code. Weird enough, if pykeops is not installed then keops kernels in gpytorch.kernels.keops fallback to non-keops kernels. The fallback in my case was happening silently, with no warning (somehow the warning generated here was suppressed).
I figured this out by inspecting source code. IMHO, I think that gpytorch.kernels.keops should raise some exception when it's used whitout pykeops installed.
