Direct kernel connection broken when using GPU for tensorflow

Environment data

VS Code version: 1.55.2
Jupyter Extension version (available under the Extensions sidebar): 2021.5.745244803
Python Extension version (available under the Extensions sidebar): 2021.3.680753044
OS (Windows | Mac | Linux distro) and version: Windows 10 Pro 10.0.19042 Build 19042
Python and/or Anaconda version: 3.8.5 64-bit (conda)
Type of virtual environment used: N/A
Jupyter server running: Local

GPU and Tensorflow
GPU-----------------------------
Name: NVIDIA GeForce RTX 3080
Driver: <IP_ADDRESS>11
CUDA version: 11.0
CDNN version: 8.0.4
Tensorflow-----------------------
tensorflow-gpu v. 2.5.0rc1
Expected behaviour
Fitting the model should produce an output like:
Epoch 1/5
328/328 [==============================] - 1188s 4s/step - loss: 7.7233 - accuracy: 0.2909 - val_loss: 0.6931 - val_accuracy: 0.5000
Epoch 2/5
328/328 [==============================] - 1156s 4s/step - loss: 2.8059 - accuracy: 0.6556 - val_loss: 0.6932 - val_accuracy: 0.5000
Epoch 3/5
328/328 [==============================] - 1155s 4s/step - loss: 3.8943 - accuracy: 0.7137 - val_loss: 0.6804 - val_accuracy: 0.5625
Epoch 4/5
328/328 [==============================] - 1152s 4s/step - loss: 1.3005 - accuracy: 0.7359 - val_loss: 0.7149 - val_accuracy: 0.3750
Epoch 5/5
328/328 [==============================] - 1303s 4s/step - loss: 1.1984 - accuracy: 0.7431 - val_loss: 0.7768 - val_accuracy: 0.5625
Actual behaviour
Fitting the model using my GPU in tensorflow causes the direct kernel connection to break. Before this, I was running the models just fine only using the CPU.
Steps to reproduce:
I can provide details/a copy of my notebook if necessary.

Logs
I can trim up the logs as necessary - for now, I put the entire log as it was output after clearing the logs and only running the problematic cell.

Info 2021-04-17 14:38:03: Executing cell NotebookImport#105
Info 2021-04-17 14:38:03: Submitting code for 3be15650-12d7-495f-aa70-231a5d4073cc
Info 2021-04-17 14:38:03: UpdateWorkingDirectoryAndPath
Info 2021-04-17 14:38:03: Preferred kernel for file:///g%3A/My%20Drive/Colab%20Notebooks/teaching/gwu/machine_learning_I/spring_2021/project/pneumonia.ipynb is undefined
Info 2021-04-17 14:38:03: Kernel switching to busy
Info 2021-04-17 14:38:03: Preferred kernel for file:///g%3A/My%20Drive/Colab%20Notebooks/teaching/gwu/machine_learning_I/spring_2021/project/pneumonia.ipynb is undefined
Info 2021-04-17 14:38:03: Preferred kernel for file:///g%3A/My%20Drive/Colab%20Notebooks/teaching/gwu/machine_learning_I/spring_2021/project/pneumonia.ipynb is undefined
Info 2021-04-17 14:38:05: KernelProcess output: Content-Length: 256
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","method":"log","params":{"level":"INFO","msg":"write to stderr: 2021-04-17 14:38:05.431710: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)\n","pid":15564}}Content-Length: 233
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","method":"output","params":{"source":"stderr","out":"2021-04-17 14:38:05.431710: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)\n"}}
Info 2021-04-17 14:38:05: Python Daemon (pid: 15564): write to stderr: 2021-04-17 14:38:05.431710: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
Warn 2021-04-17 14:38:05: Kernel 15564 as possibly died, StdErr from Kernel Process 2021-04-17 14:38:05.431710: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
Warn 2021-04-17 14:38:05: StdErr from Kernel Process 2021-04-17 14:38:05.431710: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
Info 2021-04-17 14:38:05: Preferred kernel for file:///g%3A/My%20Drive/Colab%20Notebooks/teaching/gwu/machine_learning_I/spring_2021/project/pneumonia.ipynb is undefined
Info 2021-04-17 14:38:09: KernelProcess output: Content-Length: 245
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","method":"log","params":{"level":"INFO","msg":"write to stderr: 2021-04-17 14:38:09.396190: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n","pid":15564}}Content-Length: 222
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","method":"output","params":{"source":"stderr","out":"2021-04-17 14:38:09.396190: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n"}}
Info 2021-04-17 14:38:09: Python Daemon (pid: 15564): write to stderr: 2021-04-17 14:38:09.396190: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
Warn 2021-04-17 14:38:09: Kernel 15564 as possibly died, StdErr from Kernel Process 2021-04-17 14:38:09.396190: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
Warn 2021-04-17 14:38:09: StdErr from Kernel Process 2021-04-17 14:38:09.396190: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
Info 2021-04-17 14:38:11: KernelProcess output: Content-Length: 247
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","method":"log","params":{"level":"INFO","msg":"write to stderr: 2021-04-17 14:38:11.838750: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n","pid":15564}}Content-Length: 224
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","method":"output","params":{"source":"stderr","out":"2021-04-17 14:38:11.838750: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n"}}
Info 2021-04-17 14:38:11: Python Daemon (pid: 15564): write to stderr: 2021-04-17 14:38:11.838750: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
Warn 2021-04-17 14:38:11: Kernel 15564 as possibly died, StdErr from Kernel Process 2021-04-17 14:38:11.838750: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
Warn 2021-04-17 14:38:11: StdErr from Kernel Process 2021-04-17 14:38:11.838750: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
Info 2021-04-17 14:38:12: KernelProcess output: Content-Length: 243
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","method":"log","params":{"level":"INFO","msg":"write to stderr: 2021-04-17 14:38:12.205208: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n","pid":15564}}Content-Length: 220
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","method":"output","params":{"source":"stderr","out":"2021-04-17 14:38:12.205208: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n"}}
Info 2021-04-17 14:38:12: Python Daemon (pid: 15564): write to stderr: 2021-04-17 14:38:12.205208: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
Warn 2021-04-17 14:38:12: Kernel 15564 as possibly died, StdErr from Kernel Process 2021-04-17 14:38:12.205208: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
Warn 2021-04-17 14:38:12: StdErr from Kernel Process 2021-04-17 14:38:12.205208: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
Info 2021-04-17 14:38:13: KernelProcess output: Content-Length: 127
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","method":"log","params":{"level":"WARNING","msg":"Kernel has exited with exit code<PHONE_NUMBER>, ","pid":15564}}
Warn 2021-04-17 14:38:13: Python Daemon (pid: 15564): Kernel has exited with exit code<PHONE_NUMBER>,
Info 2021-04-17 14:38:13: KernelProcess output: Content-Length: 86
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","method":"kernel_died","params":{"exit_code":3221226505,"reason":""}}
Error 2021-04-17 14:38:13: Kernel died [s [Error]: Kernel died with exit code<PHONE_NUMBER>. C:\Users\raide\anaconda3\lib\site-packages\traitlets\traitlets.py:2196: FutureWarning: Supporting extra quotes around Unicode is deprecated in traitlets 5.0. Use 'hmac-sha256' instead of '"hmac-sha256"' – or use CUnicode.
warn(
C:\Users\raide\anaconda3\lib\site-packages\traitlets\traitlets.py:2151: FutureWarning: Supporting extra quotes around Bytes is deprecated in traitlets 5.0. Use 'dd38de00-ed20-41ff-b708-37f00dbe5b06' instead of 'b"dd38de00-ed20-41ff-b708-37f00dbe5b06"'.
warn(
2021-04-17 14:34:33.306745: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-04-17 14:34:39.571693: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-04-17 14:34:39.572982: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll
2021-04-17 14:34:39.592463: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6
coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s
2021-04-17 14:34:39.592680: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-04-17 14:34:39.637506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-04-17 14:34:39.637662: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-04-17 14:34:39.642221: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-04-17 14:34:39.648292: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-04-17 14:34:39.656579: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-04-17 14:34:39.659885: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-04-17 14:34:39.717349: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-04-17 14:34:39.717500: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-04-17 14:37:26.143074: 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.
2021-04-17 14:37:26.144182: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6
coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s
2021-04-17 14:37:26.144408: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-04-17 14:37:26.144506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-04-17 14:37:26.144654: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-04-17 14:37:26.144758: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-04-17 14:37:26.144864: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-04-17 14:37:26.144976: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-04-17 14:37:26.145094: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-04-17 14:37:26.145407: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-04-17 14:37:26.145618: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-04-17 14:37:27.263329: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-04-17 14:37:27.263469: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0
2021-04-17 14:37:27.263526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N
2021-04-17 14:37:27.263958: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 8444 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 3080, pci bus id: 0000:01:00.0, compute capability: 8.6)
2021-04-17 14:37:27.265922: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-04-17 14:38:05.431710: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
2021-04-17 14:38:09.396190: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-04-17 14:38:11.838750: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-04-17 14:38:12.205208: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
at c:\Users\raide\.vscode\extensions\ms-toolsai.jupyter-2021.5.745244803\out\client\extension.js:47:765724
at c:\Users\raide\.vscode\extensions\ms-toolsai.jupyter-2021.5.745244803\out\client\extension.js:47:432685
at c:\Users\raide\.vscode\extensions\ms-toolsai.jupyter-2021.5.745244803\out\client\extension.js:47:432903
at Immediate._onImmediate (c:\Users\raide\.vscode\extensions\ms-toolsai.jupyter-2021.5.745244803\out\client\extension.js:47:434468)
at processImmediate (internal/timers.js:456:21)] {

category: 'kerneldied',
stdErr: C:\\Users\\raide\\anaconda3\\lib\\site-packages\\traitlets\\traitlets.py:2196: FutureWarning: Supporting extra quotes around Unicode is deprecated in traitlets 5.0. Use 'hmac-sha256' instead of '"hmac-sha256"' – or use CUnicode.\r\n +
'  warn(\r\n' +
C:\\Users\\raide\\anaconda3\\lib\\site-packages\\traitlets\\traitlets.py:2151: FutureWarning: Supporting extra quotes around Bytes is deprecated in traitlets 5.0. Use 'dd38de00-ed20-41ff-b708-37f00dbe5b06' instead of 'b"dd38de00-ed20-41ff-b708-37f00dbe5b06"'.\r\n +
'  warn(\r\n' +
'2021-04-17 14:34:33.306745: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n' +
'2021-04-17 14:34:39.571693: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set\n' +
'2021-04-17 14:34:39.572982: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll\n' +
'2021-04-17 14:34:39.592463: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n' +
'pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6\n' +
'coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s\n' +
'2021-04-17 14:34:39.592680: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n' +
'2021-04-17 14:34:39.637506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n' +
'2021-04-17 14:34:39.637662: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n' +
'2021-04-17 14:34:39.642221: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n' +
'2021-04-17 14:34:39.648292: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n' +
'2021-04-17 14:34:39.656579: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n' +
'2021-04-17 14:34:39.659885: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n' +
'2021-04-17 14:34:39.717349: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n' +
'2021-04-17 14:34:39.717500: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n' +
'2021-04-17 14:37:26.143074: 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\n' +
'To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n' +
'2021-04-17 14:37:26.144182: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n' +
'pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6\n' +
'coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s\n' +
'2021-04-17 14:37:26.144408: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n' +
'2021-04-17 14:37:26.144506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n' +
'2021-04-17 14:37:26.144654: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n' +
'2021-04-17 14:37:26.144758: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n' +
'2021-04-17 14:37:26.144864: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n' +
'2021-04-17 14:37:26.144976: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n' +
'2021-04-17 14:37:26.145094: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n' +
'2021-04-17 14:37:26.145407: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n' +
'2021-04-17 14:37:26.145618: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n' +
'2021-04-17 14:37:27.263329: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:\n' +
'2021-04-17 14:37:27.263469: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 \n' +
'2021-04-17 14:37:27.263526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N \n' +
'2021-04-17 14:37:27.263958: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 8444 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 3080, pci bus id: 0000:01:00.0, compute capability: 8.6)\n' +
'2021-04-17 14:37:27.265922: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set\n' +
'2021-04-17 14:38:05.431710: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)\n' +
'2021-04-17 14:38:09.396190: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n' +
'2021-04-17 14:38:11.838750: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n' +
'2021-04-17 14:38:12.205208: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n',
exitCode:<PHONE_NUMBER>,
reason: C:\\Users\\raide\\anaconda3\\lib\\site-packages\\traitlets\\traitlets.py:2196: FutureWarning: Supporting extra quotes around Unicode is deprecated in traitlets 5.0. Use 'hmac-sha256' instead of '"hmac-sha256"' – or use CUnicode.\r\n +
'  warn(\r\n' +
C:\\Users\\raide\\anaconda3\\lib\\site-packages\\traitlets\\traitlets.py:2151: FutureWarning: Supporting extra quotes around Bytes is deprecated in traitlets 5.0. Use 'dd38de00-ed20-41ff-b708-37f00dbe5b06' instead of 'b"dd38de00-ed20-41ff-b708-37f00dbe5b06"'.\r\n +
'  warn(\r\n' +
'2021-04-17 14:34:33.306745: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n' +
'2021-04-17 14:34:39.571693: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set\n' +
'2021-04-17 14:34:39.572982: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll\n' +
'2021-04-17 14:34:39.592463: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n' +
'pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6\n' +
'coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s\n' +
'2021-04-17 14:34:39.592680: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n' +
'2021-04-17 14:34:39.637506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n' +
'2021-04-17 14:34:39.637662: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n' +
'2021-04-17 14:34:39.642221: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n' +
'2021-04-17 14:34:39.648292: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n' +
'2021-04-17 14:34:39.656579: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n' +
'2021-04-17 14:34:39.659885: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n' +
'2021-04-17 14:34:39.717349: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n' +
'2021-04-17 14:34:39.717500: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n' +
'2021-04-17 14:37:26.143074: 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\n' +
'To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n' +
'2021-04-17 14:37:26.144182: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n' +
'pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6\n' +
'coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s\n' +
'2021-04-17 14:37:26.144408: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n' +
'2021-04-17 14:37:26.144506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n' +
'2021-04-17 14:37:26.144654: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n' +
'2021-04-17 14:37:26.144758: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n' +
'2021-04-17 14:37:26.144864: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n' +
'2021-04-17 14:37:26.144976: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n' +
'2021-04-17 14:37:26.145094: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n' +
'2021-04-17 14:37:26.145407: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n' +
'2021-04-17 14:37:26.145618: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n' +
'2021-04-17 14:37:27.263329: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:\n' +
'2021-04-17 14:37:27.263469: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 \n' +
'2021-04-17 14:37:27.263526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N \n' +
'2021-04-17 14:37:27.263958: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 8444 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 3080, pci bus id: 0000:01:00.0, compute capability: 8.6)\n' +
'2021-04-17 14:37:27.265922: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set\n' +
'2021-04-17 14:38:05.431710: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)\n' +
'2021-04-17 14:38:09.396190: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n' +
'2021-04-17 14:38:11.838750: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n' +
'2021-04-17 14:38:12.205208: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n'
} C:\Users\raide\anaconda3\lib\site-packages\traitlets\traitlets.py:2196: FutureWarning: Supporting extra quotes around Unicode is deprecated in traitlets 5.0. Use 'hmac-sha256' instead of '"hmac-sha256"' – or use CUnicode.
warn(
C:\Users\raide\anaconda3\lib\site-packages\traitlets\traitlets.py:2151: FutureWarning: Supporting extra quotes around Bytes is deprecated in traitlets 5.0. Use 'dd38de00-ed20-41ff-b708-37f00dbe5b06' instead of 'b"dd38de00-ed20-41ff-b708-37f00dbe5b06"'.
warn(
2021-04-17 14:34:33.306745: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-04-17 14:34:39.571693: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-04-17 14:34:39.572982: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll
2021-04-17 14:34:39.592463: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6
coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s
2021-04-17 14:34:39.592680: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-04-17 14:34:39.637506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-04-17 14:34:39.637662: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-04-17 14:34:39.642221: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-04-17 14:34:39.648292: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-04-17 14:34:39.656579: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-04-17 14:34:39.659885: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-04-17 14:34:39.717349: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-04-17 14:34:39.717500: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-04-17 14:37:26.143074: 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.
2021-04-17 14:37:26.144182: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6
coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s
2021-04-17 14:37:26.144408: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-04-17 14:37:26.144506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-04-17 14:37:26.144654: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-04-17 14:37:26.144758: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-04-17 14:37:26.144864: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-04-17 14:37:26.144976: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-04-17 14:37:26.145094: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-04-17 14:37:26.145407: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-04-17 14:37:26.145618: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-04-17 14:37:27.263329: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-04-17 14:37:27.263469: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0
2021-04-17 14:37:27.263526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N
2021-04-17 14:37:27.263958: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 8444 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 3080, pci bus id: 0000:01:00.0, compute capability: 8.6)
2021-04-17 14:37:27.265922: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-04-17 14:38:05.431710: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
2021-04-17 14:38:09.396190: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-04-17 14:38:11.838750: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-04-17 14:38:12.205208: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
Error 2021-04-17 14:38:13: KernelProcess Exit Exit -<PHONE_NUMBER>, C:\Users\raide\anaconda3\lib\site-packages\traitlets\traitlets.py:2196: FutureWarning: Supporting extra quotes around Unicode is deprecated in traitlets 5.0. Use 'hmac-sha256' instead of '"hmac-sha256"' – or use CUnicode.
warn(
C:\Users\raide\anaconda3\lib\site-packages\traitlets\traitlets.py:2151: FutureWarning: Supporting extra quotes around Bytes is deprecated in traitlets 5.0. Use 'dd38de00-ed20-41ff-b708-37f00dbe5b06' instead of 'b"dd38de00-ed20-41ff-b708-37f00dbe5b06"'.
warn(
2021-04-17 14:34:33.306745: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-04-17 14:34:39.571693: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-04-17 14:34:39.572982: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll
2021-04-17 14:34:39.592463: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6
coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s
2021-04-17 14:34:39.592680: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-04-17 14:34:39.637506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-04-17 14:34:39.637662: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-04-17 14:34:39.642221: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-04-17 14:34:39.648292: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-04-17 14:34:39.656579: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-04-17 14:34:39.659885: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-04-17 14:34:39.717349: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-04-17 14:34:39.717500: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-04-17 14:37:26.143074: 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.
2021-04-17 14:37:26.144182: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6
coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s
2021-04-17 14:37:26.144408: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-04-17 14:37:26.144506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-04-17 14:37:26.144654: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-04-17 14:37:26.144758: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-04-17 14:37:26.144864: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-04-17 14:37:26.144976: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-04-17 14:37:26.145094: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-04-17 14:37:26.145407: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-04-17 14:37:26.145618: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-04-17 14:37:27.263329: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-04-17 14:37:27.263469: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0
2021-04-17 14:37:27.263526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N
2021-04-17 14:37:27.263958: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 8444 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 3080, pci bus id: 0000:01:00.0, compute capability: 8.6)
2021-04-17 14:37:27.265922: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-04-17 14:38:05.431710: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
2021-04-17 14:38:09.396190: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-04-17 14:38:11.838750: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-04-17 14:38:12.205208: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
[s [Error]: Kernel died with exit code<PHONE_NUMBER>. C:\Users\raide\anaconda3\lib\site-packages\traitlets\traitlets.py:2196: FutureWarning: Supporting extra quotes around Unicode is deprecated in traitlets 5.0. Use 'hmac-sha256' instead of '"hmac-sha256"' – or use CUnicode.
warn(
C:\Users\raide\anaconda3\lib\site-packages\traitlets\traitlets.py:2151: FutureWarning: Supporting extra quotes around Bytes is deprecated in traitlets 5.0. Use 'dd38de00-ed20-41ff-b708-37f00dbe5b06' instead of 'b"dd38de00-ed20-41ff-b708-37f00dbe5b06"'.
warn(
2021-04-17 14:34:33.306745: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-04-17 14:34:39.571693: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-04-17 14:34:39.572982: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll
2021-04-17 14:34:39.592463: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6
coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s
2021-04-17 14:34:39.592680: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-04-17 14:34:39.637506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-04-17 14:34:39.637662: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-04-17 14:34:39.642221: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-04-17 14:34:39.648292: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-04-17 14:34:39.656579: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-04-17 14:34:39.659885: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-04-17 14:34:39.717349: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-04-17 14:34:39.717500: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-04-17 14:37:26.143074: 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.
2021-04-17 14:37:26.144182: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6
coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s
2021-04-17 14:37:26.144408: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-04-17 14:37:26.144506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-04-17 14:37:26.144654: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-04-17 14:37:26.144758: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-04-17 14:37:26.144864: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-04-17 14:37:26.144976: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-04-17 14:37:26.145094: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-04-17 14:37:26.145407: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-04-17 14:37:26.145618: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-04-17 14:37:27.263329: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-04-17 14:37:27.263469: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0
2021-04-17 14:37:27.263526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N
2021-04-17 14:37:27.263958: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 8444 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 3080, pci bus id: 0000:01:00.0, compute capability: 8.6)
2021-04-17 14:37:27.265922: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-04-17 14:38:05.431710: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
2021-04-17 14:38:09.396190: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-04-17 14:38:11.838750: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-04-17 14:38:12.205208: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
at c:\Users\raide\.vscode\extensions\ms-toolsai.jupyter-2021.5.745244803\out\client\extension.js:47:765724
at c:\Users\raide\.vscode\extensions\ms-toolsai.jupyter-2021.5.745244803\out\client\extension.js:47:432685
at c:\Users\raide\.vscode\extensions\ms-toolsai.jupyter-2021.5.745244803\out\client\extension.js:47:432903
at Immediate._onImmediate (c:\Users\raide\.vscode\extensions\ms-toolsai.jupyter-2021.5.745244803\out\client\extension.js:47:434468)
at processImmediate (internal/timers.js:456:21)] {

category: 'kerneldied',
stdErr: C:\\Users\\raide\\anaconda3\\lib\\site-packages\\traitlets\\traitlets.py:2196: FutureWarning: Supporting extra quotes around Unicode is deprecated in traitlets 5.0. Use 'hmac-sha256' instead of '"hmac-sha256"' – or use CUnicode.\r\n +
'  warn(\r\n' +
C:\\Users\\raide\\anaconda3\\lib\\site-packages\\traitlets\\traitlets.py:2151: FutureWarning: Supporting extra quotes around Bytes is deprecated in traitlets 5.0. Use 'dd38de00-ed20-41ff-b708-37f00dbe5b06' instead of 'b"dd38de00-ed20-41ff-b708-37f00dbe5b06"'.\r\n +
'  warn(\r\n' +
'2021-04-17 14:34:33.306745: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n' +
'2021-04-17 14:34:39.571693: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set\n' +
'2021-04-17 14:34:39.572982: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll\n' +
'2021-04-17 14:34:39.592463: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n' +
'pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6\n' +
'coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s\n' +
'2021-04-17 14:34:39.592680: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n' +
'2021-04-17 14:34:39.637506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n' +
'2021-04-17 14:34:39.637662: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n' +
'2021-04-17 14:34:39.642221: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n' +
'2021-04-17 14:34:39.648292: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n' +
'2021-04-17 14:34:39.656579: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n' +
'2021-04-17 14:34:39.659885: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n' +
'2021-04-17 14:34:39.717349: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n' +
'2021-04-17 14:34:39.717500: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n' +
'2021-04-17 14:37:26.143074: 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\n' +
'To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n' +
'2021-04-17 14:37:26.144182: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n' +
'pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6\n' +
'coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s\n' +
'2021-04-17 14:37:26.144408: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n' +
'2021-04-17 14:37:26.144506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n' +
'2021-04-17 14:37:26.144654: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n' +
'2021-04-17 14:37:26.144758: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n' +
'2021-04-17 14:37:26.144864: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n' +
'2021-04-17 14:37:26.144976: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n' +
'2021-04-17 14:37:26.145094: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n' +
'2021-04-17 14:37:26.145407: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n' +
'2021-04-17 14:37:26.145618: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n' +
'2021-04-17 14:37:27.263329: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:\n' +
'2021-04-17 14:37:27.263469: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 \n' +
'2021-04-17 14:37:27.263526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N \n' +
'2021-04-17 14:37:27.263958: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 8444 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 3080, pci bus id: 0000:01:00.0, compute capability: 8.6)\n' +
'2021-04-17 14:37:27.265922: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set\n' +
'2021-04-17 14:38:05.431710: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)\n' +
'2021-04-17 14:38:09.396190: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n' +
'2021-04-17 14:38:11.838750: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n' +
'2021-04-17 14:38:12.205208: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n',
exitCode:<PHONE_NUMBER>,
reason: C:\\Users\\raide\\anaconda3\\lib\\site-packages\\traitlets\\traitlets.py:2196: FutureWarning: Supporting extra quotes around Unicode is deprecated in traitlets 5.0. Use 'hmac-sha256' instead of '"hmac-sha256"' – or use CUnicode.\r\n +
'  warn(\r\n' +
C:\\Users\\raide\\anaconda3\\lib\\site-packages\\traitlets\\traitlets.py:2151: FutureWarning: Supporting extra quotes around Bytes is deprecated in traitlets 5.0. Use 'dd38de00-ed20-41ff-b708-37f00dbe5b06' instead of 'b"dd38de00-ed20-41ff-b708-37f00dbe5b06"'.\r\n +
'  warn(\r\n' +
'2021-04-17 14:34:33.306745: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n' +
'2021-04-17 14:34:39.571693: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set\n' +
'2021-04-17 14:34:39.572982: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll\n' +
'2021-04-17 14:34:39.592463: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n' +
'pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6\n' +
'coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s\n' +
'2021-04-17 14:34:39.592680: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n' +
'2021-04-17 14:34:39.637506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n' +
'2021-04-17 14:34:39.637662: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n' +
'2021-04-17 14:34:39.642221: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n' +
'2021-04-17 14:34:39.648292: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n' +
'2021-04-17 14:34:39.656579: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n' +
'2021-04-17 14:34:39.659885: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n' +
'2021-04-17 14:34:39.717349: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n' +
'2021-04-17 14:34:39.717500: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n' +
'2021-04-17 14:37:26.143074: 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\n' +
'To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n' +
'2021-04-17 14:37:26.144182: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n' +
'pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6\n' +
'coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s\n' +
'2021-04-17 14:37:26.144408: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n' +
'2021-04-17 14:37:26.144506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n' +
'2021-04-17 14:37:26.144654: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n' +
'2021-04-17 14:37:26.144758: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n' +
'2021-04-17 14:37:26.144864: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n' +
'2021-04-17 14:37:26.144976: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n' +
'2021-04-17 14:37:26.145094: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n' +
'2021-04-17 14:37:26.145407: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n' +
'2021-04-17 14:37:26.145618: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n' +
'2021-04-17 14:37:27.263329: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:\n' +
'2021-04-17 14:37:27.263469: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 \n' +
'2021-04-17 14:37:27.263526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N \n' +
'2021-04-17 14:37:27.263958: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 8444 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 3080, pci bus id: 0000:01:00.0, compute capability: 8.6)\n' +
'2021-04-17 14:37:27.265922: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set\n' +
'2021-04-17 14:38:05.431710: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)\n' +
'2021-04-17 14:38:09.396190: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n' +
'2021-04-17 14:38:11.838750: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n' +
'2021-04-17 14:38:12.205208: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n'
}
Error 2021-04-17 14:38:13: Disposing session as kernel process died ExitCode:<PHONE_NUMBER>, Reason: C:\Users\raide\anaconda3\lib\site-packages\traitlets\traitlets.py:2196: FutureWarning: Supporting extra quotes around Unicode is deprecated in traitlets 5.0. Use 'hmac-sha256' instead of '"hmac-sha256"' – or use CUnicode.
warn(
C:\Users\raide\anaconda3\lib\site-packages\traitlets\traitlets.py:2151: FutureWarning: Supporting extra quotes around Bytes is deprecated in traitlets 5.0. Use 'dd38de00-ed20-41ff-b708-37f00dbe5b06' instead of 'b"dd38de00-ed20-41ff-b708-37f00dbe5b06"'.
warn(
2021-04-17 14:34:33.306745: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-04-17 14:34:39.571693: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-04-17 14:34:39.572982: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll
2021-04-17 14:34:39.592463: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6
coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s
2021-04-17 14:34:39.592680: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-04-17 14:34:39.637506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-04-17 14:34:39.637662: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-04-17 14:34:39.642221: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-04-17 14:34:39.648292: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-04-17 14:34:39.656579: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-04-17 14:34:39.659885: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-04-17 14:34:39.717349: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-04-17 14:34:39.717500: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-04-17 14:37:26.143074: 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.
2021-04-17 14:37:26.144182: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6
coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s
2021-04-17 14:37:26.144408: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-04-17 14:37:26.144506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-04-17 14:37:26.144654: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-04-17 14:37:26.144758: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-04-17 14:37:26.144864: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-04-17 14:37:26.144976: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-04-17 14:37:26.145094: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-04-17 14:37:26.145407: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-04-17 14:37:26.145618: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-04-17 14:37:27.263329: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-04-17 14:37:27.263469: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0
2021-04-17 14:37:27.263526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N
2021-04-17 14:37:27.263958: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 8444 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 3080, pci bus id: 0000:01:00.0, compute capability: 8.6)
2021-04-17 14:37:27.265922: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-04-17 14:38:05.431710: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
2021-04-17 14:38:09.396190: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-04-17 14:38:11.838750: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-04-17 14:38:12.205208: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
Info 2021-04-17 14:38:13: Dispose Kernel process
Info 2021-04-17 14:38:13: kill daemon
Error 2021-04-17 14:38:13: Raw kernel process exited code: [object Object]
Info 2021-04-17 14:38:13: Shutdown session - current session
Info 2021-04-17 14:38:13: shutdownSession 71da38df-07b0-48c7-99f2-983ed2104700, .python385jvsc74a57bd01c2ff3f27b1d39e8867631319c303ba8a3a55737704eb8675f7c2ccc4ffb3962.C:/Users/raide/anaconda3\python.exe.C:\Users\raide\anaconda3\python.exe.Python 3.8.5 64-bit (conda) - start
Info 2021-04-17 14:38:13: Session can be shutdown .python385jvsc74a57bd01c2ff3f27b1d39e8867631319c303ba8a3a55737704eb8675f7c2ccc4ffb3962.C:/Users/raide/anaconda3\python.exe.C:\Users\raide\anaconda3\python.exe.Python 3.8.5 64-bit (conda)
Info 2021-04-17 14:38:13: Dispose Kernel process
Info 2021-04-17 14:38:13: Dispose Kernel process
Info 2021-04-17 14:38:13: Preferred kernel for file:///g%3A/My%20Drive/Colab%20Notebooks/teaching/gwu/machine_learning_I/spring_2021/project/pneumonia.ipynb is undefined
Info 2021-04-17 14:38:13: Finished execution for NotebookImport#105
Info 2021-04-17 14:38:13: shutdownSession 71da38df-07b0-48c7-99f2-983ed2104700, .python385jvsc74a57bd01c2ff3f27b1d39e8867631319c303ba8a3a55737704eb8675f7c2ccc4ffb3962.C:/Users/raide/anaconda3\python.exe.C:\Users\raide\anaconda3\python.exe.Python 3.8.5 64-bit (conda) - shutdown complete
Info 2021-04-17 14:38:13: Dispose Kernel process
Info 2021-04-17 14:38:13: Finished executing cell NotebookImport#105
Info 2021-04-17 14:38:13: Shutdown session - get restart session
Info 2021-04-17 14:38:13: Shutdown session - shutdown restart session
Info 2021-04-17 14:38:13: shutdownSession 8ed93d27-59d1-4cbf-b80e-be8834f039c7, .python385jvsc74a57bd01c2ff3f27b1d39e8867631319c303ba8a3a55737704eb8675f7c2ccc4ffb3962.C:/Users/raide/anaconda3\python.exe.C:\Users\raide\anaconda3\python.exe.Python 3.8.5 64-bit (conda) - start
Info 2021-04-17 14:38:13: Session can be shutdown .python385jvsc74a57bd01c2ff3f27b1d39e8867631319c303ba8a3a55737704eb8675f7c2ccc4ffb3962.C:/Users/raide/anaconda3\python.exe.C:\Users\raide\anaconda3\python.exe.Python 3.8.5 64-bit (conda)
Info 2021-04-17 14:38:13: Dispose Kernel process
Info 2021-04-17 14:38:13: kill daemon
Info 2021-04-17 14:38:13: KernelProcess output: Content-Length: 122
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","method":"log","params":{"level":"INFO","msg":"Execute rpc method kill_kernel in DS Daemon","pid":15564}}
Info 2021-04-17 14:38:13: Python Daemon (pid: 15564): Execute rpc method kill_kernel in DS Daemon
Info 2021-04-17 14:38:13: KernelProcess output: Content-Length: 122
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","method":"log","params":{"level":"INFO","msg":"Execute rpc method kill_kernel in DS Daemon","pid":30204}}Content-Length: 154
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","method":"log","params":{"level":"INFO","msg":"Execute rpc method kill_kernel from C:\Users\raide\anaconda3\python.exe","pid":30204}}Content-Length: 119
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","method":"log","params":{"level":"INFO","msg":"Kill kernel in DS Kernel Launcher Daemon","pid":30204}}Content-Length: 130
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","method":"log","params":{"level":"INFO","msg":"Kill kernel in DS Kernel Launcher Daemon, pid 20192","pid":30204}}Content-Length: 38
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","id":2,"result":null}
Info 2021-04-17 14:38:13: KernelProcess output: Content-Length: 154
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","method":"log","params":{"level":"INFO","msg":"Execute rpc method kill_kernel from C:\Users\raide\anaconda3\python.exe","pid":15564}}Content-Length: 119
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","method":"log","params":{"level":"INFO","msg":"Kill kernel in DS Kernel Launcher Daemon","pid":15564}}Content-Length: 130
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","method":"log","params":{"level":"INFO","msg":"Kill kernel in DS Kernel Launcher Daemon, pid 33368","pid":15564}}Content-Length: 38
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc":"2.0","id":2,"result":null}
Info 2021-04-17 14:38:13: Python Daemon (pid: 30204): Execute rpc method kill_kernel in DS Daemon
Info 2021-04-17 14:38:13: Python Daemon (pid: 15564): Execute rpc method kill_kernel from C:\Users\raide\anaconda3\python.exe
Info 2021-04-17 14:38:13: Python Daemon (pid: 30204): Execute rpc method kill_kernel from C:\Users\raide\anaconda3\python.exe
Info 2021-04-17 14:38:13: Python Daemon (pid: 15564): Kill kernel in DS Kernel Launcher Daemon
Info 2021-04-17 14:38:13: Python Daemon (pid: 30204): Kill kernel in DS Kernel Launcher Daemon
Info 2021-04-17 14:38:13: Python Daemon (pid: 15564): Kill kernel in DS Kernel Launcher Daemon, pid 33368
Info 2021-04-17 14:38:13: Python Daemon (pid: 30204): Kill kernel in DS Kernel Launcher Daemon, pid 20192
Info 2021-04-17 14:38:13: Dispose Kernel process
Info 2021-04-17 14:38:13: Dispose Kernel process
Info 2021-04-17 14:38:13: shutdownSession 8ed93d27-59d1-4cbf-b80e-be8834f039c7, .python385jvsc74a57bd01c2ff3f27b1d39e8867631319c303ba8a3a55737704eb8675f7c2ccc4ffb3962.C:/Users/raide/anaconda3\python.exe.C:\Users\raide\anaconda3\python.exe.Python 3.8.5 64-bit (conda) - shutdown complete
Info 2021-04-17 14:38:13: Dispose Kernel process
Info 2021-04-17 14:38:13: Shutdown session -- complete
Info 2021-04-17 14:38:13: KernelProcess Exit Exit -<PHONE_NUMBER> C:\Users\raide\anaconda3\lib\site-packages\traitlets\traitlets.py:2196: FutureWarning: Supporting extra quotes around Unicode is deprecated in traitlets 5.0. Use 'hmac-sha256' instead of '"hmac-sha256"' – or use CUnicode.
warn(
C:\Users\raide\anaconda3\lib\site-packages\traitlets\traitlets.py:2151: FutureWarning: Supporting extra quotes around Bytes is deprecated in traitlets 5.0. Use 'dd38de00-ed20-41ff-b708-37f00dbe5b06' instead of 'b"dd38de00-ed20-41ff-b708-37f00dbe5b06"'.
warn(
2021-04-17 14:34:33.306745: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-04-17 14:34:39.571693: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-04-17 14:34:39.572982: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll
2021-04-17 14:34:39.592463: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6
coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s
2021-04-17 14:34:39.592680: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-04-17 14:34:39.637506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-04-17 14:34:39.637662: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-04-17 14:34:39.642221: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-04-17 14:34:39.648292: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-04-17 14:34:39.656579: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-04-17 14:34:39.659885: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-04-17 14:34:39.717349: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-04-17 14:34:39.717500: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-04-17 14:37:26.143074: 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.
2021-04-17 14:37:26.144182: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 3080 computeCapability: 8.6
coreClock: 1.71GHz coreCount: 68 deviceMemorySize: 10.00GiB deviceMemoryBandwidth: 707.88GiB/s
2021-04-17 14:37:26.144408: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2021-04-17 14:37:26.144506: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-04-17 14:37:26.144654: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-04-17 14:37:26.144758: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2021-04-17 14:37:26.144864: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2021-04-17 14:37:26.144976: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2021-04-17 14:37:26.145094: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2021-04-17 14:37:26.145407: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2021-04-17 14:37:26.145618: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-04-17 14:37:27.263329: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-04-17 14:37:27.263469: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0
2021-04-17 14:37:27.263526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N
2021-04-17 14:37:27.263958: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 8444 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 3080, pci bus id: 0000:01:00.0, compute capability: 8.6)
2021-04-17 14:37:27.265922: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-04-17 14:38:05.431710: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
2021-04-17 14:38:09.396190: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2021-04-17 14:38:11.838750: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2021-04-17 14:38:12.205208: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
Info 2021-04-17 14:38:13: KernelProcess Exit Exit - undefined

Figured out the issue.
To get my GPU ready for Tensorflow, I followed the instructions here. Notice in step 5.2 the author describes moving three files from cuDNN into CUDA. Turns out that the interpreter was expecting all of the files from each of the three folders in the cuDNN.zip so simply copying all the files over into the appropriate CUDA folder solved the issue.


Better Fibonacci algorithm

We could probably have a better algorithm to generate the Fibonacci series.
The present one is a bad solution for big series.

Maybe add different ones and time them.

And while fixing Fibonacci's 2 functions names: the first to print and the other to output a list is silly.
The former is just a matter of printing the latter. :-P


with embedded and corrections

When you click on quit button iframe doesn't close

same on firefox and chrome

we cannot go back to the precedent url after creating a visio, it's maybe linked to react router and the history or how the new url is push to the browser


Fixed incorrect ID offset for Trigger Button

Trigger Button is reported as Trackpad Click Button because of incorrect
ID

Great catch, thanks so much! (Apparently I didn't test that bit as well as I thought I did... probably could have used an enum to avoid this in the first place.)


Bump python version

Python 3.7 reached its End of Life (EOL) a few months ago, so it's time to say goodbye.
https://devguide.python.org/versions/

And a new release should be uploaded once CI is done.

Strange, setuptools==59.6.0 seems to coincide with the last release to support Python 3.7 🤔
https://setuptools.pypa.io/en/stable/history.html

I think I found it. https://github.com/pypa/cibuildwheel/blob/461bed51d3619c4c670f008148de8ce1465ba586/cibuildwheel/resources/constraints-python38.txt#L31
We need to update<EMAIL_ADDRESS>in the workflow https://github.com/kodonnell/qoi/blob/main/.github/workflows/wheels.yml
The latest version 2.16.2 seems to support Python 3.8 to 3.12 👍 https://github.com/pypa/cibuildwheel/tree/v2.16.2/cibuildwheel/resources

Thanks!


Format on save chops up the file sometimes

Before format on save:

After format:

Hi!
I've just tested it with latest VSCode, RustyCode, rustfmt and example you provided was formatted just fine. Can you check again please?

Which OS are you using?


Add lint checking to CI.

Depends on #1007.

I am sorry to say this, but this too many different types of changes to the code base for me to properly grasp. I find it difficult to review this PR.

It's okay. git add --patch is our friend for this :) Fixed.


UTxO HD LMDB (MVP)

Functional requirements

Move the UTxO, stake address & delegation, and stake distribution from memory to disk
Full advantage of modern SSDs requires extra implementation effort to implement IO pipeline. We might require this to be in place before release if the performance is too bad without IO pipelining.
Default should be RAM:
a) SPOs can always adjust using the command line param;
b) Daedalus users should be alerted that if they move to HD they will need to revalidate from genesis

Superseded by https://github.com/input-output-hk/cardano-node/issues/5495


Fixes #1267: Prevent suggested issue w/ empty titles

Fixes #1267
This pull request fixes the issue where suggestions would be displayed with an empty title.
Now, the user must enter a minimum of 3 characters in order to generate suggestions. Also if the user clears the title field leaves less than 3 characters, the suggestion box is removed.

Grazie Marco! There's already a check in getSearchableWords:
https://github.com/marcobeltempo/refined-github/blob/30976cd24b991dd661c89082e0092a63530ff8ed/source/features/display-issue-suggestions.js#L20
And if the suggestions remain faded if the search query is no longer long enough. It's fine this way as the search results are still useful to what the user previously typed.

I guess the issue is actually about completely a empty field, rather than just "less than 3"

@bfred-it thanks for the review!
(title.trim().length === 0) is a much cleaner fix


Remove redundant conditions in OpportunitiesController

There are two redundant conditions in OpportunitiesController.php:246

@sunxiaoguang nice catch, partialy true
These are the following variables that should be controlled
$accounting_payment_conditions = AccountingPaymentConditions::select('id')->where( 'default', 1)->first();
$accounting_payment_methods = AccountingPaymentMethod::select('id')->where( 'default', 1)->first();
$accounting_deliveries = AccountingDelivery::select('id')->where( 'default', 1)->first();

@sunxiaoguang nice catch, partialy true
These are the following variables that should be controlled
$accounting_payment_conditions = AccountingPaymentConditions::select('id')->where( 'default', 1)->first();
$accounting_payment_methods = AccountingPaymentMethod::select('id')->where( 'default', 1)->first();
$accounting_deliveries = AccountingDelivery::select('id')->where( 'default', 1)->first();

I see. Updated to control by these three variables. PTAL


We initially opened  #7445 as a proof-of-concept for using worktrees to detect conflicts as part of a rebase, and if we are happy with shipping this to address #6960 we should apply this same approach to our existing merge conflict detection.

We initially opened  #7445 as a proof-of-concept for using worktrees to detect conflicts as part of a rebase, and if we are happy with shipping this to address #6960 we should apply this same approach to our existing merge conflict detection.
This will address at least two known issues with our current git merge-tree approach:

#5664 - incorrectly reporting there will be conflicts
#5568 - incorrectly reporting the number of conflicted files

The worktree approach is favourable here because it lets us rely on Git's behaviour when merging and rebasing, rather than using an approximation. It should also let us perform the work while not affecting the user's working directory.
Originally posted by @shiftkey in https://github.com/desktop/desktop/issues/8049

Please provide error log and detailed CLI command.

@mnoo4577 Looks like this issue was about GitHub Desktop? Perhaps you tried moving this to the wrong repository?


Remove version: ImageLine.FLStudio version <IP_ADDRESS>85

[Automated] It returns code over 400 in all urls
Microsoft Reviewers: Open in CodeFlow

Close with reason: URL works;


Event List block: Change default filter

Given a calendar event that was starting yesterday and ends tomorrow. It's a strange behavior if this event doesn't show up today in the calendars "events list" block. But that's exactly like it works actually. When the event's start date is reached, the event disappears from the event list.
That's why I propose to change the filter to "filterByEndTimeAfter($time)".
The event will then be visible until the event's end is reached. And it will disappear from the page (event list block) when the event's end time is in the past.

To make this easier to test and understand I made an example using the existing time filtering and core77's proposed change. The example shows that events that started "yesterday" and end after the current time are not displayed using the existing filtering.
Example
Events:

started and ended yesterday
started yesterday and ends later today
started earlier today and ends later today
start and end later today
started yesterday and ends tomorrow
starts and ends tomorrow

Current:

Changes:


Set ldap version in requirements

Coverage remained the same at 85.602% when pulling 57c9462f9d77b9a110aeb97a9829e57524023dbf on ldap-version into a21254925af56ef29d43875b36cdf1303162aca8 on master.


Fails to build from source

SBT version 0.13.8
sbt publishLocal
[info] 'compiler-interface' not yet compiled for Scala 2.9.1.final. Compiling...
error: error while loading CharSequence, class file '/Library/Java/JavaVirtualMachines/jdk1.8.0_65.jdk/Contents/Home/jre/lib/rt.jar(java/lang/CharSequence.class)' is broken
(bad constant pool tag 18 at byte 10)
error: error while loading AnnotatedElement, class file '/Library/Java/JavaVirtualMachines/jdk1.8.0_65.jdk/Contents/Home/jre/lib/rt.jar(java/lang/reflect/AnnotatedElement.class)' is broken
(bad constant pool tag 18 at byte 76)
error: error while loading Arrays, class file '/Library/Java/JavaVirtualMachines/jdk1.8.0_65.jdk/Contents/Home/jre/lib/rt.jar(java/util/Arrays.class)' is broken
(bad constant pool tag 18 at byte 765)
error: error while loading Comparator, class file '/Library/Java/JavaVirtualMachines/jdk1.8.0_65.jdk/Contents/Home/jre/lib/rt.jar(java/util/Comparator.class)' is broken
(bad constant pool tag 18 at byte 20)
/var/folders/g5/vwqh3f854dz660v7zzn0s0680000gn/T/sbt_b1d75137/xsbt/ExtractAPI.scala:479: error: java.util.Comparator does not take type parameters
  private[this] val sortClasses = new Comparator[Symbol] {
                                      ^
5 errors found
[info] 'compiler-interface' not yet compiled for Scala 2.9.1.final. Compiling...
error: error while loading CharSequence, class file '/Library/Java/JavaVirtualMachines/jdk1.8.0_65.jdk/Contents/Home/jre/lib/rt.jar(java/lang/CharSequence.class)' is broken
(bad constant pool tag 18 at byte 10)
error: error while loading AnnotatedElement, class file '/Library/Java/JavaVirtualMachines/jdk1.8.0_65.jdk/Contents/Home/jre/lib/rt.jar(java/lang/reflect/AnnotatedElement.class)' is broken
(bad constant pool tag 18 at byte 76)
error: error while loading Arrays, class file '/Library/Java/JavaVirtualMachines/jdk1.8.0_65.jdk/Contents/Home/jre/lib/rt.jar(java/util/Arrays.class)' is broken
(bad constant pool tag 18 at byte 765)
error: error while loading Comparator, class file '/Library/Java/JavaVirtualMachines/jdk1.8.0_65.jdk/Contents/Home/jre/lib/rt.jar(java/util/Comparator.class)' is broken
(bad constant pool tag 18 at byte 20)
/var/folders/g5/vwqh3f854dz660v7zzn0s0680000gn/T/sbt_8dc31eb3/xsbt/ExtractAPI.scala:479: error: java.util.Comparator does not take type parameters
  private[this] val sortClasses = new Comparator[Symbol] {
                                      ^
5 errors found
[error] (compile:doc) Error compiling sbt component 'compiler-interface'
[error] (compile:compileIncremental) Error compiling sbt component 'compiler-interface'
[error] Total time: 4 s, completed May 13, 2016 11:49:31 AM

Hi @0xABAB,
This error is usually caused by using Java 8 rather than Java 7. Are you able to compile it using something along the lines of sbt -java-home $path_to_java7 compile?
By the way - if you are modifying the library for use in the Scala Tracker, you should be aware that the next version of the Scala Tracker won't have scala-util as a dependency.

Yeah, I already noticed the latter. I am now trying the -M4 version of the tracker which indeed eliminates this dependency.
I don't have an interest in scala-util otherwise.
Regarding the Java7/8 thing. I always like it when builds are explicitly supported in at least one environment in a scripted way. So, you could add a script like ./snowplowbuild which would then make sure that the build always works in every (*nix based) environment.
As outlined in the Oracle JDK Support Roadmap, after April 2015, Oracle will not post further updates of Java SE 7 to its public download sites.

Java 7 is basically EOL, so no point in doing anything with it anymore, IMHO.


split-header feature fixed on top

[x] Feature request

Is there any way to create an header/title feature with those behavior:

split-header (header/title): stay fixed;
split-area: scollable

Sorry but out of the scope for me.


Fix gem name

from [embulk-plugin-postgres-json] to [embulk-output-postgres-json]

Nice pull-request! Thank you.


Add support for nullable types

Nullable versions DateOnly? and TimeOnly? are still unmapped even after registering this extension via UseDateOnlyTimeOnly().
The 'DateOnly?' property '<model>' could not be mapped because the database provider does not support this type.

Could you provide some repro code?


Add memorial to Ken on team page

Ken Moore was a google.org fellow who passed away May 22, 2021.

work on issue #999


fix: add confirm modal to expensify card page

Details

Fixed Issues

$ https://github.com/Expensify/App/issues/48386
PROPOSAL: https://github.com/Expensify/App/issues/48386#issuecomment-2323508986
Tests

Create a workspace with currency is not USD$
Open Expensify Card Page
Click on Issue New Card
Verify that: Confirm modal appears

[x] Verify that no errors appear in the JS console

Offline tests

QA Steps

Create a workspace with currency is not USD$
Open Expensify Card Page
Click on Issue New Card
Verify that: Confirm modal appears

[x] Verify that no errors appear in the JS console

PR Author Checklist

[x] I linked the correct issue in the ### Fixed Issues section above
[x] I wrote clear testing steps that cover the changes made in this PR

[x] I added steps for local testing in the Tests section
[x] I added steps for the expected offline behavior in the Offline steps section
[x] I added steps for Staging and/or Production testing in the QA steps section
[x] I added steps to cover failure scenarios (i.e. verify an input displays the correct error message if the entered data is not correct)
[x] I turned off my network connection and tested it while offline to ensure it matches the expected behavior (i.e. verify the default avatar icon is displayed if app is offline)
[x] I tested this PR with a High Traffic account against the staging or production API to ensure there are no regressions (e.g. long loading states that impact usability).

[x] I included screenshots or videos for tests on all platforms
[x] I ran the tests on all platforms & verified they passed on:

[x] Android: Native
[x] Android: mWeb Chrome
[x] iOS: Native
[x] iOS: mWeb Safari
[x] MacOS: Chrome / Safari
[x] MacOS: Desktop

[x] I verified there are no console errors (if there's a console error not related to the PR, report it or open an issue for it to be fixed)
[x] I followed proper code patterns (see Reviewing the code)

[x] I verified that any callback methods that were added or modified are named for what the method does and never what callback they handle (i.e. toggleReport and not onIconClick)
[x] I verified that the left part of a conditional rendering a React component is a boolean and NOT a string, e.g. myBool && <MyComponent />.
[x] I verified that comments were added to code that is not self explanatory
[x] I verified that any new or modified comments were clear, correct English, and explained "why" the code was doing something instead of only explaining "what" the code was doing.
[x] I verified any copy / text shown in the product is localized by adding it to src/languages/* files and using the translation method

[x] If any non-english text was added/modified, I verified the translation was requested/reviewed in #expensify-open-source and it was approved by an internal Expensify engineer. Link to Slack message:

[x] I verified all numbers, amounts, dates and phone numbers shown in the product are using the localization methods
[x] I verified any copy / text that was added to the app is grammatically correct in English. It adheres to proper capitalization guidelines (note: only the first word of header/labels should be capitalized), and is either coming verbatim from figma or has been approved by marketing (in order to get marketing approval, ask the Bug Zero team member to add the Waiting for copy label to the issue)
[x] I verified proper file naming conventions were followed for any new files or renamed files. All non-platform specific files are named after what they export and are not named "index.js". All platform-specific files are named for the platform the code supports as outlined in the README.
[x] I verified the JSDocs style guidelines (in STYLE.md) were followed

[x] If a new code pattern is added I verified it was agreed to be used by multiple Expensify engineers
[x] I followed the guidelines as stated in the Review Guidelines
[x] I tested other components that can be impacted by my changes (i.e. if the PR modifies a shared library or component like Avatar, I verified the components using Avatar are working as expected)
[x] I verified all code is DRY (the PR doesn't include any logic written more than once, with the exception of tests)
[x] I verified any variables that can be defined as constants (ie. in CONST.js or at the top of the file that uses the constant) are defined as such
[x] I verified that if a function's arguments changed that all usages have also been updated correctly
[x] If any new file was added I verified that:

[x] The file has a description of what it does and/or why is needed at the top of the file if the code is not self explanatory

[x] If a new CSS style is added I verified that:

[x] A similar style doesn't already exist
[x] The style can't be created with an existing StyleUtils function (i.e. StyleUtils.getBackgroundAndBorderStyle(theme.componentBG))

[x] If the PR modifies code that runs when editing or sending messages, I tested and verified there is no unexpected behavior for all supported markdown - URLs, single line code, code blocks, quotes, headings, bold, strikethrough, and italic.
[x] If the PR modifies a generic component, I tested and verified that those changes do not break usages of that component in the rest of the App (i.e. if a shared library or component like Avatar is modified, I verified that Avatar is working as expected in all cases)
[x] If the PR modifies a component related to any of the existing Storybook stories, I tested and verified all stories for that component are still working as expected.
[x] If the PR modifies a component or page that can be accessed by a direct deeplink, I verified that the code functions as expected when the deeplink is used - from a logged in and logged out account.
[x] If the PR modifies the UI (e.g. new buttons, new UI components, changing the padding/spacing/sizing, moving components, etc) or modifies the form input styles:

[x] I verified that all the inputs inside a form are aligned with each other.
[x] I added Design label and/or tagged @Expensify/design so the design team can review the changes.

[x] If a new page is added, I verified it's using the ScrollView component to make it scrollable when more elements are added to the page.
[x] If the main branch was merged into this PR after a review, I tested again and verified the outcome was still expected according to the Test steps.

Screenshots/Videos

Android: Native
https://github.com/user-attachments/assets/1fea9a9c-a1d9-4e81-b762-f7dbda9749ac

Android: mWeb Chrome
https://github.com/user-attachments/assets/8063155b-eca1-4f32-bd2a-274f1293713c

iOS: Native
https://github.com/user-attachments/assets/9d0dcf6f-3019-4782-98dd-60619d0b9ce3

iOS: mWeb Safari
https://github.com/user-attachments/assets/0220940f-8005-4800-8eca-e72f95e582a8

MacOS: Chrome / Safari
https://github.com/user-attachments/assets/28d0af2e-b1db-4ff3-b4c7-b810d0e05cfd

MacOS: Desktop
https://github.com/user-attachments/assets/7492c211-aa3b-4db0-a77b-e2aafaf731df

:hand: This PR was not deployed to staging yet because QA is ongoing. It will be automatically deployed to staging after the next production release.

I think the PR is already on production, right? I wonder what happened here for the messages to fail


update dynamic allocation enabled flag

@moliu2019 : Thanks for your contribution! The author(s) have been notified to review your proposed change.

@juluczni
Can you review this PR?
IMPORTANT: When this content is ready to merge, you must add #sign-off in a comment or the approval may get overlooked.
#label:"aq-pr-triaged"
@MicrosoftDocs/public-repo-pr-review-team

@moliu2019 Thanks for the fix. We will merge it soon.

#please-close

@Jak-MS please merge this PR.

#re-open

#please-open

#sign-off


documentation should explain the scheduletime  time zone info

documentation should explain the scheduletime  time zone info

Thanks for updating the doc!

LGTM


add type_neq test

Codecov Report

Merging #7 into master will increase coverage by 5.07%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master       #7      +/-   ##
==========================================
+ Coverage   90.86%   95.93%   +5.07%
==========================================
  Files           9        9
  Lines         197      197
==========================================
+ Hits          179      189      +10
+ Misses         18        8      -10

Impacted Files
Coverage Δ

py_hcl/firrtl_ir/width.py
95.23% <0%> (+4.76%)
:arrow_up:

py_hcl/firrtl_ir/field.py
90% <0%> (+5%)
:arrow_up:

py_hcl/firrtl_ir/tpe.py
98.63% <0%> (+10.95%)
:arrow_up:

Continue to review full report at Codecov.

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Formatters cannot be run on new files until they have been saved

Issue Type: Bug
When creating a new file, it can not be formatted until it is saved.
An existing issue I found in the C++ extension repo indicated this is an problem with VS Code, not the extension
https://github.com/microsoft/vscode-cpptools/issues/8230
Steps to Reproduce:

Install an extension that supports formatting a specific file type
Create a new file, set its language to one the formatter supports
Open the command palette and type "Format"
Notice most of the formatting options are missing (Format Modified Lines, Format Selection, Format Document With...)
Select Format Document
Notice the error message: There is no formatter for 'language' files installed.

VS Code version: Code 1.67.0 (57fd6d0195bb9b9d1b49f6da5db789060795de47, 2022-05-04T12:06:02.889Z)
OS version: Windows_NT x64 10.0.19044
Restricted Mode: No

System Info

Item
Value

CPUs
AMD Ryzen 9 5950X 16-Core Processor             (32 x 3400)

GPU Status
2d_canvas: enabledcanvas_oop_rasterization: disabled_offdirect_rendering_display_compositor: disabled_off_okgpu_compositing: enabledmultiple_raster_threads: enabled_onoop_rasterization: enabledopengl: enabled_onrasterization: enabledraw_draw: disabled_off_okskia_renderer: enabled_onvideo_decode: enabledvideo_encode: enabledvulkan: disabled_offwebgl: enabledwebgl2: enabled

Load (avg)
undefined

Memory (System)
31.91GB (23.65GB free)

Process Argv
--crash-reporter-id 478f35b5-a10c-4d20-a3c1-631ecbaf47b0

Screen Reader
no

VM
0%

Extensions (15)

Extension
Author (truncated)
Version

unique-lines
bib
1.0.0

auto-align
bla
0.0.13

graphviz-preview
EFa
1.5.0

vsc-material-theme-icons
equ
2.3.1

vscode-pull-request-github
Git
0.42.0

customize-ui
ioc
0.1.61

monkey-patch
ioc
0.1.16

vsc-space-block-jumper
jmf
1.2.2

polacode-fixed-edition
mrr
0.3.6

remote-containers
ms-
0.234.0

remote-wsl
ms-
0.66.2

cpptools
ms-
1.9.8

code-settings-sync
Sha
3.4.3

dot
Ste
0.0.1

vscode-todo-highlight
way
1.0.5

(1 theme extensions excluded)

An existing issue I found in the C++ extension repo indicated this is an problem with VS Code, not the extension
https://github.com/microsoft/vscode-cpptools/issues/8230

It is an extension issue: they register for different kind of documents, e.g different languages like C++ or Java and different uri-schemes like file (for things stored on local disk), http, or untitled (for document that aren't saved yet). Extensions must explicitly opt-in to these schemes or they will be ignored

Notice the error message: There is no formatter for 'language' files installed.

And yes, the message is shown on purpose because. From muscle memory folks select the format document shortcut and we want to make them aware, e.g motivate them to install a formatter (that works everywhere)

the message is shown on purpose

I'm sorry could you repeat that?
You lie to the user on purpose to confuse them into thinking there's a different problem than the real one?
I spent 12 god damn hours trying to find out why, despite having an installed formatter, I got the error message "no formatter," and only after 12 god damn hours did it occur to me that maybe VSCode simply had a bug
(which, spoiler, it does, that is to say, it erroneously tells the user that there is no formatter installed for file format X when the fact of the matter is that there is no formatter installed for unsaved files of format X)

The bug is not caused by extensions. The bug is caused by VS Code not being able to use extensions because of arbitrary restrictions (in this case, the file nees to be saved on disk first for the formatter to function, for SOME reason my brain is CLEARLY too puny to understand /s).


vfilter with multiple conditions

It seems that vfilter, vmap, etc can't handle multiple conditions?
x       = rand(10)
cond(a) = ((a > 0.25) && (a < 0.75))

vfilter(cond,x) # ERROR: TypeError: non-boolean (VectorizationBase.Mask{4, UInt8}) used in boolean context
filter(cond,x)  # this works

vmap(cond,x)    # ERROR: TypeError: non-boolean (VectorizationBase.Mask{4, UInt8}) used in boolean context
map(cond,x)     # this works

Thanks

Use & and | rather than && and ||.

Let me know if you have any further issues.
Unfortunately, supporting && and || is not possible without compiler magic.
LoopModels, the eventual successor to LoopVectorization.jl, will support those.
But LoopVectorization.jl is implemented largely using multiple dispatch, and it is not possible to overload && and || as these are syntax, not functions.
As a word of caution, note that & and | don't have the same precedence as && and ||, so you'll have to be sure and add parenthesis whenever using them, like you did in your example.