JSOCOPS-18, NRC-21, NRC-21b updates to SIAF

Work in progress, creating the PR to start dumping the updates as they become available

Thanks, Mario.

I realized I had opened the PR against master. Went back to using siaf-updates as the base

As a quick check I generated the products and looked at the values in nircam_diff_PRDOPSSOC-045_pre-delivery.txt. It look slike the expected changes (so far) are there.

There will be seevral warning messages when running the generate scripts.

@mgennaro Thank you for the update. Are these warnings about the apertures the same mentioned in your PR #219?

The PR is ready for review. NIRCam 21 and 21-b job is done! @mfixstsci @Witchblade101

Generating files now

Output of generate_nircam.py below. I believe these are all expected warnings. No errors.
(pysiaf-37) minmei:generate dlong$ python generate_nircam.py
generate_nircam.py:111: DeprecationWarning: np.int is a deprecated alias for the builtin int. To silence this warning, use int by itself. Doing this will not modify any behavior and is safe. When replacing np.int, you may wish to use e.g. np.int64 or np.int32 to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
polynomial_degree = np.int((np.sqrt(8 * number_of_coefficients + 1) - 3) / 2)
generate_nircam.py:166: DeprecationWarning: np.float is a deprecated alias for the builtin float. To silence this warning, use float by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.float64 here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
v2_offset = np.float(wedge_offsets['v2_offset'][wedge_offsets['name'] == sca_name])
generate_nircam.py:167: DeprecationWarning: np.float is a deprecated alias for the builtin float. To silence this warning, use float by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.float64 here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
v3_offset = np.float(wedge_offsets['v3_offset'][wedge_offsets['name'] == sca_name])
Verification WARNING: NRCA1_GRISMTS has non-integer sum between YDetRef 1082.7145285391678 and YSciRef 1082.7145285391678 DetSciYAngle 0
Verification WARNING: NRCA1_GRISMTS256 has non-integer sum between YDetRef<PHONE_NUMBER>7331313 and YSciRef<PHONE_NUMBER>7331313 DetSciYAngle 0
Verification WARNING: NRCA1_GRISMTS128 has non-integer sum between YDetRef<PHONE_NUMBER>7331313 and YSciRef 65.95021227331311 DetSciYAngle 0
Verification WARNING: NRCA1_GRISMTS64 has non-integer sum between YDetRef<PHONE_NUMBER>7331313 and YSciRef 33.95021227331312 DetSciYAngle 0
Verification WARNING: NRCA5_TAGRISMTS32_F405N has non-integer sum between YDetRef 110.693 and YSciRef 16.693 DetSciYAngle 0
Verification WARNING: NRCB4_GRISMTS256 has non-integer sum between YDetRef<PHONE_NUMBER>408218 and YSciRef<PHONE_NUMBER>408218 DetSciYAngle 0
Verification WARNING: NRCB4_GRISMTS128 has non-integer sum between YDetRef<PHONE_NUMBER>408218 and YSciRef 65.09383854082179 DetSciYAngle 0
Verification WARNING: NRCB4_GRISMTS64 has non-integer sum between YDetRef<PHONE_NUMBER>408218 and YSciRef 33.09383854082179 DetSciYAngle 0
Verification WARNING: NRCA5_MASK430R has non-integer sum XDetRef 1075.5 and XSciRef 160.7 DetSciYAngle 0
Verification WARNING: NRCA5_FULL_MASK430R has non-integer sum XDetRef 1075.5 and XSciRef 973.7 DetSciYAngle 0
Verification WARNING: NRCA4_MASKSWB_NARROW has non-integer sum between YDetRef 535.5 and YSciRef 335.7 DetSciYAngle 180
Verification WARNING: NRCA4_FULL_MASKSWB_NARROW has non-integer sum between YDetRef 535.5 and YSciRef 1508.7 DetSciYAngle 180
Verification WARNING: NRCA5_MASKLWB has non-integer sum between YDetRef 1682.3 and YSciRef 175.3 DetSciYAngle 0
Verification WARNING: NRCA5_FULL_MASKLWB has non-integer sum between YDetRef 1682.3 and YSciRef 1682.3 DetSciYAngle 0
Verification WARNING: NRCA5_MASKLWB_F300M has non-integer sum between YDetRef 1682.1 and YSciRef 175.1 DetSciYAngle 0
Verification WARNING: NRCA5_FULL_MASKLWB_F300M has non-integer sum between YDetRef 1682.1 and YSciRef 1682.1 DetSciYAngle 0
Verification WARNING: NRCA5_MASKLWB_F277W has non-integer sum between YDetRef 1682.1 and YSciRef 175.1 DetSciYAngle 0
Verification WARNING: NRCA5_FULL_MASKLWB_F277W has non-integer sum between YDetRef 1682.1 and YSciRef 1682.1 DetSciYAngle 0
Verification WARNING: NRCA5_MASKLWB_F335M has non-integer sum between YDetRef 1682.2 and YSciRef 175.2 DetSciYAngle 0
Verification WARNING: NRCA5_FULL_MASKLWB_F335M has non-integer sum between YDetRef 1682.2 and YSciRef 1682.2 DetSciYAngle 0
Verification WARNING: NRCA5_MASKLWB_F360M has non-integer sum between YDetRef 1682.2 and YSciRef 175.2 DetSciYAngle 0
Verification WARNING: NRCA5_FULL_MASKLWB_F360M has non-integer sum between YDetRef 1682.2 and YSciRef 1682.2 DetSciYAngle 0
Verification WARNING: NRCA5_MASKLWB_F356W has non-integer sum between YDetRef 1682.2 and YSciRef 175.2 DetSciYAngle 0
Verification WARNING: NRCA5_FULL_MASKLWB_F356W has non-integer sum between YDetRef 1682.2 and YSciRef 1682.2 DetSciYAngle 0
Verification WARNING: NRCA5_MASKLWB_F410M has non-integer sum between YDetRef 1682.2 and YSciRef 175.2 DetSciYAngle 0
Verification WARNING: NRCA5_FULL_MASKLWB_F410M has non-integer sum between YDetRef 1682.2 and YSciRef 1682.2 DetSciYAngle 0
Verification WARNING: NRCA5_MASKLWB_F430M has non-integer sum between YDetRef 1682.3 and YSciRef 175.3 DetSciYAngle 0
Verification WARNING: NRCA5_FULL_MASKLWB_F430M has non-integer sum between YDetRef 1682.3 and YSciRef 1682.3 DetSciYAngle 0
Verification WARNING: NRCA5_MASKLWB_F460M has non-integer sum between YDetRef 1682.4 and YSciRef 175.4 DetSciYAngle 0
Verification WARNING: NRCA5_FULL_MASKLWB_F460M has non-integer sum between YDetRef 1682.4 and YSciRef 1682.4 DetSciYAngle 0
Verification WARNING: NRCA5_MASKLWB_F480M has non-integer sum between YDetRef 1682.4 and YSciRef 175.4 DetSciYAngle 0
Verification WARNING: NRCA5_FULL_MASKLWB_F480M has non-integer sum between YDetRef 1682.4 and YSciRef 1682.4 DetSciYAngle 0
Verification WARNING: NRCA5_MASKLWB_F444W has non-integer sum between YDetRef 1682.4 and YSciRef 175.4 DetSciYAngle 0
Verification WARNING: NRCA5_FULL_MASKLWB_F444W has non-integer sum between YDetRef 1682.4 and YSciRef 1682.4 DetSciYAngle 0
Verification WARNING: NRCA5_MASKLWB_NARROW has non-integer sum between YDetRef 1682.6 and YSciRef 175.6 DetSciYAngle 0
Verification WARNING: NRCA5_FULL_MASKLWB_NARROW has non-integer sum between YDetRef 1682.6 and YSciRef 1682.6 DetSciYAngle 0
Wrote Siaf to xml file /Users/dlong/miniconda3/envs/pysiaf-37/lib/python3.7/site-packages/pysiaf/pre_delivery_data/NIRCam/NIRCam_SIAF.xml
Wrote Siaf to xlsx file /Users/dlong/miniconda3/envs/pysiaf-37/lib/python3.7/site-packages/pysiaf/pre_delivery_data/NIRCam/NIRCam_SIAF.xlsx
JWST nircam Siaf with 320 apertures
nircam
Wrote difference file to /Users/dlong/miniconda3/envs/pysiaf-37/lib/python3.7/site-packages/pysiaf/pre_delivery_data/NIRCam/nircam_diff_PRDOPSSOC-045_pre-delivery.txt
JWST nircam Siaf with 320 apertures
nircam
Apertures with significant roundtrip error differences:
AperName           siaf0_metric        siaf0_dx_mean     ...   difference_dx_rms       difference_dy_rms
---------------------- ------------------ --------------------- ...


Add "part 3" to <twisted-edwards.sage>

merging to branch skaunov-patches to merge all in one commit


fix use_wall_clock spelling in README

self explanatory :)

@simutisernestas thanks for the fix! Would you mind signing off your commit?

@christophebedard done : )


feat!: (IAC-1014) update orchestration deploy to orchestration deploy manifest

Changes
Swap the sas-orchestration deploy deployment method to instead be sas-orchestration deploy manifest a sas-orchestration experimental deployment method which deploys Viya using a site.yaml rather file than a SASDeployment.yaml CRD file.
To use this feature, set the existing variable in your ansible-vars.yaml V4_DEPLOYMENT_OPERATOR_ENABLED:false.
The sas-orchestration deploy option which uses the CRD has been removed.
Tests

Scenario
Provider
K8s Version
Deployment Method
Orchestration
Cadence
Order
Task

1
GCP
v1.26.5-gke.2100
ansible
deploy manifest
fast:2020
******
viya install & uninstall

2
GCP
v1.26.5-gke.2100
docker
deploy manifest
fast:2020
******
viya install & uninstall

3
GCP
v1.26.5-gke.2100
ansible
deploy manifest
fast:2020
******
MT

4
GCP
v1.26.5-gke.2100
docker
deploy manifest
fast:2020
******
MT

5
GCP
v1.26.5-gke.2100
ansible
deploy manifest
fast:2020
******
BTL

6
GCP
v1.26.5-gke.2100
docker
deploy manifest
fast:2020
******
BTL

7
GCP
v1.26.5-gke.2100
docker
deployment operator
fast:2020
******
viya install & uninstall

LGTM, consider running ansible-lint against your changed files with .ansible-lint in #459 to check for any rule violations

@dhoucgitter, if you agree, I think for now I am going to forgo ansible linting this PR with the upcoming linter implementation PR #459 since this is currently going into a experimental branch. The timing of the "public" release of this feature has yet to be determined.
That being said, after each viya4-deployment release I do plan on rebasing this experimental "deploy-manifest-site-yaml" branch. When the linter implementation changes in #459 gets released (probably after the next planned release?) a rebase will pick up those changes and I'll end up having to fix the warnings that start getting reported for the 4 files I modified. A quick check says the issues are only key-order and task name casing in the 4 files so it shouldn't be a significant change.
I put a note in IAC-1102, the ticket to release this feature, to also consider any linting changes I may have to make.

LGTM, consider running ansible-lint against your changed files with .ansible-lint in #459 to check for any rule violations

@dhoucgitter, if you agree, I think for now I am going to forgo ansible linting this PR with the upcoming linter implementation PR #459 since this is currently going into a experimental branch. The timing of the "public" release of this feature has yet to be determined.
That being said, after each viya4-deployment release I do plan on rebasing this experimental "deploy-manifest-site-yaml" branch. When the linter implementation changes in #459 gets released (probably after the next planned release?) a rebase will pick up those changes and I'll end up having to fix the warnings that start getting reported for the 4 files I modified. A quick check says the issues are only key-order and task name casing in the 4 files so it shouldn't be a significant change.
I put a note in IAC-1102, the ticket to release this feature, to also consider any linting changes I may have to make.

sure, sounds good Jay


New binding AWS SES

Describe the feature
New binding AWS SES
Release Note

RELEASE NOTE: ADD New binding AWS SES

Thanks for adding this @fjvela! I've triaged this to the 1.4 release.

/assign


Note that Astyanax is being retired?

This blog post says that Astyanax is being retired, but the README says:

Astyanax is currently in use at Netflix. Issues generally are fixed as quickly as possible and releases done frequently.

which implies it is not being retired. It could be good to update the README to note this library being retired?

@danielcompton Astyanax is in sunset mode in Netflix i.e. any new use-case should NOT be using Astyanax but any existing projects using Astyanax can continue to do so. We believe that organic movement of applications (rewrite/refactor) should be sufficient in removing that dependency on Astyanax and applications adopting Cassandra java driver.
We will patch Astyanax if we find some serious issue but there is no active development. But I agree on making the README to reflect the reality of being in "maintenance" mode.


Does the "clip gradient" configuration apply to the weights of all layers?

I have some questions about the "clip gradient" configuration.
I remember in Caffe, when the "clip gradient" configuration is set for the SGD solver, it will possibly down scale the gradients, such that the summation of the L2 norms of the gradients of all the layers is smaller than the specified number (e.g., 10).
I'm wondering is the behavior the same in MXNet? I have this question because I think MXNet will send to other GPUs the weight updates of one layer as soon as the backward propagation of that layer is done, without waiting for the other layers. So I guess it's not possible for MXNet to clip the gradients based on the summation of the L2 norms of all weights?

It's possible. But it will slowdown performance. you need to write your own training loop for that

@piiswrong Thank you for pointing out this, and actually I'm more curious about what's the current default behavior of gradient clipping in MXNet. Will it clip the gradient of each weight independently?

yes

closing for now as it is answered


unique_ptr compile error with gcc

Pulling the most recent changes I have encountered a compiler error on my linux development machine running gcc Ubuntu 5.4.0 with the following error:

src/curl/http_client.h: error: 'unique_ptr' in namespace 'std' does not name a template type std::unique_ptr<CURL, detail::CurlEasyDeleter> m_handle;

Compiling on my OSX machine does not show any errors.  After a quick debug I have found that putting #include <memory> in http_client.h resolves my linux compile issue.  Should I just make a PR for this?

It should be already fixed in https_client branch which I’ll merge soon. But if you need a fix ASAP then please do.

I've merged HTTPS branch to master including the missing  <memory> fix. It should be fine now.


InvalidArgumentError with Conv1D which has the same dilation_rate as the batch size, using tf.keras.Model.fit, on TPU

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): yes
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Colab
TensorFlow version (use command below): 2.3.0
Python version: 3.6.9
Accelerator: TPU

Describe the current behavior
When I optimized Conv1D, which has the same dilation_rate as the batch size, using tf.keras.Model.fit, I encountered the following error.
InvalidArgumentError: 9 root error(s) found.
  (0) Invalid argument: {{function_node __inference_train_function_5549}} Compilation failure: Reshape's input dynamic dimension is decomposed into multiple output dynamic dimensions, but the constraint is ambiguous and XLA can't infer the output dimension %reshape.40 = f32[8,8,2047,128]{3,2,1,0} reshape(f32[<=64,2047,128]{2,1,0} %reshape.39), metadata={op_type="BatchToSpaceND" op_name="dilated_conv1d_1/conv1d_1/conv1d/BatchToSpaceND"}. Constraint: multiple_of: 8, stride: 1
	TPU compilation failed
	 [[{{node tpu_compile_succeeded_assert/_4759666286058538557/_4}}]]
	 [[tpu_compile_succeeded_assert/_4759666286058538557/_4/_197]]
  (1) Invalid argument: {{function_node __inference_train_function_5549}} Compilation failure: Reshape's input dynamic dimension is decomposed into multiple output dynamic dimensions, but the constraint is ambiguous and XLA can't infer the output dimension %reshape.40 = f32[8,8,2047,128]{3,2,1,0} reshape(f32[<=64,2047,128]{2,1,0} %reshape.39), metadata={op_type="BatchToSpaceND" op_name="dilated_conv1d_1/conv1d_1/conv1d/BatchToSpaceND"}. Constraint: multiple_of: 8, stride: 1
	TPU compilation failed
	 [[{{node tpu_compile_succeeded_assert/_4759666286058538557/_4}}]]
	 [[tpu_compile_succeeded_assert/_4759666286058538557/_4/_157]]
  (2) Invalid argument: {{function_node __inference_train_function_5549}} Compilation failure: Reshape's input dynamic dimension is decomposed into multiple output dynamic dimensions, but the constraint is ambiguous and XLA can't infer the output dimension %reshape.40 = f32[8,8,2047,128]{3,2,1,0} reshape(f32[<=64,2047,128]{2,1,0} %reshape.39), metadata={op_type="BatchToSpaceND" op_name="dilated_conv1d_1/conv1d_1/conv1d/BatchToSpaceND"}. Constraint: multiple_of: 8, stride: 1
	TPU compilation failed
	 [[{{node tpu_compile_succeeded_assert/_4759666286058538557/_4}}]]
	 [[tpu_compile_succeeded_assert/_4759666286058538557/_4/_137]]
  (3) ...

This error does not occur if I forward using strategy.run.
A detailed error log is attached below.
Describe the expected behavior
I want to optimize it without errors.
Standalone code to reproduce the issue
Colab https://colab.research.google.com/drive/1W-eM2EwzYSMhHyN4GDUd22nKSLrrka3v?usp=sharing
gist https://gist.github.com/Hiroshiba/9c1914dbf57228204a4ed1f661168d36
Other info / logs Include any logs or source code that would be helpful to

---------------------------------------------------------------------------
InvalidArgumentError                      Traceback (most recent call last)
<ipython-input-5-5265a4b37c17> in <module>()
     13     steps_per_epoch=5,
     14     epochs=1,
---> 15     shuffle=False,
     16 )

14 frames
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py in _method_wrapper(self, *args, **kwargs)
    106   def _method_wrapper(self, *args, **kwargs):
    107     if not self._in_multi_worker_mode():  # pylint: disable=protected-access
--> 108       return method(self, *args, **kwargs)
    109
    110     # Running inside `run_distribute_coordinator` already.

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing)
   1101               logs = tmp_logs  # No error, now safe to assign to logs.
   1102               end_step = step + data_handler.step_increment
-> 1103               callbacks.on_train_batch_end(end_step, logs)
   1104         epoch_logs = copy.copy(logs)
   1105

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/callbacks.py in on_train_batch_end(self, batch, logs)
    438     """
    439     if self._should_call_train_batch_hooks:
--> 440       self._call_batch_hook(ModeKeys.TRAIN, 'end', batch, logs=logs)
    441
    442   def on_test_batch_begin(self, batch, logs=None):

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/callbacks.py in _call_batch_hook(self, mode, hook, batch, logs)
    287       self._call_batch_begin_hook(mode, batch, logs)
    288     elif hook == 'end':
--> 289       self._call_batch_end_hook(mode, batch, logs)
    290     else:
    291       raise ValueError('Unrecognized hook: {}'.format(hook))

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/callbacks.py in _call_batch_end_hook(self, mode, batch, logs)
    307       batch_time = time.time() - self._batch_start_time
    308
--> 309     self._call_batch_hook_helper(hook_name, batch, logs)
    310
    311     if self._check_timing:

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/callbacks.py in _call_batch_hook_helper(self, hook_name, batch, logs)
    340       hook = getattr(callback, hook_name)
    341       if getattr(callback, '_supports_tf_logs', False):
--> 342         hook(batch, logs)
    343       else:
    344         if numpy_logs is None:  # Only convert once.

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/callbacks.py in on_train_batch_end(self, batch, logs)
    959
    960   def on_train_batch_end(self, batch, logs=None):
--> 961     self._batch_update_progbar(batch, logs)
    962
    963   def on_test_batch_end(self, batch, logs=None):

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/callbacks.py in _batch_update_progbar(self, batch, logs)
   1014     if self.verbose == 1:
   1015       # Only block async when verbose = 1.
-> 1016       logs = tf_utils.to_numpy_or_python_type(logs)
   1017       self.progbar.update(self.seen, list(logs.items()), finalize=False)
   1018

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/utils/tf_utils.py in to_numpy_or_python_type(tensors)
    535     return t  # Don't turn ragged or sparse tensors to NumPy.
    536
--> 537   return nest.map_structure(_to_single_numpy_or_python_type, tensors)
    538
    539

/usr/local/lib/python3.6/dist-packages/tensorflow/python/util/nest.py in map_structure(func, *structure, **kwargs)
    633
    634   return pack_sequence_as(
--> 635       structure[0], [func(*x) for x in entries],
    636       expand_composites=expand_composites)
    637

/usr/local/lib/python3.6/dist-packages/tensorflow/python/util/nest.py in <listcomp>(.0)
    633
    634   return pack_sequence_as(
--> 635       structure[0], [func(*x) for x in entries],
    636       expand_composites=expand_composites)
    637

/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/utils/tf_utils.py in _to_single_numpy_or_python_type(t)
    531   def _to_single_numpy_or_python_type(t):
    532     if isinstance(t, ops.Tensor):
--> 533       x = t.numpy()
    534       return x.item() if np.ndim(x) == 0 else x
    535     return t  # Don't turn ragged or sparse tensors to NumPy.

/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in numpy(self)
   1061     """
   1062     # TODO(slebedev): Consider avoiding a copy for non-CPU or remote tensors.
-> 1063     maybe_arr = self._numpy()  # pylint: disable=protected-access
   1064     return maybe_arr.copy() if isinstance(maybe_arr, np.ndarray) else maybe_arr
   1065

/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in _numpy(self)
   1029       return self._numpy_internal()
   1030     except core._NotOkStatusException as e:  # pylint: disable=protected-access
-> 1031       six.raise_from(core._status_to_exception(e.code, e.message), None)  # pylint: disable=protected-access
   1032
   1033   @property

/usr/local/lib/python3.6/dist-packages/six.py in raise_from(value, from_value)

InvalidArgumentError: 9 root error(s) found.
  (0) Invalid argument: {{function_node __inference_train_function_5549}} Compilation failure: Reshape's input dynamic dimension is decomposed into multiple output dynamic dimensions, but the constraint is ambiguous and XLA can't infer the output dimension %reshape.40 = f32[8,8,2047,128]{3,2,1,0} reshape(f32[<=64,2047,128]{2,1,0} %reshape.39), metadata={op_type="BatchToSpaceND" op_name="dilated_conv1d_1/conv1d_1/conv1d/BatchToSpaceND"}. Constraint: multiple_of: 8, stride: 1
	TPU compilation failed
	 [[{{node tpu_compile_succeeded_assert/_4759666286058538557/_4}}]]
	 [[tpu_compile_succeeded_assert/_4759666286058538557/_4/_197]]
  (1) Invalid argument: {{function_node __inference_train_function_5549}} Compilation failure: Reshape's input dynamic dimension is decomposed into multiple output dynamic dimensions, but the constraint is ambiguous and XLA can't infer the output dimension %reshape.40 = f32[8,8,2047,128]{3,2,1,0} reshape(f32[<=64,2047,128]{2,1,0} %reshape.39), metadata={op_type="BatchToSpaceND" op_name="dilated_conv1d_1/conv1d_1/conv1d/BatchToSpaceND"}. Constraint: multiple_of: 8, stride: 1
	TPU compilation failed
	 [[{{node tpu_compile_succeeded_assert/_4759666286058538557/_4}}]]
	 [[tpu_compile_succeeded_assert/_4759666286058538557/_4/_157]]
  (2) Invalid argument: {{function_node __inference_train_function_5549}} Compilation failure: Reshape's input dynamic dimension is decomposed into multiple output dynamic dimensions, but the constraint is ambiguous and XLA can't infer the output dimension %reshape.40 = f32[8,8,2047,128]{3,2,1,0} reshape(f32[<=64,2047,128]{2,1,0} %reshape.39), metadata={op_type="BatchToSpaceND" op_name="dilated_conv1d_1/conv1d_1/conv1d/BatchToSpaceND"}. Constraint: multiple_of: 8, stride: 1
	TPU compilation failed
	 [[{{node tpu_compile_succeeded_assert/_4759666286058538557/_4}}]]
	 [[tpu_compile_succeeded_assert/_4759666286058538557/_4/_137]]
  (3) Invalid argument: {{function_node __inference_train_function_5549}} Compilation failure: Reshape's input dynamic dimension is decomposed into multiple output dynamic dimensions, but the constraint is ambiguous and XLA can't infer the output dimension %reshape.40 = f32[8,8,2047,128]{3,2,1,0} reshape(f32[<=64,2047,128]{2,1,0} %reshape.39), metadata={op_type="BatchToSpaceND" op_name="dilated_conv1d_1/conv1d_1/conv1d/BatchToSpaceND"}. Constraint: multiple_of: 8, stride: 1
	TPU compilation failed
	 [[{{node tpu_compile_succeeded_assert/_4759666286058538557/_4}}]]
	 [[tpu_compile_succeeded_assert/_4759666286058538557/_4/_187]]
  (4) Invalid argument: {{function_node __inference_train_function_5549}} Compilation failure: Reshape's input dynamic dimension is decomposed into multiple output dynamic dimensions, but the constraint is ambiguous and XLA can't infer the output dimension %reshape.40 = f32[8,8,2047,128]{3,2,1,0} reshape(f32[<=64,2047,128]{2,1,0} %reshape.39), metadata={op_type="BatchToSpaceND" op_name="dilated_conv1d_1/conv1d_1/conv1d/BatchToSpaceND"}. Constraint: multiple_of: 8, stride: 1
	TPU compilation failed
	 [[{{ ... [truncated]

I have tried in colab with TF version 2.3 and was able to reproduce the issue.Please, find the gist here.However i am seeing different error message in TF nightly versions(2.4.0-dev20200930).Please find the gist here..Thanks!

Removing assignment as I'm no longer working on Python TensorFlow. Sorry!

BatchToSpaceND is not longer called on TPU. I think we should fix this gist reported by @ravikyram first: https://colab.research.google.com/gist/ravikyram/9e5e9c9a9d8f5835890ec4b14fda32f5/untitled409.ipynb Is there anyone from TF team can help?

That error is most likely due to a version mismatch between the TF client and the backend. Let's check back in after the next TensorFlow release when it's on Cloud TPUs.

Was able to reproduce your issue in Tensorflow 2.5, please find the gist here. Thanks!

I'm getting this error right now with 2.5.0 and functional API
out = layers.Conv1D(dil_channels, 2, padding="causal", dilation_rate=d, use_bias=False, kernel_initializer=initializer)(x)

How is this error so old please fix... I moved back to TF to use TPUs but it's 90% errors and two weeks of wasted time, I'm going back to pytorch. Sorry for the complaining, but TF with TPU has been impossible to work with in all aspects and I'm at my wits' end when after finally dropping down to the functional API, something you'd think should be simple and work well, it turns out you can't use dilation != 1 in conv layers. It's 2021. What's your answer, move to JAX? JAX tells me to train a model in tensorflow in order to save it for production lol... how does deepmind get anything done?

Hi @sachinprasadhs, the problem should have been fixed by @yunxing. Could you try TF nightly?

@rxsang
I am able to replicate the issue on tf [2.6 as well], please find the gist here

Any updates here? Conv1D with delation still not working. I tryed tf2.6 and tf-nightly [2.7.0.dev20210831-cp37-cp37m-manylinux2010_x86_64]

@rxsang
I am able to replicate the issue on tf [2.6 as well], please find the gist here

Hello, I found the temporary solution:
You should to set drop_remainder to "True" to fix the size of batch.

dataset = tf.data.Dataset.from_tensor_slices(data).shuffle(buffer_size=batch_size).repeat().batch(batch_size, **drop_remainder=True**)

Hi @Hiroshiba !
We are checking to see whether you still need help in this issue . Did you check with above suggestion yet? Thanks!

I don't know, but let's close it!


Incompatible version of importlib-metadata when installing mmdet3d

Environment
ubuntu18.04
cuda 11.1
Problem description
During the process of installing mmdet3d,  I encounter the problem of incompatible versions between flake8 5.0.4 and importlib-metadata.
Problem Reproduction

Following the official install.md, I came to step 6 "Install mmdet3d from source code".
when running "python setup.py install", it shows dependency conflict that flake8 needs importlib to be < 4.3:

I tried to degrade importlib-metadata to 4.2, but when it seemed that mmdet3d and another package "markdown" need importlib-metadata to be >=4.4.

Question
I've searched the Internet and other issues, but I still can't find the solution. So could anyone please tell me which version of importlib do you use, or the proper process of  installing mmdet3d? Thank you for your generous help!

Hi, we use import lib-metadata as 4.0.0. And you may refer to #49 to get full pip list.

Hi, we use import lib-metadata as 4.0.0. And you may refer to #49 to get full pip list.

Thank you for your reply! I'll try it again.

The conflict comes from the versions of importlib_metadata, flake8 and markdown. I install the specific version of these packages following  issue #49, and finally finish the installation. The issue is closed, and thank weiyithu again.


Conductor docker image fail to register task

Hi, I am brand new to conductor so I still don't understand completely what goes on under the hood. I am running the docker images by using docker-compose and I can see the following running on my docker desktop (MacOS):
conductor:ui                                          <IP_ADDRESS>:5000->5000/tcp
conductor:server                                      8090/tcp, <IP_ADDRESS>:8088->8080/tcp
docker.elastic.co/elasticsearch/elasticsearch:5.6.8   <IP_ADDRESS>:9200->9200/tcp, <IP_ADDRESS>:9300->9300/tcp
v1r3n/dynomite                                        8101/tcp, 22122/tcp, 22222/tcp, <IP_ADDRESS>:8102->8102/tcp
I am getting this error when I call /api/metadata/taskdefs:
169704475 [pool-2-thread-1] DEBUG com.netflix.dyno.connectionpool.impl.ConnectionPoolImpl  - Updating hosts: UP=[Host [hostname=dyno1, ipAddress=null, port=8102, rack: us-east-1c, datacenter: us-east-1, status: Up, hashtag=null, password=null]], DOWN=[]
169704475 [pool-2-thread-1] DEBUG com.netflix.dyno.connectionpool.impl.ConnectionPoolImpl  - HostConnectionPool already exists for host: Host [hostname=dyno1, ipAddress=null, port=8102, rack: us-east-1c, datacenter: us-east-1, status: Up, hashtag=null, password=null], ignoring addHost
169705743 [pool-2-thread-1] DEBUG com.netflix.dyno.connectionpool.impl.health.ConnectionPoolHealthTracker  - Running, pending pools size: 0
169708510 [pool-5-thread-1] DEBUG com.netflix.dyno.connectionpool.impl.health.ConnectionPoolHealthTracker  - Running, pending pools size: 0
169715713 [pool-2-thread-1] DEBUG com.netflix.dyno.connectionpool.impl.health.ConnectionPoolHealthTracker  - Running, pending pools size: 0
169716269 [qtp1069131391-66] ERROR com.netflix.conductor.server.resources.GenericExceptionMapper  - Error PoolTimeoutException url: 'metadata/taskdefs'
at com.sun.jersey.server.impl.model.method.dispatch.AbstractResourceMethodDispatchProvider$VoidOutInvoker._dispatch(AbstractResourceMethodDispatchProvider.java:167)
at com.sun.jersey.server.impl.model.method.dispatch.ResourceJavaMethodDispatcher.dispatch(ResourceJavaMethodDispatcher.java:75)
at com.sun.jersey.server.impl.uri.rules.RootResourceClassesRule.accept(RootResourceClassesRule.java:84)
at com.sun.jersey.server.impl.application.WebApplicationImpl._handleRequest(WebApplicationImpl.java:1542)
at com.sun.jersey.server.impl.application.WebApplicationImpl._handleRequest(WebApplicationImpl.java:1473)
at com.sun.jersey.spi.container.servlet.ServletContainer.service(ServletContainer.java:558)
at com.sun.jersey.spi.container.servlet.ServletContainer.service(ServletContainer.java:733)
The response body is:
{     "code": "INTERNAL_ERROR",     "message": "INTERNAL_ERROR - PoolTimeoutException: [host=Host [hostname=dyno1, ipAddress=null, port=8102, rack: us-east-1c, datacenter: us-east-1, status: Up, hashtag=null, password=null], latency=800964(0), attempts=0]Fast fail waiting for connection from pool",     "retryable": false,     "instance": "93ad7a567e40" }
I did not modify any configuration files in the docker containers so this is from a  fresh run from docker.
I appreciate any help to get me started.
Thanks.

Hey @miguelC, It's not clear from the logs about what is happening. My best guess from the debug logs is that post 8102 is taken by some other service, and unable to map to dynomite.
Can you try debugging backwards, and see if you can connect to dynomite server.


Ionic 2: Icons inside of ion-items/buttons are cuts

Ionic version:  (check one with "x")
[ ] 1.x
[X] 2.x
I'm submitting a ...  (check one with "x")
[X] bug report
[ ] feature request
[ ] support request => Please do not submit support requests here, use one of these channels: https://forum.ionicframework.com/ or http://ionicworldwide.herokuapp.com/
Current behavior:
Ionic 2.0.1: The icons inside of ion-items/buttons are cuts
Expected behavior:
Normal full icons inside ion-items/buttons, no cuts
Steps to reproduce:
Just put an ion-icon inside a button  with the ion-item directive inside a ion-list component
Related code:
<ion-list>
    <button ion-item icon-left (click)="logout()">
      <ion-icon name="log-out"></ion-icon>
      Logout
    </button>
</ion-list>

Plunker example preview
Other information:

stackoverflow question
Ionic info: (run ionic info from a terminal/cmd prompt and paste output below):
Your system information:
Cordova CLI: 6.5.0
Ionic Framework Version: 2.0.0
Ionic CLI Version: 2.2.1
Ionic App Lib Version: 2.2.0
Ionic App Scripts Version: 1.0.0
ios-deploy version: Not installed
ios-sim version: Not installed
OS: Windows 10
Node Version: v7.4.0
Xcode version: Not installed

Thanks for opening an issue with us, we will look into this.

@slzr This is because you're mixing up button and item attributes. icon-left shouldn't be applied on items. The icon-left attribute is useful for button styles to place the icon to the left of the text. What you want here is either:
<button ion-item (click)="logout()">
  <ion-icon name="log-out"></ion-icon>
  Logout
</button>

or:
<button ion-item (click)="logout()">
  <ion-icon item-left name="log-out"></ion-icon>
  Logout
</button>

For more information on item placement check out the API docs: http://ionicframework.com/docs/v2/api/components/item/Item/#item-placement
Thanks! :)

using item-left displays icon in the middle of the field, pushing button to the bottom


fix: wrap isImage in a try-catch

Instead of failing the whole code flow, just silently parse as false and skip the item

LGTM. Thank you for contributing!

released in v2.0.8! 🚀


Perform Brakeman Audit

Brakeman is a scanner. We should perform an audit to determine what we need to fix, if anything.

Audit was completed.
The results are here
We need to investigate the vulnerability and confirm whether we are in fact, vulnerable.

It looks like you're fine (also hey! I watch this repo a lot).

@jalcine good looking out!

I was concerned about the raw calls in _main_content.html.erb, but I haven't been able to prove conclusively that this is a problem.
We're getting a lot more traffic, and some White power groups have noticed us, so I'd like to batten down the hatches.

That's real. If anything, nixing them altogether (if feasible) could make that less of a worry.

Yeah, I thought so. It's used for the rich editing piece. Thinking of having people use Markdown instead (OWASP recommendations)

...and this is clean.


[msbuild] add vcpkg to  search path

Adds vcpkg to the Lib Tasks <AdditionalLibraryDirectories>lib search path.
In our company we have to add some vcpkg libs to Librarian -> Additional Dependencies, but the vcpkg lib dir is missing from Librarian -> Additional Library Directories.
@BillyONeal

Thanks for the bugfix!


Enemy -1 Quarry?

The game does not allow for you to knock the enemy Resource to a zero level?
Quarry, Magic, Dungeon.
Was this done on purpose?  I have not played a version, were this was the case.
Am i doing something wrong?

Yes it's on purpose. The original Arcomage game does not allow any generator to be reduced to zero.
Actually in the very early versions of ArcoMage HD it's allowed. Someone mentioned that to me, I was not quite sure so I asked in the Discord "Might and Magic" server to make sure it's not allowed in the original game before I changed it here.
It's also mentioned in the tutorial image:
https://raw.githubusercontent.com/arcomage/arcomage-hd/main/misc/readme_images/manual.jpg
("Minimum generator ...")

If zero is allowed, the player with 0 generator will get unreasonably horrible disadvantage. It'll perhaps also be possible that the game never ends, or becomes slow and boring when both player have 0 generator.

The versions i have played, which allowed this, were a homebrew for the Nintendo DS & the Stand-Alone Windows 98 version from 3DO.
I just did some reading... here is a review of the Stand-Alone version.
"Unlike in the Might and Magic version of Arcomage, the stand-alone version allows resource generators to be knocked down to zero, and the computer tends to take full advantage of this fact whenever possible, leading to a great deal of cursing at the screen."
:)
You have been corroborated, and i guess that IS an original rule!  So, i am glad to be playing the authentic M&M version!
I do like the Acromage HD AI, too.  It is a much more worthy opponent, than the two versions i have played.
This truly represents a duel of mages!
Thank you!

I searched the review you've read https://www.old-games.com/download/5055/arcomage . Nice review. And yes I believe in ArcoMage HD I fixed all those problems mentioned in the review: 0 generator; AI damaging itself, AI discarding valuable cards.
Enjoy the game.

Thanks for your time, all the information, and most importantly your work!
Well done.

For future reference:
a7ac788d890965c3d36047515a9c5f89fce952bd
dbc5683087998505f5881c683470b4d21dbc3bad


Login first click fails

i think the bug got resolved when redux was implemented, i can no longer recreate the bug, im pretty sure it's gone liao.


[BUG]: it's "skimage" NOT "scikit-image" !!!

In install.py you have:
if not launch.is_installed("ffmpeg-python"):
    launch.run_pip("install ffmpeg-python", "Install \"ffmpeg-python\" requirements for TemporalKit extension")

but this is causing "scikit-image" to always be reinstalled, because this is not the way the package is referred to in code.
The correct name is "skimage":
if not launch.is_installed("skimage")
Please fix it asap as this is causing environments to break, inconsistencies and so many headaches.

Actually, this should be addressed in sd-webui instead: https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/13487


Help Wanted:  Documentation

We want to provide a good documentation and realworld examples that people can use
A getting started guide would be amazing.

Every help is welcome here  and a great way to contribute to this project

I would love to work on this.

sounds good!


Ionic Cloud more than one user logging in at once fails

Ionic version:  (check one with "x")
[ ] 1.x
[X] 2.x
I'm submitting a ...  (check one with "x")
[X] bug report
[ ] feature request
[ ] support request => Please do not submit support requests here, use one of these channels: https://forum.ionicframework.com/ or http://ionicworldwide.herokuapp.com/
Current behavior:

When more than one user tries to authenticate with Instagram at the same time, an error occurs with one or more of the users: "message": "Invalid state parameter provided"
See Ionic Cloud number 182
Expected behavior:

Steps to reproduce:

Related code:
https://github.com/driftyco/ionic-cloud/issues/182

Other information:

Ionic info: (run ionic info from a terminal/cmd prompt and paste output below):
Ionic Cloud Issues 182

I have posted on Ionic Cloud and Cloud Issues, would be great to hear back as it's been 2 days now and I've got 150 angry beta testers.

Please post at https://github.com/driftyco/ionic-cloud-issues

Thanks for opening an issue with us! Going to close this as a duplicate of https://github.com/driftyco/ionic-cloud/issues/182


Dratf : Add support for bridge jobs

Add support for bridge jobs
Pipeline bridges doc : https://docs.gitlab.com/ee/api/jobs.html#list-pipeline-bridges

Mocks are coming

Mocks  in next PR


Fixed using display file with extfile(*extdesc)

When declaring a display file with 'extfile(*extdesc)' keyword, we need to retrieve the "extdesc" keyword and value in order to retrieve the variable.
Actualy the system search for 'DISPLAY' file
DSPFFD FILE(\*LIBL/DISPLAY) OUTPUT(\*OUTFILE) OUTFILE(ILEDITOR/RDIS934745)
So it return a CPF3012.
Changes
Retrieve the name's file if 'extfile' is '*extdesc' to retrieve variables.
Before :

After :

Checklist

[X] have tested my change
[ ] updated relevant documentation
[X] Remove any/all console.logs I added
[ ] eslint is not complaining
[ ] have added myself to the contributors' list in the README
[X] for feature PRs: PR only includes one feature enhancement.

I like the idea, but the outline view really has to show the name of the definition and not the one of the definition properties. I will have to ask around about this idea and I will get back to you.

If you look at my screenshot, you can see that without the correction, the variables does not appear.
That the goal of the modification.
I can change to display the name of the definition.
Let me know.

@sebCIL Oh yes! Please change the name that is shown (it should be Display that appears in the outline) and then I will do some testing to ensure it works.
Sorry for my bad comment above. I am kind of slow at the moment.

No problem, my description and screenshot  was not very clear.
I'll tell you when it's done.

Done.
I took the opportunity to change the description and the screenshots.

Thank you @sebCIL !!


Fix media plugin / hack for style elements

The media attribute is automatically removed for stylesheet
links if there are no print styles defined.
Previously however, the aforementioned 'autoremoving' behaviour
only applied to elements with rel=stylesheet, and it did not
apply to style elements.
This commit addresses the problem by including style elements
in the query selector.

Fixes #61 (Github)
Signed-off-by: Ian Lai<EMAIL_ADDRESS>

Does this also include media queries in the stylesheets themselves?
Try generating a PDF of this page: http://athena-demo-2.surge.sh/
docker run --rm -v $(pwd):/converted/ arachnysdocker/athenapdf athenapdf 'http://athena-demo-2.surge.sh/' athena-demo-2.pdf
and compare to the PDF generated from wkhtmltopdf:
wkhtmltopdf 'http://athena-demo-2.surge.sh/' athena-demo-2-wk.pdf
With the versions I've got, athenapdf ignores the "screen" and "only screen" while wkhtmltopdf ignores "print" and "only print"
This may explain some of the missing background colors I was seeing in issue #61

@foundryspatial-duncan, unfortunately not.
Ideally, it'll be great if we can toggle the CSS media between print and screen on Electron itself (and not rely on the hack we have at the moment), but this is not currently possible.

Shoot, that's a big one. If there's a goal of having a PDF that renders the same in the browser, this would be a big hurdle (Bootstrap etc. being full of media queries out of the box).


vascular system

The PO is_a hierarchy is:
+/ PO:0009011 ! plant structure [DEF: "Any morphological or anatomical feature of a plant."]
++is_a PO:0009007 ! tissue [DEF: "Group of cells organized into a structural and functional unit; the component cells may be alike (simple tissue) or varied (complex tissue)."]
+++is_a PO:0000034 ! vascular system ***  [DEF: "Total of the vascular tissues in their specific arrangement in a plant or plant organ."]
This is different from animal anatomy ontologies which are organized by CARO in which anatomical system is a sibling to (portion of) tissue
E.g.
+is_a CARO:0000003 ! anatomical structure [DEF: "Material anatomical entity that has inherent 3D shape and is generated by coordinated expression of the organism's own genome."]
++is_a CARO:0000043 ! portion of tissue ***  [DEF: "Anatomical structure, that consists of similar cells and intercellular matrix, aggregated according to genetically determined spatial relationships."]
++is_a CARO:0000054 ! anatomical group [DEF: "Anatomical structure consisting of at least two non-overlapping organs, multi-tissue aggregates or portion of tissues or cells of different types that does not constitute an organism, organ, multi-tissue aggregate, or portion of tissue."]
+++is_a CARO:0000011 ! anatomical system ***  [DEF: "Anatomical group that is has as its parts distinct anatomical structures interconnected by anatomical structures at a lower level of granularity."]
Would the CARO definition of tissue work for plants?
can we have 'anatomical system' as sibling to tissue underneath plant structure?
Also - the def of vascular system is:
PO:0000034 ! vascular system [DEF: "Total of the vascular tissues in their specific arrangement in a plant or plant organ."]
The disjunction (or) is confusing. Does an individual plant have a single vascular system, with different parts (e.g. flower vascular system)? Or does an individual plant have multiple separate vascular systems (e.g. flower vascular system)
If the former, then the relation between X vascular system and vascular system should be part_of. The definitions should read "the part of the vascular system that is in X"
If the latter, then the relation should be is_a, and the definitions should read "a vascular system that is in X"
Currentlyin PO all relations are is_a, with the exception of
PO:0000035 ! cotyledon vascular system [DEF: "Vascular system of the cotyledon."]
The definition follows the same structure as the other X vascular system terms. Any reason for the difference in ontology structure?
My preference would be to define VS as the entire system running throughout the plant. We would then have terms like "X vasculature" which would be is_a vasculature, part_of X. This would require a new term "vasculature" which would be defined as a segment of the VS in an organ.
PO also states that "flower vascular system" is_a flower. This is wrong, the relation should be part_of.
Reported by: cmungall
Original Ticket: obo/plant-ontology-po-term-requests/50

See also #41


zephyr: CMakeLists.txt: support nrfjprog mass erase flag

NOTE: depends on https://github.com/zephyrproject-rtos/zephyr/pull/6809 -- DO NOT MERGE unless that's merged as well
The upstream Zephyr runner for nrfjprog now supports an --erase
toggle, which controls whether a mass-erase is done. Add that to its
invocation when CONF_ZEPHYR_TRY_MASS_ERASE is given, just like is done
for dfu-util and pyocd.

@mbolivar Should this be merged? Otherwise please close the PR.

@mbolivar Should this be merged? Otherwise please close the PR.

Sorry, I lost track of this one. Yes, it would be great to merge this one.

@carlescufi  This was not merged before for some reason. Was it nrfjprog incompatibility between nrf51/52? I mean uicr erase behavior or something.

This is coming kind of late in the rc for this release. Would we be ok releasing 1.3.0, and then merging this?

For sure.

@mbolivar There's a mismatch on the domain of your commit and sob (@foundries.io vs @opensourcefoundries.com)

Dang company has been renamed too many times :). Thank you, fixed.

Maybe just reserve a consistent domain to use: something like<EMAIL_ADDRESS>


Proposal for improved bot support

Documentation: https://docs.google.com/document/d/13ec6iqTQc7gMYGtiyP6qkzsgi3APVwuoXqJFHrfLEP4/edit?usp=sharing
Date: 14/03/2018

kinda note to self: may be worth considering https://github.com/matrix-org/matrix-doc/issues/1242 in this proposal

@benparsons when you get a chance, this can be moved to ready-for-review. I'm not sure which core team member to make the victim for review though.

@turt2live is done. Website cron tomorrow morning.
I will be away next week, suspect @ara4n will be most likely pingable entity for this kind of request (sorry chief!), also @uhoreg if he has permission?

It's open to the community to review, although iirc the proposal process requires someone from the core team to look it over as well. If both reviewed it, that'd be awesome :)

An interesting thing, I overlooked that. Would be great to see it in the spec by the end of the year :)

don't have much to add, just want to say that I really love this and hope it's not being forgotten.
Also kinda wondered if clients then should show users what the bot will see (what commands this bot supports) before actually inviting a bot to a room so that a user can make an informed decision. though I'm unsure what should happen when a bot introduces m.bot key when it's already in the room or changes what commands it supports. would be nice if a bot couldn't just introduce passive commands without users (or at least admins/moderators) in the room being aware of that.
but that's probably out of scope for this proposal.

Also kinda wondered if clients then should show users what the bot will see (what commands this bot supports) before actually inviting a bot to a room so that a user can make an informed decision.

This would likely require extensible profiles (#489).

Just to mention that because all of the content of this proposal is in a Google Doc (somewhat ironically, for a privacy-focused/open protocols project!), it's pretty difficult to find this when searching for issues relating to E2EE and bots. Maybe someone with privileges could tag this issue with e2e and whichever other tags are relevant?
Also, tangentially, anyone know if https://element.io/integration-manager-privacy-notice is incomplete in regard to when data might be exposed to 3rd parties?
Bots
All unencrypted events in rooms in which a Element-managed bot is participating are theoretically visible to New Vector.

Wouldn't that also extend to encrypted events if the Element-managed bot supports participation in E2EE rooms? Or do none of the bots they make available support E2EE currently?
Adding some keywords here for searchability: encryption, integration, widget.

This MSC was written about 4 processes ago - for it to get maintenance, it'd be converted to markdown like all the rest. As people have mentioned, this MSC is largely blocked behind other MSCs so there's not much interest in keeping it up to date at the moment.

Also, tangentially, anyone know if https://element.io/integration-manager-privacy-notice is incomplete in regard to when data might be exposed to 3rd parties?

This seems offtopic for this discussion. I'd recommend asking the integration manager team at Element for more information (possibly via a support email of some kind).


Make pubsub option emitSelf configurable

First and foremost: Thanks for this great package and the hard work! :+1:

Version: 0.26.0
Platform: Linux Kubuntu-18 4.18.0-25-generic
Subsystem:

Type: Feature

Severity: Low
Description:
Currently is the option emitSelf for pubsub packages (libp2p/js-libp2p-floodsub and ChainSafe/gossipsub-js) hardcoded in the code.
https://github.com/libp2p/js-libp2p/blob/fd738f9d51e2166861ce8327c8ef2f4eb52a27be/src/pubsub.js#L10
Both pubsub packages support the emitSelf option. It would be nice to add the option to specify if self-published messages should be received.
Example:
export class Bundle extends libp2p {
  constructor(_options) {
    const defaults = {
      modules: {
        transport: [TCP],
        streamMuxer: [Mplex],
        connEncryption: [SECIO],
        peerDiscovery: [Bootstrap],
        dht: DHT,
        pubsub: GossipSub,
      },
      config: {
        pubsub: {
          enabled: true,
+         emitSelf: false,
        },
      },
    };
    super(defaultsDeep(_options, defaults));
  }

Steps to reproduce the error:

If this feature request is granted I would like to have this issue assigned to me :slightly_smiling_face:

Yes, we should pass the configuration into the Pubsub initialization. We should account for other Pubsub options as well when doing this, such as the strict signing and verification params https://github.com/libp2p/js-libp2p-pubsub/blob/v0.2.0/src/index.js#L30-L31. I'd expect the whole pubsub config object to get passed.

Fixed in #404


Bug? Differences between Graph() of version 0.3.3 and latest Keras API when I built Bidirectional GRU with two layers.

Two problems happened when I used the latest Keras API.

After the model was trained, I saved the model architecture and weights. However, the reloaded model can't do prediction. Then I find I have to recompile a exactly same model and just loaded the weights. Actually, the model architecture can't be reloaded successfully. In addition, I didn't find such problem in 0.3.3.
GRU_model = model_from_json(open('GRU_model_architecture.json').read()) # -->something wrong in source code?
GRU_model.load_weights('GRU_model_weights.h5')

I built a Bidirectional GRU with two layers with the latest Keras API by the following codes. I find the results haven't been improved by comparing with the normal GRU model with one layer. However, it showed there are huge differences between the simple GRU and complex GRU models when I used the old version 0.3.3 by Graph(). In the latest version, have the model really compiled? No error was reported during running.  Bug or my bad coding..?

latest version
def Bi_2l_GRU(self, X, Y, vec_dim, sent_length, first_output_dim, drop_percent, nepoch):

    inputs = Input(shape=(None, vec_dim), batch_shape=(1, None, vec_dim), name='inputs')
    layer1_out1 = GRU(sent_length, activation='tanh', return_sequences=True, dropout_U=drop_percent, dropout_W=drop_percent)(inputs)
    layer1_out2 = GRU(sent_length, activation='tanh', return_sequences=True, dropout_U=drop_percent, dropout_W=drop_percent, go_backwards=True)(inputs)
    layer1_loss = TimeDistributed(Dense(first_output_dim, activation='softmax'))(layer1_out1, layer1_out2)
    layer2_out1 = GRU(sent_length, activation='tanh', return_sequences=True, dropout_U=drop_percent, dropout_W=drop_percent)(layer1_loss)
    layer2_out2 = GRU(sent_length, activation='tanh', return_sequences=True, dropout_U=drop_percent, dropout_W=drop_percent, go_backwards=True)(layer1_loss)
    predictions = TimeDistributed(Dense(3, activation='softmax'))(layer2_out1, layer2_out2)
    model = Model(input=inputs, output=predictions)
    model.compile(optimizer='rmsprop', loss='categorical_crossentropy', metrics=['accuracy'])

    for epoch in xrange(nepoch):
        print 'epoch:', epoch
        for idx, (seq, label) in enumerate(zip(X, Y)):
            #model.train_on_batch(np.array([seq]), np.array([label.T]))
            loss, accuracy = model.train_on_batch(np.array([seq]), np.array([label.T]))
            if idx % 50 == 0:
                print "\tidx={0}, loss={1}, accuracy={2}".format(idx, loss, accuracy)
    return model

version 0.3.3
def Bi_2l_GRU(self, X, Y, vec_dim, HIDDEN_SIZE, nepoch):

    model = Graph()
    model.add_input(name='input', input_shape=(None, vec_dim))
    model.add_node(GRU(HIDDEN_SIZE, activation='tanh', return_sequences=True), name='forward', input='input')
    model.add_node(GRU(HIDDEN_SIZE, activation='tanh', return_sequences=True, go_backwards=True), name='backward', input='input')
    model.add_node(Dropout(0.5), name='dropout', merge_mode='concat', inputs=['forward', 'backward'])
    model.add_node(GRU(HIDDEN_SIZE, activation='tanh', return_sequences=True), name='level2_forward', input='dropout')
    model.add_node(GRU(HIDDEN_SIZE, activation='tanh', return_sequences=True, go_backwards=True), name='level2_backward', input='dropout')
    model.add_node(Dropout(0.5), name='level2_dropout', merge_mode='concat', inputs=['level2_forward', 'level2_backward'])
    model.add_node(TimeDistributed(Dense(3, activation='softmax')), name='softmax', input='level2_dropout')
    model.add_output(name='output', input='softmax')
    model.compile('adam', {'output': 'categorical_crossentropy'}, metrics=["accuracy"])

    for epoch in xrange(nepoch):
        print 'epoch:', epoch
        for idx, (seq, label) in enumerate(zip(X, Y)):
            loss, accuracy = model.train_on_batch({'input':np.array([seq]), 'output':np.array([label.T])})
            if idx % 50 == 0:
                print "\tidx={0}, loss={1}, accuracy={2}".format(idx, loss, accuracy)
    return model

[Yes ] Check that you are up-to-date with the master branch of Keras. You can update with:
pip install git+git://github.com/fchollet/keras.git --upgrade --no-deps

[ Yes] If running on Theano, check that you are up-to-date with the master branch of Theano. You can update with:
pip install git+git://github.com/Theano/Theano.git --upgrade --no-deps

[ Yes] Provide a link to a GitHub Gist of a Python script that can reproduce your issue (or just copy the script here if it is short).

What is your question exactly? The two models aren't equivalent. You use different dropout methods and optimizers, for example.


Editing a saved query no longer opens the query in sql lab

A clear and concise description of what the bug is.
How to reproduce the bug

Go to sql lab
Create a saved query
Close out all tabs in sql lab
Go to the saved query list page
Click on edit for the saved query

Expected results
You are taken back to sql lab with your saved query opened
Actual results
Tab doesn't open for the saved query
Screenshots
https://github.com/apache/superset/assets/47334392/5d1cc39c-309b-4e40-b758-d0a235753a0a
Environment
(please complete the following information):

browser type and version:
superset version: superset version
python version: python --version
node.js version: node -v
any feature flags active:

Checklist
Make sure to follow these steps before submitting your issue - thank you!

[ ] I have checked the superset logs for python stacktraces and included it here as text if there are any.
[ ] I have reproduced the issue with at least the latest released version of superset.
[ ] I have checked the issue tracker for the same issue and I haven't found one similar.

Additional context
Add any other context about the problem here.

Here is another view. If you use the action to copy the link and follow the link, you get a 404 for the endpoint savedqueryviewapi/api/get/{id}
https://github.com/apache/superset/assets/47334392/072b5933-1412-4db4-9311-4ce647e97454


chore(tracing): remove tracingMiddleware

Pull Request Test Coverage Report for Build 1703

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 63.793%

Totals

Change from base Build 1701:
0.0%

Covered Lines:
101

Relevant Lines:
152

💛  - Coveralls


add "--subscription" in global pamaters

Docs Build status updates of commit 8ff1fab:
:white_check_mark: Validation status: passed

File
Status
Preview URL
Details

.docsreference.azurecli.json
:white_check_mark:Succeeded

For more details, please refer to the build report.
Note: Broken links written as relative paths are included in the above build report. For broken links written as absolute paths or external URLs, see the broken link report.
For any questions, please:Try searching the docs.microsoft.com contributor guidesPost your question in the Docs support channel

@yonzhan, This is part of the reference autogeneration process.  If @daxianji007 has added it, I assume it should be merged.  What kind of feedback are you looking for from the other reviewers?

@dbradish-microsoft I confirmed with the dev team that every CLI command has a --subscription parameter. So, I will complete this PR.

@dbradish-microsoft Em... I see. This is added to all commands but some commands explictly ignored it. The Docs Pipeline currently does not support different "Global Parameters" for different commands (since it is 'global'). We can track this and implememt it when we have time to do kind of refactor.

CCing @chasewilson for awareness and I defer further discussion to the engineering team.


renewal request

Source name
scan-manga
Source language
french
Source link
https://m.scan-manga.com/?po
Other details
the extension is no longer functional and must be renewed
Acknowledgements

[X] I have updated all installed extensions.
[X] I have opened WebView and checked that the source website is down.
[X] I have searched the existing issues and this is a new ticket, NOT a duplicate or related to another open or closed issue.
[X] I have written a meaningful title with the source name.
[X] I will fill out all of the requested information in this form.

Add a :+1: reaction to issues you find important.

Duplicate of #2232, it's already been reported before. Search the existing issues first before opening a new one, and acknowledging that you did when you clearly didn't.
Also, wrong issue request, this is for when the site is dead & gone. But again, already reported before


fix: onInit throwing useEffect not defined

Description
Fixes issue
https://github.com/BuilderIO/mitosis/issues/428

@chadalen you need to update the jest tests in packages/core, by running yarn run snapupdate

@chadalen you need to update the jest tests in packages/core, by running yarn run snapupdate

Done

@chadalen Looking at the github actions again, it looks like you also need to run prettier! yarn run fmt:prettier in the root of the project and you're all set on your first contribution here 😄

@chadalen Haha please do!! That would be greatly appreciated 🙏🏽

And welcome to the Mitosis contributor club!


Deletion of downloaded files?

When unpackerr finished extraction, the file is imported, i thought unpackerr will delete the unpacked files and the donloaded files.
Instead, only the extracted files are deleted.
Does an option exist, to also delete the downloaded files?

Ah, i should have mentioned that im only using usenet.

Make sure you're using the latest beta: https://github.com/davidnewhall/unpackerr/releases/tag/v0.8.0-beta2
And set delete_orig to true: https://github.com/davidnewhall/unpackerr/blob/master/examples/unpackerr.conf.example#L82-L85

Great, thank you!


Account unlock issue when CaseInsensitiveUsername=false for username which have both upper and lower case.

When the following property is false, IDENTITY_LOGIN_DATA_CACHE is not working properly for usernames which have both upper and lower cases.
CaseInsensitiveUsername=false

@IsuraD Is the latest IS version affected by this?


test/encode: move requires to class level

This change moves common slash.requires to the class
level on derived test classes to remove the duplication
that previously occurred across each class test method.
The class-level slash.requires on subclasses are supported
since slash 1.7.10.
Signed-off-by: U. Artie Eoff<EMAIL_ADDRESS>

cc: @Bin-QA

cc: @Bin-CI


use node 18

:tada: This PR is included in version 10.3.0 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


python3Packages.jsonstreams: 0.5.0 -> 0.6.0

Motivation for this change
A new version is available.  Changelog.
Things done

[x] Tested using sandboxing (nix.useSandbox on NixOS, or option sandbox in nix.conf on non-NixOS linux)
Built on platform(s)

[x] NixOS
[ ] macOS
[ ] other Linux distributions

[ ] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[x] Tested compilation of all pkgs that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review wip"
[x] Tested execution of all binary files (usually in ./result/bin/)
[x] Fits CONTRIBUTING.md.

Result of nixpkgs-review pr 126450 run on x86_64-linux 1

4 packages built:

python38Packages.jsonstreams
python38Packages.scancode-toolkit
python39Packages.jsonstreams
python39Packages.scancode-toolkit


Is rubyfmt compatible with standardrb on rules?

I'm considering using rubyfmt for formatting and standardrb for LSP diagnostics, but I'm uncertain if rubyfmt and standardrb agree on the same rules (e.g. indentation or spaces inside brackets). Does rubyfmt implement the same rules as standardrb?

According to @searls comments at standard #482 and #159:

The long-term goal of Standard & rubyfmt has always been eventual agreement in formatting rules.

I guess rubyfmt & standard are compatible.


Can't connect to MySQL server

Hello, have an issue on a new install...
After making prescribed config changes, I run the ./quick-start.py, and everything appears to startup. I have it connecting to a remote DB.
However after startup, when I try to run docker-compose -f docker-prod.yml run --rm --entrypoint 'python manage.py createsuperuser' api I get the following error...
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/site-packages/django/db/backends/base/base.py", line 216, in ensure_connection
    self.connect()
  File "/usr/local/lib/python3.6/site-packages/django/db/backends/base/base.py", line 194, in connect
    self.connection = self.get_new_connection(conn_params)
  File "/usr/local/lib/python3.6/site-packages/django/db/backends/mysql/base.py", line 227, in get_new_connection
    return Database.connect(**conn_params)
  File "/usr/local/lib/python3.6/site-packages/MySQLdb/__init__.py", line 86, in Connect
    return Connection(*args, **kwargs)
  File "/usr/local/lib/python3.6/site-packages/MySQLdb/connections.py", line 204, in __init__
    super(Connection, self).__init__(*args, **kwargs2)
_mysql_exceptions.OperationalError: (2003, 'Can\'t connect to MySQL server on \'<IP_ADDRESS>\' (110 "Operation timed out")')

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "manage.py", line 10, in <module>
    execute_from_command_line(sys.argv)
  File "/usr/local/lib/python3.6/site-packages/django/core/management/__init__.py", line 381, in execute_from_command_line
    utility.execute()
  File "/usr/local/lib/python3.6/site-packages/django/core/management/__init__.py", line 375, in execute
    self.fetch_command(subcommand).run_from_argv(self.argv)
  File "/usr/local/lib/python3.6/site-packages/django/core/management/base.py", line 316, in run_from_argv
    self.execute(*args, **cmd_options)
  File "/usr/local/lib/python3.6/site-packages/django/contrib/auth/management/commands/createsuperuser.py", line 59, in execute
    return super().execute(*args, **options)
  File "/usr/local/lib/python3.6/site-packages/django/core/management/base.py", line 352, in execute
    self.check_migrations()
  File "/usr/local/lib/python3.6/site-packages/django/core/management/base.py", line 442, in check_migrations
    executor = MigrationExecutor(connections[DEFAULT_DB_ALIAS])
  File "/usr/local/lib/python3.6/site-packages/django/db/migrations/executor.py", line 18, in __init__
    self.loader = MigrationLoader(self.connection)
  File "/usr/local/lib/python3.6/site-packages/django/db/migrations/loader.py", line 49, in __init__
    self.build_graph()
  File "/usr/local/lib/python3.6/site-packages/django/db/migrations/loader.py", line 212, in build_graph
    self.applied_migrations = recorder.applied_migrations()
  File "/usr/local/lib/python3.6/site-packages/django/db/migrations/recorder.py", line 61, in applied_migrations
    if self.has_table():
  File "/usr/local/lib/python3.6/site-packages/django/db/migrations/recorder.py", line 44, in has_table
    return self.Migration._meta.db_table in self.connection.introspection.table_names(self.connection.cursor())
  File "/usr/local/lib/python3.6/site-packages/django/db/backends/base/base.py", line 255, in cursor
    return self._cursor()
  File "/usr/local/lib/python3.6/site-packages/django/db/backends/base/base.py", line 232, in _cursor
    self.ensure_connection()
  File "/usr/local/lib/python3.6/site-packages/django/db/backends/base/base.py", line 216, in ensure_connection
    self.connect()
  File "/usr/local/lib/python3.6/site-packages/django/db/utils.py", line 89, in __exit__
    raise dj_exc_value.with_traceback(traceback) from exc_value
  File "/usr/local/lib/python3.6/site-packages/django/db/backends/base/base.py", line 216, in ensure_connection
    self.connect()
  File "/usr/local/lib/python3.6/site-packages/django/db/backends/base/base.py", line 194, in connect
    self.connection = self.get_new_connection(conn_params)
  File "/usr/local/lib/python3.6/site-packages/django/db/backends/mysql/base.py", line 227, in get_new_connection
    return Database.connect(**conn_params)
  File "/usr/local/lib/python3.6/site-packages/MySQLdb/__init__.py", line 86, in Connect
    return Connection(*args, **kwargs)
  File "/usr/local/lib/python3.6/site-packages/MySQLdb/connections.py", line 204, in __init__
    super(Connection, self).__init__(*args, **kwargs2)
django.db.utils.OperationalError: (2003, 'Can\'t connect to MySQL server on \'<IP_ADDRESS>\' (110 "Operation timed out")')

The issue that I have is that it obviously could connect to the database during the install/startup, because what once was an empty database has tables in it when I look. Any ideas?

I figured out the issue... the docker-compose -f docker-prod.yml run --rm --entrypoint 'python manage.py createsuperuser' api command doesn't respect the docker-prod.override.yml file and thus started in a different docker network.

Glad you figured it out. I'll be sure to update the docs.

So how do you fix it?  I'm having the same issue.

I use Portainer for a GUI to easily mange my docker containers, so I consoled into the API container that was created by the script via portainer and manually ran the command python manage.py createsuperuser .
I guess a real resolution to this would be for the devs to find a way to have the docker-compose -f docker-prod.yml run --rm --entrypoint 'python manage.py createsuperuser' api command respect the contents of the override file.

You can chain the yml files together like:
docker-compose -f docker-prod.yml -f docker-prod.version.yml -f docker-prod.override.yml run --rm --entrypoint 'python manage.py createsuperuser' api

This is what is happening in the quick start script but, I must have missed it in the docs.
See: https://github.com/open-eats/OpenEats/blob/master/quick-start.py#L113-L116 for an example.

Running the above "chained" command still gives the MariaDB access error, though.

Are you running ur DB locally or via docker containers?

Default setup, so in the docker container.

Default setup, so in the docker container.

seems more like: https://github.com/open-eats/OpenEats/issues/93
I'm not sure what the issue is yet, I'm looking into it.

Any luck?  The wife has a bunch of recipes laid out waiting to input into somewhere and your app looks promising :)

This issue isn't resolved...

Did you try my suggestion of using portainer and just using the console to run the command?

It's a workaround but doesn't resolve the root cause (which should be fixed if anyone else tries to use it).  I wasn't planning on learning Portainer since I'm not very experienced at this, but I suppose I should at this point since the dev is probably busy with his day job.

In looking at #93 it appears that's the same issue, so this is probably fine to close, anyways.  Cheers :)

That was my main reasoning for it.


pkg/math/bits: implement bit shift operations

The bits package has rotate, but not shift operations.

This issue has been migrated to https://github.com/cue-lang/cue/issues/156.
For more details about CUE's migration to a new home, please see https://github.com/cue-lang/cue/issues/1078.


Alloc trait removed in 1.43 nightlies

We just tried building a test-application with 1.43.0-nightly, 2020-02-05, and it seems like core::alloc::Alloc got removed. Cfr. https://github.com/rust-lang/rust/issues/32838 and the new core::alloc nightly documentation.
I am not experienced enough with custom allocators in Rust to fix this myself, and I don't really find what it was replaced with, so I'm just letting you know. Cc @vanarill

Thanks for the report. This will be fixed soon in the new Drone 0.12 release.


wxPython30: fix on darwin

Motivation for this change
Things done

[x] Tested using sandboxing
(nix.useSandbox on NixOS,
or option build-use-sandbox in nix.conf
on non-NixOS)
Built on platform(s)

[x] NixOS
[x] macOS
[ ] Linux

[ ] Tested compilation of all pkgs that depend on this change using nix-shell -p nox --run "nox-review wip"
[x] Tested execution of all binary files (usually in ./result/bin/)
[x] Fits CONTRIBUTING.md.

I think we should send this to staging.

This has only 5 reverse dependencies.

Thank you!


Clarify the need for -- after forward-headers

I tried to clarify the need for -- after forward-headers (a Yargs array option). I though including the relevant Yargs docs would be a bit to technical?
Related issue: https://github.com/APIs-guru/graphql-faker/issues/49

@peteruithoven Thanks 👍 Merged 🎉


switching active address is slow

fixed in https://github.com/DarkFlorist/TheInterceptor/commit/659702ab169d885506034db1c544647fc9dba7e5


RequestMapping with multiple values/paths

Using the spring annotation @RequestMapping it is possible to define multiple paths for one controller method:
@RequestMapping(value = {"/v1.0/accept", "/v.1.1/accept"} ...)
This is very useful when one method keeps the same over the course of multiple api versions.
The generated swagger.json only contains the first path defined in the array. Is there a way to generate a swagger.json containing all the available paths or a way to define a pattern for paths which should be included?

I have the same issue and I made some changes on my fork to include this feature.
You can find an "alpha" version here: my local branch.
Please build it with -Dskiptest since I have not fixed tests yet.
Please give me any suggestion and feedback.

any news on supporting this? My project defines multiple paths for one controller in order to apply different forms of endpoint security, and this would be a great feature to have.


Map not showing its shows blank screen.

The map isn't showing up in my application. The map view has the Google logo on the bottom left, but it's otherwise blank. I tried removing and re-adding the plugin, but that didn't work either.
So i tried removed and added in the plugin but not worked.These below commands i used...
tns remove nativescript-google-maps-sdk
tns add nativescript-google-maps-sdk
The API key is specified in the proper file according to the instructions, so that's definitely not the issue.

For me that has happened in a few circumstances.  First, make sure you have a live internet connection within the app, otherwise it can't download maps.
Next, make sure the app itself hasn't frozen, crashed, or been paused for some reason.  Can you verify it's working using other UI components?
Third, I would double check you have a valid API key for the correct platform, in the correct format. I don't mean to question what you've done, but I've messed that up and seen the exact result you describe.

I have internet connection speed also good..

Try viewing the android logs (adb logcat) - probably doesn't like you key.

I have the same problem here. Something in particular to search for on the logs?

I have the same problem here.

Look in the android logcat, see if there is anything related to google services api.  If you're on an old android device, there is a known issue with Android 4.2.2: https://github.com/dapriett/nativescript-google-maps-sdk/issues/7

This is logcat...
D/OpenGLRenderer(13211): CanvasContext() 0x7f920639c0 initialize 0x7fa924ce10 E/GED     (13211): Failed to get GED Log Buf, err(0) I/OpenGLRenderer(13211): Initialized EGL, version 1.4 D/MALI    (13211): eglCreateContext:206: [MALI] eglCreateContext display 0x7fa905f280, share context 0x0 here. E/b       (13211): Authentication failed on the server. E/Google Maps Android API(13211): Authorization failure.  Please see https://developers.google.com/maps/documentation/android-api/start for how to correctly set up the map. D/MALI    (13211): gles_context_new:248: Create GLES ctx 0x7f92231008 successfully D/MALI    (13211): eglCreateContext:543: [MALI] eglCreateContext end. Created context 0x7f92221940 here. E/libGLESv2(13211): init_tshook E/Google Maps Android API(13211): In the Google Developer Console (https://console.developers.google.com) E/Google Maps Android API(13211): Ensure that the "Google Maps Android API v2" is enabled. E/Google Maps Android API(13211): Ensure that the following Android Key exists: E/Google Maps Android API(13211):       API Key: AIzaSyCbIkTmFkfqDewyUF-Qw2tgLqnMZqcHup0 E/Google Maps Android API(13211):       Android Application (<cert_fingerprint>;<package_name>): 23:7D:3A:46:D5:83:22:4D:E9:E4:18:A3:9E:AF:71:21:A4:52:71:84;org.nativescript.APPOTISEG D/ActivityThread( 2103): SVC-UNBIND_SERVICE handled : 0 / BindServiceData{token=android.os.BinderProxy@28feabc7 intent=Intent { act=com.google.android.gms.usagereporting.service.START p kg=com.google.android.gms }} D/ActivityThread( 2103): SVC-Destroying service: com.google.android.gms.usagereporting.service.UsageReportingService@2d183142 D/ActivityThread( 2103): SVC-STOP_SERVICE handled : 0 / android.os.BinderProxy@28feabc7 D/libtspower(13211): /proc/13211/maps: offset is 0x92D20000, size is 45056, system bit is 64, version(2.01.18) D/libtspower(13211): ts_funcs_arr[3]: min = 0x7f92d24dd8, max = 0x7f92d2504c D/libtspower(13211): encrypt data in file begin = 19928, end = 20556 D/libtspower(13211): begin decrypt... D/libtspower(13211): end decrypt. D/libtspower(13211): in ts_init D/libGLESv2(13211): loaded libtspower.so D/ActivityThread( 3079): SVC-UNBIND_SERVICE handled : 0 / BindServiceData{token=android.os.BinderProxy@1f7ab5a3 intent=Intent { cmp=com.google.android.gms/.maps.auth.ApiTokenService }} I/SurfaceFlinger(  267): EventThread Client Pid (13211) created D/ActivityThread( 3079): SVC-Destroying service: com.google.android.gms.maps.auth.ApiTokenService@1adf361b D/ActivityThread( 3079): SVC-STOP_SERVICE handled : 0 / android.os.BinderProxy@1f7ab5a3 I/OpenGLRenderer(13211): Get enable program binary service property (1) I/OpenGLRenderer(13211): Initializing program atlas... D/ProgramBinary/Service(13211): BpProgramBinaryService.getFileDescriptor D/ProgramBinary/Service(13211): BpProgramBinaryService.getProgramMapLen D/ProgramBinary/Service(13211): BpProgramBinaryService.getProgramMapArray D/ProgramBinary/Service(13211): BpProgramBinaryService.getProgramBinaryLen I/OpenGLRenderer(13211): Program binary detail: Binary length is 121028, program map length is 112. I/OpenGLRenderer(13211): Succeeded to mmap program binaries. File descriptor is 92, and path is /dev/ashmemo. I/OpenGLRenderer(13211): No need to use file discriptor anymore, close fd(92). D/OpenGLRenderer(13211): TaskManager() 0x7fa92282f0, cpu = 8, thread = 4 D/OpenGLRenderer(13211): Enabling debug mode 0 D/Surface (13211): Surface::connect(this=0x7fa924ce00,api=1) I/BufferQueueProducer(  267): [org.nativescript.APPOTISEG/com.tns.NativeScriptActivity](this:0x7fa5bdf000,id:213,api:1,p:13211,c:267) connect(P): api=1 producer=(13211:org.nativescript. APPOTISEG) producerControlledByApp=true

Looks like an issue with your API key:
'''
Authentication failed on the server. E/Google Maps Android API(13211): Authorization failure. Please see https://developers.google.com/maps/documentation/android-api/start for how to correctly set up the map.
'''

But the key I'm using already functions normally in other apps ..
Any permissions that have to give the app?

Do you have Google Maps Android API enabled for that key?

Sorry @dapriett really was it, I was using a JavaScript API Key.

Resolved: Using Google Maps Android API KEY and not the Google Maps JavaScript KEY.

Glad it worked, good luck.

helpful thread

I have the same issue, how can i check the API key being used is correct or not. Gmap = mapView.getMap(); should be replaced with getMapAsync() as it is precoded. I have created another key but still map do not appear ..just it is as google and blank

Run the app while your device is connected to android studio, then check logcat for fingerprint:package_name, you can search for it and check the API key and package name from there

it helped me solve my problem please pay attention to the package name


[Bug]: I can't register or login to the ragflow

Is there an existing issue for the same bug?

[X] I have checked the existing issues.

RAGFlow workspace code commit ID
latest
RAGFlow image version
infiniflow/ragflow:v0.15.1-slim
Other environment information
No response
Actual behavior

Expected behavior
No response
Steps to reproduce
can't login

Additional information
No response

Check the error message from backend service.
docker logs -f ragflow-server

Make sure all your services are up and running. with docker logs -f ragflow-server

Make sure all your services are up and running. with docker logs -f ragflow-server

above is the logs

Check the error message from backend service. docker logs -f ragflow-server

here is the logs

I have installed ragflow on 3 devices ,one windos PC successed to login. Another windos PC and a linux PC caused the same bug,can't login.

RAGFlow depends on python module: polars which need CPU supporting AVX2. Check the CPU of your host.

RAGFlow depends on python module: polars which need CPU supporting AVX2. Check the CPU of your hos

I have solved the problem use polars-lts-gpu instead of polars which can fix the bug.

I have solved the problem use polars-lts-gpu instead of polars which can fix the bug.

I met same problem ，how to solve to use polars-lts-cpu instead of polars,thank you


feat: add support for pixel_format and source_rect

Fixes #28

Was unable to test completely because of Segfault encountered as mentioned in #28
Will update the PR with a comment once I have been able to test successfully

See if you can test this with the new version v0.2.2

Yup. Tested with the new version and it works as expected. 🎉
I guess its ready to merge now?
@1313

I'll do a 2.3 release later tonight.

@all-contributors please add @Pranav2612000 Code


[673] Refactor DfE Sign-in to handle password resets without a monk…

…ey patch

CCS came up with a more elgant approach and enables us to completely remove the monkey patch for the OpenIDConnect gem: https://github.com/Crown-Commercial-Service/crown-marketplace/commit/2d169633f7e6c7ba5c9ff3425c47b87e3651a40b
I was also able to refactor several bits of configuration away
I simplified the guard clauses on every ENV fetch to a single line at the top of the file. It clearly explains that Docker is the reason we need to handle the scenario where ENV is not available, as it isn’t using the docker build phase.
To remind us of why we need to do this. At the end of a password reset journey using DfE Sign-in, that service redirects services back to our service. They use the same URL as the one used during the authentication phase, however this time it doesn’t have a valid payload. Omniauth promptly treats this request as unauthorised instead of linking the user to the sign in page. Since we cannot configure 2 callback URL’s within DSI, we are checking the payload in a before step, when it doesn’t exist at all we redirect that use to the sign in step.

Trello card URL:
https://trello.com/c/0fBiG9GY/673-replace-dfe-sign-in-monkey-patch
Changes in this PR:
Screenshots of UI changes:
Before
After
Next steps:

[ ] Terraform deployment required?

[ ] New development configuration to be shared?

 Replace DfE Sign-in monkey patch

Closing in favour of https://github.com/dxw/teacher-vacancy-service/pull/658 which has an improved understanding of the situation.


feature: disable google analytics through .env config

current version of index.html has an embedded googletagmanager script. Is there a way to disable it without manually altering existing html file and rebuilding the image? Thanks!

Good idea, if you know shell scripting or any other way to accomplish this task please send a PR https://github.com/openspeedtest/Docker-Image , now learning go lang and trying to build a CLI-Client for OpenSpeedTest. So i can come back to this only after few months.

Also we need .env setup for PageTitle, SVG Logo etc.
Basically need shell script? to edit index.html automatically using .env data when deploying the app.

Thanks for a quick reply, I will take a look and see what I can help with, although I am not a scripting expert by all means :) Perhaps can you tag this issue with "Help needed" maybe someone else would be able to jump in and help.

Now build an image with the changes you need. We can work on this later.

This is very privacy-unfriendly. The default installation should not be pinging a google analytics ID.
I was thinking about deploying this system for my non-profit ISP, but once I saw that you were trying to capture data with Google, plus you are submitting all test data back to your own server (where nobody knows what you are doing with that info), I decided against using it.

Hi, @ZPrimed
No personally identifiable data is collected, it's Same GA found on almost all websites.
If you look at GA Code, all we get is page views. Nothing else.
This is helpful for optimizing the application.
GA told me last year 500K+ users used IE.
So that I can optimize this application for those users & It will improve this application.
Almost all platforms or application collect data like this, including apple, Microsoft, Google etc.  it is to improve the product or service they offer.
submitting all test data back to your own server (where nobody knows what you are doing with that info)
Wrong, we will not submit data back to our servers after each test, it is useless and i don't have the storage or server capacity to process those data.
Most of the time this application is used in LAN or behind cooperate firewall, Even GA will not work. So how can we send those results back to our server?
if you use hosted.html it is just a iFrame with SelfHosted widget. IT WILL send data back to our server and store it on our database. It is a feature for people who don't want to maintain a database.
By default if you use index.html / default page it will not send data back to server after each test.
If you click the results after test , it will take you to our website result page. that will read the values from the URL. It will not store the result to a database.
That is an important feature. Email the result page to an IT Professional for troubleshooting connectivity issues.
So they can see the speed, jitter & ping along with transferred data. So you can find and fix issues by analyzing those values on the result page. Even if you are offline, you can copy the link and view it online later.
https://github.com/openspeedtest/Speed-Test/issues/29
Most people don't need or maintain a database server and need a way to share results. that is why this exists.
Now you can build your own image https://github.com/openspeedtest/Docker-Image
So that you can remove GA, if you really need.

No personally identifiable data is collected, it's Same GA found on almost all websites.

The ip address is rated as a identifiable data regarding to the ECJ. And it is illegal for the owner of the website to send this data to google if the user is from the european union (gdpr violation). As example: Google Font is a huge problem at the moment and people need to pay a lot of fines if the just put it in there website directly from the google server.

@duracell
We are not logging IP or any other PII. You can see that from GA code.
Can you see IP address in GA? i can't. Maybe because GA is loaded from Google Servers.
Anyway
UA is going EOL within few months.
Google Analytics 4 properties
In Google Analytics 4, IP anonymization is not necessary since IP addresses are not logged or stored.
I understand the importance of providing options.
very soon (Early Next Year) we will implement .env config
Now i don't know shell scripting.
It will take less than 30 seconds to remove GA and build your own image  https://github.com/openspeedtest/Docker-Image

We are not logging IP or any other PII. You can see that from GA code.
Can you see IP address in GA? i can't. Maybe because GA is loaded from Google Servers.

The problem is that google gets a request and can see the ip address. The same is with google analytics, fonts and every request to 3rd-party (https://rewis.io/urteile/urteil/lhm-20-01-2022-3-o-1749320/). And I know I can build my own image, but I would really recommend to have a default which is legal to use in the eu.
At the end it's your decision and the (legal) responsibility of the users, but this risk only to have google tag data? Is it really worth it?

Changing the logo, changing the title, removing GA, changing colors, etc., are the most requested features for the docker image.
Instead of writing a complex shell script to provide an Env variable, users can modify the index.html file or CSS. Then mount the file to the container.
https://forums.docker.com/t/how-to-change-logo-inside-html-file-via-environment-variables/131397/13

@jedi-admin @ZPrimed @duracell @C8opmBM
I lost the joy of looking at the stats. Now, this is a headache. So I am deleting GA from this project and Deleting Issues related to this very soon.

Removed GA! from the project.

Updated docker image! Goodbye!
Thanks..


add emily_zola_theme

emily is a KISS theme for Zola.
Features:

simple & clean
mobile-friendly
MathJax support

Demo site is here.

Nice! I think you should probably add some paddings to the code blocks though (eg on https://emily-zola-theme.netlify.app/post/markdown-syntax-guide/)
I'll merge the PR in a few hours

Nice! I think you should probably add some paddings to the code blocks though (eg on https://emily-zola-theme.netlify.app/post/markdown-syntax-guide/)
I'll merge the PR in a few hours

Thanks! Added code block padding.

Thanks! Added code block padding.

Thanks!

Thanks!


[Bug] code-oss does not work in kali linux wsl2

VS Code Version: 1.69.0
OS Version: Windows 10 Pro 21H2 19044.1766

When running code-oss in kali wsl2 I get the following:

I tried reinstalling code-oss with apt and I searched for answers online but I could not find anything related

Updated VS Code and Windows and it works now


Integer query param with "[" in it throws "invalid type" error

I'm currently using prism to mock an api endpoint where one of the query parameters is called page[limit], with a type of integer. The mock api works fine if I omit this query param, but when I make a request with the query string ?page%5Blimit%5D=100, it throws this error:
{
  "errors": [
    {
      "context": "request.url.queryString",
      "description": "Invalid type. Expected: [array,integer], given: string",
      "field": "page[limit]",
      "location": "page[limit]",
      "type": "invalid_type"
    }
  ]
}

This error isn't thrown if I change the name of the param to limit, or if I change the type to string.
Am I doing something wrong here, or is this a bug?

Hi @DaveWM this would be a bug. What Prism should be doing is trying to parse url params as int, boolean, etc, before applying the validation. Prism v2, which @pytlesk4 is working on, should fix this issue - we're aiming to have it released towards the end of July.

@marbemac great, thanks for the info :). Should I close this issue, or leave it open until Prism v2 is released?

@DaveWM Leave it open please.

duplicate #43