Function book

Hello,
I wonder do you have function book available online? I am plot the heat map trying to add the x/y axis, but I try many common way and it doesn't work.
Thank you!

Hi!
I would recommend taking a look at our docs, in particular here are the docs for the HeatmapGraphic.
The kwargs position_x, position_y, and position_z correspond to the respective axis position, these can be set by passing float values when instantiating the graphic.
@zhouyi0812 Is this what you are referring to?

Hello!
Thank you for sharing!
Hmm, I mean how to label the x/y axis.
I have tried: plot.add_xlabel and something similar but looks did not work.
Thank you for your help!

Yes, I see what you are saying now. We do not currently support axes labels. We are still waiting for some developments with pygfx before implementing. You can play with the TextGraphic manually if you want.
Also it looks like your toolbar is not rendering properly. If you are using Jupyter Notebook I recommend switching to Jupyter Lab instead!

closing, @zhouyi0812 feel free to re-open if you have more questions or open another issue.


Added Battle Talent shortcut

Battle Talent modding community is getting bigger and bigger. We already have over a 100 mod weapons  right now in the 3 weeks that we have mod support and it would be great to have a default shortcut for everyone to simplify the modding process!
Game link:
https://sidequestvr.com/app/2348/battle-talent (soon app lab).
Mods link:
https://battletalent.mod.io/

LGTM Thank you!


chore(python): added pyproject.toml

closes #154
@dbluhm any chance you can review this? I followed some guides, and the demo is working, but python setup still remains a small mystery to me :).
Signed-off-by: blu3beri<EMAIL_ADDRESS>

I'm not super familiar with how bundling binaries looks in pyproject.toml so I'll read up a bit and review! (Looks good to me though)

Did some digging; it would seem that poetry is not currently well suited to building platform specific wheels. It might be possible but the poetry build command can only build pure python wheels right now. @ryjones could you provide a little more detail on why a pyproject.toml specifically is required to get PyPI tokens? We can set up the pyproject.toml to configure setuptools (which looks like the best option for building platform specific wheels) instead of poetry but I'm not sure that will fit the workflow you were hoping for.
Input from @andrewwhitehead (who has far more experience building python packages with bundled binaries) would probably also be helpful, if you get a chance.

@dbluhm I was following this guide: https://realpython.com/pypi-publish-python-package/#configure-your-package

@blu3beri I propose we construct a minimal pyproject.toml with just:
# pyproject.toml

[build-system]
requires = ["setuptools>=61.0.0", "wheel"]
build-backend = "setuptools.build_meta"

And continue using setuptools for builds, following the same pattern as askar and indy-shared-rs.

Thanks for the work @dbluhm! I will change the PR and revert the setup.py and double check with askar.


Getting the error with retinanet TypeError: call() got an unexpected keyword argument 'training'

OS Platform and Distribution (Linux Ubuntu 18.04):
TensorFlow version:  2.1.0
Keras version:  2.3.1
Python version:  3.6.9
CUDA/cuDNN version:
GPU model and memory:  AMD radeon vii(vega 20)
Used the below link for refence:
https://colab.research.google.com/drive/1ldnii3sGJaUHPV6TWImykbeE_O-8VIIN

I had trained retinanet model with custom dataset for object detection. I training and testing working fine, Now I want to deploy the model on android mobile for that I have to convert my model to tflite. While executing the below code I am getting the error
from keras_retinanet.models import load_model
model = load_model('path to the trained keras model/resnet50_csv_30.h5', backbone_name='resnet50')
con = tf.lite.TFLiteConverter.from_keras_model(model)

TypeError                                 Traceback (most recent call last)
 in
----> 1 con = tf.lite.TFLiteConverter.from_keras_model(model)
~/.local/lib/python3.6/site-packages/tensorflow_core/lite/python/lite.py in from_keras_model(cls, model)
399
400     func = _saving_utils.trace_model_call(model, input_signature)
--> 401     concrete_func = func.get_concrete_function()
402     return cls([concrete_func])
403
~/.local/lib/python3.6/site-packages/tensorflow_core/python/eager/def_function.py in get_concrete_function(self, *args, **kwargs)
907       if self._stateful_fn is None:
908         initializers = []
--> 909         self._initialize(args, kwargs, add_initializers_to=initializers)
910         self._initialize_uninitialized_variables(initializers)
911
~/.local/lib/python3.6/site-packages/tensorflow_core/python/eager/def_function.py in _initialize(self, args, kwds, add_initializers_to)
495     self._concrete_stateful_fn = (
496         self._stateful_fn._get_concrete_function_internal_garbage_collected(  # pylint: disable=protected-access
--> 497             *args, **kwds))
498
499     def invalid_creator_scope(*unused_args, **unused_kwds):
~/.local/lib/python3.6/site-packages/tensorflow_core/python/eager/function.py in _get_concrete_function_internal_garbage_collected(self, *args, **kwargs)
2387       args, kwargs = None, None
2388     with self._lock:
-> 2389       graph_function, _, _ = self._maybe_define_function(args, kwargs)
2390     return graph_function
2391
~/.local/lib/python3.6/site-packages/tensorflow_core/python/eager/function.py in _maybe_define_function(self, args, kwargs)
2701
2702       self._function_cache.missed.add(call_context_key)
-> 2703       graph_function = self._create_graph_function(args, kwargs)
2704       self._function_cache.primary[cache_key] = graph_function
2705       return graph_function, args, kwargs
~/.local/lib/python3.6/site-packages/tensorflow_core/python/eager/function.py in _create_graph_function(self, args, kwargs, override_flat_arg_shapes)
2591             arg_names=arg_names,
2592             override_flat_arg_shapes=override_flat_arg_shapes,
-> 2593             capture_by_value=self._capture_by_value),
2594         self._function_attributes,
2595         # Tell the ConcreteFunction to clean up its graph once it goes out of
~/.local/lib/python3.6/site-packages/tensorflow_core/python/framework/func_graph.py in func_graph_from_py_func(name, python_func, args, kwargs, signature, func_graph, autograph, autograph_options, add_control_dependencies, arg_names, op_return_value, collections, capture_by_value, override_flat_arg_shapes)
976                                           converted_func)
977
--> 978       func_outputs = python_func(*func_args, **func_kwargs)
979
980       # invariant: func_outputs contains only Tensors, CompositeTensors,
~/.local/lib/python3.6/site-packages/tensorflow_core/python/eager/def_function.py in wrapped_fn(*args, **kwds)
437         # wrapped allows AutoGraph to swap in a converted function. We give
438         # the function a weak reference to itself to avoid a reference cycle.
--> 439         return weak_wrapped_fn().wrapped(*args, **kwds)
440     weak_wrapped_fn = weakref.ref(wrapped_fn)
441
~/.local/lib/python3.6/site-packages/tensorflow_core/python/keras/saving/saving_utils.py in _wrapped_model(*args)
148     with base_layer_utils.call_context().enter(
149         model, inputs=inputs, build_graph=False, training=False, saving=True):
--> 150       outputs_list = nest.flatten(model(inputs=inputs, training=False))
151
152     try:
~/.local/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py in symbolic_fn_wrapper(*args, **kwargs)
73         if _SYMBOLIC_SCOPE.value:
74             with get_graph().as_default():
---> 75                 return func(*args, **kwargs)
76         else:
77             return func(*args, **kwargs)
~/.local/lib/python3.6/site-packages/keras/engine/base_layer.py in call(self, inputs, **kwargs)
487             # Actually call the layer,
488             # collecting output(s), mask(s), and shape(s).
--> 489             output = self.call(inputs, **kwargs)
490             output_mask = self.compute_mask(inputs, previous_mask)
491
TypeError: call() got an unexpected keyword argument 'training'
My model architecture:
Model: "retinanet"

Layer (type)                    Output Shape         Param #     Connected to
input_1 (InputLayer)            (None, None, None, 3 0

padding_conv1 (ZeroPadding2D)   (None, None, None, 3 0           input_1[0][0]

conv1 (Conv2D)                  (None, None, None, 6 9408        padding_conv1[0][0]

bn_conv1 (BatchNormalization)   (None, None, None, 6 256         conv1[0][0]

conv1_relu (Activation)         (None, None, None, 6 0           bn_conv1[0][0]

pool1 (MaxPooling2D)            (None, None, None, 6 0           conv1_relu[0][0]

res2a_branch2a (Conv2D)         (None, None, None, 6 4096        pool1[0][0]

bn2a_branch2a (BatchNormalizati (None, None, None, 6 256         res2a_branch2a[0][0]

res2a_branch2a_relu (Activation (None, None, None, 6 0           bn2a_branch2a[0][0]

padding2a_branch2b (ZeroPadding (None, None, None, 6 0           res2a_branch2a_relu[0][0]

res2a_branch2b (Conv2D)         (None, None, None, 6 36864       padding2a_branch2b[0][0]

bn2a_branch2b (BatchNormalizati (None, None, None, 6 256         res2a_branch2b[0][0]

res2a_branch2b_relu (Activation (None, None, None, 6 0           bn2a_branch2b[0][0]

res2a_branch2c (Conv2D)         (None, None, None, 2 16384       res2a_branch2b_relu[0][0]

res2a_branch1 (Conv2D)          (None, None, None, 2 16384       pool1[0][0]

bn2a_branch2c (BatchNormalizati (None, None, None, 2 1024        res2a_branch2c[0][0]

bn2a_branch1 (BatchNormalizatio (None, None, None, 2 1024        res2a_branch1[0][0]

res2a (Add)                     (None, None, None, 2 0           bn2a_branch2c[0][0]
bn2a_branch1[0][0]

res2a_relu (Activation)         (None, None, None, 2 0           res2a[0][0]

res2b_branch2a (Conv2D)         (None, None, None, 6 16384       res2a_relu[0][0]

bn2b_branch2a (BatchNormalizati (None, None, None, 6 256         res2b_branch2a[0][0]

res2b_branch2a_relu (Activation (None, None, None, 6 0           bn2b_branch2a[0][0]

padding2b_branch2b (ZeroPadding (None, None, None, 6 0           res2b_branch2a_relu[0][0]

res2b_branch2b (Conv2D)         (None, None, None, 6 36864       padding2b_branch2b[0][0]

bn2b_branch2b (BatchNormalizati (None, None, None, 6 256         res2b_branch2b[0][0]

res2b_branch2b_relu (Activation (None, None, None, 6 0           bn2b_branch2b[0][0]

res2b_branch2c (Conv2D)         (None, None, None, 2 16384       res2b_branch2b_relu[0][0]

bn2b_branch2c (BatchNormalizati (None, None, None, 2 1024        res2b_branch2c[0][0]

res2b (Add)                     (None, None, None, 2 0           bn2b_branch2c[0][0]
res2a_relu[0][0]

res2b_relu (Activation)         (None, None, None, 2 0           res2b[0][0]

res2c_branch2a (Conv2D)         (None, None, None, 6 16384       res2b_relu[0][0]

bn2c_branch2a (BatchNormalizati (None, None, None, 6 256         res2c_branch2a[0][0]

res2c_branch2a_relu (Activation (None, None, None, 6 0           bn2c_branch2a[0][0]

padding2c_branch2b (ZeroPadding (None, None, None, 6 0           res2c_branch2a_relu[0][0]

res2c_branch2b (Conv2D)         (None, None, None, 6 36864       padding2c_branch2b[0][0]

bn2c_branch2b (BatchNormalizati (None, None, None, 6 256         res2c_branch2b[0][0]

res2c_branch2b_relu (Activation (None, None, None, 6 0           bn2c_branch2b[0][0]

res2c_branch2c (Conv2D)         (None, None, None, 2 16384       res2c_branch2b_relu[0][0]

bn2c_branch2c (BatchNormalizati (None, None, None, 2 1024        res2c_branch2c[0][0]

res2c (Add)                     (None, None, None, 2 0           bn2c_branch2c[0][0]
res2b_relu[0][0]

res2c_relu (Activation)         (None, None, None, 2 0           res2c[0][0]

res3a_branch2a (Conv2D)         (None, None, None, 1 32768       res2c_relu[0][0]

bn3a_branch2a (BatchNormalizati (None, None, None, 1 512         res3a_branch2a[0][0]

res3a_branch2a_relu (Activation (None, None, None, 1 0           bn3a_branch2a[0][0]

padding3a_branch2b (ZeroPadding (None, None, None, 1 0           res3a_branch2a_relu[0][0]

res3a_branch2b (Conv2D)         (None, None, None, 1 147456      padding3a_branch2b[0][0]

bn3a_branch2b (BatchNormalizati (None, None, None, 1 512         res3a_branch2b[0][0]

res3a_branch2b_relu (Activation (None, None, None, 1 0           bn3a_branch2b[0][0]

res3a_branch2c (Conv2D)         (None, None, None, 5 65536       res3a_branch2b_relu[0][0]

res3a_branch1 (Conv2D)          (None, None, None, 5 131072      res2c_relu[0][0]

bn3a_branch2c (BatchNormalizati (None, None, None, 5 2048        res3a_branch2c[0][0]

bn3a_branch1 (BatchNormalizatio (None, None, None, 5 2048        res3a_branch1[0][0]

res3a (Add)                     (None, None, None, 5 0           bn3a_branch2c[0][0]
bn3a_branch1[0][0]

res3a_relu (Activation)         (None, None, None, 5 0           res3a[0][0]

res3b_branch2a (Conv2D)         (None, None, None, 1 65536       res3a_relu[0][0]

bn3b_branch2a (BatchNormalizati (None, None, None, 1 512         res3b_branch2a[0][0]

res3b_branch2a_relu (Activation (None, None, None, 1 0           bn3b_branch2a[0][0]

padding3b_branch2b (ZeroPadding (None, None, None, 1 0           res3b_branch2a_relu[0][0]

res3b_branch2b (Conv2D)         (None, None, None, 1 147456      padding3b_branch2b[0][0]

bn3b_branch2b (BatchNormalizati (None, None, None, 1 512         res3b_branch2b[0][0]

res3b_branch2b_relu (Activation (None, None, None, 1 0           bn3b_branch2b[0][0]

res3b_branch2c (Conv2D)         (None, None, None, 5 65536       res3b_branch2b_relu[0][0]

bn3b_branch2c (BatchNormalizati (None, None, None, 5 2048        res3b_branch2c[0][0]

res3b (Add)                     (None, None, None, 5 0           bn3b_branch2c[0][0]
res3a_relu[0][0]

res3b_relu (Activation)         (None, None, None, 5 0           res3b[0][0]

res3c_branch2a (Conv2D)         (None, None, None, 1 65536       res3b_relu[0][0]

bn3c_branch2a (BatchNormalizati (None, None, None, 1 512         res3c_branch2a[0][0]

res3c_branch2a_relu (Activation (None, None, None, 1 0           bn3c_branch2a[0][0]

padding3c_branch2b (ZeroPadding (None, None, None, 1 0           res3c_branch2a_relu[0][0]

res3c_branch2b (Conv2D)         (None, None, None, 1 147456      padding3c_branch2b[0][0]

bn3c_branch2b (BatchNormalizati (None, None, None, 1 512         res3c_branch2b[0][0]

res3c_branch2b_relu (Activation (None, None, None, 1 0           bn3c_branch2b[0][0]

res3c_branch2c (Conv2D)         (None, None, None, 5 65536       res3c_branch2b_relu[0][0]

bn3c_branch2c (BatchNormalizati (None, None, None, 5 2048        res3c_branch2c[0][0]

res3c (Add)                     (None, None, None, 5 0           bn3c_branch2c[0][0]
res3b_relu[0][0]

res3c_relu (Activation)         (None, None, None, 5 0           res3c[0][0]

res3d_branch2a (Conv2D)         (None, None, None, 1 65536       res3c_relu[0][0]

bn3d_branch2a (BatchNormalizati (None, None, None, 1 512         res3d_branch2a[0][0]

res3d_branch2a_relu (Activation (None, None, None, 1 0           bn3d_branch2a[0][0]

padding3d_branch2b (ZeroPadding (None, None, None, 1 0           res3d_branch2a_relu[0][0]

res3d_branch2b (Conv2D)         (None, None, None, 1 147456      padding3d_branch2b[0][0]

bn3d_branch2b (BatchNormalizati (None, None, None, 1 512         res3d_branch2b[0][0]

res3d_branch2b_relu (Activation (None, None, None, 1 0           bn3d_branch2b[0][0]

res3d_branch2c (Conv2D)         (None, None, None, 5 65536       res3d_branch2b_relu[0][0]

bn3d_branch2c (BatchNormalizati (None, None, None, 5 2048        res3d_branch2c[0][0]

res3d (Add)                     (None, None, None, 5 0           bn3d_branch2c[0][0]
res3c_relu[0][0]

res3d_relu (Activation)         (None, None, None, 5 0           res3d[0][0]

res4a_branch2a (Conv2D)         (None, None, None, 2 131072      res3d_relu[0][0]

bn4a_branch2a (BatchNormalizati (None, None, None, 2 1024        res4a_branch2a[0][0]

res4a_branch2a_relu (Activation (None, None, None, 2 0           bn4a_branch2a[0][0]

padding4a_branch2b (ZeroPadding (None, None, None, 2 0           res4a_branch2a_relu[0][0]

res4a_branch2b (Conv2D)         (None, None, None, 2 589824      padding4a_branch2b[0][0]

bn4a_branch2b (BatchNormalizati (None, None, None, 2 1024        res4a_branch2b[0][0]

res4a_branch2b_relu (Activation (None, None, None, 2 0           bn4a_branch2b[0][0]

res4a_branch2c (Conv2D)         (None, None, None, 1 262144      res4a_branch2b_relu[0][0]

res4a_branch1 (Conv2D)          (None, None, None, 1 524288      res3d_relu[0][0]

bn4a_branch2c (BatchNormalizati (None, None, None, 1 4096        res4a_branch2c[0][0]

bn4a_branch1 (BatchNormalizatio (None, None, None, 1 4096        res4a_branch1[0][0]

res4a (Add)                     (None, None, None, 1 0           bn4a_branch2c[0][0]
bn4a_branch1[0][0]

res4a_relu (Activation)         (None, None, None, 1 0           res4a[0][0]

res4b_branch2a (Conv2D)         (None, None, None, 2 262144      res4a_relu[0][0]

bn4b_branch2a (BatchNormalizati (None, None, None, 2 1024        res4b_branch2a[0][0]

res4b_branch2a_relu (Activation (None, None, None, 2 0           bn4b_branch2a[0][0]

padding4b_branch2b (ZeroPadding (None, None, None, 2 0           res4b_branch2a_relu[0][0]

res4b_branch2b (Conv2D)         (None, None, None, 2 589824      padding4b_branch2b[0][0]

bn4b_branch2b (BatchNormalizati (None, None, None, 2 1024        res4b_branch2b[0][0]

res4b_branch2b_relu (Activation (None, None, None, 2 0           bn4b_branch2b[0][0]

res4b_branch2c (Conv2D)         (None, None, None, 1 262144      res4b_branch2b_relu[0][0]

bn4b_branch2c (BatchNormalizati (None, None, None, 1 4096        res4b_branch2c[0][0]

res4b (Add)                     (None, None, None, 1 0           bn4b_branch2c[0][0]
res4a_relu[0][0]

res4b_relu (Activation)         (None, None, None, 1 0           res4b[0][0]

res4c_branch2a (Conv2D)         (None, None, None, 2 262144      res4b_relu[0][0]

bn4c_branch2a (BatchNormalizati (None, None, None, 2 1024        res4c_branch2a[0][0]

res4c_branch2a_relu (Activation (None, None, None, 2 0           bn4c_branch2a[0][0]

padding4c_branch2b (ZeroPadding (None, None, None, 2 0           res4c_branch2a_relu[0][0]

res4c_branch2b (Conv2D)         (None, None, None, 2 589824      padding4c_branch2b[0][0]

bn4c_branch2b (BatchNormalizati (None, None, None, 2 1024        res4c_branch2b[0][0]

res4c_branch2b_relu (Activation (None, None, None, 2 0           bn4c_branch2b[0][0]

res4c_branch2c (Conv2D)         (None, None, None, 1 262144      res4c_branch2b_relu[0][0]

bn4c_branch2c (BatchNormalizati (None, None, None, 1 4096        res4c_branch2c[0][0]

res4c (Add)                     (None, None, None, 1 0           bn4c_branch2c[0][0]
res4b_relu[0][0]

res4c_relu (Activation)         (None, None, None, 1 0           res4c[0][0]

res4d_branch2a (Conv2D)         (None, None, None, 2 262144      res4c_relu[0][0]

bn4d_branch2a (BatchNormalizati (None, None, None, 2 1024        res4d_branch2a[0][0]

res4d_branch2a_relu (Activation (None, None, None, 2 0           bn4d_branch2a[0][0]

padding4d_branch2b (ZeroPadding (None, None, None, 2 0           res4d_branch2a_relu[0][0]

res4d_branch2b (Conv2D)         (None, None, None, 2 589824      padding4d_branch2b[0][0]

bn4d_branch2b (BatchNormalizati (None, None, None, 2 1024        res4d_branch2b[0][0]

res4d_branch2b_relu (Activation (None, None, None, 2 0           bn4d_branch2b[0][0]

res4d_branch2c (Conv2D)         (None, None, None, 1 262144      res4d_branch2b_relu[0][0]

bn4d_branch2c (BatchNormalizati (None, None, None, 1 4096        res4d_branch2c[0][0]

res4d (Add)                     (None, None, None, 1 0           bn4d_branch2c[0][0]
res4c_relu[0][0]

res4d_relu (Activation)         (None, None, None, 1 0           res4d[0][0]

res4e_branch2a (Conv2D)         (None, None, None, 2 262144      res4d_relu[0][0]

bn4e_branch2a (BatchNormalizati (None, None, None, 2 1024        res4e_branch2a[0][0]

res4e_branch2a_relu (Activation (None, None, None, 2 0           bn4e_branch2a[0][0]

padding4e_branch2b (ZeroPadding (None, None, None, 2 0           res4e_branch2a_relu[0][0]

res4e_branch2b (Conv2D)         (None, None, None, 2 589824      padding4e_branch2b[0][0]

bn4e_branch2b (BatchNormalizati (None, None, None, 2 1024        res4e_branch2b[0][0]

res4e_branch2b_relu (Activation (None, None, None, 2 0           bn4e_branch2b[0][0]

res4e_branch2c (Conv2D)         (None, None, None, 1 262144      res4e_branch2b_relu[0][0]

bn4e_branch2c (BatchNormalizati (None, None, None, 1 4096        res4e_branch2c[0][0]

res4e (Add)                     (None, None, None, 1 0           bn4e_branch2c[0][0]
res4d_relu[0][0]

res4e_relu (Activation)         (None, None, None, 1 0           res4e[0][0]

res4f_branch2a (Conv2D)         (None, None, None, 2 262144      res4e_relu[0][0]

bn4f_branch2a (BatchNormalizati (None, None, None, 2 1024        res4f_branch2a[0][0]

res4f_branch2a_relu (Activation (None, None, None, 2 0           bn4f_branch2a[0][0]

padding4f_branch2b (ZeroPadding (None, None, None, 2 0           res4f_branch2a_relu[0][0]

res4f_branch2b (Conv2D)         (None, None, None, 2 589824      padding4f_branch2b[0][0]

bn4f_branch2b (BatchNormalizati (None, None, None, 2 1024        res4f_branch2b[0][0]

res4f_branch2b_relu (Activation (None, None, None, 2 0           bn4f_branch2b[0][0]

res4f_branch2c (Conv2D)         (None, None, None, 1 262144      res4f_branch2b_relu[0][0]

bn4f_branch2c (BatchNormalizati (None, None, None, 1 4096        res4f_branch2c[0][0]

res4f (Add)                     (None, None, None, 1 0           bn4f_branch2c[0][0]
res4e_relu[0][0]

res4f_relu (Activation)         (None, None, None, 1 0           res4f[0][0]

res5a_branch2a (Conv2D)         (None, None, None, 5 524288      res4f_relu[0][0]

bn5a_branch2a (BatchNormalizati (None, None, None, 5 2048        res5a_branch2a[0][0]

res5a_branch2a_relu (Activation (None, None, None, 5 0           bn5a_branch2a[0][0]

padding5a_branch2b (ZeroPadding (None, None, None, 5 0           res5a_branch2a_relu[0][0]

res5a_branch2b (Conv2D)         (None, None, None, 5 2359296     padding5a_branch2b[0][0]

bn5a_branch2b (BatchNormalizati (None, None, None, 5 2048        res5a_branch2b[0][0]

res5a_branch2b_relu (Activation (None, None, None, 5 0           bn5a_branch2b[0][0]

res5a_branch2c (Conv2D)         (None, None, None, 2 1048576     res5a_branch2b_relu[0][0]

res5a_branch1 (Conv2D)          (None, None, None, 2 2097152     res4f_relu[0][0]

bn5a_branch2c (BatchNormalizati (None, None, None, 2 8192        res5a_branch2c[0][0]

bn5a_branch1 (BatchNormalizatio (None, None, None, 2 8192        res5a_branch1[0][0]

res5a (Add)                     (None, None, None, 2 0           bn5a_branch2c[0][0]
bn5a_branch1[0][0]

res5a_relu (Activation)         (None, None, None, 2 0           res5a[0][0]

res5b_branch2a (Conv2D)         (None, None, None, 5 1048576     res5a_relu[0][0]

bn5b_branch2a (BatchNormalizati (None, None, None, 5 2048        res5b_branch2a[0][0]

res5b_branch2a_relu (Activation (None, None, None, 5 0           bn5b_branch2a[0][0]

padding5b_branch2b (ZeroPadding (None, None, None, 5 0           res5b_branch2a_relu[0][0]

res5b_branch2b (Conv2D)         (None, None, None, 5 2359296     padding5b_branch2b[0][0]

bn5b_branch2b (BatchNormalizati (None, None, None, 5 2048        res5b_branch2b[0][0]

res5b_branch2b_relu (Activation (None, None, None, 5 0           bn5b_branch2b[0][0]

res5b_branch2c (Conv2D)         (None, None, None, 2 1048576     res5b_branch2b_relu[0][0]

bn5b_branch2c (BatchNormalizati (None, None, None, 2 8192        res5b_branch2c[0][0]

res5b (Add)                     (None, None, None, 2 0           bn5b_branch2c[0][0]
res5a_relu[0][0]

res5b_relu (Activation)         (None, None, None, 2 0           res5b[0][0]

res5c_branch2a (Conv2D)         (None, None, None, 5 1048576     res5b_relu[0][0]

bn5c_branch2a (BatchNormalizati (None, None, None, 5 2048        res5c_branch2a[0][0]

res5c_branch2a_relu (Activation (None, None, None, 5 0           bn5c_branch2a[0][0]

padding5c_branch2b (ZeroPadding (None, None, None, 5 0           res5c_branch2a_relu[0][0]

res5c_branch2b (Conv2D)         (None, None, None, 5 2359296     padding5c_branch2b[0][0]

bn5c_branch2b (BatchNormalizati (None, None, None, 5 2048        res5c_branch2b[0][0]

res5c_branch2b_relu (Activation (None, None, None, 5 0           bn5c_branch2b[0][0]

res5c_branch2c (Conv2D)         (None, None, None, 2 1048576     res5c_branch2b_relu[0][0]

bn5c_branch2c (BatchNormalizati (None, None, None, 2 8192        res5c_branch2c[0][0]

res5c (Add)                     (None, None, None, 2 0           bn5c_branch2c[0][0]
res5b_relu[0][0]

res5c_relu (Activation)         (None, None, None, 2 0           res5c[0][0]

C5_reduced (Conv2D)             (None, None, None, 2 524544      res5c_relu[0][0]

P5_upsampled (UpsampleLike)     (None, None, None, 2 0           C5_reduced[0][0]
res4f_relu[0][0]

C4_reduced (Conv2D)             (None, None, None, 2 262400      res4f_relu[0][0]

P4_merged (Add)                 (None, None, None, 2 0           P5_upsampled[0][0]
C4_reduced[0][0]

P4_upsampled (UpsampleLike)     (None, None, None, 2 0           P4_merged[0][0]
res3d_relu[0][0]

C3_reduced (Conv2D)             (None, None, None, 2 131328      res3d_relu[0][0]

P6 (Conv2D)                     (None, None, None, 2 4718848     res5c_relu[0][0]

P3_merged (Add)                 (None, None, None, 2 0           P4_upsampled[0][0]
C3_reduced[0][0]

C6_relu (Activation)            (None, None, None, 2 0           P6[0][0]

P3 (Conv2D)                     (None, None, None, 2 590080      P3_merged[0][0]

P4 (Conv2D)                     (None, None, None, 2 590080      P4_merged[0][0]

P5 (Conv2D)                     (None, None, None, 2 590080      C5_reduced[0][0]

P7 (Conv2D)                     (None, None, None, 2 590080      C6_relu[0][0]

regression_submodel (Model)     (None, None, 4)      2443300     P3[0][0]
P4[0][0]
P5[0][0]
P6[0][0]
P7[0][0]

classification_submodel (Model) (None, None, 4)      2443300     P3[0][0]
P4[0][0]
P5[0][0]
P6[0][0]
P7[0][0]

regression (Concatenate)        (None, None, 4)      0           regression_submodel[1][0]
regression_submodel[2][0]
regression_submodel[3][0]
regression_submodel[4][0]
regression_submodel[5][0]

classification (Concatenate)    (None, None, 4)      0           classification_submodel[1][0]
classification_submodel[2][0]
classification_submodel[3][0]
classification_submodel[4][0]
classification_submodel[5][0]
Total params: 36,445,192
Trainable params: 12,884,040
Non-trainable params: 23,561,152

Kindly help me in this
Thanks in advance

Same issue.

Same issue. Any workarounds?

same issue. Kindly if anyone has solution, post it here?

Same here. Any workaround?

SOLVED ISSUE SUBCLASSING KERAS MODEL CLASS
In my case I'm subclassing the keras Model class, just as an example:
class Basic(tf.keras.Model):
    def __init__(self):
        super().__init__()

        self.dense1 = tf.keras.layers.Dense(32, input_shape=(10,), activation='relu')
        self.dense2 = tf.keras.layers.Dense(2, activation='sigmoid')

    def __call__(self, inputs):
        x = self.dense1(inputs)
        x = self.dense2(x)
        return x

model = Basic()
model.compile(loss="categorical_crossentropy", optimizer='Adam', metrics=["accuracy"])
model.fit(X_encoded, y)

Running this I got this error: TypeError: __call__() got an unexpected keyword argument 'training'
The only thing I needed was to add training=False parameter to the __call__ function, so the code would be:
class Basic(tf.keras.Model):
    def __init__(self):
        super().__init__()

        self.dense1 = tf.keras.layers.Dense(32, input_shape=(10,), activation='relu')
        self.dense2 = tf.keras.layers.Dense(1, activation='sigmoid')

    def __call__(self, inputs, training=False):
        x = self.dense1(inputs)
        x = self.dense2(x)
        return x

model = Basic()
model.compile(loss="categorical_crossentropy", optimizer='Adam', metrics=["accuracy"])
model.fit(X_encoded, y)

Hope this helps

[unrelated but related]
For those who reached this error via tf.KerasLayer(fname,signature="serving_default",...), changing to hub.load(fname) solved the issue for me.
The error seems to result from some automation in hub.load when loading models that were converted from TF1 to TF2

@sumannelli Could you please try as per the above comment and let us know if it helps ? Thanks!

Closing this issue due to lack of recent activity & assuming this issue as resolved .Please feel free to reopen if you still have concern.Thanks!


Review docs getting started content

Placeholder to review for various changes that may be needed soon

duplicate of https://github.com/linode/manager/issues/1868


Chunked leveldb access

Here are the (squashed) commits we discussed. Let me know if you see any issues.
Thanks,
Derek

Could you rebase your work of the lastest master?  Github is reporting that the pull request cannot be merged automatically.

Sure thing, sorry about that.
On Mar 6, 2012, at 7:17 AM, Hiram Chirino wrote:

Could you rebase your work of the lastest master?  Github is reporting that the pull request cannot be merged automatically.

Reply to this email directly or view it on GitHub:
https://github.com/fusesource/leveldbjni/pull/9#issuecomment-4344977

--
Derek Chen-Becker
Lead Infrastructure Engineer
<EMAIL_ADDRESS>303-752-1700

Rescinding. Will re-request with a merged branch


Two finger scrolling on touch devices

Do you want to request a feature or report a bug?
Feature
What is the current behavior?
Two finger scrolling on touch devices is missing, and two finger touches  result in selection of elements. Figuring out the implementation is almost, but not quite in my grasp ;)
If the current behavior is a bug, please provide the steps to reproduce and create a JSFiddle.

What is the expected behavior?
Two fingered scrolling on touch devices should retain the current selection and allow scrolling the content area without selecting elements; essentially just pausing the selecting logic during .move() and letting the OS native two finger scroll work as usual.
Your environment:
Selection-version: 1.5.0 (CDN)
Browser-version:  Safari (iPadOS 13)
Operating-system:  iPadOS 13

I've added a trigger method which can be used to achieve that kind of functionality, in your case it'd be:
// Intercept start of selection
selection.on('beforestart', (() => {
    let timeout = null;

    return ({oe}) => {

        // Check if user already tapped inside of a selection-area.
        if (timeout !== null) {

            // A second pointer-event occured, ignore that one.
            clearTimeout(timeout);
            timeout = null;
        } else {

            // Wait 50ms in case the user uses two fingers to scroll.
            timeout = setTimeout(() => {

                // OK User used only one finger, we can safely initiate a selection and reset the timer.
                selection.trigger(oe);
                timeout = null;
            }, 50);
        }

        // Never start automatically.
        return false;
    };
})());

Added in a10c61fcb1a84228cdca94a3f97b82ea094cad73, I'll publish a new release in a few days :)

I've created a examples.md file were future requests like this can be demonstrated :)


Feat: qwik-table adapter

Hi TanStack team,
I've created a qwik-table adapter designed to integrate the table core with the Qwik framework. I have tested(not fully) and created examples for column sorting, pagination, and row selection.
I thought it was a good idea to share this as a first version and get some thoughts on whether this looks promising or not.
I welcome any feedback and look forward to contributing/helping make the adapter as perfect as the core itself is xD.
This discussion is related: https://github.com/TanStack/table/discussions/5281

Looks good, will probably test this out tomorrow!

@anxhirr I worked a bit on this PR. I think it might be in a better place now. All tests passing. Build output looks fine.
What's the dummy state in the adapter for though?

On the first version, I was getting some serialization error if I did not provide it.
Now, That error seems to be gone so we can simply remove it

@anxhirr I'm fixing the filters example. Also, you should be able to use pnpm test and expect tests to pass after my next commit.

@anxhirr I'm fixing the filters example. Also, you should be able to use pnpm test and expect tests to pass after my next commit.

Oh, well thanks. Yeah, my brain is not braining, I completely forgot we have tests.

@anxhirr Take a look at my adapter changes. I made it mostly mirror the react-table adapter. I don't know much about Qwik stores vs signals vs whatever, or why NoSerialize is needed here, but it seems to be working better, especially with the initial State.
React on Left. Qwik on Right:

@KevinVandy I made some other small changes, feel free to look.
I switched store to signal since Qwik store is supposed to be used when storing multiple states/signals inside the same object, when in this case we don't.
Also, noSerialize  is used because since table core is a third part lib qwik can not serialize($) its functions.

@anxhirr This is looking solid, (I mean qwik), pardon the pun. If we're confident that these are best practices, we just need to do some documentation setup. There's some small amount of work to do in the "docs" folder in this repo that I'll do quick.
I also have an open PR for TanStack.com that I'll get one of the other maintainers to merge for me soon. https://github.com/TanStack/tanstack.com/pull/196

@anxhirr This can be a future PR after this one, but would you be interested in forking the "React Table State" docs for what is needed for Qwik? https://tanstack.com/table/latest/docs/framework/react/guide/table-state

@anxhirr What is this error in each of the examples?
main.tsx:202  QWIK ERROR One of the children of  is not an accepted value. JSX children must be either: string, boolean, number, , Array, undefined/null, or a Promise/Signal. Instead, it's a function named "header".
Error: One of the children of  is not an accepted value. JSX children must be either: string, boolean, number, , Array, undefined/null, or a Promise/Signal. Instead, it's a function named "header".

@anxhirr What is this error in each of the examples?
main.tsx:202 QWIK ERROR One of the children of is not an accepted value. JSX children must be either: string, boolean, number, , Array, undefined/null, or a Promise/Signal. Instead, it's a function named "header". Error: One of the children of is not an accepted value. JSX children must be either: string, boolean, number, , Array, undefined/null, or a Promise/Signal. Instead, it's a function named "header".

Just checked, and fixed, very strange tho why it did not appear on my side before I did the commit

@anxhirr This can be a future PR after this one, but would you be interested in forking the "React Table State" docs for what is needed for Qwik? https://tanstack.com/table/latest/docs/framework/react/guide/table-state
Probably as simple as replacing React.useState with Qwik.useSignal in a few places, I imagine.

@KevinVandy For sure I can help with docs. This weekend I might have plenty of free time

@anxhirr I'm actually not sure if state should be in a useSignal or useStore still. The state is a bunch of nested objects.
I'm guessing the only difference is that useStore would re-render even if you do something like columnPinning.left.push(column.id), while the current useSignal will not. I guess useSignal is safer (from a react dev's perspective).
This can, of course, change later if needed.

@anxhirr I'm actually not sure if state should be in a useSignal or useStore still. The state is a bunch of nested objects.
I'm guessing the only difference is that useStore would re-render even if you do something like columnPinning.left.push(column.id), while the current useSignal will not. I guess useSignal is safer (from a react dev's perspective).
This can, of course, change later if needed.

Hi, Yeah I'm not a Qwik expert either but changing it in the future would not be a breaking change I think.
I see this was merged. Do I need to change/add any docs or you handled it all by yourself?

I see this was merged. Do I need to change/add any docs or you handled it all by yourself?

Any holes in the docs, especially more examples, are welcome to PRs always.

Hello! trying this out in a hobby project. Looks like I'm running into a crash in dev mode. Looks like it's related to the use of useSignal / useStore inside this hook. I'm new to Qwik myself so not sure if that's accurate - just going by the error message.
Looks like Context might be an alternative that could work?
https://qwik.dev/docs/components/context/
10:31:13 am [vite] Internal server error: Code(20) https://github.com/BuilderIO/qwik/blob/main/packages/qwik/src/core/error/error.ts#L28
  File: /work/src/routes/(app)/orders/current/index.tsx:17:13
  15 |  const Table = component$(() => {
  16 |
  17 |    const t = useQwikTable({
     |               ^
  18 |      data: [],
  19 |      columns: [],

Create an issue with a sandbox reproducing this error?

https://github.com/TanStack/table/issues/5455
done :+1: Thanks again.

@KevinVandy not sure if you saw my comments above

@wmertens we'd love help remaking the quick adapter the right way. Especially for v9 in the alpha branch.


lsm: simplify compaciton dependency injection

Now that we have pointer stability, we no longer need to inject forest just-in-time during compaction.

:heart: you for giving us pointer stability !


add ProfessionalExperience form

For an example of how to fill this template out, see this Pull Request in the Wiki.
Description

Added a form for Professional Experience.
Please let me know if any changes are required.
Related Issue

closes #5
Acceptance Criteria

[x] Create a component called ProfessionalExperience.js and save it in a folder called components in the src directory
[x] Heading: Professional Experience
[x] Form with above mentioned fields
[x] Inputfields must be editable
[x] Input fields are accessible
[x] Save button does not require functionality
[x] No stylings but plain html
[x] The new component is imported and displayed in the App.js component
[x] Only the new component is displayed

Type of Changes

Type

:bug: Bug fix

✓
:sparkles: New feature

:hammer: Refactoring

:100: Add tests

:link: Update dependencies

:scroll: Docs

Updates
Before

After

Testing Steps / QA Criteria

Fill out the required fields in Professional Experience form
Form won't be submitted unless all required fields are properly filled.

Thanks for your contribution 🎉


zoom into scene (BiggerTowers) in hanoi.py

When running this scene class "BiggerTowers" the scene video seemed to be zoomed and not in the normal size as video on the youtube

Use version of Python 2:
https://github.com/3b1b/manim/tree/e4d44bf2bfdd1343da75041b215c9675b8018a79

still the same problem


Recursively render sub-documents that are attributes

This feature allows for better serialization of our hierarchical intermediate representation as well as some better developer ergonomics.
So, before, to render a sub-document:
import CommonMarkRenderer, { Annotation } from '@atjson/renderer-commonmark';

export default class extends CommonMarkRenderer {
  *figure(node: Annotation): Iterable<any> {
     return `![node.description](node.url)|||${this.render(node.caption)}|||`
  }
}

After, this becomes:
import CommonMarkRenderer, { Annotation } from '@atjson/renderer-commonmark';

export default class extends CommonMarkRenderer {
  *figure(node: Annotation): Iterable<any> {
     return `![node.description](node.url)|||${node.caption}|||`
  }
}

This makes sense to me - seems an unnecessary gotcha to fail at rendering sub-documents when it's obvious what the correct action should be.

Yeah, I can see that; I think we'll need to figure out what it means when something goes wrong rendering sub-documents.


peer review 1 issue 3 solved (by using RDS)

Has the TA approved this?
Also, I think we should not have a .bash_history file in our repo ...


This fixes #612.
Issue

close #612.

Overview (Required)
See #612.
Links
Screenshot

Thanks for your quick work!
@takahirom this AGP reverting, will it not affect other your work (another libraries)?


Citizens NPC Quest GUI Name Appearance Stuck on Original Name

Hello,
Whenever I set an item for the GUI of an NPC (for the quests gui) it always reverts the name to the quest name but in purple text. So for exmaple if I made a gui icon that has a name such as &6Burger  for the quest named "Pizza" it always changes the icons item name to Pizza in purple color
I'm still not sure if this is a bug or I'm doing something completely wrong but I really don't want the item icons for the Quest NPC GUI to have purple names and not be customization. It really makes it look kind of bad in the GUI

Each item gets its name from the quest itself; not the item's display name. You would need to add the color code to the start of applicable quest names.


Cleaning up the CMakeLists.txt

This cleans up the CMakeLists.txt so we have distinct src and samples projects and does some minimal cleanup so that resources can be resolved relative to the host executable.

(I expect I have some cleanup for Unix still)

I've merged in a fix to this branch for the worldobject active state as discussed in the discord. I'll just quickly verify everything is working but I don't see why it wouldn't, the fixes were minor.


Create an endpoint to update the amount of trophies of the user (put request User controller)

Expect a header with the userId and the amount of trophies in the requestBody : RestSpecification Nr. 4
Retreive the user with the userId from header and add the amount of trophies that were passed on to the existing amount.


Expose property MOBILE_APP_PROMO of interface_config in openfire admin

Mobile users are forced to the mobile app instead of being able to use the mobile browser. Now that all browsers support webrtc, this should be configurable
See https://discourse.igniterealtime.org/t/using-ofmeet-on-browser-android/81745

Yes it does not as I found that out myself. For now, I have hacked jitsi meet to remove it
https://github.com/jitsi/jitsi-meet/blob/eb19f94598488fd64cc2be322f97b4f63c43d5c2/react/features/deep-linking/functions.js
Android works fine, but IOS is only doing audio. The new UI look seems preffered to mobile.
I think we should delay any work on this until mobile browsers are supported properly.


About output

Hello,I want know what is the output after running the example. I found a folder called checkpoints with two zip packs, but I don't know how to use it.The input data is video, but what is the output data?Can you answer it for me？ Thank you

We have updated README.md for eval/deployment instructions. Please check it out!


Added uniqueness flag to intersect1d

Given the nature of the two arrays, this might offer consistently faster intersection computation.

Hello @SkBlaz! Thanks for opening this PR. We checked the lines you've touched for PEP 8 issues, and found:

In the file umap/plot.py:

Line 209:89: E501 line too long (106 > 88 characters)

Thanks.


fix: changed conditions for variables as variables were undefined

Description
After parsing, while updating data tree variables were undefined and to update we compare values by turning it into string. that was failing
Fixes #9730
Type of change

Please delete options that are not relevant.

Bug fix (non-breaking change which fixes an issue)

Checklist:

[ ] My code follows the style guidelines of this project
[ ] I have performed a self-review of my own code
[ ] I have commented my code, particularly in hard-to-understand areas
[ ] I have made corresponding changes to the documentation
[ ] My changes generate no new warnings
[ ] I have added tests that prove my fix is effective or that my feature works
[ ] New and existing unit tests pass locally with my changes

Test coverage results :test_tube:
:red_circle: Total coverage has decreased
// Code coverage diff between base branch:release and head branch: Critical-9730-fix

Status
File
% Stmts
% Branch
% Funcs
% Lines

:red_circle:
total
55.12 (0)
37.01 (-0.01)
34.01 (0)
55.64 (0)

:green_circle:
app/client/src/utils/autocomplete/TernServer.ts
52.94 (0.23)
41.67 (0.84)
36.21 (0)
56.99 (0.25)

:red_circle:
app/client/src/workers/evaluationUtils.ts
57.46 (0)
53.94 (-2.39)
62.26 (0)
55.19 (0)

/ok-to-test sha=11057cf

Tested and verified on DP


Geometric fill/outline tools

Feature branch: geometry
It would be nice to have a selection of functions to draw a variety of geometric shapes efficiently, both filled and hollow.
Some ideas for useful shapes:

[x] Cuboids
[x] Point-to-point shapes / polygons
[x] Circles, ellipses and cylinders
[ ] Ellipsoids
[ ] Arches
[x] Repeated shapes
[x] Transformed shapes
[ ] Rotated shapes

Suggested implementation:
Using various combinations of Bresenham's algorithms

It would likely make sense to do this in a new module and have the fill command move there.

Moved to https://github.com/avdstaaij/gdpc/issues/25


Update declarative Pipeline and Git/Maven demos to reflect the current state of the Vanilla package

Contributes to #261

I will merge it to simplify development of the master branch. CI is still broken, yes...


[manyblock mode] how are you ensuring that all the blocks are executed in order?

I have posted a question regarding the ordering of blocks' execution when there are more blocks than there can be on a device at a given point in time. Nvidia's dev answered that: 1) we cannot assume anything about the order of block's execution
and 2) if block becomes resident, it does not retire until all threads in the block have gone to competition. (https://devtalk.nvidia.com/default/topic/1044740/performance-cost-of-too-many-blocks-/?offset=8#5301239).
However, many blocks uses hundreds of thousands of blocks, and the blocks have to be executed in the order of sample and layer ( 1st layer of 1st sample should be completed for 2nd layer of 1st sample to proceed, and 1st sample should be completed for 2nd sample can proceed ). I have read every line of nv_wavenet_persistent.cuh, and it seems like either one of the two things that the dev has said has to be wrong. Either you can specify the order of blocks, or block can be taken out of execution even if it has not gone to completion ( you use an infinite while-loop to make a block wait for the previous layer, and use block-wise synchronization to make sure that previous sample has been created. Maybe one of these causes block's early retiring? ). Or is it the "barrier.sync" PTX code that is ensuring the correctness of execution of blocks?
Thanks

The code is relying on thread block launch ordering which, as was described in that thread is a gray area that we shouldn't be depending on, so it's a bug in the code :)
A correct implementation will use atomics to determine the ordered block indices.

Oh okay, thanks.
I wanted to make sure there wasn't any code I overlooked, as I am trying to build a parallel version of wavenet from studying your code :)


 The error message is not quite human firendly. cardano-wallet-jormungandr should exit with error message explaining that --config is generated automatically and one cannot provide --config in launch
Steps to Reproduce

$ cardano-wallet-jormungandr launch --genesis-block-hash adbdd5ede31637f6c9bad5c271eec0bc3d0cb9efb86a5b913bb55cba549d0770 -- --config node_config.yaml

Expected behavior
Friendly error message:
No need to provide --config bleblb.yaml
We will generate Jormungandr config for you.

Actual behavior
Long unfriendly error:
[iohk.cardano-wallet.launch:Info:ThreadId 4] [2019-10-16 15:32:29.83 UTC] Using directory: /home/piotr/.local/share/cardano-wallet/jormungandr/testnet
[iohk.cardano-wallet.launch:Info:ThreadId 4] [2019-10-16 15:32:29.83 UTC] Using directory: /home/piotr/.local/share/cardano-wallet/jormungandr/testnet/wallets
[iohk.cardano-wallet.launch:Info:ThreadId 4] [2019-10-16 15:32:29.83 UTC] Running as v2019.9.13
[iohk.cardano-wallet.launch:Info:ThreadId 4] [2019-10-16 15:32:29.83 UTC] Wallet backend server starting...
error: The argument '--config <node_config>' was provided more than once, but cannot be used multiple times

USAGE:
    jormungandr --genesis-block-hash <block_0_hash> --log-level <log_level> --config <node_config>

For more information try --help
[iohk.cardano-wallet.launch:Info:ThreadId 4] [2019-10-16 15:32:29.83 UTC] Node is Jörmungandr on testnet
[iohk.cardano-wallet.launch:Info:ThreadId 4] [2019-10-16 15:32:29.83 UTC] Generated Jörmungandr's configuration to: /home/piotr/.local/share/cardano-wallet/jormungandr/testnet/jormungandr-config.yaml
[iohk.cardano-wallet.launch:Notice:ThreadId 4] [2019-10-16 15:32:29.83 UTC] Starting process jormungandr
     --genesis-block-hash adbdd5ede31637f6c9bad5c271eec0bc3d0cb9efb86a5b913bb55cba549d0770
     --config /home/piotr/.local/share/cardano-wallet/jormungandr/testnet/jormungandr-config.yaml
     --log-level info
     --config node_config.yaml

[iohk.cardano-wallet.launch.jormungandr.17162:Info:ThreadId 4] [2019-10-16 15:32:29.83 UTC] Process jormungandr started with pid 17162
[iohk.cardano-wallet.launch:Error:ThreadId 4] [2019-10-16 15:32:29.84 UTC] Child process jormungandr exited with status 1
[iohk.cardano-wallet.launch:Alert:ThreadId 4] [2019-10-16 15:32:29.84 UTC] The node exited with status ExitFailure 1

Resolution Plan

PR

Number
Base

#862
develop

QA

how are we with this one?

no longer applies


Add EF Core framework & SQLite support

Added EF Core to the application. It uses SQLite.
Created a new service, which communicates with DB with async methods.

Remove this PR due to wrong EF Core version.


Add npm package to the repo (link)

Been researching about it a bit and seems like the way to display the package on github UI is only through publish it to github packages, so we also need to publish the package to github registry i.e registry=https://npm.pkg.github.com.
I was actually planning to add the action so that we publish to github packages but after reading for while not sure its worth it because if people need to install / use package via github registry they need to append org / user name in our case it would be npx scaffold-eth/create-eth. Checkout this stackoverflow discussion
And event this example mentioned in github packages docs indeed also has forces you append user / org name before  package name.
So I am not sure if its worth configuring because by doing this will also distribute the audience / numbers once using npm registry npx create-eth@latest and other will be fetching from npx scaffold-eth/create-eth@latest

Definitely not worth it! Thanks for looking into it @technophile-04


FileHandle#map compilation compatibility for GWT

Fixes #5257
I don't think implementing a MappedByteBuffer class in GWT emu classes is worth the hassle. Android/Desktop specific code can always cast to MappedByteBuffer to invoke the 3 utility functions it implements.

Works for me with desktop:run and html:dist when I depend on this version in a freshly-made project. I don't know how the FileChannel imports of non-existent classes worked before 418fd7f , but I suspect GWT could tell they were unused and so didn't try to import them. They also weren't ever built by a desktop JDK, and those may be more strict. Thanks for fixing this!


Prototype of interacting with bsky notifications.

Hi! This a prototype of what interacting with the notifications would look like.
I put everything in the client.py script because it is easier to call since this is not an installable package right now :(
client.get_notifications() runs the test.
There is a line that is currently commented that would (if uncommented) reset the notifications:
 client.app.bsky.notification.update_seen({'seen_at': last_seen_at})
I left it commented so I don't have to constantly create new notifications but I tested it and it works.

Perfect, thank you so much for this!
And hmm, the packages that run in the cloud aren't installable as Digital Ocean doesn't support pyproject.toml files and they have to be installed differently anyway, but that's a fair point that it would be nicer for local development - will consider adding a pyproject.toml to the service projects.


Add npm i to binary creation doc

The documentation to create a unique binary does not work as is, it needs npm install as well:
Single Binary
Execute the following commands to create a single executable binary for the tool:
git clone https://github.com/bitnami-labs/readme-generator-for-helm
cd ./readme-generator-for-helm
npm install
npm install -g pkg
pkg . -o readme-generator-for-helm

Otherwise it will create a crashing binary ^^

Thanks a lot @pleymor for the suggestion. Please feel free to open a PR with your proposal, we will be happy to review it.


Incorrect handling of @Consumes annotation with list of media-types

The @Consumes annotation can specify a comma-separated list of supported media-types, such as (from the javadoc):  "image/jpeg, image/gif"
It looks like resty-gwt is copying such a string directly to the request header, resulting in an invalid Content-Type / 400 error from the server.

fixed via #304


exception is occuring when elastic server is missing

Below is the code for serilog elastic search.It's working perfectly when elastic service is running but fails when the server is not available
  .WriteTo.Elasticsearch(new ElasticsearchSinkOptions(new Uri("http://localhost:9200/")) // humio elastic bulk endpoint
                            {
                                AutoRegisterTemplate = true,
                                OverwriteTemplate = true,
                                DetectElasticsearchVersion = true,
                                AutoRegisterTemplateVersion = AutoRegisterTemplateVersion.ESv7,
                                NumberOfReplicas = 1,
                                NumberOfShards = 2,
                                RegisterTemplateFailure = RegisterTemplateRecovery.FailSink,
                                FailureCallback = e => Console.WriteLine("Unable to submit event " + e.MessageTemplate),
                                EmitEventFailure = EmitEventFailureHandling.WriteToSelfLog |
                                                   EmitEventFailureHandling.WriteToFailureSink |
                                                   EmitEventFailureHandling.RaiseCallback,
                                //FailureSink = new FileSink("./fail-{Date}.txt", new JsonFormatter(), null, null)
                                //ModifyConnectionSettings = x => x.BasicAuthentication(username: "", password: "88WS28JEuB0G2WC3cYufdgTINAxOGQvliBrqH5Vqutjb")  // password is ingest token from humio
                            })

exception is occuring when elastic server is missing
Elasticsearch.Net.ElasticsearchClientException: 'No connection could be made because the target machine actively refused it.. Call: Status code unknown from: GET /_cat/nodes?h=v'
HttpRequestException: No connection could be made because the target machine actively refused it.
SocketException: No connection could be made because the target machine actively refused it.

This exception was originally thrown at this call stack:
System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()
System.Runtime.CompilerServices.TaskAwaiter.ThrowForNonSuccess(System.Threading.Tasks.Task)
System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(System.Threading.Tasks.Task)
System.Runtime.CompilerServices.ConfiguredTaskAwaitable.ConfiguredTaskAwaiter.GetResult()
System.Net.Http.ConnectHelper.ConnectAsync(string, int, System.Threading.CancellationToken)

Failing at the registration of the template due to not finding the server and you have the RegisterTemplateFailure set to fail the sink. In that case, it will indeed raise an exception so you know your template registration is potentially not correct.
So I m not sure what your issue is about as this is excepted behaviour.

I have a similar situation which I've nailed down to "DetectElasticsearchVerion = true". When this is set, failure to contact elasticsearch will throw and fail the app from starting. No combination of RegisterTemplateFailure, FailureSink & EmitEventFailure will prevent the app from crashing. Those options only appear to work when manually setting AutoRegisterTemplateVersion and DetectElasticsearchVersion = false.

@LucidObscurity thanks for the pointer. I created a PR to address this issue. Care to have a look if this is what you mean?

Thanks @mivano! The selflog upon failure is exactly what I would intuitively expect.

Perfect, will merge the PR. Thanks!


Updated the schema

https://github.com/open-feature/open-feature-operator/pull/60

Looks like we added a commit signing requirement? Was that done on purpose?

Looks like we added a commit signing requirement? Was that done on purpose?

I think that was done at the org level


Mock File Operations in compare_and_replace Tests

Description: Mock file operations in the compare_and_replace tests to simulate different file system behaviors, such as:

Creating files with different modification times.
Mocking file deletion via handle_and_remove.

Resources: Refer to the pytest mocking section for instructions on using unittest.mock.
Path: twinTrim/dataStructures/allFileMetadata.py
Code to be added: tests
Note: Ensure to maintain the file structure as per the existing files and tests.

Can i be assigned this?

@eleensmathew
Yes,
make sure to create a separate branch before making the necessary changes and retain the folder structure.

you can assign that task to me..

Hi @SaanyaGarg5 i am working on it

Is this issue still open if yes than i love to contribute

@SaanyaGarg5
are you still up to work on this?

@mienpham04
Yes,
make sure to create a separate branch before making the necessary changes and retain the folder structure.

Hi @Kota-Karthik,
I would like to take on the task of mocking file operations in the tests for the compare_and_replace method as outlined in issue #3. This is a crucial step to ensure the robustness of the file operations under different scenarios.
Here's how I plan to approach this:
Mocking File Operations:
I will simulate file creation with various modification times to test the behavior of the compare_and_replace method.
I will also mock the file deletion process using handle_and_remove to accurately test different outcomes without affecting the actual file system.
Test Framework: I’ll utilize pytest along with unittest.mock as specified in the resources.
File Structure: I will ensure that the tests are well-organized and maintain the existing file structure for clarity and maintainability.
Could you please assign this issue to me

@JahnaviDhanaSri
I suggest you to go through CONTRIBUTING.MD

@Kota-Karthik can you assign this task to me?

@Hafsa-shoaib989 you are assigned. Start working, you have 2 days.


init translation commit

@microsoft-github-policy-service agree

I am very sorry, it's a mistake 😥


Current build fails due to 'libc6:i386' configuration issue

Hello! Thank you for your wonderful project by the way! It's made my life much easier!
I'm currently attempting to build the Dockerfile locally (using podman), and I'm receiving the following error (note: I did disable playonlinux installation as I won't be using it, but that doesn't appear to be the issue here):
Processing triggers for wine (5.0.3-3) ...
Processing triggers for libc-bin (2.31-4) ...
Processing triggers for libgdk-pixbuf-2.0-0:i386 (2.42.2+dfsg-1) ...
E: Could not configure 'libc6:i386'.
W: Could not perform immediate configuration on 'libgcc-s1:i386'. Please see man 5 apt.conf under APT::Immediate-Configure for details. (2)
Error: error building at STEP "RUN echo "deb http://deb.debian.org/debian buster contrib" >> /etc/apt/sources.list &&     env DEBIAN_FRONTEND=noninteractive dpkg --add-architecture i386 &&     apt-get update &&     env DEBIAN_FRONTEND=noninteractive apt-get install -y       fonts-wine       locales       ttf-mscorefonts-installer       wget       winbind       winetricks &&     mkdir -p /usr/share/wine/gecko &&     cd /usr/share/wine/gecko &&       wget https://dl.winehq.org/wine/wine-gecko/2.47/wine_gecko-2.47-x86.msi &&       wget https://dl.winehq.org/wine/wine-gecko/2.47/wine_gecko-2.47-x86_64.msi &&     mkdir -p /usr/share/wine/mono &&     cd /usr/share/wine/mono &&       wget https://dl.winehq.org/wine/wine-mono/4.7.1/wine-mono-4.7.1.msi &&     env DEBIAN_FRONTEND=noninteractive apt-get install -y       gettext       gnome-icon-theme       q4wine       xterm &&     env DEBIAN_FRONTEND=noninteractive apt-get install -y       libxv1       mesa-utils       mesa-utils-extra &&     env DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends       libpulse0       pavucontrol       pasystray": error while running runtime: exit status 100

Seems to be some kind of issue with the 32 bit binaries on Debian. Unfortunately, my knowledge is pretty limited here.

Actually, figured out the issue - I was building this image directly, but not it's parent of the x11docker/xfce image, which was pulling down a really old version of Debian by default.
I'm now building all packages, including the xserver (Nvidia), xfce, and this, and it all works just fine now.
Sorry for the bother!

Thank you for the report and also posting your solution!
Great to hear that this project is pretty useful for you.

I had a look at the Dockerfile and found a minor bug:
The image builds upon x11docker/xfce that in turn is based on Debian bullseye.
But the Dockerfile added a sources.list contrib entry pointing to previous Debian buster.
This affects mainly playonlinux and has no major impact.
However, it is fixed now and I want to let it know to you.

Awesome, thank you for the updates!


I have a problem when run rrt_connect3D.py

I try run the Sampling_based_Planning\rrt_3D\FMT_star3D.py, Sampling_based_Planning\rrt_3D\rrt_connect3D.py. Then, I got this.

Is this normal?

Hi，Have you encountered this error？While I run 'Anytime_Dstar3d',there is a problem.
ValueError: operands could not be broadcast together with shapes (25,2,3) (0,)

Hi，Have you encountered this error？While I run 'Anytime_Dstar3d',there is a problem. ValueError: operands could not be broadcast together with shapes (25,2,3) (0,)

Have you resolved it? I've encountered a similar situation.

Hi，Have you encountered this error？While I run 'Anytime_Dstar3d',there is a problem. ValueError: operands could not be broadcast together with shapes (25,2,3) (0,)

Have you resolved it? I've encountered a similar situation.

No,I am not.


Decode and normalize URIs before processing them

URIs must be at least decoded in order to process sub-delims as defined in RFC 3986, because slashes and their encoded counterparts are equivalent when processing paths. Normalization before the processing also makes sense to avoid unnecessary stripping of path parameters in case of path traversal. This fixes a bug where URIs like "/test;%2F.." would not properly resolve to "/", but to "/test".

URL processing and mapping has to follow a lot of rules from specifications to avoid inconsistencies which would be security issues. So this is one of them.
Indeed creative encoding can cause path traversals on the backends. To be honest, a good security practice is to not use user input as paths in your app, rather use some other kind of mapping. So no traversal then.

Could you please elaborate how a URI is not user input and how it can be prevented that a user calls a URI on a web application? I can't follow you.
Relative paths are explicitly allowed in URIs, and that includes parent directories as well, see the mentioned RFC that defines URIs and how to handle them.
This PR was meant to fix a bug in the path processing of Tomcat because it does not decode slashes in paths and that leads to the stripping of the remainder of the URI after the ; character. I have also added test cases for this issue.

Nope. Read the RFC again. Specifically <IP_ADDRESS>.

Thanks for checking back! The section you are referring to does not really negate my statement however. If I get you right you are talking about this specific thing?

These URIs should be normalized by decoding any percent-encoded octet that corresponds to an unreserved character

This does not mean that reserved characters can't be decoded or? Maybe we can debate this together to clear my confusion. Let me point out to you the relevant parts of the RFC that I am talking about:
2.4.  When to Encode or Decode

Once produced, a URI is always in its percent-encoded form.

That means, a URI should be decoded to properly process it right?

When a URI is dereferenced, the components and subcomponents [...] must be parsed and separated before the percent-encoded octets within those components can be safely decoded, as otherwise the data may be mistaken for component delimiters.

This has been done, my change only affects the path component of the whole scheme. That means the components were already separated and decoding can take place, also for delimiters. Note that decoding unreserved characters can optionally happen anytime earlier:

[...] percent-encoded octets corresponding to characters in the unreserved set, which can be decoded at any time.

Also check the example from 5.4. Reference Resolution Examples: A base URI of http://a/b/c/d;p?q and a relative path of g;x=1/../y should resolve to http://a/b/c/y.
One more note to parent directories, as they are totally valid and should be normalized as well. Just to clear this up, taken from 3.3. Path:

The path segments "." and "..", also known as dot-segments, are defined for relative reference within the path name hierarchy [...] to indicate relative position within the hierarchical tree of names.  This is similar to their role within some operating systems' file directory structures to indicate the current directory and parent directory, respectively.

Nope, %2F is NOT equivalent to / in a URI as explained in section 2.2 of RFC 3986.

Alright, I guess I got this wrong then, thanks for your detailed explanations.
In case others are wondering about the same issue I found two bugs for reference on prominent software projects that apparently implemented it wrong then:

https://github.com/golang/go/issues/3659
https://trac.nginx.org/nginx/ticket/727


Delete worldobuectcontroller

Thank you for contributing, but this pull request doesn't seem to improve the project.


Expose User/Org information under site.github.owner

Fixes #149.
Tested locally for a User object, captured everything I was interested in (full name, email, company, bio, ...)
/cc @parkr @benbalter
Thanks!
Filipe

Update: Fixed the test case, so now CI tests pass.
I also managed to test this on a project page (by setting env variable PAGES_REPO_NWO) and confirmed the organization object looks OK.
I investigated filtering fields such as email (using c.user(owner, "type" => "public"), similar to c.list_repos() below), but that does not work... If you really think that information should be filtered out, can you suggest a way to do that?
Thanks!
Filipe


[Bug] [Workflow Definition] There is a problem with the workflow tree structure function, and the actual tree view is inconsistent with the preview diagram

Search before asking

[X] I had searched in the issues and found no similar issues.

What happened

What you expected to happen
Demonstrate a complete workflow.
How to reproduce
None.
Anything else
No response
Version
dev
Are you willing to submit PR?

[ ] Yes I am willing to submit a PR!

Code of Conduct

[X] I agree to follow this project's Code of Conduct

I will fix it

It is a bug here, seem our tree view have the max depth


Different behaviour when querying in VMUI vs Grafana

Hey guys, here is something i found
Querying the same query but grafana returns an error (only min and max stats, avg, mean stats are fine)

VMUI returned multiple results

However, avg stats is ok but only returned 1 result

VMUI returned multiple results

I would expect the same behaviour when I query from VMUI vs Grafana. Is this the case?

Hi @Loori-R, thanks for your quick response. Would the Grafana Datasource support  /select/logsql/hits endpoint in the future?

Hi @Loori-R, thanks for your quick response. Would the Grafana Datasource support  /select/logsql/hits endpoint in the future?

Yes, support for the /select/logsql/hits endpoint is planned. You can follow the progress here: #15.

Hi @tommysitehost !
I checked your request and the plugin works well. Because stats and stats range API works with numbers. And your request will return something like {"max(body.hostname)":"we.xn--yfro4i67o"}.
You should modify your query to get the correct results from from the VictoriaLogs

hey @dmitryk-dk,
I just wanna point out that min and max stats do not work on the same dataset, while the avg, mean stats work.

hey @dmitryk-dk,
I just wanna point out that min and max stats do not work on the same dataset, while the avg, mean stats work.

Can you create an issue in the VictoriaMetrics repository and describe this issue. Because the plugin just transfer data from VictoriaLogs to the Grafana.

@tommysitehost, FYi: victorialogs-datasource supports /select/logsql/hits starting from v0.11.0.


Peer to peer code Review

You have done a good effort and a great job on this project

keep it up 🥇. Your project is complete!
Congratulations! 🎉

Your project looks neat!
To Highlight

Descriptive commit messages ✔
Good overall design ✔

Cheers and Happy coding!👏👏👏


Fix import graphscope.nx failed on python3.6

What do these changes do?

Related issue number

Fixes #1125

Could you give more details about why the import syntax affects python 3.6 compatibility?
import ... as ... seems equivalent to from .. import ... in occurences in this PR.

Could you give more details about why the import syntax affects python 3.6 compatibility?
import ... as ... seems equivalent to from .. import ... in occurences in this PR.

https://stackoverflow.com/a/36557560


Add qgrid, jupyter themes to image

Request from Vijaykumar Maraviya on Teams:

Also, there are few third-party extensions which could be of interest such as Jupyter Themes, Qgrid. Given enough interest from users wanting to use it, will it be possible to add them in the setup?

We should be able to easily add these

@yuvipanda, I believe this was solved by https://github.com/utoronto-2i2c/jupyterhub-deploy/pull/43, right? Should we close it?

@yuvipanda, I believe this was solved by https://github.com/utoronto-2i2c/jupyterhub-deploy/pull/43, right? Should we close it?


How to consume secret variables?

I have yet to find a good example for how to consume Variables marked secret in the designer.
I have a "Run a Python script" task that needs to consumes secrets via environment variables.
How do I expose the SECRET environment variables I created under the pipeline Variables tab to my "Run a Python script" task as environment variables?
Python aside, the documentation above for consuming secrets is lacking some detail.  As someone new to Azure Devops build pipeline, I am looking for something more concrete than "To pass a secret to a script, use the Environment section of the scripting task's input variables."
If this were the first place I looked, I would keep looking.  But I have been scouring the web for a decent example for quite some time without finding anything helpful.  So, leaving the feedback here, which seems a reasonable place since you are documenting Variables :)
Thanks!

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

ID: dd7e0bd3-1f7d-d7b6-cc72-5ef63c31b46a
Version Independent ID: dae87abd-b73d-9120-bcdb-6097d4b40f2a
Content: Variables - Azure Pipelines
Content Source: docs/pipelines/process/variables.md
Product: devops
Technology: devops-cicd
GitHub Login: @andyjlewis
Microsoft Alias: alewis

+1 my variable values just get passed as "***"

+1 same for me, very annoying

I've found out that the variables are being passed, they are just being masked to *** in the console output.
I'd suggest this is documented someplace or instead out outputting ***, output something explicit like MASKED

I cannot confirm this. Of course, they are being mapped as *** but also the real value resolves to *** then. It is not working as far as I can tell.

I can confirm that is how it works.  If you attempt to print/echo/log the secret value, the platform does its best to mask it with ***.  They touched on this in the updated version of the page.
The article focuses on YAML definitions, which I have never edited directly.  So I will also add that you can also map in your secrets under the Environment Variables section by creating an environment variable with the value of your secret's name.  I'm work with a Linux a build agent and a sample secret mapping looks like this:
In the pipeline's Variables section, define: Name: MY_SECRET,  Value: the_secret
In the task's Environment Variables section, add: Name: MY_SECRET,   Value: $(MY_SECRET)
Note that "Name" under Environment Vairables can be whatever you like but I choose to map mine to the same as the name used in the pipeline's Variables section.
Thank you for updating the article with the additional information for consuming the secrets!

Hello @jaryder - why are you closing issues, which are apparently not solved??
This is NOT working. I just get *** as the actual value.

Hi @maddylliieeee - I closed it because this is working for me.
How are you using the secrets?
How are you confirming *** as the value?
It should only be *** in the logs.  It should be the actual secret where you are using it.

Hi @jaryder !
I am using them in an Azure DevOps release pipeline.
The pipeline deploys several applications into a k8s cluster thereby relying on environment variables for configuration.
The values are read from env and used to modify generic docker files according to the use case.
As soon as I switch the password variable to "secret" it disappears from the output of "env", which I inserted for troubleshooting purposes.
Result in my application is that the password is simply missing/empty.
Best regards
Marius

Hi @maddylliieeee ,
Did you map the (secret) variables into the task's environment?
There is a configuration section in most tasks where you can set environment variables for the task.
I am using them in an Azure DevOps build pipeline but I would be highly surprised if they worked any differently in the release pipeline...

Hm the documentation to map them is not very good in my opinion. I am using the classic release pipeline editor and not the YAML one. Can't seem to find a way to map them into a Bash task.
My task has an environment section but how to map an existing secret pipeline-scope variable?

Hi,

Click + Add
Give it a name (this is the name it will have in the task's environment)
Give it a value like: $()

For example:
Assume in the pipeline's Variables section the following variable has been defined:
Name: MY_SECRET, Value: the_secret
In the task's Environment Variables section, add:
Name: MY_SECRET, Value: $(MY_SECRET)
Best,
jaryder

This works perfectly, just that one has to consider case sensitivity.
E.g. pipeline variable Public is being translated into ENV variable SECRET, whereas variable Secret set via Environment of the task is being translated into Secret.
So it must be mapped explicitly to SECRET in order to have my script pick it up correctly.
And the documentation - in my opinion - is rather poor.
But besides this - works great! Thanks for your patience @jaryder!


is this project dead?

...at least, I do not see any activity (but several open issues).
I just tried to make my own "thing" - but failed (of course)
Right now, I have no idea how to "register" my thing properly...

I just learned that I have to add a line to "things/index.ts" in order to register my thing...

I now learned that the
OSAP_Port_DeviceNames namePort("multi_io");

must contain the name of the Thing constructor on the JS/TS side - but the device still does not pop up...


Velocity model extension.

@mloubout  said "The model we read is the true model, we need to extend it for the PML layer (add nbpml in each direction and pad it with the boundary value)"
@mloubout - is this the usual solution? A second option would be to assume that the nbpml on the boundary is sacrificed? Either way the boundary will not be accurate.

It is absolutely necessary as the source and receiver are on top. sacrificing the points would remove the water layer and probably put the source inside the damping region.

@ggorman
There is actually a way to do without extending, but you need to play with indexes to axcees the boundary value from inside the PML

Padding added.


Question about adversarial robustness

Hi, Rao
Thank you for your great work!
When measuring GFNet's advertising robustness through FGSM and PGD, can I know specific conditions and hyperparameters?
It would be even better if I could get the code you used!

Hi @JHLEE17, thanks for your interest in our work. We directly use the publicly available repo EasyRobust to evaluate our model and baseline models. We use the default hyperparameters of this repo.

Thank you so much!!!


Dashboard for Polkadot Decoded

refer to: https://mb.web3go.xyz/collection/116-polkadot-decoded
Two dashboards are needed for Polkadot decoded presentation:

Dashboard for Crowdloan:
Link： https://mb.web3go.xyz/public/dashboard/c3c10928-1d80-4b40-959f-4aa50bea9ece

[x]             a.  Daily trend Contributors
[x]             b.  Daily trend Contributions
[x]             c.  Top 10 Contributors with the label. (we already have )
[x]             d.  Stacked daily trend contributions per  Won project for the first 2 campaigns
[x]             e.  Total contributors and contributions

Dashboard for XC20 token:
Link:  https://mb.web3go.xyz/public/dashboard/39cd624b-c4f5-4d52-8a4c-f739fd060c93

On Moonbeam

[x]         a. XC20 Tokens TVL Daily Trend
[x]         b. XC20 Tokens TVL Breakdown
[x]         c.  XC20 Token Locked in Defi contracts    (XC20 Token锁定在哪些dex里)
[x]         d. XC20 Token  Inflows-Outflows  in Defi contracts  (XC20 Token 在dex里的进出交易量)

work on dashboard and finished.  https://mb.web3go.xyz/collection/116-polkadot-decoded


[bug] Fix disappearing verse on network error

If the user clicks on a verse and the app can't make a connection to the server, the verse disappears. This commit fixes the bug. A future change should improve the UX here and notify the user that something has gone wrong.
Test plan: tried it in dev.

This fixes #346.


Release/0.46.4

Codecov Report

Merging #1478 (9552606) into develop (492d477) will increase coverage by 3.69%.
The diff coverage is 80.46%.

@@             Coverage Diff             @@
##           develop    #1478      +/-   ##
===========================================
+ Coverage    57.94%   61.63%   +3.69%
===========================================
  Files          407      643     +236
  Lines        15371    15737     +366
  Branches      2931     2817     -114
===========================================
+ Hits          8907     9700     +793
+ Misses        6187     5746     -441
- Partials       277      291      +14

Impacted Files
Coverage Δ

src/alert/_example/icon.vue
100.00% <ø> (ø)

src/alert/_usage/index.vue
0.00% <ø> (ø)

src/anchor/_usage/index.vue
0.00% <ø> (ø)

src/avatar/_example/base.vue
100.00% <ø> (ø)

src/avatar/_usage/index.vue
0.00% <ø> (ø)

src/badge/_usage/index.vue
0.00% <ø> (ø)

src/breadcrumb/_example/custom.vue
100.00% <ø> (ø)

src/breadcrumb/_example/dropdown.vue
100.00% <ø> (ø)

src/button/_example/icon.vue
100.00% <ø> (ø)

src/button/_usage/index.vue
0.00% <ø> (ø)

... and 459 more

Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.


feat: implement spec 0.7.0 changes

run any event handler immediately if the provider is in the associated state, not just ready
add providerName to event details
add STALE provider state
update/add associated tests
also fixed spec/test associations mismatches from previous changes

fixes: https://github.com/open-feature/java-sdk/issues/599

Let's try and merge this tomorrow unless someone identifies a blocker.

@thiyagu06 I've accepted the change you proposed. Can you re-review?


Status feedback during processing

Original author<EMAIL_ADDRESS>(August 24, 2011 23:36:57)
When processing large datasets, Refine will gives a spinning circle but no indication of it's progress.  This leaves the user without knowing if the operation/data set is to large for Refine to reasonably handle given machine performance or if Refine is frozen.
Some basic information such as "current command" applied to x/y rows and or basic time completion estimations would ease this problem.
Original issue: http://code.google.com/p/google-refine/issues/detail?id=438

The "Working…" dialog is generically shown when most HTTP requests from the frontend take a long time to be processed by the backend. It is a sort of fallback for requests that should normally be quick but take unexpectedly longer than usual. It would of course be great if for all of them one could have a better progress report, but we cannot realistically do that uniformly for all API endpoints (it would require even more endpoints to poll for the state of those computations!)
Improving the user experience for large datasets is something I am actively working on at the moment and a lot of this work is about avoiding such "Waiting…" screens. For instance, if you create a new column based on an existing column in 3.x, with a Jython expression which takes a long time to compute (such as making an HTTP request via Jython, for instance because more control over the headers is wished), then you will get such a "Working…" screen until the expression is evaluated on the entire grid. In 4.x this is instead replaced by a progress indicator like the one you get for other long-running operations. Given the statement of the issue it is hard to tell if that's the use case the author was aiming at though.
In cases of outright failure, it is possible that this "Working…" screen is shown indefinitely. This is likely linked to the very poor handling of XHR requests both from the backend (not exposing proper HTTP response codes) and the frontend (not handling error responses). We have #165 for that.
Therefore closing this.


No error reported when attempting to delete a non-existing pipeline

What happened?:
I tried to delete a pipeline with a non existing name. The command completed successfully without any output.
What you expected to happen?:
An error would be displayed specifying that I tried to delete a non-existing pipeline
How to reproduce it (as minimally and precisely as possible)?:
pachctl delete pipeline 'non-existing-pipe-name'
Anything else we need to know?:
This is mostly an issue when attempting to delete a pipeline and having a typo. The user would think the pipeline was deleted. In reality its still there and jobs would continue to run.
Environment?:

Pachyderm CLI and pachd server version (use pachctl version):
1.10

This is intentional on our end so that you don't have to handle errors when writing cleanup scripts.

I see.


Group membership confirmation does not work from email

If a user requests to join a group, an email is sent to users that looks like
Dear David
User X has requested to join your HydroShare group (CUAHSI JupyterHub).
Click here to find information about the requesting user.
Click on the link below to accept this request.
https://www.hydroshare.org/hsapi/_internal/group_membership/5gv-d7c93829c83d5bca7366/2/1947/?next=/
The HydroShare Team

However clicking on the link to accept does not work.  It results in an error “The link you clicked is no longer valid. Please ask to join the group again.”
If I then log into HydroShare I am able to accept their membership at the groups page.  After that clicking on the link results in "The link you clicked is no longer valid."
This is a regression bug.

I've also recieved the "link is no  longer valid" message and thought it was because someone else accepted the user into the group. Do these links expire after a specified amount of time?

There are three messages I have seen clicking the links
(1) “The link you clicked is no longer valid. Please ask to join the group again.”
(2) "The link you clicked is no longer valid."
(3) "User 'username' just joined the group 'CyberGIS-Jupyter for Water'"
I just received (3) this morning when I clicked on a link in my email.  I am not sure which occur when related to how old the link is and whether I am logged into HydroShare or not.
Links should expire after a certain time (but that should be about a week).

The activation emails expire after a week.
I'm wondering if this is a string encoding problem.  Message (1) occurs when a GroupMembershipRequest exists but the credentials fail to authenticate.  Message (2) occurs when no GroupMembershipRequest is found.  The tokens/ids are parameters in the url.

@Castronova's explanation for (2) makes sense and is consistent with what I'm seeing in the code.  (1) would occur if the token expires.

Looking over this more I don't think there is a regression.  I think it's a caused by more group activity due to the group authentication with several moderators managing users combined with poor messaging feedback.  I can update the messaging to distinguish between an invalid group membership link and a redeemed membership link.  If we continue to see invalid membership links reported, then we will know if there is a problem with the link generation.


Bug: WebGPU hardware instancing fails with more complicated models

DO NOT MERGE THIS.
I made this into a pull request as that's an easier way to show the example of it going wrong. On WebGL this example renders just fine. On WebGPU I get the following error:
WebGPU validation error: Instance range (first: 0, count: 1000) requires a larger buffer (64000) than the bound buffer size (1524) of the vertex buffer at slot 1 with stride 64.
 - While encoding [RenderPassEncoder "RenderPassForward"].DrawIndexed(48, 1000, 0, 0, 0).

Debug group stack:
 > "grass"
 > "Material: defaultGlbMaterial"
 > "Node: grass"
 > "World(OPAQUE)"
 > "Untitled"
 > "Pass:RenderPassForward"
  while rendering

You can also test it with another model using this diff:
diff --git a/examples/src/examples/graphics/hardware-instancing/example.mjs b/examples/src/examples/graphics/hardware-instancing/example.mjs
index aeb6df131..91a6ea285 100644
--- a/examples/src/examples/graphics/hardware-instancing/example.mjs
+++ b/examples/src/examples/graphics/hardware-instancing/example.mjs
@@ -7,7 +7,7 @@ if (!(canvas instanceof HTMLCanvasElement)) {
 }

 const assets = {
-    grass: new pc.Asset('grass', 'container', { url: rootPath + '/static/assets/models/grass.glb' }),
+    grass: new pc.Asset('grass', 'container', { url: rootPath + '/static/assets/models/icosahedron.glb' }),
     helipad: new pc.Asset(
         'helipad-env-atlas',
         'texture',
@@ -74,7 +74,8 @@ assetListLoader.load(() => {

     const grass = assets.grass.resource.instantiateRenderEntity();

-    grass.children[0].render.meshInstances[0].material = material;
+    grass.children[0].children[0].render.meshInstances[0].material = material;
+    grass.children[0].children[1].render.meshInstances[0].material = material;

     // add the box entity to the hierarchy
     app.root.addChild(grass);
@@ -115,8 +116,8 @@ assetListLoader.load(() => {
         });

         // initialize instancing using the vertex buffer on meshInstance of the created box
-        const grassMeshInst = grass.children[0].render.meshInstances[0];
-        grassMeshInst.setInstancing(vertexBuffer);
+        grass.children[0].children[0].render.meshInstances[0].setInstancing(vertexBuffer);
+        grass.children[0].children[1].render.meshInstances[0].setInstancing(vertexBuffer);
     }

     // Set an update function on the app's update event

This actually gives a different error:
WebGPU validation error: Attribute shader location (13) is used more than once.
 - While validating attributes[1].
 - While validating buffers[1].
 - While validating vertex state.
 - While calling [Device "PlayCanvasWebGPUDevice"].CreateRenderPipeline([RenderPipelineDescriptor "RenderPipelineDescr-1"]).
  while rendering Pass:RenderPassForward | Untitled | World(OPAQUE) | Node: Object_3 | Material: Untitled | Object_3

@mvaligursky any idea what could be happening here, I'm lost.

So glad you found and reported this! We've had an issue with morph-many example not working correctly on WebGPU, and this exposed why, as I could not figure out exactly what the problem was.
See more details here: https://github.com/playcanvas/engine/pull/6274
Closing, but ping again if something is still off. Thanks!


Adds Timestamp.forEpochSeconds()

Implements #301 by adding Timestamp.forEpochSeconds to allow easy conversion from Java 8's java.time.Instant.
This test works on my local machine when I target Java 8.  (It's not included in this PR since we can't yet update ion-java to Java 8.)
@Test
public void convertFromInstantTest() {
    Instant i = Instant.now();
    Timestamp ts = Timestamp.forEpochSecond(i.getEpochSecond(), i.getNano());
    assertEquals(i.toString(), ts.toString());
    System.out.println(i.toString());
    System.out.println(ts.toString());
}

Output is:
2020-08-12T18:28:26.439Z
2020-08-12T18:28:26.439Z

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.

Conceptually, this looks perfect.


saving/recording HLS ?

Hello ,
To record live-stream I've followed the instruction , and works perfectly ( https://github.com/arut/nginx-rtmp-module/wiki/Directives#record )
I wanted to know if it's possible to record and save the HLS fragments . When record is done , it's send to another server to get saved , but will require transcoding . But if I were able to save the HLS as it is , would make it much easier the transfer without the re-encoding .
Is there anyway ?

i don't understand exactly your issue but i think i will put your you on right way with to thing . firstly
RECORD directive is only to record rtmp to .flv no other container can be specified . secondly if you want to save HLS fragment my advice is to change default hls directory who is located in tempory directory in http server  and redirect it to mnt directory somethig like this.
 location /hls {
            # Disable cache
            add_header 'Cache-Control' 'no-cache';

            # CORS setup
            add_header 'Access-Control-Allow-Origin' '*' always;
            add_header 'Access-Control-Expose-Headers' 'Content-Length';

            # allow CORS preflight requests
            if ($request_method = 'OPTIONS') {
                add_header 'Access-Control-Allow-Origin' '*';
                add_header 'Access-Control-Max-Age' 1728000;
                add_header 'Content-Type' 'text/plain charset=UTF-8';
                add_header 'Content-Length' 0;
                return 204;
            }
            # MIME type for HLS
            types {
                application/dash+xml mpd;
                application/vnd.apple.mpegurl m3u8;
                video/mp2t ts;
            }

            alias /mnt/hls/;   #this was previsously /tmp/dash
        }

if directive alias don't work change it to root.

@lejahmal The idea is to not re-transcode the stream .
If you have a website where you can stream , and you want to save the video for playback , saving it into .flv will require a transcoding again into mp4 or HLS .
So if I were able to save it as HLS , then move it to the platform ( with script ) , would save me time of transcoding ( I already transcode the stream {360/480/720} )  .

You could use the on_publish_done.
   exec_publish_done  	/bin/bash -c 'mv /stream_path/$name /destination/$name';


Select/Selectize ui.remove_ui does not remove label

Lines 212-239 _input_select.py
return div(
shiny_input_label(resolved_id, label),
div(
tags.select(
*choices_tags,
{"class": "shiny-input-select"},
class_=None if selectize else "form-select",
id=resolved_id,
multiple=multiple,
size=size,
),
(
TagList(
tags.script(
dumps(opts),
type="application/json",
data_for=resolved_id,
data_eval=dumps(extract_js_keys(opts)),
),
selectize_deps(),
)
if selectize
else None
),
),
class_="form-group shiny-input-container",
style=css(width=width),
)
Main Issue
In bold the tag with the id for the selective element is a div that does not contain the label. So calling remove_ui('div:has(> #id)') will leave a stray label behind. The fix should just be moving the **TagList into the parent div.

I can see that it'd be helpful in this case if the ID of the select input (or an attribute reflecting the ID of the select input) were higher up in the DOM structure.
Fortunately, for your use case, you can wrap the select element that you know you'll want to remove in a ui.div() with it's own ID that you can use in ui.remove().
Here's an example (also on shinylive):
from shiny.express import input, ui
from shiny import reactive

with ui.div(id="thing-select"):
    ui.input_selectize("thing", "Thing", choices=["a", "b", "c"])

ui.input_action_button("remove_thing", "Remove Selectize")

@reactive.effect
@reactive.event(input.remove_thing)
def _():
    ui.remove_ui("#thing-select")

I'm using regular shiny not express. I have tried that before, it's in a longer piece of code that adds and removes named elements.


feat: add support for Unity 2019

Description

Added support for Unity 2019 by back-porting some C# 8.0 syntax to C# 7.3 and changed an internal interface. The internal interface was used to determine if a UnityWebRequest was successful or not and relied on a property that wasn't available back in Unity 2019 and was fixed by a #if UNITY_2020_1_OR_NEWER build conditional.
Fixes warnings about Naming Rule Violations.
Fixes UnitTests that wouldn't run in Unity 2021

Fixes #71 Fixes #70
Checklist

[ ] Tested manually
[ ] Unit tests pass with no errors or warnings
[ ] Documentation updated (if applicable)
[ ] Reviewed by at least 1 other contributor

Glad this turned out not to be a big headache. Everything looks good to me 👍


Add Mayank Khanna to Contributers list

Add me to contributers list.

Hi  @khanna98, I'm quite elated about your pull request. I wanna evolve this project to addresses various problems faced by first-time contributors. I'd love to learn about your journey in open source community, the problems, pain points you had etc.
Could you explain how you felt when you went through the tutorial, made a pull request and learned that I merged it?
We’ve recently added social share  to our web app. Could you please go to https://roshanjossey.github.io/first-contributions/#social-share and share your first contribution to open source?
Also, check out projects with easy issues while you’re there.


mouseover text entries for diffs on history pages are badly formatted.

For example:

This is fixed - the mouseover is not shown anymore.


test: refactor and write tests for search function

No change to logic. This is a pure refactor so that it's possible to test the findBrother() function. This adds basic test coverage for findBrother().
Test: npm test

Codecov Report
Attention: Patch coverage is 75.00000% with 7 lines in your changes are missing coverage. Please review.

Project coverage is 64.37%. Comparing base (8a4331e) to head (4779793).
Report is 1 commits behind head on main.

Files
Patch %
Lines

main.js
75.00%
7 Missing :warning:

:exclamation: Your organization needs to install the Codecov GitHub app to enable full functionality.
Additional details and impacted files
@@            Coverage Diff             @@
##             main      #46      +/-   ##
==========================================
+ Coverage   60.13%   64.37%   +4.23%
==========================================
  Files           2        2
  Lines         148      160      +12
==========================================
+ Hits           89      103      +14
+ Misses         59       57       -2

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.