Tensorflow doesn't seem to work on rtx2060

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System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow):yes
OS Platform and Distribution (e.g., Linux Ubuntu 16.04):windows 10
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:none
TensorFlow installed from (source or binary):binary
TensorFlow version (use command below): V2.4.0rc4-71-g582c8d236cb 2.4.0
Python version: 3.8.0
Bazel version (if compiling from source):nonenone
GCC/Compiler version (if compiling from source):none
CUDA/cuDNN version : cuda_11.1.1_456.81/cuDNN v8.0.5
GPU model and memory:RTX2060，6G
CPU~~~~~~~~~~~~~:AMD 2600X  16G
You can collect some of this information using our environment capture
script
You can also obtain the TensorFlow version with:

TF 1.0: python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"
TF 2.0: python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"

Describe the current behavior
I try to use tensorflow to construct mtcnn + facenet to realize face recognition, and refer to this https://github.com/kpzhang93/MTCNN_face_detection_alignment
When running mtcnn network, I found that the performance of rtx2060 was very poor. The occupancy rate reported by Windows system was only about 3%, and the occupancy rate queried by NVIDIA SMI was less than 7%.
I thought it was my code problem. Until I ran the MNIST sample, I found that this problem might be universal on my computer
Describe the expected behavior
The utilization rate of rtx2060 should be more than 60%. In the case of MNIST, every batch should be used_ The size is set to 256, which seems to only increase the pressure on the video memory.
Through NVIDIA SMI monitoring, the efficiency of rtx2060 is only about 4%
and
I added the running log of my dumnist below. According to the computing power of rtx2060, the time consumed by running this code should be reduced by more than half.
Standalone code to reproduce the issue
For the recurrence of MNIST, I do as follows:
import tensorflow as tf
import sys
import os
import datetime
gpu = tf.config.list_physical_devices('GPU')
tf.config.experimental.set_memory_growth(gpu[0], True)

starttime = datetime.datetime.now()

mnist = tf.keras.datasets.mnist
(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0

model = tf.keras.models.Sequential([
    tf.keras.layers.Flatten(),
    tf.keras.layers.Dense(128, activation="relu"),
    tf.keras.layers.Dense(10, activation='softmax')
])
model.compile(optimizer='adam',
              loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=False),
              metrics=['sparse_categorical_accuracy'])

checkpoint_save_path = "./checkpoint/mnist/mnist.ckpt"
if os.path.exists(checkpoint_save_path + '.index'):
    print('------------load the model-----------')
    model.load_weights(checkpoint_save_path)

cp_callback = tf.keras.callbacks.ModelCheckpoint(
    filepath=checkpoint_save_path,
    save_weights_only=True,
    save_best_only=True
)
history = model.fit(x_train, y_train, batch_size=128, epochs=20,
                    validation_data=(x_test, y_test), validation_freq=1,
                    callbacks=[cp_callback])
model.summary()
endtime = datetime.datetime.now()
print((endtime - starttime).seconds)
sys.exit()`

**Other info / logs** Include any logs or source code that would be helpful to
I conducted 20 rounds of tests and the log is as follows:

runfile('E:/IDEA/pythonProject/mnist.py', wdir='E:/IDEA/pythonProject')
2021-03-08 00:27:44.912688: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-03-08 00:27:46.503950: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-03-08 00:27:46.505289: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll
2021-03-08 00:27:46.541927: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:27:00.0 name: GeForce RTX 2060 computeCapability: 7.5
coreClock: 1.68GHz coreCount: 30 deviceMemorySize: 6.00GiB deviceMemoryBandwidth: 312.97GiB/s
2021-03-08 00:27:46.542220: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-03-08 00:27:46.569789: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-03-08 00:27:46.569959: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-03-08 00:27:46.575380: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-03-08 00:27:46.577802: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-03-08 00:27:46.588545: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-03-08 00:27:46.593147: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-03-08 00:27:46.594651: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-03-08 00:27:46.594860: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-03-08 00:27:46.930131: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021-03-08 00:27:46.931110: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:27:00.0 name: GeForce RTX 2060 computeCapability: 7.5
coreClock: 1.68GHz coreCount: 30 deviceMemorySize: 6.00GiB deviceMemoryBandwidth: 312.97GiB/s
2021-03-08 00:27:46.931392: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-03-08 00:27:46.931527: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-03-08 00:27:46.931660: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-03-08 00:27:46.931788: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-03-08 00:27:46.931926: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-03-08 00:27:46.932050: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-03-08 00:27:46.932189: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-03-08 00:27:46.932316: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-03-08 00:27:46.932480: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-03-08 00:27:47.489887: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-03-08 00:27:47.490098: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0
2021-03-08 00:27:47.490232: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N
2021-03-08 00:27:47.490534: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4720 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2060, pci bus id: 0000:27:00.0, compute capability: 7.5)
2021-03-08 00:27:47.491188: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
------------load the model-----------
2021-03-08 00:27:47.600796: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
Epoch 1/20
2021-03-08 00:27:47.960346: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-03-08 00:27:48.494384: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
1875/1875 [==============================] - 6s 3ms/step - loss: 0.0204 - sparse_categorical_accuracy: 0.9939 - val_loss: 0.0778 - val_sparse_categorical_accuracy: 0.9767
Epoch 2/20
1875/1875 [==============================] - 5s 2ms/step - loss: 0.0180 - sparse_categorical_accuracy: 0.9952 - val_loss: 0.0765 - val_sparse_categorical_accuracy: 0.9793
Epoch 3/20
1875/1875 [==============================] - 5s 3ms/step - loss: 0.0135 - sparse_categorical_accuracy: 0.9961 - val_loss: 0.0812 - val_sparse_categorical_accuracy: 0.9766
Epoch 4/20
1875/1875 [==============================] - 5s 3ms/step - loss: 0.0110 - sparse_categorical_accuracy: 0.9968 - val_loss: 0.0808 - val_sparse_categorical_accuracy: 0.9780
Epoch 5/20
1875/1875 [==============================] - 4s 2ms/step - loss: 0.0102 - sparse_categorical_accuracy: 0.9970 - val_loss: 0.0850 - val_sparse_categorical_accuracy: 0.9777
Epoch 6/20
1875/1875 [==============================] - 4s 2ms/step - loss: 0.0092 - sparse_categorical_accuracy: 0.9971 - val_loss: 0.0846 - val_sparse_categorical_accuracy: 0.9782
Epoch 7/20
1875/1875 [==============================] - 5s 2ms/step - loss: 0.0081 - sparse_categorical_accuracy: 0.9975 - val_loss: 0.1029 - val_sparse_categorical_accuracy: 0.9765
Epoch 8/20
1875/1875 [==============================] - 5s 2ms/step - loss: 0.0063 - sparse_categorical_accuracy: 0.9983 - val_loss: 0.0903 - val_sparse_categorical_accuracy: 0.9786
Epoch 9/20
1875/1875 [==============================] - 5s 2ms/step - loss: 0.0076 - sparse_categorical_accuracy: 0.9977 - val_loss: 0.0801 - val_sparse_categorical_accuracy: 0.9811
Epoch 10/20
1875/1875 [==============================] - 4s 2ms/step - loss: 0.0074 - sparse_categorical_accuracy: 0.9976 - val_loss: 0.0942 - val_sparse_categorical_accuracy: 0.9792
Epoch 11/20
1875/1875 [==============================] - 5s 2ms/step - loss: 0.0051 - sparse_categorical_accuracy: 0.9986 - val_loss: 0.1002 - val_sparse_categorical_accuracy: 0.9788
Epoch 12/20
1875/1875 [==============================] - 5s 2ms/step - loss: 0.0048 - sparse_categorical_accuracy: 0.9985 - val_loss: 0.1038 - val_sparse_categorical_accuracy: 0.9785
Epoch 13/20
1875/1875 [==============================] - 5s 3ms/step - loss: 0.0045 - sparse_categorical_accuracy: 0.9986 - val_loss: 0.1138 - val_sparse_categorical_accuracy: 0.9776
Epoch 14/20
1875/1875 [==============================] - 4s 2ms/step - loss: 0.0063 - sparse_categorical_accuracy: 0.9978 - val_loss: 0.1081 - val_sparse_categorical_accuracy: 0.9791
Epoch 15/20
1875/1875 [==============================] - 5s 2ms/step - loss: 0.0034 - sparse_categorical_accuracy: 0.9991 - val_loss: 0.1001 - val_sparse_categorical_accuracy: 0.9803
Epoch 16/20
1875/1875 [==============================] - 5s 2ms/step - loss: 0.0022 - sparse_categorical_accuracy: 0.9993 - val_loss: 0.1246 - val_sparse_categorical_accuracy: 0.9783
Epoch 17/20
1875/1875 [==============================] - 5s 2ms/step - loss: 0.0066 - sparse_categorical_accuracy: 0.9978 - val_loss: 0.1079 - val_sparse_categorical_accuracy: 0.9804
Epoch 18/20
1875/1875 [==============================] - 4s 2ms/step - loss: 0.0020 - sparse_categorical_accuracy: 0.9995 - val_loss: 0.1111 - val_sparse_categorical_accuracy: 0.9795
Epoch 19/20
1875/1875 [==============================] - 5s 2ms/step - loss: 0.0034 - sparse_categorical_accuracy: 0.9991 - val_loss: 0.1124 - val_sparse_categorical_accuracy: 0.9784
Epoch 20/20
1875/1875 [==============================] - 4s 2ms/step - loss: 0.0056 - sparse_categorical_accuracy: 0.9982 - val_loss: 0.1386 - val_sparse_categorical_accuracy: 0.9756
Model: "sequential"

Layer (type)                 Output Shape              Param
=================================================================
flatten (Flatten)            (None, 784)               0

dense (Dense)                (None, 128)               100480

dense_1 (Dense)              (None, 10)                1290
=================================================================
Total params: 101,770
Trainable params: 101,770
Non-trainable params: 0

94
===========================LOGs END===========================

I also have a sample log to provide:
This occurs in running cifar 10
For the recurrence of cifar10, I do as follows:
import tensorflow as tf
import os
import numpy as np
from matplotlib import pyplot as plt
from tensorflow.keras.layers import Conv2D, BatchNormalization, Activation, MaxPool2D, Dropout, Flatten, Dense
from tensorflow.keras import Model
import datetime
import time
import sys
starttime = datetime.datetime.now()
os.environ['TF_CPP_MIN_LOG_LEVEL'] = "3"
np.set_printoptions(threshold=np.inf)
cifar10 = tf.keras.datasets.cifar10
(x_train, y_train), (x_test, y_test) = cifar10.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0
gpu_options = tf.compat.v1.GPUOptions(per_process_gpu_memory_fraction=0.333)
sess = tf.compat.v1.Session(config=tf.compat.v1.ConfigProto(gpu_options=gpu_options, allow_soft_placement=True))
gpu = tf.compat.v1.ConfigProto()
gpu.gpu_options.allow_growth = True
session = tf.compat.v1.InteractiveSession(config=gpu)
CBAPD
C : 655  same
B : yes
A : relu
P : 2*2  2
D : none
F : Flatten
Dense1 : 全连接  128NN relu activation Dropout 0.2
Dense2 : 全连接   10NN softmax
class Baseline(Model):
def init(self):
super(Baseline, self).init()
self.c1 = Conv2D(filters=6, kernel_size=(5, 5), padding="same")
self.b1 = BatchNormalization()
self.a1 = Activation('relu')
self.p1 = MaxPool2D(pool_size=(2, 2), strides=2, padding='same')
self.d1 = Dropout(0.2)
    self.flatten = Flatten()
    self.f1 = Dense(128, activation='relu')
    self.d2 = Dropout(0.2)
    self.f2 = Dense(10, activation='softmax')

def call(self, x):
    x = self.c1(x)
    x = self.b1(x)
    x = self.b1(x)
    x = self.a1(x)
    x = self.p1(x)
    x = self.d1(x)
    x = self.flatten(x)
    x = self.f1(x)
    x = self.d2(x)
    y = self.f2(x)
    return y

model = Baseline()

sparse_categorical_accuracy
model.compile(optimizer='adam',
loss=tf.losses.SparseCategoricalCrossentropy(from_logits=False),
metrics=['sparse_categorical_accuracy'])
checkpoint_save_path = "./checkpoint/Baseline.ckpt"
if os.path.exists(checkpoint_save_path + '.index'):
print('--------------load the mode as Baseline--------------')
model.load_weights(checkpoint_save_path)
配置断点续训--写入
cp_callback = tf.keras.callbacks.ModelCheckpoint(filepath=checkpoint_save_path,
save_weights_only=True,
save_best_only=True)
history = model.fit(x_train, y_train,
batch_size=128, epochs=4000,
validation_data=(x_test, y_test), validation_freq=1,
callbacks=[cp_callback])
model.summary()
file = open('./weights.txt', 'w')
for i in model.trainable_variables:
file.write(str(i.name) + '\n')
file.write(str(i.shape) + '\n')
file.write(str(i.numpy()) + '\n')
file.close()
-------------- show    --------------#
acc = history.history['sparse_categorical_accuracy']
val_acc = history.history['val_sparse_categorical_accuracy']
loss = history.history['loss']
val_loss = history.history['val_loss']
plt.subplot(1, 2, 1)
plt.plot(acc, label='Training Accuracy')
plt.plot(val_acc, label='Validation Accuracy')
plt.title('Training and Validation Accuracy')
plt.legend()
plt.subplot(1, 2, 1)
plt.plot(loss, label='Training Loss')
plt.plot(val_loss, label='Validation Loss')
plt.title('Training and Validation Loss')
plt.legend()
plt.show()
endtime = datetime.datetime.now()
print((endtime - starttime).seconds)
time.sleep(30)
sys.exit()
LOGS START
runfile('E:/IDEA/pythonProject/Cifar10_Model.py', wdir='E:/IDEA/pythonProject')
2021-03-08 01:22:55.988089: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-03-08 01:22:58.319151: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021-03-08 01:22:58.321647: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll
2021-03-08 01:22:58.356526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:27:00.0 name: GeForce RTX 2060 computeCapability: 7.5
coreClock: 1.68GHz coreCount: 30 deviceMemorySize: 6.00GiB deviceMemoryBandwidth: 312.97GiB/s
2021-03-08 01:22:58.356964: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-03-08 01:22:58.366034: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-03-08 01:22:58.366261: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-03-08 01:22:58.371026: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-03-08 01:22:58.373161: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-03-08 01:22:58.383581: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-03-08 01:22:58.387809: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-03-08 01:22:58.389278: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-03-08 01:22:58.389559: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-03-08 01:22:58.959324: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-03-08 01:22:58.959530: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0
2021-03-08 01:22:58.959678: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N
2021-03-08 01:22:58.960071: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4720 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2060, pci bus id: 0000:27:00.0, compute capability: 7.5)
2021-03-08 01:22:58.960919: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-03-08 01:22:58.964583: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-03-08 01:22:58.964863: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:27:00.0 name: GeForce RTX 2060 computeCapability: 7.5
coreClock: 1.68GHz coreCount: 30 deviceMemorySize: 6.00GiB deviceMemoryBandwidth: 312.97GiB/s
2021-03-08 01:22:58.965261: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-03-08 01:22:58.965476: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-03-08 01:22:58.965700: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-03-08 01:22:58.965871: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-03-08 01:22:58.966116: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-03-08 01:22:58.966320: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-03-08 01:22:58.966507: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-03-08 01:22:58.966694: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-03-08 01:22:58.966937: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-03-08 01:22:58.967419: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:27:00.0 name: GeForce RTX 2060 computeCapability: 7.5
coreClock: 1.68GHz coreCount: 30 deviceMemorySize: 6.00GiB deviceMemoryBandwidth: 312.97GiB/s
2021-03-08 01:22:58.967837: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-03-08 01:22:58.968044: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-03-08 01:22:58.968261: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-03-08 01:22:58.968468: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-03-08 01:22:58.968665: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-03-08 01:22:58.968876: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-03-08 01:22:58.969097: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-03-08 01:22:58.969326: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-03-08 01:22:58.969546: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-03-08 01:22:58.969759: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-03-08 01:22:58.969905: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0
2021-03-08 01:22:58.969996: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N
2021-03-08 01:22:58.970168: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 4720 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2060, pci bus id: 0000:27:00.0, compute capability: 7.5)
2021-03-08 01:22:58.970540: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
--------------load the mode as Baseline--------------
2021-03-08 01:22:59.294021: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
Epoch 1/4000
2021-03-08 01:22:59.933410: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-03-08 01:23:00.409513: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-03-08 01:23:00.416814: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-03-08 01:23:01.401150: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code: 0
2021-03-08 01:23:01.473301: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:01.474022: W tensorflow/stream_executor/gpu/redzone_allocator.cc:314] Internal: ptxas exited with non-zero error code -1, output:
Relying on driver to perform ptx compilation.
Modify $PATH to customize ptxas location.
This message will be only logged once.
2021-03-08 01:23:01.549213: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:01.625852: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:01.700407: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:01.773802: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:01.851961: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:01.922854: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:01.995014: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:02.070523: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:02.149133: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:02.222853: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:02.296621: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:02.371945: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:02.441581: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:02.514017: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:02.593597: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:02.669747: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:02.748396: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:02.825343: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:02.897071: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:02.971146: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:03.049402: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:03.124899: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:03.202434: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:03.413842: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:03.487559: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:03.561893: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:03.638064: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:03.712285: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:03.782712: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:03.853222: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:03.927721: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:03.998730: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:04.073533: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:04.147819: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:04.222011: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:04.296984: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:04.369178: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:04.442802: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:04.517602: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:04.588613: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:04.658139: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:04.731727: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
2021-03-08 01:23:04.808468: I tensorflow/core/platform/windows/subprocess.cc:308] SubProcess ended with return code:<PHONE_NUMBER>
1556/1563 [============================>.] - ETA: 0s - loss: 0.8424 - sparse_categorical_accuracy: 0
.........
LOGS END********
I've come up with a new question when I'm editing the review. I need your advice, if you don't mind：
"Subprocess ended with return code:<PHONE_NUMBER>" reveals some errors that I can't explain. I mean, these errors happened. I only know this series of error codes, but I don't know where it happened.
In fact, when I run facenet and mtcnn, tensorflow only prompts this passage for a long time, including when I run this project https://github.com/kpzhang93/MTCNN_face_detection_alignment
In my opinion, the common feature of these problems is that the utilization rate of rtx2060 is very low (not only in Windows Task Manager, NVIDIA-SMI also gives the same conclusion, the error between the two is not more than 4%, which is certain, because the latter is 4% utilization rate, while the former is 0% QAQ)
What should I do? Continue to try different combinations of CUDA, cudnn and tensorflow? Because of this, I have been broken down for a day QAQ

I see you are using cuda 11.1 version can please try with cuda 11.0 as listed in tested build config.
Thanks!

我看到您使用的是cuda 11.1版本，请尝试使用cuda 11.0（如已测试的build config中所列）。
谢谢！

我看到您使用的是cuda 11.1版本，请尝试使用cuda 11.0（如已测试的build config中所列）。
谢谢！

I see you are using cuda 11.1 version can please try with cuda 11.0 as listed in tested build config.
Thanks!

I have re installed tensorflow and CUDA 11.0, and its conclusion seems to have no improvement. I don't know what to do

Does adding TF_DISABLE_RZ_CHECK=1 to the environment help?

@GungnirASHTTTTT did you check by enabling the above flag?
Also, can you please try with recent TF versions (TF2.7 and tf-nightly) and let us know whether it is still an issue for you? Thanks!


[synthetics-job-manager] - Upgrading chart version and app version after deploy

Is this a new chart?
No.
What this PR does / why we need it:
Just updates the node api runtime version that is latest after a deploy that happened this morning.
Which issue this PR fixes
(optional, in fixes #<issue number>(, fixes #<issue_number>, ...) format, will close that issue when PR gets merged)

fixes #
Just a version upgrade after a deploy.

Special notes for your reviewer:
Checklist
[Place an '[x]' (no spaces) in all applicable fields. Please remove unrelated fields.]

[X] Chart Version bumped
[X] Variables are documented in the README.md
[X] Title of the PR starts with chart name (e.g. [mychartname])

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.


cli: Hide Watch Usage output when running on non-interactive envs

Summary

Watch Usage options are useless in non-interactive environments (like Docker). Currently jest-cli is smart enough to know that it should not clear the terminal in those environments, with this PR it will also not output Watch Usage related stuff either, making the UI cleaner.
Also, because the terminal is not cleared after a test run, the subsequent runs will not print a new line after the "Press w to show more" text, which makes it hard to read and a really bad UX once you have watch running for a couple of test runs.
I'm not familiar with the code base at all, so let me know if there is anything that should be done differently and I'll fix it =D
Test plan

Output in interactive environments is not affected.
Here is how the output looks in Docker before and after this PR:
Before:

After:

Looks good!
One small comment if you are running jest in watch mode within Docker. You could pass the -it flags and then it would make it interactive docker run -it my-image yarn test

Thanks for sending a PR. Can you make sure "yarn test" passes? :)

I renamed and moved isInteractive to jest-util and also replaced usage of process.stdout.isTTY && !isCI with it.
I couldn't figure out why tests are failing in circleci though. Locally I tried yarn test, yarn test-ci and yarn test-ci-partial and everything passes. Do you guys have any idea of what could be wrong?

Do they pass when you do CI=true yarn test? Or somehow emulate the terminal on CI

Thanks @SimenB that was exactly it =D
Tests are passing now, I also added tests to is_interactive.
CircleCI is failing because of a yarn error and I can't trigger another build manually, that should be passing though.

I triggered a new CI run.
Can you update the changelog?


.get() obscures .use()

When adding a .get() route, express adds a handler to stack that checks all routes. When adding a middleware with .use() after a .get() route has been added, that middleware may potentially never be called.
Maybe I don't understand .use() properly; I assumed that it adds middleware that is supposed to run before any concrete routes added with .get()/.post()/.... Is that in fact the case or am I misusing express?

closing for now. routes as middleware is something we can revisit later


Fix/faucet connection error

This PR aims to fix the way connection errors are caught by the faucet client, by:

adding a new FaucetConnectionError dedicated to the GQLWS failure
translating error into a readable message (generic)

Codecov Report

Merging #595 (b2c77d1) into main (4adbc6e) will decrease coverage by 0.30%.
The diff coverage is 20.00%.

@@            Coverage Diff             @@
##             main     #595      +/-   ##
==========================================
- Coverage   96.73%   96.43%   -0.31%
==========================================
  Files          74       74
  Lines         950      954       +4
  Branches      146      146
==========================================
+ Hits          919      920       +1
- Misses         29       32       +3
  Partials        2        2

Impacted Files
Coverage Δ

src/domain/faucet/entity/error.ts
75.00% <0.00%> (-25.00%)
:arrow_down:

src/adapters/faucet/secondary/graphql/client.ts
55.55% <50.00%> (+2.61%)
:arrow_up:

:mega: We’re building smart automated test selection to slash your CI/CD build times. Learn more

:tada: This PR is included in version 2.1.0 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


New version: dotPDNLLC.paintdotnet version 5.0.13

Pull request has been created with komac v2.1.1 :rocket:

For moderators
This account is automated by Github Actions and the source code was created by CoolPlayLin. If you have any questions about any pull request, don't hesitate to ping Exorcism0666.

[!warning]
With the new version of Komac, numerous Pull Requests may contain bugs or unwanted elements. If such issues arise, please tag russellbanks so that these bugs can be addressed in future updates.

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良い一日をお過ごしください！

Automatic Validation ended with:

2024-03-06T01:39:51.6791435Z ##[error] Manifest Error: Required field missing. [NestedInstallerFiles] Manifest Error: Only one entry for NestedInstallerFiles can be specified for non-portable InstallerTypes. [NestedInstallerFiles] Manifest Error: Required field missing. [NestedInstallerFiles] Manifest Error: Only one entry for NestedInstallerFiles can be specified for non-portable InstallerTypes. [NestedInstallerFiles] Manifest Error: Required field missing. [NestedInstallerFiles] Manifest Error: Required field missing. [NestedInstallerFiles] Manifest Error: Only one entry for NestedInstallerFiles can be specified for non-portable InstallerTypes. [NestedInstallerFiles] Manifest Error: Required field missing. [NestedInstallerFiles] Manifest Error: Only one entry for NestedInstallerFiles can be specified for non-portable InstallerTypes. [NestedInstallerFiles] Manifest Error: Required field missing. [NestedInstallerFiles]

(Automated response - build 861.)


OBS builds stuck again?

$subj

Could you elaborate further please? What exactly do you mean by stuck?

~ $ sudo pacman -Syy
Place your finger on the fingerprint reader
:: Synchronizing package databases...
 core                                      138.5 KiB   280 KiB/s 00:00 [########################################] 100%
 extra                                    1585.4 KiB  1287 KiB/s 00:01 [########################################] 100%
 community                                   5.8 MiB  2.92 MiB/s 00:02 [########################################] 100%
 home_ungoogled_chromium_Arch             1309.0   B  2.18 KiB/s 00:01 [########################################] 100%
~ $ sudo pacman -Ss | grep chromium
extra/chromium 93.0.4577.82-1
community/browserpass-chromium 3.7.2-1 [installed]
community/chromium-bsu <IP_ADDRESS>-1
    Headless chrome/chromium automation library
home_ungoogled_chromium_Arch/ungoogled-chromium 92.0.4515.159-1 [installed]
~ $ grep -A3 chromium /etc/pacman.conf
[home_ungoogled_chromium_Arch]
SigLevel = Required TrustAll
Server = https://download.opensuse.org/repositories/home:/ungoogled_chromium/Arch/$arch
~ $

So chromium is at 93.0.4577.82-1 while ungoogled-chromium is stuck at 92.0.4515.159-1 for quite a while (29 days). The current version has weird bug where it displays artifacts over images, I'm eagerly waiting for the 93+ update. Thank you

Please excuse, I might not be well enough educated about OBS, I see you made 80f1f75150671203ada5f49c96b5fb2855709775 but I don't see anything happening in OBS. Do you need to submit a request manually?

OBS and GitHub releases are tied to tags in the git history.
The ungoogled-chromium repository only has a pull request with support for 93 versions at the moment so I can't create a new git tag here

I have on commit builds in the testing OBS repository on my todo list but that will take a while still. Until now I recommend that you download the package artifact from the latest successful GitHub Actions run, those also run on commit

The OBS repository now contains the latest chromium release.

@networkException thanks, I appreciate the work you're doing


Fix for gcsfs protocol which is tuple

_strip_protocol should already deal with this, I don't suppose that the code is ever reached. You could check this with simple print/pdb.

@martindurant I did this change because of the actual problem I had while chaining FS's.
GCSFS = fsspec.filesystem('gcs')

FS = fsspec.filesystem(
    "filecache",
    target_protocol=GCSFS,
)

FS.open('somefile')

This code fails on the latest release of filespec and my PR fixes it.

OK, right got it - I thought this was the other way around.
The PR fails lint, but otherwise looks good.

@martindurant fixed formatting

Thank you!


[SPARK-16662][PySpark][SQL] fix HiveContext warning bug

What changes were proposed in this pull request?
move the HiveContext deprecate warning printing statement into HiveContext constructor.
so that this warning will appear only when we use HiveContext
otherwise this warning will always appear if we reference the pyspark.ml.context code file.
How was this patch tested?
Manual.

Test build #62677 has started for PR 14301 at commit bfde7b2.

Test build #62677 has finished for PR 14301 at commit bfde7b2.

This patch passes all tests.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test PASSed.

Test PASSed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/62677/
Test PASSed.

Seems reasonable

Merged to master


Separate eslint and prettier into package

Since already tsconfig and tailwindconfig are separated ,
it would be good to separate prettier and eslint into distinct packages as well.

This is good idea, feel free to open PR 🥇

Because of https://github.com/Jonghakseo/chrome-extension-boilerplate-react-vite/pull/519#issuecomment-2226812823 i closing this, if you want to find solution and implement that in the working way, feel free to reopen :)


[SocialNetwork] Is there value in providing an enum of all supported networks?

Currently, we have a simple SocialNetworkId type that is a string. My original intention here was for it to be an enum. I'm not sure if there is any true value to doing that however.
Since users can add custom networks via Socialite.addNetwork(), we may see value in adding a type?: 'default' | 'custom' property. If we ever do that, perhaps the enum becomes more valuable?

I think that what we have now is fine. Currently, we can:
const excludedNetworks: SocialiteId[] = ['discord', 'facebook', 'reddit'];

This should satisfy our needs. Will close for now.


CentOS 7 cannot execute binary file

Hi
i'm trying to install Go 1.10.3 on CentOS 7 from this tutorial https://golang.org/doc/install?download=go1.10.3.linux-amd64.tar.gz#install
im unpacked from archive with command tar -C /usr/local -xzf go1.10.3.linux-amd64.tar.gz
created env and project folder with commands:
[root@osboxes ~]# export GOROOT=/usr/local/go
[root@osboxes ~]# export GOPATH=$HOME/go/app
[root@osboxes ~]# export PATH=$GOPATH/bin:$GOROOT/bin:$PATH

OS version etc...
3.10.0-693.2.2.el7.centos.plus.i686 #1 SMP Tue Sep 26 14:45:56 UTC 2017 i686 i686 i386 GNU/Linux
after installation steps i am getting error:
[root@osboxes ~]# go version
bash: /usr/local/go/bin/go: cannot execute binary file
[root@osboxes ~]# go bug
bash: /usr/local/go/bin/go: cannot execute binary file

3.10.0-693.2.2.el7.centos.plus.i686

It seems your kernel is 32bit. But you installed 64bit executable.

@mattn fail :)

@Nurlan199206 - Could you kindly clarify your response ?
Are you saying it is failing even after you installed the 32bit version ?

Closing based on https://github.com/golang/go/issues/26272#issuecomment-403289352


Installing haystack-ai and farm-haystack together can cause issues

Hey, @abaranovskis-redsamurai...
I noticed that this project uses haystack-ai and farm-haystack together.
We recently verified that this causes issues: https://github.com/deepset-ai/haystack/discussions/6684#discussioncomment-8022284
I'm writing this to let you know...
In case you want to maintain this project, you can:

only use farm-haystack (haystack 1.x) and replace PyPDFToDocument with PDFToTextConverter
migrate to haystack-ai (haystack 2.0-beta): more effort, requires a rewrite

Thanks, I will look into it.


Crash fix and Simplified Chinese support

There was a mistake made which reverted the previous commit. So I made this new pull request


Joynernacci Sequence | Python

Finding nth term in joynernacci sequence -
what will change -
Type of Issue -
Please add/delete options that are not relevant.

[x] Adding New Code

Programming Language
Please add/delete options that are not relevant.

[x] Python

Self Check

Ask for issue assignment before making Pull Request.
Add your file in the proper folder
Clean Code and Documentation for better readability
Add Title and Description of the program in the file

:star2: Star it :fork_and_knife:Fork it :handshake: Contribute to it!
Happy Coding,

Please assign this issue to me. Thanks!


9 Digit Zip Code Formatting

Is there a way to make a dash appear only when entering a zip code greater than 5 digits?  Right now I have the following regex defined for entry:
[/[1-9]/, /\d/, /\d/, /\d/, /\d/, '-', /\d/, /\d/, /\d/, /\d/]
If I only enter five digits and tab away from my input I would like for the dash to disappear.

@Coolranch I guess this is a case for a mask as a fun ction.
Take a look at the mask property:
https://github.com/text-mask/text-mask/blob/master/componentDocumentation.md#mask
There is also an addon which does similar:
https://github.com/text-mask/text-mask/blob/master/addons/src/createNumberMask.js
Best Michael

@Coolranch Did you ever find a solution for your issue?

@dhcrain , one quick and dirty solution would be to add conditional logic in your mask:
 mask={[/\d/, /\d/, /\d/, /\d/, /\d/, (values.postalCode.length > 5 ? "-" : /\d/), /\d/, /\d/, /\d/, /\d/]}

hope that helps

const mask = ((rawValue: string) => {
  if (_.trim(rawValue, '_').length > 5) {
    return [/\d/, /\d/, /\d/, /\d/, /\d/, '-', /\d/, /\d/, /\d/, /\d/];
  }
  return [/\d/, /\d/, /\d/, /\d/, /\d/];
});


Role Access - As an EAO staff with an IDIR you are granted Viewer role by default

As a person with an IDIR who works in the EAO
I want to have viewer access to EPIC.track by default
so that a white screen does not block me from accessing EPIC.track.
Acceptance Criteria
Scenario 1:
GIVEN ... you have an IDIR and work in the EAO
WHEN ... you log into EPIC.track
THEN ... you can view EPIC.track
Scenario 2:
GIVEN ... you have an IDIR and do not work in the EAO
WHEN ... you log into EPIC.track
THEN ... you are met with an error message: Sorry, you don't have permission to access this page; if you think you should have access, please contact the administrator for assistance.

Based on the latest discussion, people should not see data unless we intentionally grant them access. So setting the default role automatically doesn't work.
Till Jan, the plan is to have blank screen there and Connor or anyone with user management permission in epictrack can login to the app and go to Admin->Users , find the user and assign them appropriate role.
The long term plan is to show them a screen and let them know who to contact to get permission or send an automated email to the sytem email address to let someone know that there is an access request generated and act accordingly.


Add file size checks to shard recovery

There were instances where the shard was recovered as a zero byte file.
We do not know the root cause of this, so add a check and classify the
error so that we can monitor future occurances of this behavior.
Add unit tests for shard recovery

@electrum - I thought this was merged in. Can you take a look?

Looks good


small bug in parameters setting

Hi,
thanks for your great work! I tried and success! but I found a small bug, when change the connector_port, it seems that only change the backend service ip, while the frontend still use the default 8081 to connect a websocket. I think they should change simultaneously.

what's more, if the frontend port 8080 can be changed will be better.


Small improvement and some additional language support added

Added Romanian & French translation support. External links are now opening in a new tab.

Hi,
Thanks for your contribution. I cherry-picked the translations but I found checkboxes a little buggy and frankly unnecessary, so I'm closing this. I suggest you create a plugin if you still want to have custom-themed checkboxes and radio buttons.


[SPARK-24303][PYTHON] Update cloudpickle to v0.4.4

What changes were proposed in this pull request?
cloudpickle 0.4.4 is released - https://github.com/cloudpipe/cloudpickle/releases/tag/v0.4.4
There's no invasive change - the main difference is that we are now able to pickle the root logger, which fix is pretty isolated.
How was this patch tested?
Jenkins tests.

cc @ueshin and @BryanCutler

Test build #90709 has started for PR 21350 at commit 02f2545.

Merged build finished. Test PASSed.

Test PASSed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/testing-k8s-prb-make-spark-distribution/3280/
Test PASSed.

Test build #90709 has finished for PR 21350 at commit 02f2545.

This patch passes all tests.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test PASSed.

Test PASSed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/90709/
Test PASSed.

LGTM.

merged to master


Add Filters and Sorting for Reports on the Map

Enhance the map interface by adding filters and sorting options for reports. Users should be able to filter reports by type (e.g., potholes, garbage) or status (e.g., pending, resolved) and sort them based on proximity or date of submission.

@Shubham-Zone can you please assign it to me. I want to try this issue Thanks.


Fix documentation errors

This PR fixes errors on make html and make doctest of sphinx. It leaves some warnings caused by duplicated link target names ([1] appearing in multiple docstrings rendered in one page); they should be fixed by splitting classes into separate pages instead of fixing the docstrings themselves.

Could you apply the change of #2759 as well ?

Applied.

I fixed the errors occurred on Sphinx 1.6.1.


Set up new trusted publication workflow

Description
This PR:

Set up a new GitHub Actions workflow publish.yml to publish virtual_ecosystem to PyPI when new GitHub release is published.
This uses PyPI trusted publishing, so PyPI auth tokens need to be set up or shared.
Updates the existing test workflow in ci.yml so that it can be re-used as the first step of the the publish.yml workflow.
Adds a documentation page to the website describing the whole release process.

Fixes #405 (issue)
Type of change

[x] New feature (non-breaking change which adds functionality)
[ ] Optimization (back-end change that speeds up the code)
[ ] Bug fix (non-breaking change which fixes an issue)

Key checklist

[ ] Make sure you've run the pre-commit checks: $ pre-commit run -a
[ ] All tests pass: $ poetry run pytest

Further checks

[x] Code is commented, particularly in hard-to-understand areas
[ ] Tests added that prove fix is effective or that feature works

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

Project coverage is 94.11%.  Consider uploading reports for the commit 5db65c0 to get more accurate results

Additional details and impacted files
@@           Coverage Diff            @@
##           develop     #408   +/-   ##
========================================
  Coverage    94.11%   94.11%
========================================
  Files           68       68
  Lines         3434     3434
========================================
  Hits          3232     3232
  Misses         202      202

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


TNO-1892: Filter media type, add page, all but source filtering

Add filter media type page

just curious if there is an issue if a product doesnt have a media type associated with it, what happens?


Change Power Limit for each Port individually

I don't know if the micro inverter is supporting it... so just a question: is it possible to control the power limit individually for each port?
I need this for limiting the overall power dynamically.... so if some modules are shaded but others bring full power, I want to have the combined power of all modules set to for example to 500W. (we have 600W limit in germany at the moment)
So I'm planning a script, which reduces individual modules so that all together are limited to the global limit. So let's say if the global limit is 500W and each module have 400W peek, at the moment we can only limit each module to 250W.
But if I know, that one panel is directed to east, the other one to west, the script can set the limit for one panel to 100W because the shaded module can not deliver more anyway, so it's not a real limit. But now the script can configure the other module to 400W limit. Both limits together are not higher than the overall limit, but the module which get's sun at the moment can use it's max power and the shaded module is limited but not really influenced. The script should detect the optimum distribution of module limits itself (based on the current power values.
The script should also work by using more than one micro inverter... so we could combine 3 inverters with together 6 modules. In the future in germany we can use max 2000W peek solar power, but all solar modules together should be limited to 800W at any time. I don't know, if this automation could be added as well to your integration, but as long as we have at least the possibility to set the max for each port individually, everybody can create an automation for that.

That won't work. Internally the HMS-800 has two separate MPPTs that limit at ~430W even if there is more input power.
I have four panels with 1670Wp in sum. 835Wp per input.

Unfortunately the inverter does not supporting the power limit per port, only for the entire device.
But your use case might still be possible: it should not really matter which module produces more. By setting the power limit of the inverter you can always hard limit it to e.g. 600 W.
In case you use multiple inverters it might get a bit trickier: you would have to dynamically adjust the output power of the inverters based on the reported values.

Unfortunately the inverter does not support setting the power limit per port, only for the entire device.

Ok, with openDTU I thought it is possible to set individual limits for each string, that's why I asked... but perhaps this is a wrong understanding from my side.

But your use case might still be possible: it should not really matter which module produces more. By setting the power limit of the inverter you can always hard limit it to e.g. 600 W.

At the moment we can set the limit for a 800W inverter to 75% if we want to reach 600W limit ... so for string 1 the max 400W are limited to 300W and for string 2 the same right? So if module 1 is shaded and is generating only 50W, module 2 is still limited to 300W and both modules are creating together only 350W.  But normally 450 W are possible as well without a limit and without violating the global 600W limit... it's just an software issue, but perhaps this is  hoymiles firmware issue.

In case you use multiple inverters it might get a bit trickier: you would have to dynamically adjust the output power of the inverters based on the reported values.

Yes exactly, but if I can't set the limit individually for each string, than this is not so perfectly possible. I can implement a regulator, which increments the limits, as long as the global power is less than the threshold but I guess I have always this 30s dead time and I could violate the max value in that time, so this is not a valid way. Whtever we configure, at any time the sum of the individual limits should never exceed the global limit.
If I would be able to set the limit for each string individually, than I could split the global max value (600W) to all strings so that all together will not exceed the global maximum.
Example for 2 800W Inverter with 2 strings per inverter:
So the module 1 which is producing max 200W can be dynamical limited to 200W
Module 2 (current max 300W - dyn. limit 300W)
Module 3 (current max 50W - dyn. limit 50W)
Module 4 (current max 60W - dyn. limit 50W)
All together are still limited to 600W,  if sun/shadow is changing we can only generate less power, never more than the maximum... so we fulfill the regulations.
At the moment I can only set the limit statically for all to
600W/(2x800W) => 37,5% to limit the complete system to 600W max. ... this is max power of 150W for each string.
The overall power in my example would be 150W + 150W + 50W + 60W = 410W
So if it's really not possible to set the limit for each string individually, we could at least set the limit for inverter 1 (module 1+2) dynamically to 250W (for each string) and the limit for inverter2 to 50W:
200W + 250W + 50W + 50W = 600W
Even if the sun is changing and homeassistant dynamic regulation is crashing, it will never generate more than 600W => regulation fulfilled.

That won't work. Internally the HMS-800 has two separate MPPTs that limit at ~430W even if there is more input power.
I have four panels with 1670Wp in sum. 800Wp + 870Wp at input 1 / 2.

You connect 2 modules in parallel right? Do you have some problems with this setup, because you have always one module which is generating full power and another one idle in parallel.
My idea was to have 2 inverters with 4 individual strings and limiting to 600/800W by SW.

Only with bigger inverters you need to set the limit once. The HMS-1600 has four MPPT with a max output of ~430W each. So it doesn't matter which panel has sun or not. The combined output will never be more than 800W (if configured) and one single output never > ~430W

My understanding of the limit is, that it is not  limiting the overall inverter power. It's always limiting the individual string. So if 2 strings of an HMS-1600 have max power, they are still limited, independent on the generated power of string 3 and 4.

At the moment we can set the limit for a 800W inverter to 75% if we want to reach 600W limit ... so for string 1 the max 400W are limited to 300W and for string 2 the same right?

No. You limit the output to 600W. The input could be 400W + 200W nevertheless.

You connect 2 modules in parallel right? Do you have some problems with this setup, because you have always one module which is generating full power and another one idle in parallel.

No problems as long as you use exactly the same modules in parallel. I use south + easy and east + west direction.

My understanding of the limit is, that it is not limiting the overall inverter power. It's always limiting the individual string.
Your understanding seems to be wrong. ;)


Fix docker-compose build errors

Hi! Thank you for a useful tool 😆
I've got 2 errors when I execute docker-compose build command.
So I've added a test to CI for checking that the build always succeeds, and fixed those errors.

matplotlib installation error

You can check the error message at https://travis-ci.com/blooper05/cloudmapper/builds/76671423#L691-L787
Fixed by adding a dependent package. (https://github.com/duo-labs/cloudmapper/commit/4a09e0cb176fe9a88edefef8bb8355b42cfba429)

pandas installation error

You can check the error message at https://travis-ci.com/blooper05/cloudmapper/builds/76676190#L695-L735
It seems a known issue of pandas https://github.com/pandas-dev/pandas/issues/20775 .
Fixed by adding an environment variable according to the above URL. (https://github.com/duo-labs/cloudmapper/commit/983bc4813703d7a98910e8536c2de6a30dea8cb5)

Please check my changes and merge them if you can. Thanks!

Since I did one of original Docker PR I may pick this up again next month.
Maybe.


Error running flutter application

Error:
E/flutter ( 8774): [ERROR:flutter/shell/common/shell.cc(209)] Dart Error: error: import of dart:mirrors is not supported in the current Dart runtime
E/flutter ( 8774): [ERROR:flutter/runtime/dart_isolate.cc(141)] Could not prepare isolate.
E/flutter ( 8774): [ERROR:flutter/runtime/runtime_controller.cc(377)] Could not create root isolate.
E/flutter ( 8774): [ERROR:flutter/shell/common/shell.cc(492)] Could not launch engine with configuration.

Main:
Future<void> main() async {
  MySQL db = MySQL(
    host: "localhost",
    user: "root",
    password: "123",
    db: "test",
  );
  await db.init();
  runApp(MyApp());
}

table:
//The table Annotation indicates to be a table in mysql
//NOTE: You can add a different class name to your table
//@Table (name: 'table_user')

import 'package:orm_mysql/orm_mysql.dart';

@Table()
class banner_images {
  // the tables must have an id, this is the indication of the mysql primary key
  // NOTE: By default the id is auto increment.
  // to change this do: @Id (autoIncrement: false)
  @Id()
  int banner_id;

  // this annotation indicates that this column cannot be null in your database
  @NotNull()
  String banner_imbanner_type_idurl;

  int banner_type_id;

  int banner_dest_id;

  banner_images(
      {this.banner_id,
      this.banner_imbanner_type_idurl,
      this.banner_type_id,
      this.banner_dest_id});

// it is necessary to have a fromJson constructor for the orm to work
  banner_images.fromJson(Map<String, dynamic> json) {
    banner_id = json['banner_id'];
    banner_imbanner_type_idurl = json['banner_imbanner_type_idurl'];
    banner_type_id = json['banner_type_id'];
    banner_dest_id = json['banner_dest_id'];
  }

// it is necessary to have a toJson function for the orm to work
  Map<String, dynamic> toJson() {
    final Map<String, dynamic> data = Map<String, dynamic>();
    data['banner_id'] = this.banner_id;
    data['banner_imbanner_type_idurl'] = this.banner_imbanner_type_idurl;
    data['banner_type_id'] = this.banner_type_id;
    data['banner_dest_id'] = this.banner_dest_id;
    return data;
  }
}

Object:
banner_imagesRepository x = banner_imagesRepository();
Test:
x.findAll().then((value) => print(value.map((e) => e.toJson())));

the library use dart: mirrors not compatible with the flutter

the library use dart: mirrors not compatible with the flutter

What about making it for flutter

I'm planning. But I will have to use a code generator.

I'm planning. But I will have to use a code generator.

That is right
You can merge with Sqfentity package
It is very nice sqflite with good generator

https://github.com/CpdnCristiano/mysql_simple_orm

I have this version, without dart mirrors.
Notes, do not use datetime, or fkcolumn

https://github.com/CpdnCristiano/mysql_simple_orm

Thanks.
Is it compatible with flutter web

Stable: boolean, vachar, int

Stable: boolean, vachar, int

This for web?

Aha, It is based on mysql1 which isn't compatible with web.
Anyway, Thanks for your effort.
It is a very nice mysql orm package.


[SPARK-49138][SQL] Fix CollationTypeCasts of several expressions

What changes were proposed in this pull request?
Fix for CreateMap and ArrayAppend expressions.
Why are the changes needed?
While adding TypeCoercion for collations these two expressions were missed out, so this PR adds them to the rules so that they follow expected behaviour.
Does this PR introduce any user-facing change?
No.
How was this patch tested?
Added testcases in CollationSuite.
Was this patch authored or co-authored using generative AI tooling?
No.

@uros-db please take a look

@cloud-fan ready for review/merge

thanks, merging to master!


0.2.2: missing files in pypi sdist tarball: unable to run tests

Hi! I'm currently bringing python-dbus-next to the official Arch Linux repositories.
As best practice we usually run tests against the packages (if there are any). Unfortunately this fails due to missing files, when using the sdist tarball on pypi:
============================= test session starts ==============================
platform linux -- Python 3.9.6, pytest-6.2.4, py-1.10.0, pluggy-0.13.1 -- /usr/bin/python
cachedir: .pytest_cache
rootdir: /build/python-dbus-next/src/python-dbus-next-0.2.2, configfile: pytest.ini
plugins: timeout-1.4.2, asyncio-0.15.1
timeout: 5.0s
timeout method: signal
timeout func_only: False
collecting ... collected 74 items / 2 errors / 72 selected

==================================== ERRORS ====================================
_________________ ERROR collecting test/test_introspection.py __________________
test/test_introspection.py:5: in <module>
    example_data = open(f'{os.path.dirname(__file__)}/data/introspection.xml', 'r').read()
E   FileNotFoundError: [Errno 2] No such file or directory: '/build/python-dbus-next/src/python-dbus-next-0.2.2/test/data/introspection.xml'
___________________ ERROR collecting test/test_marshaller.py ___________________
test/test_marshaller.py:20: in <module>
    table = json.load(open(os.path.dirname(__file__) + '/data/messages.json'))
E   FileNotFoundError: [Errno 2] No such file or directory: '/build/python-dbus-next/src/python-dbus-next-0.2.2/test/data/messages.json'
=========================== short test summary info ============================
ERROR test/test_introspection.py - FileNotFoundError: [Errno 2] No such file ...
ERROR test/test_marshaller.py - FileNotFoundError: [Errno 2] No such file or ...
!!!!!!!!!!!!!!!!!!! Interrupted: 2 errors during collection !!!!!!!!!!!!!!!!!!!!
============================== 2 errors in 0.30s ===============================

Hi,
Thanks so much for packaging. Running tests are only supported in the provided docker container because they interact with a real dbus daemon. https://github.com/altdesktop/python-dbus-next/blob/7d651b62792e5688e6ef8c9c25770fbe291eb219/Makefile#L22-L24

I can run the tests using dbus-run-session -- pytest -v.
Unfortunately in 0.2.3 the sdist tarball on pypi is still missing some files:
==================================== ERRORS ====================================
_________________ ERROR collecting test/test_introspection.py __________________
test/test_introspection.py:5: in <module>
    example_data = open(f'{os.path.dirname(__file__)}/data/introspection.xml', 'r').read()
E   FileNotFoundError: [Errno 2] No such file or directory: '/build/python-dbus-next/src/python-dbus-next-0.2.3/test/data/introspection.xml'
___________________ ERROR collecting test/test_marshaller.py ___________________
test/test_marshaller.py:20: in <module>
    table = json.load(open(os.path.dirname(__file__) + '/data/messages.json'))
E   FileNotFoundError: [Errno 2] No such file or directory: '/build/python-dbus-next/src/python-dbus-next-0.2.3/test/data/messages.json'
=========================== short test summary info ============================
ERROR test/test_introspection.py - FileNotFoundError: [Errno 2] No such file ...
ERROR test/test_marshaller.py - FileNotFoundError: [Errno 2] No such file or ...
!!!!!!!!!!!!!!!!!!! Interrupted: 2 errors during collection !!!!!!!!!!!!!!!!!!!!
============================== 2 errors in 0.31s ===============================

Just hit this. In my case, I'm packaging dbus_next for Gentoo Linux at my third-party overlay. We prefer to locally run tests on installation for obvious reasons, because tests passing == package working. usually. crossing fingers here.
Sadly, local test execution doesn't appear to be supported. We're reluctantly disabling tests for dbus_next – but not particularly happy about that.
Perhaps the requisite files could simply be bundled with release tarballs as @dvzrv suggests? It's usually best to just let the users sort it out. :man_shrugging:

If you would like to make that change, you can go ahead. However, keep in mind that these are integration tests and may make assumptions about dbus configuration that may not be true on your system. You may use dbus-run-session to run the tests but this may not be compatible with future changes to the test suite that may be made such as system bus interactions, alternative transports, or testing of a daemon with an alternative configuration. You should decide which tests you need to skip based on your application. I will merge changes to some tests that make it possible to run with dbus-run-session when it's not intrusive, but I won't merge changes into the tests for compatibility between systems or bus implementations.

Affirmative. Would it also be feasible to gracefully @pytest.mark.skipif(..., reason='Non-portable dbus test.') the relevant integration tests away, in that case? Tests that can only reliably run within a unique non-portable environment (e.g., a particular Docker container running a particular dbus configuration) should ideally just be skipped with an informative message rather than fatally halting the entire test suite.
Just my :coin: :coin: as a friendly package maintainer, of course.

You should decide which tests you need to skip based on your application.

B-b-but... I'm packaging for Gentoo Linux. There is no specific "application" as such.
The intended userbase is literally all users running Gentoo Linux. The intended use case is dbus_next installed as a system-wide Python package for use by other downstream reverse dependencies also installed as system-wide Python packages (e.g., bleak).
Again, the test suite itself should gracefully scale by selectively ignoring unit and integration tests that are inapplicable to the current execution environment. Thankfully, @pytest.mark.skip makes that trivial – assuming it's trivial for your test suite to detect whether it's running in your Docker container, of course. That should be trivial. That's usually just a lookup of a unique environment variable exported by your Docker container.
Annnnnyway. I've marked our Gentoo ebuild for dbus_next as RESTRICT=test for now, meaning that tests are known to fail and should be ignored. I'm fine with that. It is what it is. :man_shrugging:

On Arch Linux we have now started to discourage the use of PyPI hosted sdist tarballs (https://rfc.archlinux.page/0020-sources-for-python-packaging/).


feature: support multiple errors in compiler schema validation

This is in relation to an Issue I raised here: https://github.com/santhosh-tekuri/jsonschema/issues/116
This code style was taken from https://github.com/santhosh-tekuri/jsonschema/blob/7c04a73909949a11eeaed5dd06e0303fc49e47b5/schema.go#L738-L745
I wasn't sure what Location values would be good to set here or a better message, but showcases what is possible.
The output of Example 3 shown in the issue linked above with this fork is:
jsonschema file:///home/hayden/projects/golang-playground/schema3.json compilation failed
[I#] [S#] Multiple schema errors occurred
  [I#] [S#] doesn't validate with file:///home/hayden/projects/golang-playground/extension_meta.json#
    [I#] [S#/required] missing properties: 'foo'
    [I#/foobar] [S#/properties/foobar/minLength] length must be >= 3, but got 1
  [I#] [S#] doesn't validate with file:///home/hayden/projects/golang-playground/extension_meta_2.json#
    [I#] [S#/required] missing properties: 'bar'

this was intentional. ValidationError by design represents errors from validating by single schema.
here you are combining ValidationErrors from each meta schema another another ValidationSchema. This looks fine.
but ValidationError's output formats like basic, detailed won't make sense in such case if you combine it from multiple schemas.
if extensions were implemented as jsonschema vocabularies, then what you are suggesting will become implicit;

in other words, there is a tight relationship the tree structure of validationError with output formats. you cannot arbitrary nest them;
may be we can create new error type, called MetaValidationError which collects all errors. since most use cases will not use custom schemas, it is left to not to short circuit, for ease of error api;


nixos/doc: avoid bash argument list size limit

Description of changes
see #277861. as the module list grows the argument size in the lazy-options nix call grows, eventually reaching a hard limit and causing the build to fail. writing the list to a file instead and import it instead of providing it directly circumvents this.
Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

For non-Linux: Is sandboxing enabled in nix.conf? (See Nix manual)

[ ] sandbox = relaxed
[ ] sandbox = true

[x] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
24.05 Release Notes (or backporting 23.05 and 23.11 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[x] Fits CONTRIBUTING.md.

Add a :+1: reaction to pull requests you find important.

I saw some interesting path issues here:
error: getting status of '/nix/store/invgr43j5mgqpvkc72iddamjagirqgr0-nixos/modules/nix/store/5mgg6b53r261gf32c4gx3b5a0j2475al-source/nixos/modules/config/appstream.nix': No such file or directory

It seems like the modulePath is different from the path of docModules so the prefix is not removed. I am using flake+colmena so it might be some from toolchain while I am not sure exactly sure how documentation.nix works and do further debug, thus leaving a note here.


Document Recovery etcd with permanent failures

https://blog.containership.io/etcd/
https://github.com/etcd-io/etcd/blob/master/Documentation/op-guide/recovery.md

#121


script: inject launch files into container

@HiroIshida
Why did you stop supporting docker run ? Running the container outside of the detic_ros directory was very convenient.

You can still run the container outside from the docker, although you need to catkin build this package
rosrun detic_ros run_container.py
This PR makes it easy to inject launch files into the container by specifying  mounting directly

Ah, I see. So it also can be built as a catkin package. Thank you for your
info.
2024年8月20日(火) 9:34 Hirokazu Ishida @.***>:

@mqcmd196 https://github.com/mqcmd196
You can still run the container outside from the docker, although you need
to catkin build this package
rosrun detic_ros run_container.py
This PR makes it easy to inject launch files into the container by
specifying mounting directly
—
Reply to this email directly, view it on GitHub
https://github.com/HiroIshida/detic_ros/pull/45#issuecomment-2297749095,
or unsubscribe
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You are receiving this because you were mentioned.Message ID:
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Sometimes persisted buffers are lost

noticing this when transitioning multiple times, an error occurs about lines and we lose all of our persisted buffers

This happens when you open a workspace you are already in for some reason.

All the buffers become empty when saved, and then are not hydrated because they don't exist...

This was a race condition caused by not closing the buffer file written to, fixed via ffaa024


Wrong trevis settings (default has changed)

Issue
Previous default virtualization environment for travis was the 'SUDO-ENABLED' (the required one to run the tests) but now is the 'CONTAINER-BASED' and test will not work on forks.
Source:
First row of the table on
https://docs.travis-ci.com/user/ci-environment/#Virtualization-environments
Steps to Reproduce
Fork the repository and enable travis on the fork.
Expected result
Travis should work out of the box and tests that runs on the original branch should work also on the forked one.
Current result
Test fails because are killed by Travis due to 'Tests running in parallel using too many processes or threads (e.g. using the parallel_test gem)'
Source:
https://docs.travis-ci.com/user/common-build-problems/#My-build-script-is-killed-without-any-error
Possible Fix
Explicitly specify the virtualization environment on the .travis.yml file. Pull request will follow.

Closing this in favor of #740.


Migrate crypto tests from JUnit 4.0 to JUnit 5.0

This PR should resolve #5568

hey @7suyash7 did you mean to close this PR?


Add list of default relays and config to enable them

📝 Summary
Closes #305
💡 Motivation and Context

✅ I have completed the following steps:

[ ] Run make lint
[ ] Run make test
[ ] Added tests (if applicable)

There is still something missing here because I cannot merge with the default config.


fetchText no longer works

I have a test that was passing just fine and now it doesn't.  There is indeed the text on the page I'm testing for but for some reason my fetchText is no longer working.  I've included both my tests and gulpfile.
gulpfile.js
"use strict";

var app = require('./server'),
    gulp = require('gulp'),
    shell = require('gulp-shell'),
    wait = require('gulp-wait'),
    watchify = require('watchify'),
    mocha = require('gulp-mocha'),
    runSequence = require('run-sequence'),
    browserify = require('browserify'),
    source = require('vinyl-source-stream'),
    gutil = require('gulp-util'),
    del = require('del'),
    babelify = require('babelify');

var scriptsCount = 0;

var config = {
    port: 3000,
    watch: {
        src: './src/*.js',
    },
    build: {
        bundle: {
            destination: './build/app/js'
        }
    },
    app: {
        path: './src/components/app.js'
    },
    test:{
        root: 'test/**',
        src: {
            unit:'test/unit/**/*-test.js',
            acceptance: 'test/features/specs/*-spec.js'
        },
        mocha: {
            reporter: 'spec'
        }
    }
};

gulp.task('default', function (done){
    runSequence('clean:build','bundleApp','watch','startApp','tests-acceptance', done)
});

gulp.task('clean:build', function () {
    return del(['./build/app/js/*.js'])
});

gulp.task('watch', function () {
    gulp.watch([config.watch.src]);
});

gulp.task('startApp', function () {
    var server = app.listen(config.port, function(){
        console.log('Ready on port %d', server.address().port);
    }).on('error', function(err) {
        console.log(err);
    });
});

gulp.task('bundleApp', function () {
    return bundleApp();
});

function bundleApp() {
    scriptsCount++;

    var appBundler = browserify({
        cache: {},
        packageCache: {},
        plugin: [watchify],
        entries: config.app.path,
        debug: true
    });

    return appBundler
        .transform("babelify", {presets: ["es2015", "react"]})
        .bundle()
        .on('error', gutil.log)
        .pipe(source('bundle.js'))
        .pipe(gulp.dest(config.build.bundle.destination))
}

gulp.task('tests-acceptance', function() {
    process.env.PORT = 8000;
    return gulp.src(config.test.src.acceptance, { read: false })
        .pipe(shell(['mocha-casperjs ' + config.test.src.acceptance]))
});

my-spec.js
"use strict";

var page = null;

describe('Feature: View List of Companies', function() {
    before(function () {
        casper.start('http://localhost:3000');
        page = this;
    });

    it('When I go to the main landing page', function () {
        casper.then(function () {
            expect(page).to.be.a('object');
        });
    });

    describe('Scenario 1: No Companies are Listed', function () {
        it('should see that no companies are listed', function () {
            casper.then(function () {
                expect(this.fetchText('h3')).to.equal('No Companies Found');
            });
        });
    });

    casper.run(function() {
        exitPhantomJS();
    });
});

function exitPhantomJS(){
    this.exit();
}

this fails and I can't figure out why expect(this.fetchText('h3')).to.equal('No Companies Found');

Again this test was passing fine in the past, so I don't know what changed on either my end or the casperjs end to cause it to just stop passing all of a sudden.

@dschinkel What does your package.json look like?

ahhhhhh!!!!  the problem is that it's no longer an .  I rendered a react component so it's really rendered as

@dschinkel So, you have it working now?

Yes.  Just gotta figure out how I'm gonna handle testing react components with this but yea.

If you have any insights to share upon figuring it out, please let us know and we can look at adding your learnings to the docs to help others.

will do, thanks!

@dschinkel The best bet is to use a selector that is specific enough to catch your element but not too specific to allow for some variation. Searching for text should be used as a "last-resort" only. Always prefer waitForSelector, waitUntilVisible and then use the functions that work on selectors to test for content over using fetchText. The latter has its problems and selecting elements by DOM tree is rock-solid. You may use either CSS or XPath selectors.
My rule of thumb here is:

use long path segments for the selectors, e.g. #content .foo .bar .baz h3 (if you know that your IDs never change, use the closest / innermost ID to start with)
do not overspecify the classes for the nodes in question, i.e. do not select #content.wrapper .foo.center.black .bar.float.whatnot h3.my.fancy.subheading

ok thanks a lot istr!  wasn't aware that I was kinda going the wrong route on the casper API

it's still problematic.  Because react throws in other ids in other types of DOM elements such as .  For example, my test still fails because it can't see the in this situation because the div it's contained in contains a **data-reactroot ** No Companies Found

Would something like waitForSelectorTextChange help?
casper.waitForSelectorTextChange('#companyList h3', function() { /** assertions */ });

So in this case, would it make sense to do something like waitForSelector('h3') right?

No, this is not specific enough. The real id attributes are the key here. They are unique and probably won't change dynamically. @BIGjuevos pointed out a selector that has a good chance to work.

you left me with a good point.  I haven't really needed to apply selectors like ids in my code yet.  Maybe once I start to use a little more CSS I might have something better and more specific to work off of but right now I haven't had a need to start using ids, as my app is just starting and is very infant right now...

so thinking something like this:
        it('should see that no companies are listed', function () {
            casper.waitForSelector('#companyList', then(function () {
                expect(.to.equal('No Companies Found');
            });
        });

assuming now I'm presenting the id in the div there.  Not sure how to assert it while inside the waitfor though

Check this out
I still can't move forward with Casper.
Here is my latest test, just testing out the waitForSelector:
describe('Scenario 1: No Companies are Listed', function () {
    it('should see that no companies are listed', function () {
        casper.waitForSelector('#companyList', function () {});
    });
});

watch this: https://drive.google.com/file/d/0B6FDE5kMwYTleVFRM1M5dWRDaEk/view?usp=sharing

Please try to study the examples / documentation and browse for some basic use cases / code snippets. What you're asking for is a primer how to use CasperJS. The github issues are not the right place to ask for.

You know what would help?  Getting rid of the black background on the Casper site :).

If you would have watched the video, it's talking about the issue in this thread still, not my example asking about how to select inside the waitForSelector.  Please watch it.

You know what would help? Getting rid of the black background on the Casper site :).

Maybe... This is a heritage. But no excuse to avoid reading the docs and/or to search for examples before filing a bug here.

There's still a problem with Casper reading DOM when react attributes are in DOM elements

No. There is a problem in your application (duplicate ID). Your screencast exposes this. See attached screenshot.

It would be nice if you could respect that the github page is meant for contributions to CasperJS, not for helping out actually using it. Thanks for understanding.

My fault bad example.  There are still problems with casper even when that's not there but whatever...

You know what would help? Getting rid of the black background on the Casper site :)

Please, you can download the docs as PDF too, you make me feel down :( https://media.readthedocs.org/pdf/casperjs/1.1.0/casperjs.pdf

does that make you feel even better :)

does that make you feel even better

No. Some reading of netiquette is highly advised. Please respect other people's time. I am locking this conversation now.

In response to a PM I am unlocking this again.
@dschinkel You pointed out that you think that there "there is still a problem with Casper not being able to read elements with non-native dom attributes in them".
If so, please

create a minimal working test that isolates this issue only
check that this is not a problem with the engine (PhantomJS), i.e. verify that your example works when used directly with PhantomJS and without CasperJS
if it is not a problem with PhantomJS and it turns out to be a real issue with CasperJS, post your minimal working test case that demonstrates the problem in a separate issue with a title that clearly depicts the problem, e.g "Unable to select DOM nodes by ID that contain non-native attributes"
clearly state the affected CasperJS and PhantomJS version you tested, as well as the platform used to run the failing example on

If you do it like this, everybody else could reproduce / verify your issue very quickly. And your posted failing example is the first step to a test case that will be part of a PR that could fix the problem.
This would help us to improve on CasperJS. Posting random large code snippets / specs / test cases without posting the code it tests, screencasts, and sarcastic comments like "does that make you feel even better" do not help at all. Thanks for your understanding.

I've opened a new issue, with code.  "check that this is not a problem with the engine (PhantomJS), i.e. verify that your example works when used directly with PhantomJS and without CasperJS".  I'm using node, so unfortunately that's not possible.

I'm using node, so unfortunately that's not possible.

It is possible, but some additional work, of course. The point is that we do not accept that you offload this additional work to us by means of filing issues against CasperJS without reflection or without having verified that the problem is with CasperJS and not with your specific test environment and/or application.
Provided that you are willing to do that additional work on your own and provided that you look into and follow some of the examples how this works (start with browsing through closed PRs and issues that provide a minimal, isolated test) I will try to guide you to the process in that other issue. The core of TDD is to be able to track down problems to single, isolated issues, so other people can easily replicate / verify and eventually fix them.

What pisses me off is this "The point is that we do not accept that you offload this additional work to us by means of filing issues against CasperJS without reflection or without having verified that the problem is with CasperJS and not with your specific test environment and/or application"
I spend 8 hours yesterday on this doing EXACTLY what you inferred I haven't done.    Are you saying I haven't?  Do you live with me?     YMMV. Sorry to see you disappointed, but I can't help it.

Locking this conversation.


Make dev.py push work with local changes by stashing.

Hey @bakert,
Your changes look good to me!
View build log
TravisBuddy Request Identifier: cf6c3fb0-0489-11ea-b305-a56282dbf54c


Unable to activate acme-client-2.0.5, because faraday-1.4.3 conflicts with faraday (~> 0.9, >= 0.9.1)

Gem::ConflictError
Unable to activate acme-client-2.0.5, because faraday-1.4.3 conflicts with faraday (~> 0.9, >= 0.9.1)
Cookbook Trace: (most recent call first)
/var/chef/cache/cookbooks/acme/recipes/default.rb:27:in `from_file'
/var/chef/cache/cookbooks/smart-webserver/recipes/default.rb:18:in `from_file'

Relevant File Content:
/var/chef/cache/cookbooks/acme/recipes/default.rb:
20:
21:  chef_gem 'acme-client' do
22:    action :install
23:    version node['acme']['gem_version']
24:    compile_time true if respond_to?(:compile_time)
25:  end
26:
27>> require 'acme-client'
28:
System Info:
chef_version=17.6.15
platform=ubuntu
platform_version=18.04
ruby=ruby 3.0.2p107 (2021-07-07 revision 0db68f0233) [x86_64-linux]
program_name=/usr/bin/chef-client
executable=/opt/chef/bin/chef-client
I also tried a newer version of chef-client and the issue still seems to exist. Does anyone know how far back I need to go with chef-client where this isn't an issue?

Solved the issue. I went to https://rubygems.org/gems/acme-client/versions and looked through the versions to find the faraday dependency that matched what came with chef-workstation using chef gem list faraday. Once you have that, set your version in the gem file or as I did, in the metadata.rb
gem 'acme-client', '= version'


Add PPP

Codecov Report
Base: 72.15% // Head: 72.15% // No change to project coverage :thumbsup:

Coverage data is based on head (3b116f7) compared to base (4fa7ead).
Patch has no changes to coverable lines.

Additional details and impacted files
@@            Coverage Diff            @@
##             master      #27   +/-   ##
=========================================
  Coverage     72.15%   72.15%
  Complexity      399      399
=========================================
  Files            70       70
  Lines          1232     1232
  Branches        125      125
=========================================
  Hits            889      889
  Misses          311      311
  Partials         32       32

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

:umbrella: View full report at Codecov.
:loudspeaker: Do you have feedback about the report comment? Let us know in this issue.


iOS: allow hybrid app tests to match both native and RN views by accessibility label

Description
This is an enhancement request.
When testing a hybrid app which has both native and RN screens, Detox only matches RN views. It seems to be impossible to test native screens in such app with current Detox implementation. Please consider adding ability to match views of both kinds in that case.
We managed to solve this problem by combining native and RN matchers in detox_matcherForAccessibilityLabel with grey_anyOf. If you think that this is a viable fix, I'd be happy to submit a PR.

Could you create a small project where Detox fails for native parts? This sounds like a bug, not enhancement request. Thanks


docs:  Reorganize the entirety of the docs and implement standards

What could be improved

The docs currently suffer from clear versions of additions.  Meaning, as they are today, you can tell which parts where added after each version and by different people.  The writing styles vary, file names vary, directory structure varies, etc.  Additionally, the toctrees vary across files and it causes a very weird caching issue with repeat builds.
Why should this be improved

For the docs to grow and provide consistency, an agreed upon manner should be decided to provide a clear structure of documentation.  Google references the Kubernetes style guide as one of the best out there: https://kubernetes.io/docs/contribute/style/style-guide/.  While I don't think we need to go that far with spelling out every possible contribution, providing clearer guidance (there is some already) as well as applying that guidance to all existing files will benefit the documents for all new comers.
Any risks?

None.
More information

While I have been working on this and do have a branch ready to go, I am holding off on submitting a PR until everyone submits their hacktoberfest submissions.  Having said that, it may also benefit contributors if we implement this now, so there is a standard for their submissions especially for the bridge packages.
In my branch, I use the Grammarly extension and it already identified numerous files with spelling errors and basic grammar errors that have been missed and not identified in other issues.  So recommending that be a start for contributors as well.

Note: the "weird thing" with TOC caching is that if you update TOC in one file those changes won't be visible in every other file after a make build. I believe it's an intended behavior, not a bug, since it minimizes the rebuild time when prototyping.
In order to get all files updated, run make clean -- it will force rebuilding of all files.

So the weird caching thing I was referencing was actual how a few toctrees were rst and not myst.  They worked, but viewing the file would sometimes go crazy between refreshes and you would get warnings about missing files.  Once I converted them all to myst markdown, it disappeared.  It very well could be what you reference as well.  Either way, I felt that making them all the same through out the docs was the right approach.

make html should still work, as long as you're in the doc/_sphinx directory. But the equivalent of make clean would be melos doc-clean.

I guess I meant if you have not ran melos bootstrap (which I have now added to the docs for building the docs) first, when you run make html it throws errors as documented here: https://github.com/flame-engine/flame/issues/1950.  Is there any benefit and should we document which is preferred (after melos setup), make html or melos doc-build?

Either one works. The melos doc-build command has the advantage that you can run it from any directory in the flame repo. The make html can only be run from doc/_sphinx, but then its output is colorized, and wherever it prints %-progress statuses, those get overwritten correctly instead of spanning multiple lines. So, whatever you find more convenient.
Regarding the CONTRIBUTING.md -- I wonder if it might be a good idea to mirror it in the docs/development section. It could be just a simple include directive.

Absolutely can do on the including the contributing.md.  It is a bit lengthy and not all required for docs where in that section it was how to setup the local environment for building the docs, BUT because of the live examples, if you aren't running melos, then the builds fail and you get 404's and such, so it definitely is a requirement.
Having said that, because it is outside the doc directory, I don't know if it will be included in the build.  Currently, I have it with a relative link, but that fails because it never gets generated.  It might have to be a url OR I think there is a way in conf to include that specific file by using include_patterns?

It works fine (at least for the local builds). For docs-site build needs to be verified (and perhaps the publish script adjusted).

Well this is the warning that I get WARNING: 'myst' reference target not found: ../../CONTRIBUTING.md#environment-setup .  Can you not do relative links  in this method?  The linter and auto-complete shows everything correctly.

No, I don't think you could make a link like that.
I was suggesting rather to include the contributing file like
```{include} ../CONTRIBUTING.md
```

so that it becomes a proper file inside the doc-site, but the content of that file is fetched from an outside source.

Ok, I knew the include but I hadn't tried it because its so large.  I will play with that a bit more.

So I also want to bring to here some options that I had been discussing with Spydon in Discord.

I created a grouping called Bridge Packages but in the Flame readme, its referenced as Bridge Libraries.

What is the preference?

Flame Oxygen is listed under Other Modules in the docs currently, but is listed under Bridge Libraries in the readme.

Should it be with bridge_packages(libraries) in the docs or should the readme be updated?

How do you feel about flame_splash_screen?

Is it a bridge_package or Other Module?

As mentioned here: https://github.com/flame-engine/flame/issues/2046 Do you want me to move spaceshooter under tutorials proper?

As mentioned here: https://github.com/flame-engine/flame/issues/2046 Do you want me to move spaceshooter under tutorials proper?

That is up to @erickzanardo, personally I think it would be good so that all tutorials are gathered on the same place.

Edit: Also while going through, I see that the bare flame game tutorial references the old version.  I believe we should use --VERSION-- for this as well, right? https://docs.flame-engine.org/1.4.0/tutorials/bare_flame_game.html

Yeah, that sounds good.


Food Item Classification

Title and Issue number
[GSSoC'23] Food Item Classification using Machine Learning #1615
[GSSoC'23] Flipkart Clone #1643
Screenshot Link -
Food Item Classification - https://drive.google.com/file/d/1kBfj3TAiJOl8nSW_M32rrnA_Lhls7DW2/view?usp=sharing
Flipkart Clone -
Link 1 - https://drive.google.com/file/d/1dylERK-SGwM9OdKieyMxAs9WMDymKH6X/view?usp=sharing
Link 2 - https://drive.google.com/file/d/1qNQSnyaE4O1uL1riemqABOYU29xkle2_/view?usp=sharing
Close #1615
Close #1643
Checklist (for both issues):

[X] I have mentioned the issue number in my Pull Request.
[X] I have commented my code, particularly in hard-to-understand areas
[X] I have created a helpful and easy to understand README.md

Create two different PRs, each one mapped to one issue at a time

@Shreyg-27 Create two different PRs, each one mapped to one issue at a time

@Shreyg-27 Create two different PRs, each one mapped to one issue at a time

Sure, I will do that.