Build failure: tensorflow-gpu - .tar.gz download failed GET returned 404 Not Found

Steps To Reproduce
Set cudaSupport = true for the system to build. Rebuild the system.
Build log
Running phase: unpackPhase
@nix { "action": "setPhase", "phase": "unpackPhase" }
unpacking source archive /nix/store/jy636qwb5bzyag808miwzcm8v1gac7n4-source
source root is source
Running phase: patchPhase
@nix { "action": "setPhase", "phase": "patchPhase" }
applying patch /nix/store/059cih80158c5l202hf37ds7kql7ilsq-source/0002-systemlib-Latest-absl-LTS-has-split-cord-libs.patch
patching file third_party/absl/system.absl.strings.BUILD
applying patch /nix/store/059cih80158c5l202hf37ds7kql7ilsq-source/0005-systemlib-Updates-for-Abseil-20220623-LTS.patch
patching file third_party/absl/system.absl.functional.BUILD
patching file third_party/absl/system.absl.random.BUILD
applying patch /nix/store/059cih80158c5l202hf37ds7kql7ilsq-source/0007-systemlibs-Add-well_known_types_py_pb2-target.patch
patching file third_party/systemlibs/protobuf.BUILD
applying patch /nix/store/v4gg19prx5gsclvz10az8lb52j2ac4ah-fix-layout-proto-duplicate-loading.patch
patching file tensorflow/python/BUILD
Hunk #1 succeeded at 5043 (offset 636 lines).
applying patch /nix/store/dik37ajgl39vwwrn2kjrfzm9714kkkx4-com_google_absl_add_log.patch
patching file third_party/absl/system.absl.base.BUILD
patching file third_party/absl/system.absl.log.BUILD
patching file third_party/absl/workspace.bzl
applying patch /nix/store/30yfi68k96k7hivqn1cpb073yqisz6w4-absl_py_argparse_flags.patch
patching file third_party/systemlibs/absl_py.absl.flags.BUILD
applying patch /nix/store/79vwly1bz4i9nq223d6yrcxk6g0bkm3g-protobuf_python.patch
patching file tensorflow/workspace2.bzl
patching file third_party/systemlibs/protobuf.python.BUILD
applying patch /nix/store/0axfx2c0svc6s1zm7g5zbpajxm4bvzw3-pybind11_protobuf_python_runtime_dep.patch
patching file tensorflow/workspace2.bzl
patching file third_party/pybind11_protobuf/python_runtime_dep.patch
applying patch /nix/store/26mixjax62wn0kzcyfqjqr6hfyj9qcn4-pybind11_protobuf_newer_version.patch
patching file tensorflow/workspace2.bzl
Hunk #1 succeeded at 873 (offset 1 line).
patching script interpreter paths in .
./configure: interpreter directive changed from "#!/usr/bin/env bash" to "/nix/store/p6k7xp1lsfmbdd731mlglrdj2d66mr82-bash-5.2p37/bin/bash"
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./tensorflow/tools/ci_build/update_version.py: interpreter directive changed from "#!/usr/bin/python" to "/nix/store/34ajada96ygm157zh3fnzhivyh7ixgvk-python3-3.12.7-env/bin/python"
./tensorflow/tools/ci_build/windows/libtensorflow_cpu.sh: interpreter directive changed from "#!/usr/bin/env bash" to "/nix/store/p6k7xp1lsfmbdd731mlglrdj2d66mr82-bash-5.2p37/bin/bash"
./tensorflow/tools/ci_build/xla/linux/gpu/run_py3.sh: interpreter directive changed from "#!/usr/bin/env bash" to "/nix/store/p6k7xp1lsfmbdd731mlglrdj2d66mr82-bash-5.2p37/bin/bash"
./tensorflow/tools/gcs_test/gcs_smoke.sh: interpreter directive changed from "#!/usr/bin/env bash" to "/nix/store/p6k7xp1lsfmbdd731mlglrdj2d66mr82-bash-5.2p37/bin/bash"
./tensorflow/tools/gcs_test/gcs_smoke_wrapper.sh: interpreter directive changed from "#!/usr/bin/env bash" to "/nix/store/p6k7xp1lsfmbdd731mlglrdj2d66mr82-bash-5.2p37/bin/bash"
./tensorflow/tools/lib_package/concat_licenses.sh: interpreter directive changed from "#!/usr/bin/env bash" to "/nix/store/p6k7xp1lsfmbdd731mlglrdj2d66mr82-bash-5.2p37/bin/bash"
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./tensorflow/tools/tf_sig_build_dockerfiles/builder.devtoolset/build_devtoolset.sh: interpreter directive changed from "#!/bin/bash -eu" to "/nix/store/p6k7xp1lsfmbdd731mlglrdj2d66mr82-bash-5.2p37/bin/bash -eu"
./tensorflow/tools/tf_sig_build_dockerfiles/builder.devtoolset/fixlinks.sh: interpreter directive changed from "#!/bin/bash" to "/nix/store/p6k7xp1lsfmbdd731mlglrdj2d66mr82-bash-5.2p37/bin/bash"
./tensorflow/tools/tf_sig_build_dockerfiles/builder.devtoolset/rpm-patch.sh: interpreter directive changed from "#!/bin/bash -eu" to "/nix/store/p6k7xp1lsfmbdd731mlglrdj2d66mr82-bash-5.2p37/bin/bash -eu"
./tensorflow/tools/tf_sig_build_dockerfiles/devel.usertools/get_test_list.sh: interpreter directive changed from "#!/bin/bash" to "/nix/store/p6k7xp1lsfmbdd731mlglrdj2d66mr82-bash-5.2p37/bin/bash"
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./tensorflow/tools/tf_sig_build_dockerfiles/devel.usertools/squash_testlogs.py: interpreter directive changed from "#!/usr/bin/env python3" to "/nix/store/34ajada96ygm157zh3fnzhivyh7ixgvk-python3-3.12.7-env/bin/python3"
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./third_party/gpus/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc.tpl: interpreter directive changed from "#!/usr/bin/env python" to "/nix/store/34ajada96ygm157zh3fnzhivyh7ixgvk-python3-3.12.7-env/bin/python"
./third_party/gpus/crosstool/clang/bin/crosstool_wrapper_driver_rocm.tpl: interpreter directive changed from "#!/usr/bin/env python" to "/nix/store/34ajada96ygm157zh3fnzhivyh7ixgvk-python3-3.12.7-env/bin/python"
./tools/tf_env_collect.sh: interpreter directive changed from "#!/usr/bin/env bash" to "/nix/store/p6k7xp1lsfmbdd731mlglrdj2d66mr82-bash-5.2p37/bin/bash"
Running phase: updateAutotoolsGnuConfigScriptsPhase
@nix { "action": "setPhase", "phase": "updateAutotoolsGnuConfigScriptsPhase" }
Running phase: configurePhase
@nix { "action": "setPhase", "phase": "configurePhase" }
patching script interpreter paths in configure
You have bazel 5.4.1- (@non-git) installed.
Do you wish to build TensorFlow with ROCm support? [y/N]: No ROCm support will be enabled for TensorFlow.

Do you wish to build TensorFlow with TensorRT support? [y/N]: No TensorRT support will be enabled for TensorFlow.

/build/source/third_party/gpus/find_cuda_config.py:124: SyntaxWarning: invalid escape sequence '\s'
  match = re.match("\s*#\s*define %s\s+(\d+)" % name, line)
/build/source/third_party/gpus/find_cuda_config.py:263: SyntaxWarning: invalid escape sequence '\d'
  pattern = "Cuda compilation tools, release \d+\.\d+, V(\d+\.\d+\.\d+)"
/build/source/third_party/gpus/find_cuda_config.py:552: SyntaxWarning: invalid escape sequence '\w'
  match = re.match("^(/[^/ ]*)+/lib/\w+-linux-gnu/?$", os.environ[env_name])
Found CUDA 11.8 in:
    /nix/store/ynh6qy5gcdmn5682kvn4gwvf64wymdkh-cuda-11.8-dev-merged/lib
    /nix/store/ynh6qy5gcdmn5682kvn4gwvf64wymdkh-cuda-11.8-dev-merged/include
Found cuDNN 8 in:
    /nix/store/00prc6qzfqnqmrmfkxnsicwsf32vljf9-cudnn-merged/lib
    /nix/store/00prc6qzfqnqmrmfkxnsicwsf32vljf9-cudnn-merged/include

Do you want to use clang as CUDA compiler? [y/N]: nvcc will be used as CUDA compiler.

Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -Wno-sign-compare]:

Would you like to interactively configure ./WORKSPACE for Android builds? [y/N]: Not configuring the WORKSPACE for Android builds.

Preconfigured Bazel build configs. You can use any of the below by adding "--config=<>" to your build command. See .bazelrc for more details.
	--config=mkl         	# Build with MKL support.
	--config=mkl_aarch64 	# Build with oneDNN and Compute Library for the Arm Architecture (ACL).
	--config=monolithic  	# Config for mostly static monolithic build.
	--config=numa        	# Build with NUMA support.
	--config=dynamic_kernels	# (Experimental) Build kernels into separate shared objects.
	--config=v1          	# Build with TensorFlow 1 API instead of TF 2 API.
Preconfigured Bazel build configs to DISABLE default on features:
	--config=nogcp       	# Disable GCP support.
	--config=nonccl      	# Disable NVIDIA NCCL support.
Configuration finished
Running phase: buildPhase
@nix { "action": "setPhase", "phase": "buildPhase" }
Extracting Bazel installation...
INFO: Options provided by the client:
  Inherited 'common' options: --isatty=1 --terminal_columns=0
INFO: Reading rc options for 'build' from /build/source/.bazelrc:
  Inherited 'common' options: --experimental_repo_remote_exec
INFO: Reading rc options for 'build' from /nix/store/5mbiv8fjqfy4ynrxvjdj6hhcg97qv0sy-bazel-rc:
  'build' options: --distdir=/nix/store/8v0s0md3d6k876s1s48qc661blf9zp0j-bazel-deps --extra_toolchains=@bazel_tools//tools/jdk:nonprebuilt_toolchain_definition --tool_java_runtime_version=local_jdk_11 --java_runtime_version=local_jdk_11
INFO: Reading rc options for 'build' from /build/source/.bazelrc:
  'build' options: --define framework_shared_object=true --define tsl_protobuf_header_only=true --define=use_fast_cpp_protos=true --define=allow_oversize_protos=true --spawn_strategy=standalone -c opt --announce_rc --define=grpc_no_ares=true --noincompatible_remove_legacy_whole_archive --enable_platform_specific_config --define=with_xla_support=true --config=short_logs --config=v2 --define=no_aws_support=true --define=no_hdfs_support=true --experimental_cc_shared_library --experimental_link_static_libraries_once=false --incompatible_enforce_config_setting_visibility
INFO: Reading rc options for 'build' from /build/source/.tf_configure.bazelrc:
  'build' options: --action_env PYTHON_BIN_PATH=/nix/store/34ajada96ygm157zh3fnzhivyh7ixgvk-python3-3.12.7-env/bin/python3.12 --action_env PYTHON_LIB_PATH=/build/site-packages --python_path=/nix/store/34ajada96ygm157zh3fnzhivyh7ixgvk-python3-3.12.7-env/bin/python3.12 --define=with_xla_support=true --action_env TF_CUDA_PATHS=/nix/store/ynh6qy5gcdmn5682kvn4gwvf64wymdkh-cuda-11.8-dev-merged,/nix/store/00prc6qzfqnqmrmfkxnsicwsf32vljf9-cudnn-merged,/nix/store/abamsnxib30shcp1ijm7xs2frpvx3bn4-nccl-2.21.5-1 --action_env CUDA_TOOLKIT_PATH=/nix/store/ynh6qy5gcdmn5682kvn4gwvf64wymdkh-cuda-11.8-dev-merged --action_env TF_CUDA_COMPUTE_CAPABILITIES=6.0,6.1,7.0,7.5,8.0,8.6,8.9,9.0 --action_env GCC_HOST_COMPILER_PATH=/nix/store/wpr8p1xkvhi6sibi3lg1byiayb34phq2-gcc-wrapper-11.5.0/bin/gcc --config=cuda --action_env TF_SYSTEM_LIBS=absl_py,astor_archive,astunparse_archive,boringssl,com_github_grpc_grpc,com_google_absl,com_google_protobuf,curl,cython,dill_archive,double_conversion,flatbuffers,functools32_archive,gast_archive,gif,hwloc,icu,jsoncpp_git,libjpeg_turbo,nasm,nsync,opt_einsum_archive,org_sqlite,pasta,png,pybind11,six_archive,snappy,tblib_archive,termcolor_archive,typing_extensions_archive,wrapt,zlib --define=INCLUDEDIR=/nix/store/s22liqjaq5vin9bd71ygvzv33ngfcbbk-tensorflow-deps-merged/include --define=PROTOBUF_INCLUDE_PATH=/nix/store/lm78qfdy5232a6hmk5dx31rjl6n4b9b5-protobuf-21.12/include
INFO: Reading rc options for 'build' from /build/source/.bazelrc:
  'build' options: --deleted_packages=tensorflow/compiler/mlir/tfrt,tensorflow/compiler/mlir/tfrt/benchmarks,tensorflow/compiler/mlir/tfrt/jit/python_binding,tensorflow/compiler/mlir/tfrt/jit/transforms,tensorflow/compiler/mlir/tfrt/python_tests,tensorflow/compiler/mlir/tfrt/tests,tensorflow/compiler/mlir/tfrt/tests/ir,tensorflow/compiler/mlir/tfrt/tests/analysis,tensorflow/compiler/mlir/tfrt/tests/jit,tensorflow/compiler/mlir/tfrt/tests/lhlo_to_tfrt,tensorflow/compiler/mlir/tfrt/tests/lhlo_to_jitrt,tensorflow/compiler/mlir/tfrt/tests/tf_to_corert,tensorflow/compiler/mlir/tfrt/tests/tf_to_tfrt_data,tensorflow/compiler/mlir/tfrt/tests/saved_model,tensorflow/compiler/mlir/tfrt/transforms/lhlo_gpu_to_tfrt_gpu,tensorflow/core/runtime_fallback,tensorflow/core/runtime_fallback/conversion,tensorflow/core/runtime_fallback/kernel,tensorflow/core/runtime_fallback/opdefs,tensorflow/core/runtime_fallback/runtime,tensorflow/core/runtime_fallback/util,tensorflow/core/tfrt/eager,tensorflow/core/tfrt/eager/backends/cpu,tensorflow/core/tfrt/eager/backends/gpu,tensorflow/core/tfrt/eager/core_runtime,tensorflow/core/tfrt/eager/cpp_tests/core_runtime,tensorflow/core/tfrt/gpu,tensorflow/core/tfrt/run_handler_thread_pool,tensorflow/core/tfrt/runtime,tensorflow/core/tfrt/saved_model,tensorflow/core/tfrt/graph_executor,tensorflow/core/tfrt/saved_model/tests,tensorflow/core/tfrt/tpu,tensorflow/core/tfrt/utils,tensorflow/core/tfrt/utils/debug
INFO: Found applicable config definition build:short_logs in file /build/source/.bazelrc: --output_filter=DONT_MATCH_ANYTHING
INFO: Found applicable config definition build:v2 in file /build/source/.bazelrc: --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1
INFO: Found applicable config definition build:cuda in file /build/source/.bazelrc: --repo_env TF_NEED_CUDA=1 --crosstool_top=@local_config_cuda//crosstool:toolchain --@local_config_cuda//:enable_cuda
INFO: Found applicable config definition build:linux in file /build/source/.bazelrc: --define=build_with_onednn_v2=true --host_copt=-w --copt=-Wno-all --copt=-Wno-extra --copt=-Wno-deprecated --copt=-Wno-deprecated-declarations --copt=-Wno-ignored-attributes --copt=-Wno-array-bounds --copt=-Wunused-result --copt=-Werror=unused-result --copt=-Wswitch --copt=-Werror=switch --copt=-Wno-error=unused-but-set-variable --define=PREFIX=/usr --define=LIBDIR=$(PREFIX)/lib --define=INCLUDEDIR=$(PREFIX)/include --define=PROTOBUF_INCLUDE_PATH=$(PREFIX)/include --cxxopt=-std=c++17 --host_cxxopt=-std=c++17 --config=dynamic_kernels --experimental_guard_against_concurrent_changes
INFO: Found applicable config definition build:dynamic_kernels in file /build/source/.bazelrc: --define=dynamic_loaded_kernels=true --copt=-DAUTOLOAD_DYNAMIC_KERNELS
WARNING: Download from https://storage.googleapis.com/mirror.tensorflow.org/github.com/tensorflow/runtime/archive/7d879c8b161085a4374ea481b93a52adb19c0529.tar.gz failed: class java.io.FileNotFoundException GET returned 404 Not Found
WARNING: Download from https://storage.googleapis.com/mirror.tensorflow.org/github.com/llvm/llvm-project/archive/dc275fd03254d67d29cc70a5a0569acf24d2280d.tar.gz failed: class java.io.FileNotFoundException GET returned 404 Not Found
INFO: Repository local_config_cuda instantiated at:
  /build/source/WORKSPACE:15:14: in <toplevel>
  /build/source/tensorflow/workspace2.bzl:966:19: in workspace
  /build/source/tensorflow/workspace2.bzl:101:19: in _tf_toolchains
Repository rule cuda_configure defined at:
  /build/source/third_party/gpus/cuda_configure.bzl:1484:33: in <toplevel>
ERROR: An error occurred during the fetch of repository 'local_config_cuda':
   Traceback (most recent call last):
	File "/build/source/third_party/gpus/cuda_configure.bzl", line 1437, column 38, in _cuda_autoconf_impl
		_create_local_cuda_repository(repository_ctx)
	File "/build/source/third_party/gpus/cuda_configure.bzl", line 1013, column 35, in _create_local_cuda_repository
		cuda_config = _get_cuda_config(repository_ctx, find_cuda_config_script)
	File "/build/source/third_party/gpus/cuda_configure.bzl", line 695, column 30, in _get_cuda_config
		config = find_cuda_config(repository_ctx, find_cuda_config_script, ["cuda", "cudnn"])
	File "/build/source/third_party/gpus/cuda_configure.bzl", line 672, column 41, in find_cuda_config
		exec_result = _exec_find_cuda_config(repository_ctx, script_path, cuda_libraries)
	File "/build/source/third_party/gpus/cuda_configure.bzl", line 666, column 19, in _exec_find_cuda_config
		return execute(repository_ctx, [python_bin, "-c", decompress_and_execute_cmd])
	File "/build/source/third_party/remote_config/common.bzl", line 230, column 13, in execute
		fail(
Error in fail: Repository command failed
/build/output/external/local_config_cuda/script.py:124: SyntaxWarning: invalid escape sequence '\s'
  match = re.match("\s*#\s*define %s\s+(\d+)" % name, line)
/build/output/external/local_config_cuda/script.py:263: SyntaxWarning: invalid escape sequence '\d'
  pattern = "Cuda compilation tools, release \d+\.\d+, V(\d+\.\d+\.\d+)"
/build/output/external/local_config_cuda/script.py:552: SyntaxWarning: invalid escape sequence '\w'
  match = re.match("^(/[^/ ]*)+/lib/\w+-linux-gnu/?$", os.environ[env_name])
ERROR: /build/source/WORKSPACE:15:14: fetching cuda_configure rule //external:local_config_cuda: Traceback (most recent call last):
	File "/build/source/third_party/gpus/cuda_configure.bzl", line 1437, column 38, in _cuda_autoconf_impl
		_create_local_cuda_repository(repository_ctx)
	File "/build/source/third_party/gpus/cuda_configure.bzl", line 1013, column 35, in _create_local_cuda_repository
		cuda_config = _get_cuda_config(repository_ctx, find_cuda_config_script)
	File "/build/source/third_party/gpus/cuda_configure.bzl", line 695, column 30, in _get_cuda_config
		config = find_cuda_config(repository_ctx, find_cuda_config_script, ["cuda", "cudnn"])
	File "/build/source/third_party/gpus/cuda_configure.bzl", line 672, column 41, in find_cuda_config
		exec_result = _exec_find_cuda_config(repository_ctx, script_path, cuda_libraries)
	File "/build/source/third_party/gpus/cuda_configure.bzl", line 666, column 19, in _exec_find_cuda_config
		return execute(repository_ctx, [python_bin, "-c", decompress_and_execute_cmd])
	File "/build/source/third_party/remote_config/common.bzl", line 230, column 13, in execute
		fail(
Error in fail: Repository command failed
/build/output/external/local_config_cuda/script.py:124: SyntaxWarning: invalid escape sequence '\s'
  match = re.match("\s*#\s*define %s\s+(\d+)" % name, line)
/build/output/external/local_config_cuda/script.py:263: SyntaxWarning: invalid escape sequence '\d'
  pattern = "Cuda compilation tools, release \d+\.\d+, V(\d+\.\d+\.\d+)"
/build/output/external/local_config_cuda/script.py:552: SyntaxWarning: invalid escape sequence '\w'
  match = re.match("^(/[^/ ]*)+/lib/\w+-linux-gnu/?$", os.environ[env_name])
INFO: Found applicable config definition build:cuda in file /build/source/.bazelrc: --repo_env TF_NEED_CUDA=1 --crosstool_top=@local_config_cuda//crosstool:toolchain --@local_config_cuda//:enable_cuda
ERROR: @local_config_cuda//:enable_cuda :: Error loading option @local_config_cuda//:enable_cuda: Repository command failed
/build/output/external/local_config_cuda/script.py:124: SyntaxWarning: invalid escape sequence '\s'
  match = re.match("\s*#\s*define %s\s+(\d+)" % name, line)
/build/output/external/local_config_cuda/script.py:263: SyntaxWarning: invalid escape sequence '\d'
  pattern = "Cuda compilation tools, release \d+\.\d+, V(\d+\.\d+\.\d+)"
/build/output/external/local_config_cuda/script.py:552: SyntaxWarning: invalid escape sequence '\w'
  match = re.match("^(/[^/ ]*)+/lib/\w+-linux-gnu/?$", os.environ[env_name])

Additional context
Using flakes, nixpkgs-24.11.
Metadata
 - system: `"x86_64-linux"`
 - host os: `Linux 6.6.63, NixOS, 24.11 (Vicuna), 24.11.20241208.1b6d067`
 - multi-user?: `yes`
 - sandbox: `yes`
 - version: `nix-env (Nix) 2.24.10`
 - channels(giulio): `""`
 - nixpkgs: `/nix/store/f5h0s1i0pnvfvbcgh6z29lq25wzl47hp-source`

Notify maintainers
@jyp and @abbradar

Note for maintainers: Please tag this issue in your PR.

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

cc/ @jyp and @abbradar


HSEARCH-2422 Always compute scores when projecting on the score in Elasticsearch

This PR is based on #1197 (HSEARCH-2393), so we'll have to merge that one first.
Relevant JIRA ticket: https://hibernate.atlassian.net/browse/HSEARCH-2422

Good to go, once the other PRs are merged!


Ensure the correct Ruby version is in Gemfile.lock

If this isn't set properly it will break Heroku deploys.

Failed as expected: https://github.com/github/opensourcefriday/pull/747/checks?check_run_id=1111196032#step:5:4


Diet beacons not disabling correctly

Mod source
Factorio Mod Portal
Operating system

=Windows 10

What kind of issue is this?

[ ] Compatibility
[ ] Locale (names, descriptions, unknown keys)
[ ] Graphical
[ ] Crash
[ ] Progression
[ ] Balance
[ ] Pypostprocessing failure
[ ] Other

What is the problem?
Diet beacons keep machines overloaded when they are not supposed to.
Steps to reproduce

Place a diet beacon & configure
Place another diet beacon and configure so that it causes an overload.
Mine one of the beacons

You will notice, even with 1 beacon on the machine it is still overloaded.
Additional context
No response
Log file
No response

should be fixed in the next update, in the meantime you can mine the affected entity and place it again, or place a beacon and change its frequency to a not conflicting one as a workaround


Navigation not working

I've updated to the latest version and the navigation is not longer working. (Up and Down) keys
<EMAIL_ADDRESS>// @flow

import type {
  Dispatch,
  State,
  Suggestion,
} from "../../types";

type AutosuggestStatusPropTypes = {
  isError: boolean;
  isFetching: boolean;
};

type SearchCompanyPropTypes = {
  currentTerm: string;
  isErrorFetchingSuggestions: boolean;
  isFetchingSuggestions: boolean;
  router: any;
  suggestions: any;

  changeSuggestionsCurrentTerm: (newTerm : string) => void;
  fetchCurrentCompanyInfo: (companyID : string) => void;
  fetchSuggestions: (search : string) => void;
  getShouldFetchCurrentCompanyInfo: (rawCompanyID : string) => boolean;
}

// --- end types

import { bindActionCreators } from "redux";
import { connect } from "react-redux";
import { withRouter } from "react-router";
import Autosuggest from "react-autosuggest";
import React from "react";

import {
  changeSuggestionsCurrentTerm as changeSuggestionsCurrentTermAction,
  fetchSuggestions as fetchSuggestionsAction,
} from "../../actions/account/suggestions";

import {
  fetchCurrentCompanyInfo as fetchCurrentCompanyInfoAction,
} from "../../actions/company/info";

import {
  getShouldFetchCurrentCompanyInfo as getShouldFetchCurrentCompanyInfoSelector,
} from "../../reducers/company/info";

import {
  getIsErrorFetchingSuggestions,
  getIsFetchingSuggestions,
  getSuggestionsByCurrentTerm,
} from "../../reducers/account/suggestions";

const getSuggestionValue = (currentTerm : string) => () => currentTerm,
  renderSuggestion = (suggestion : Suggestion) => (

      {` ${suggestion.Name}`}

  );

const AutosuggestStatus = ({ isError, isFetching } : AutosuggestStatusPropTypes) => {

  const iStyle = {
    position : "absolute",
    right    : 8,
    top      : 12,
  };

  if (isError) {
    return (

    );
  }

  if (isFetching) {
    return (

    );
  }

  return null;
};

const mapStateToProps = (state : State) => ({
    // suggestions
    currentTerm                : state.suggestions.currentTerm,
    isErrorFetchingSuggestions : getIsErrorFetchingSuggestions(state),
    isFetchingSuggestions      : getIsFetchingSuggestions(state),
    suggestions                : getSuggestionsByCurrentTerm(state),

    // company
    getShouldFetchCurrentCompanyInfo: getShouldFetchCurrentCompanyInfoSelector(state),
  }),
  mapDispatchToProps = (dispatch : Dispatch) => bindActionCreators({
    fetchSuggestions             : fetchSuggestionsAction,
    changeSuggestionsCurrentTerm : changeSuggestionsCurrentTermAction,

    // company
    fetchCurrentCompanyInfo: fetchCurrentCompanyInfoAction,
  }, dispatch);

class SearchCompany extends React.Component {

  props: SearchCompanyPropTypes;

  onChange: (event: any, something : {newValue : string}) => void;
  handleFetchRequested: (something: {value : string}) => void;
  handleClearRequested: (something: {value : string}) => Array<Suggestion>;

  handleSuggestionSelected: (
    event: any,
    something : {suggestion: Suggestion}
  ) => void;

  constructor (props : SearchCompanyPropTypes) {
    super(props);

    const {
      changeSuggestionsCurrentTerm,
    } = this.props;

    const timeoutDelay = 400;

    let timeoutFetchSuggestions : any = false;

    this.onChange = (
      event : any,
      { newValue } : {newValue: string }
    ) => changeSuggestionsCurrentTerm(newValue);

    this.handleFetchRequested = ({ value } : {value : string }) => {

      const {
        fetchSuggestions,
        currentTerm,
      } = this.props;

      const oldValue = (
          String(currentTerm).
          trim().
          toLowerCase()
        ),
        newValue = (
          String(value).
          trim().
          toLowerCase()
        ),
        theNewTermIsDifferent = (
          newValue !== oldValue
        ),
        newValueIsNotEmpty = (newValue !== ""),
        shouldFetchSuggestions = (
          theNewTermIsDifferent &&
          newValueIsNotEmpty
        );

      if (shouldFetchSuggestions) {
        if (timeoutFetchSuggestions) {
          window.clearTimeout(timeoutFetchSuggestions);
        }

        timeoutFetchSuggestions = setTimeout(() => {
          window.clearTimeout(timeoutFetchSuggestions);
          fetchSuggestions(value);
        }, timeoutDelay);
      }
    };

    this.handleClearRequested = () => [];

    this.handleSuggestionSelected = (
      event : any,
      { suggestion } : { suggestion : Suggestion }
    ) => {

      const {
        getShouldFetchCurrentCompanyInfo,
        fetchCurrentCompanyInfo,
        router,
      } = props;

      const companyID = String(suggestion.ID);

      if (getShouldFetchCurrentCompanyInfo(companyID)) {
        fetchCurrentCompanyInfo(companyID);
      }

      router.push(`/company/${companyID}`);
    };
  }

  shouldComponentUpdate (nextProps) {

    const hasSuggestionsChanged = (
        this.props.suggestions !== nextProps.suggestions
      ),
      hasValueChanged = (
        this.props.currentTerm !== nextProps.currentTerm
      ),
      hasFetchingChanged = (
        this.props.isFetchingSuggestions !== nextProps.isFetchingSuggestions
      ),
      hasErrorChanged = (
        this.props.isErrorFetchingSuggestions !== nextProps.isErrorFetchingSuggestions
      );

    return (
      hasSuggestionsChanged ||
      hasValueChanged ||
      hasFetchingChanged ||
      hasErrorChanged
    );
  }

  render () {
    const {
      isErrorFetchingSuggestions,
      isFetchingSuggestions,
      suggestions,
      currentTerm,
    } = this.props;

    const searchCompanyMessage = "Caută firmă...",
      inputProps = {
        "aria-label"      : searchCompanyMessage,
        "aria-labelledby" : searchCompanyMessage,
        "onChange"        : this.onChange,
        "placeholder"     : searchCompanyMessage,
        "tabIndex"        : 0,
        "value"           : currentTerm,
      },
      theme = {
        container            : "special-container",
        input                : "special-search-input form-control",
        suggestion           : "list-group-item suggestion-item",
        suggestionFocused    : "list-group-item active",
        suggestionsContainer : "suggestions-company-container",
      };

    return (

        <Autosuggest
          getSuggestionValue={getSuggestionValue(currentTerm)}
          inputProps={inputProps}
          onSuggestionSelected={this.handleSuggestionSelected}
          onSuggestionsClearRequested={this.handleClearRequested}
          onSuggestionsFetchRequested={this.handleFetchRequested}
          renderSuggestion={renderSuggestion}
          suggestions={suggestions}
          theme={theme}
          />
        <AutosuggestStatus
          isError={isErrorFetchingSuggestions}
          isFetching={isFetchingSuggestions}
        />

    );
  }
}

export default withRouter(
  connect(
    mapStateToProps,
    mapDispatchToProps,
  )(SearchCompany)
);

Sorry, but this code dump is not really useful.
Could you try to create a minimal Codepen example that demonstrates the issue?

Closing for now.

It is not solved,  but I can not figured out why it is not working.

@moroshko Did you encountered similar problems?

gooot it. this was the problem


Update docs and examples

#101  👈
main

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Join @catalyst17 and the rest of your teammates on  Graphite


upstream OptimismGenesisInfo to op-alloy

Describe the feature
move this function
https://github.com/paradigmxyz/reth/blob/b36bd58dbe1f2639ec5bb6bd5bcbc7b5a3cfb6fe/crates/chainspec/src/spec.rs#L1193-L1194
to op-alloy:
https://github.com/alloy-rs/op-alloy/blob/50101118dbfef913b936afa3bd4f10851fd1eafa/crates/rpc-types/src/genesis.rs#L6
Additional context
No response

I can take this

cool, I think the basefee param is reth native, so configuration of this we can still keep in reth

cool, I think the basefee param is reth native, so configuration of this we can still keep in reth

You mean OptimismBaseFeeInfo ? Because it's already in op-alloy


temp: make a workaround for policy with AllowAll to work

This patch is a workaround waiting better implementation.
It makes Trireme to ignore any policy with its TriremeAction set to policy.AllowAll. This works only during policy creation, not update yet.

Current coverage is 58.58% (diff: 0.00%)

Merging #129 into master will decrease coverage by 0.11%

@@             master       #129   diff @@
==========================================
  Files            25         25
  Lines          3029       3035     +6
  Methods           0          0
  Messages          0          0
  Branches          0          0
==========================================
  Hits           1778       1778
- Misses         1146       1151     +5
- Partials        105        106     +1

Powered by Codecov. Last update 2491711...598a1c8


Many calls to LoadInstances() in server do not have error checked

Looking through the code, I see that many calls to LoadInstances() does not have its error checked. For every call to LoadInstances, we should handle it as we are in places where we are already handling the error. This PR is relevant https://github.com/mattermost/mattermost-plugin-jira/pull/721

Hi @mickmister, I would like to give this one a shot.

Sounds good, thanks @haardikdharma10!


Capture screen in FF37-OSX not working: constraintsToFF37 mess up the constraints

I've run into an issue trying to capture the screen in FF37. When I invoke getUserMedia, no screen or window is shared, no dialogue is shown, and this appears in the logs
spec: {"audio":false,"video":{"mandatory":{"maxWidth":640,"maxFrameRate":15,"minFrameRate":15},"mozMediaSource":"screen","mediaSource":"screen"}}
ff37: {"audio":false,"video":{"mandatory":{"maxWidth":640,"maxFrameRate":15,"minFrameRate":15},"advanced":[{"mozMediaSource":{"min":"screen","max":"screen"}},{"mediaSource":{"min":"screen","max":"screen"}}]}}
TypeError: 'mediaSource' member of MediaTrackConstraintSet '[object Object]' is not a valid value for enumeration MediaSourceEnum.

It looks like the mangling done by the function constraintsToFF37 is not working/needed for FF37, as commenting out the call to the function allows me to share the screen again. I've finally changed the code from
  getUserMedia = (webrtcDetectedVersion < 38)

to
  getUserMedia = (webrtcDetectedVersion < 37)

and so far it's working fine. Could you please confirm this issue?
Thanks,

Confirmed. Thanks for reporting this! I'm working on a fix now. facingMode is likely affected as well.
A side-note on your example: The constraints you're passing in for everything but mediaSource are not to spec and don't work on Firefox, even with the adapter. That's probably why you don't notice a difference with your workaround, which effectively disables adapter's spec-translation for 37.

2nd side-note: it's just mediaSource. No implementation ever used mozMediaSource fwiw (I checked).

Thanks for confirming this. Also thanks for the tips about the constraints. I'll check them against the specs to have them according to that. Thanks also for spotting the 'mozMediaSource' issue, I'll fix that right away!

@igracia does this work for you now?

Yes, we have some automated tests running in Saucelabs and it's working.
I tried to have the constraints according to spec, as @jan-ivar pointed out, but it in fact made Chrome unable to share the screen (webcam was working fine) I still need to devote some time to test that correctly.

Chrome does screensharing it a little differently I believe and you have to execute it from an extension (you can enable getUserMedia desktop sharing via command line but that is for dev purposes only, also it can only do the whole screen, not just a window.)

Yes, I'm using my own extension for that. As I said, I need to give it a more thorough test. At the moment I checked with the spec constraints, it was a bit hectic around here so I couldn't double check that everything was in order. I'll check next week, and if it doesn't work I'll post again in a different issue.
Thanks!

Cool, sample extension here if you want some pointers.


API Design: Vertices lifetime

Hi!
The current version store the vertices slice in the following case:
if (allocatedBVHNodes < spaceNeeded) {
    verts = (bvhvec4*)vertices;
}

This means that it's technically possible to read garbage from a previous verts pointer. While this is a fixable bug, the lifetime of verts could be a bit improved since it's not directly clear from just the doc and the method declaration, that the vertices slice is kept around.
Pass Around Vertex Slice
Ideally, every function would just read the slice once, and not store it:
void BVH::Build(const bvhvec4* vertices, const unsigned primCount);
void BVH::Refit(const bvhvec4* vertices, const BVHLayout layout, const unsigned nodeIdx);
...

Makes it clear that vertices isn't bound to the bvh lifetime. It doesn't prevent user errors obviously:
bvh.Build(triangles, 36);
bvh.Refit(otherTriangles, 36); // Oops

This will be the case with the current solution as well.
SetVertices
Another solution could be to explicitly ask for the vertices?
void BVH::SetVertices(const bvhvec4* vertices, const unsigned primCount);

void BVH::Build() {
    FATAL_ERROR_IF(!verts, "BVH::Build(), no vertices (use SetVertices(vertices))" );
}

Let me know what you think, happy to contribute based on your preferences

The current approach is indeed not as safe as can be.
An intermediate solution would be to move the verts assignment outside the if statement, so that the pointer is refreshed even when there is enough space.
The solution of sending verts to each function, as you propose, is much safer still - but that also means that Intersect and IsOccluded needs to receive this data, from a point in user code where it may be quite inconvenient to obtain a verts pointer, which may perhaps lead to a different but similar copy of the verts pointer.
Another solution would be to actually copy the data pointed to by verts. Performance-wise this is not a huge issue - although it is of course wasteful, also in terms of memory use.
Or, we could have additional checks on the verts pointer and the data it points to but only in debug mode. Perhaps with a CRC32 over the data?

Copying to me is a bit much. I guess the best solution then is to keep the assignment out of the if, and add some information in the Build() doc that verts must lived throughout the entire usage of bvh, until Build is called again.

OK. For 1.0.5 the assignment is outside the if. Documentation is at the top of the priorities list, but you know how that goes... ;) At least every builder already has a comment there that says that you shouldn't delete the data.

@jbikker Would you be okay if I add a set of overloads to pass the vertices? I am asking because if I don't, it becomes impossible in Rust for the user to modify the original triangles list (since there is an immutable borrow in this library).
There are ways to circumvent that in Rust, but they aren't all amazing. I think if I could just pass the vertices slice when needed to tinybvh, would fix most of my issues.

This would be alternative access to Intersect and such? I am a bit
reluctant because a larger api will also be harder to maintain, but I don't
want to obstruct your Rust initiative either.

Jacco.

On Sat, Dec 14, 2024 at 5:07 PM David Peicho @.***>
wrote:

@jbikker https://github.com/jbikker Would you be okay if I add a set of
overloads to pass the vertices? I am asking because if I don't, it becomes
impossible in Rust for the user to modify the original triangles list
(since there is an immutable borrow in this library).
There are ways to circumvent that in Rust, but they aren't all amazing. I
think if I could just pass the vertices slice when needed to tinybvh,
would fix most of my issues.
—
Reply to this email directly, view it on GitHub
https://github.com/jbikker/tinybvh/issues/33#issuecomment-2543168966,
or unsubscribe
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.
You are receiving this because you were mentioned.Message ID:
@.***>

Actually just found a super elegant way to do it without changing anything in this library :) I hope I can release tomorrow!

That's great! Looking forward to it.
On Sat, Dec 14, 2024, 8:21 PM David Peicho @.***> wrote:

Actually just found a super elegant way to do it without changing anything
in this library :) I hope I can release tomorrow!
—
Reply to this email directly, view it on GitHub
https://github.com/jbikker/tinybvh/issues/33#issuecomment-2543318395,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AFH3PEHAAHOCWBX423TN6UD2FSANFAVCNFSM6AAAAABSZWAVNKVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDKNBTGMYTQMZZGU
.
You are receiving this because you were mentioned.Message ID:
@.***>


ImportError: cannot import name 'InvertedResidual' from 'trailmet.models.mobilenet'

Getting the following error in quantize folder where mobilenet import is done in files.
ImportError: cannot import name 'InvertedResidual' from 'trailmet.models.mobilenet' (/workspace/animesh_trailmet/trailmet/models/mobilenet.py)

Fixed in #116


Global Moth Model

A global moth species classifier

@adityajain07 Will you break up this issue into more issues, or have multiple tasks within this issue? I would recommend the former.

Sure! Here it is:

Prepare, analyze and verify the global moth checklist from GBIF
Prepare the webdataset with the latest DwC-A file
Train model

Following a conversation between AJ and DR, this model is the top priority from 23 Jul.

Code profilings to be done:

[ ] Uploading category map to W&B
[ ] Make the training code into a cli, like the ami-dataset module
[ ] Documentation
[ ] Check for preemption; resume training from last saved point
[ ] Test the code (with breakpoints) with a smaller dataset

Thanks for adding the code-profiling tasks above! How are you prioritising them with respect to the data prep/model training above?


publish<EMAIL_ADDRESS>

Requested by: @lucas-zimerman
Merge target: (default)
Quick links:

View changes
View check runs

Assign the accepted label to this issue to approve the release.
Leave a comment containing #retract under this issue to retract the release (original issuer only).
Targets

[ ] npm
[ ] github
[ ] registry

Targets marked with a checkbox have already been executed.  Administrators can manually tick a checkbox to force craft to skip it.

#retract PR changelog pointing to the wrong URL

#retract


Add DamianSawicki to organization members

Add Damian Sawicki (@DamianSawicki) to org members to make it easier to test future (and ongoing) PRs.  Contributions to date.

/cc @joamaki
FYI @ovidiutirla @kl52752 @robscott @bowei

General +1 here, can you just put it in alphabetical order?

General +1 here, can you just put it in alphabetical order?

Thanks! I believe the order in this file is first capitalized, then non-capitalized, both alphabetically.

No, it's good as is. What we'd need is a linter :smile_cat:

Wow, sorry totally missed that 😅  You are correct, please leave it as is


Set response body content is irrelevant

I want to edit the body of the response using
response.body()
But spark routes return String, always.
So if I edit the body, the return override the response body!
Am I missing something?
What is the reason spark routes always return String?

Normally you would just return returnString; instead of calling response.body(String returnString);
It's done that way because it made more sense to us compared to editing the body after it's been set.
I think there's a hack where you can do response.body("content");return "";, where the body will not be overwritten by the return value, but I don't have the time to check it out right now.

So could you say that res.body() is not useful?
Is there any reason to use that function?

In fact, @itaied246 , a spark.Route returns an Object. What are you trying to return?
Maybe you could add your custom implementation of spark.ResponseTransformer (i.e.: a json transformer) and use it as the third argument of the overloaded method of the  http-verb you are calling. For instance, if its a post, you should use the public static void post(String path, Route route, ResponseTransformer transformer) .
Hope it helps.

So could you say that res.body() is not useful?
Is there any reason to use that function?
In my opinion it's useless/dangerous and shouldn't be used. The only potential use-case I can think of is if you're building/appending the response string in multiple locations, but that's already bad design IMO. I don't know why it's part of the API and I would like to see it gone in version 3.0.

@juliccr I am trying to understand the purpose
res.body() was written for.
Since Route return an object, I don't see a reason to modify the response body.
I was looking for a way to modify the response body, and I find it easier to understand modifying the response body instead of returning an object.

Why closing it? I got to this issue because the actual behavior is misleading. I actually find the body() function useful, I don't see why it is a bad design, and if the method is there spark should consider it if used instead of the return.  For now return res.body() at the end of the rout configuration as workaround..

After reading this issue, I am still not clear on the semantic of .body()

what to do if want to return a response for xlsx file format


Not fixing indentation in long statement with multiple indentation levels and long string literals

Input
fn create_app() -> App {
    let mut app = App::new("A program name")
                .about("A program that does stuff to computers")
        .arg(
            Arg::with_name("disable_foo_bar")
            .long("disable-foo-bar")
            .help("Disable all the foos in the bar. Prevents things from going all baz on you for example")
            );
    app
}

Output
Nothing changes
Expected output
I expect the indentation of the .about(...), .long(...) and .help(...) as well as the final ); to be fixed. But they are not.
It all works as expected if the string passed to .help(....) is shorter.
fn create_app() -> App {
    let mut app = App::new("A program name")
        .about("A program that does stuff to computers")
        .arg(
            Arg::with_name("disable_foo_bar")
                .long("disable-foo-bar")
                .help("Disable all the foos in the bar. Prevents things from going all baz on you for example")
        );
    app
}

Meta

rustfmt version: Tested on both rustfmt 1.4.16-stable (939e164 2020-06-11) and rustfmt 2.0.0-rc.2-nightly (2c39e809 2020-07-10)
From where did you install rustfmt?: 1.4.16 via the default component via rustup. 2.0.0.-rc.2 from the git master branch today.

Maybe a dupe of #4183?

Yeah this is a duplicate of several issues, all driven by rustfmt's current behavior wherein if any single chain item exceeds max_width then the entire chain is left unformatted.
The general consensus/desire seems to be to have rustfmt format the chain anyway (and just let the problematic item(s) exceed the width). I spent some time a while ago fighting this and had a semi-working fix though I was somewhat unhappy with my implementation attempt and dropped it :smile:
Part of the challenge with carrying on with formatting the entire chain is dealing with certain combinations of indent_style and where the long item is within the chain. For example when indent_style is Visual and the long chain item is the parent or first item, you can end up with a formatted result that's far worse than the original.
Anyway, thanks for reporting this @faern but I'm going to close this given the dupe nature. Feel free to track #4183!


fix: add profile link into mobile nav

closes #159

:tada: This PR is included in version 1.50.2 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


feat: create frontend coding exercise

The first file should be a screenshot of what the "completed" exercise should look like. I've removed three bits of code and noted the locations with TODO's. I've also hard-coded the search results since I can sometimes get the pdf to load but usually apryse crashes.
So there are two reasons to post a review here.

I want to make sure we're ok with releasing this code to a candidate. It's lifted from our codebase and then heavily modified. I've made this a public repo. But I guess there are probably ways to zip it that might make more sense? I've run this by Chris and he's ok with it.
Give you a chance to weigh in on the idea/format/extent of the exercise.

wanted to give some feedback since interview is tomorrow. Overall this looks good but you may want to use something else as a marker other than a TODO since there's TODOs that go copied over from our original code. Or maybe remove the unrelated TODOs. Something so that the candidate isn't confused by them. I already moved away from the changes so lost the exact spots but for example I saw a comment like "TODO this should be done in the instance provider".
I think this is a good exercise that we can iterate on. Depending on the candidate does, we could probably simplify some things here

wanted to give some feedback since interview is tomorrow. Overall this looks good but you may want to use something else as a marker other than a TODO since there's TODOs that go copied over from our original code. Or maybe remove the unrelated TODOs. Something so that the candidate isn't confused by them. I already moved away from the changes so lost the exact spots but for example I saw a comment like "TODO this should be done in the instance provider".
I think this is a good exercise that we can iterate on. Depending on the candidate does, we could probably simplify some things here

I removed the excess TODO's in our code and renamed the ones that were left to "Not implemented".  I'm sure it'll be fine.
Yeah, there's definitely room for iteration here. But I was trying to be fairly strict about time-boxing this to a half a day's work on the first pass. My philosophy here is to create something a little more complicated, that requires a bit of context. In other words, something to encourage back and forth between us and the candidate to see if they know how to ask for help and can act on that advice. But I am concerned that I erred on the wrong side of hard.


Need clarification: Ollama and codellama-70b running. Will Llama Coder use this?

As title says
If I've already pulled the new (as of 2024-01-30) codellama-70b from meta (or python variant)
Will Llama Coder use this?
Or does it download the 34b and run that?
Does it just run whatever I'm running in Ollama and the list of models you provide are more "recommendations"?
Instructions seem to contradict or are not clear.
One one hand it simply says:

Local Installation
Install Ollama on local machine and then launch the extension in VSCode, everything should work as it is.

But then below that, the list of models doesn't go to 70b and probably doesn't include the new meta ones 70b, 70b python and 70b instruct?
Since my machine is capable of running it, I would prefer to.
Successfully running (and quite fast!) ollama run codellama:70b from here: https://ollama.ai/library/codellama:70b
Only reason I haven't simply installed and launched is because I don't want to end up with a 34b download in an unspecified location despite already running 70b :)
Thanks

I tried it anyway, nothing printed to the console that is running Ollama.
Weirdly it was also very slow? Not sure if it using the model I downloaded/am running in Ollama, or something else happened. How to tell, when there is no output to the console?
Console/Ubuntu in WSL is running Ollama and codellama:70b. But this page only lists codellama:70b-instruct
https://continue.dev/docs/model-setup/select-model

So maybe a 70b isn't the best (fastest) for code completion.
Which is odd because the default, as very small, surely would be less correct?? Not sure I understand completely here.
Anyway -
Say I want to run the default, stable-code:3b-code-q4_0.
Do I need to have pulled that manually via Ollama or does starting up Llama Coder do that in the background for me?
I find the instructions for these code completion tools fairly vague. I don't want it downloading models of it's own accord and storing them somewhere, if I already have them.
Is the 3b the default because it's fast or because you believe it's better than a 7b or 13b (which also seem to run fast enough on my 2x 4090s).
Is there a recommended default for Mac laptops with M chips and heat issues vs large desktop PCs with various GPUs?

For this extension you gonna need FIM (Fill-In-Middle) version of CodeLlama-70b, i.e. https://ollama.ai/library/codellama:70b-code or it's derivatives.
To use it, in extension settings select 'Custom' in 'Inference: Model' dropdown and put model name in 'Inference > Custom: Model' textbox, codellama:70b-code for example. Also make sure 'codellama' option is selected in 'Inference > Custom: Format' dropdown list.
You could try to use non-FIM model 'codellama:70b' (configured the same way as described above) but I doubt it will produce output the extension expects.

Latest version has 70b model


lsp infinite loop in chalk

In my project I always get rust-analyser stuck and have to reload vscode to get it to work again.
By attaching a debugger to the lsp_server, its never getting out of:
ra_lsp_server.exe!_ZN155_$LT$chalk_solve..solve..slg..SlgContextOps$LT$TF$GT$$u20$as$u20$chalk_engine..context..ContextOps$LT$chalk_solve..solve..slg..SlgContext$LT$TF$GT$$GT$$GT$21instantiate_ex_clause17hc19f8c48832172ebE

I think that's https://github.com/rust-lang/chalk/issues/280

cc https://github.com/rust-analyzer/rust-analyzer/issues/2052 (we need re-check this once that is fixed)

I found out the file I should not open that trigger this. I can't share it, but it contains a few methods that looks like the test case made by nikomatsakis.


bot receives messages that are not sent to him

In the following code, I create 3 contacts:

user, which represents the bot, and
contactA, contactB which represent his 2 contacts.

Then I let contactA send a message to contactB. I suppose bot will not receive this message event because it's not sent to user or any room that he is in, but actually it receives this message event. Why?
var { Wechaty, Message } = require('wechaty')
var { PuppetMock, mock: { Mocker } } = require('wechaty-puppet-mock');

async function main() {
	var mocker = new Mocker();

	var puppet = new PuppetMock({ mocker });
	var bot = new Wechaty({ puppet });

	bot.on('message', message => {
		console.log(`bot received ${message.text()} from ${message.talker().payload.id}`);
	});

	await bot.start();

	mocker.scan('https://github.com/wechaty', 1);
	var user = mocker.createContact({ id: 'user' });
	mocker.login(user);

	var contactA = mocker.createContact({ id: 'contactA' });
	var contactB = mocker.createContact({ id: 'contactB' });

	contactA.say("a").to(contactB);
};

main();

The consequence is that, if I use() a Wechaty plugin, it will not work, because Wechaty plugin never suppose it will receive any messages that is not sent to the logged-in user, isn't it?

Hi Panlina,
It's great to read your issue!
Very few people will do bot testing in our community, and you are one of them. ;-)
Can you join our Discord community and DM me? I'd love to work with you to improve the puppet-mock for Wechaty!
https://discord.gg/7q8NBZbQzt


feat(jsii): Implement --watch support

Re-wrote JSII using the TypeScript compiler services API, integrating with the ts.ProgramBuilder classes so that incremental build is possible. Additonally, error messages leverage TypeScript's built-in diagnostic formatter, and enable the rendering of code excerpts with error messages.
The error message generation can be further improved by maintaining a map of entity (type, method, property, parameter, ...) to node, which could then be used by the Validator class to emit error messages that are tied to the source code. This was omitted for now as the change is already substantial enough.
I have successfully built the AWS CDK using this enhanced compiler. Also, it produces almost no changes in the regression tests' output (only change is that it is now able to carry enum member documentation).

Rebase
Fix title of the PR


added JavaScript primitive data type question.

Please check if this PR fulfills these

[ ] The commit message is descriptive of changes
[x] You have tried at least one local test (this includes viewing the changes on your local fork)
[x] Docs have been added / updated as needed (for bug fixes / features)

What kind of change does this PR introduce?

[ ] Typo / Doc Update
[ ] Bug Fix
[x] Feature / New Item

What is the new behavior (if this is a feature change)?

[x] Added Interview Technical Question
[ ] Added Interview Whiteboard Question
[ ] Corrected existing items
[ ] Other

Adding new question ? Please check if this PR fulfills these

[x] <title> tag has been updated
[x] <h1> tag has been updated
[x] new file is kabob-case-like-this.html
[x] link to question has been added in technical.html or whiteboard.html

Other information:

This is great work! We're all still learning! Thank you for your contribution!


mdbx implementation

Closes #455
Description
Add the database interfaces and implementation.

Database: contains all of Juno's tables (or "buckets"). This is represented by mdbx's "environment" struct, which manages the on-disk database file.
Transaction: creates buckets and opens cursors on buckets.
Cursor: modifies the database, moves to keys in the database

We will probably need to add more functionality to the Cursor interface (e.g, ForEach, PutMulti, etc.) in the future, but it may make sense to add those incrementally rather than making this PR larger.
Types of changes

New feature (non-breaking change which adds functionality)
Documentation Update

Testing
Requires testing: Yes
Did you write tests??: Yes
Documentation
If this requires a documentation update, did you add one? Yes: comments added where necessary

Remaining to do:

[ ] Add error types/functions
[ ] Investigate mdbx flags and options to ensure we're using a robust configuration
[ ] Add additional functionality to the cursor interface, if possible.

Thanks for the feedback and tips @omerfirmak! Much appreciated. I've updated the comments on the db interface and will aim for your suggested git conventions in the future.


[BUG]: variable outputPath changes DotNetCoreCLI@2 build output path

Task name
DotNetCoreCLI@2
Task version
2.221.0
Environment type (Please select at least one enviroment where you face this issue)

[ ] Self-Hosted
[X] Microsoft Hosted
[ ] VMSS Pool
[ ] Container

Azure DevOps Server type
dev.azure.com (formerly visualstudio.com)
Azure DevOps Server Version (if applicable)
No response
Operation system
windows-latest
Task log
Task         : .NET Core
Description  : Build, test, package, or publish a dotnet application, or run a custom dotnet command
Version      : 2.221.0
Author       : Microsoft Corporation
Help         : https://docs.microsoft.com/azure/devops/pipelines/tasks/build/dotnet-core-cli
==============================================================================
C:\Windows\system32\chcp.com 65001
Active code page: 65001
Info: .NET Core SDK/runtime 2.2 and 3.0 are now End of Life(EOL) and have been removed from all hosted agents. If you're using these SDK/runtimes on hosted agents, kindly upgrade to newer versions which are not EOL, or else use UseDotNet task to install the required version.
C:\hostedtoolcache\windows\dotnet\dotnet.exe build D:\a\1\s\xxxAPITests\xxxAPITests.csproj "-dl:CentralLogger,\"D:\a\_tasks\DotNetCoreCLI_5541a522-603c-47ad-91fc-a4b1d163081b\2.221.0\dotnet-build-helpers\Microsoft.TeamFoundation.DistributedTask.MSBuild.Logger.dll\"*ForwardingLogger,\"D:\a\_tasks\DotNetCoreCLI_5541a522-603c-47ad-91fc-a4b1d163081b\2.221.0\dotnet-build-helpers\Microsoft.TeamFoundation.DistributedTask.MSBuild.Logger.dll\"" --configuration Release
MSBuild version 17.3.2+561848881 for .NET
  Determining projects to restore...
  Restored D:\a\1\s\xxxAPI\xxxAPI.csproj (in 658 ms).
  Restored D:\a\1\s\xxxAPITests\xxxAPITests.csproj (in 658 ms).
  xxxAPI -> D:\a\1\a\bin\PublishOutput\API\net6.0\xxxAPI.dll
  xxxAPITests -> D:\a\1\a\bin\PublishOutput\API\net6.0\xxxAPITests.dll

Build succeeded.
    0 Warning(s)
    0 Error(s)

Time Elapsed 00:00:14.99
C:\hostedtoolcache\windows\dotnet\dotnet.exe build D:\a\1\s\xxxAPI\xxxAPI.csproj "-dl:CentralLogger,\"D:\a\_tasks\DotNetCoreCLI_5541a522-603c-47ad-91fc-a4b1d163081b\2.221.0\dotnet-build-helpers\Microsoft.TeamFoundation.DistributedTask.MSBuild.Logger.dll\"*ForwardingLogger,\"D:\a\_tasks\DotNetCoreCLI_5541a522-603c-47ad-91fc-a4b1d163081b\2.221.0\dotnet-build-helpers\Microsoft.TeamFoundation.DistributedTask.MSBuild.Logger.dll\"" --configuration Release
MSBuild version 17.3.2+561848881 for .NET
  Determining projects to restore...
  All projects are up-to-date for restore.
  xxxAPI -> D:\a\1\a\bin\PublishOutput\API\net6.0\xxxAPI.dll

Build succeeded.
    0 Warning(s)
    0 Error(s)

Time Elapsed 00:00:01.54
Info: Azure Pipelines hosted agents have been updated and now contain .Net 5.x SDK/Runtime along with the older .Net Core version which are currently lts. Unless you have locked down a SDK version for your project(s), 5.x SDK might be picked up which might have breaking behavior as compared to previous versions. You can learn more about the breaking changes here: https://docs.microsoft.com/en-us/dotnet/core/tools/ and https://docs.microsoft.com/en-us/dotnet/core/compatibility/ . To learn about more such changes and troubleshoot, refer here: https://docs.microsoft.com/en-us/azure/devops/pipelines/tasks/build/dotnet-core-cli?view=azure-devops#troubleshooting
Finishing: Build .NET Core Projects

Relevant log output
Restored D:\a\1\s\xxxAPI\xxxAPI.csproj (in 658 ms).
  Restored D:\a\1\s\xxxAPITests\xxxAPITests.csproj (in 658 ms).
  xxxAPI -> D:\a\1\a\bin\PublishOutput\API\net6.0\xxxAPI.dll
  xxxAPITests -> D:\a\1\a\bin\PublishOutput\API\net6.0\xxxAPITests.dll

Aditional info
Below is the pipeline's yml. A variable $(outputPath) is declared in the "Variables" section. It is a path string to be used in a later irrelevant step.

Later the 4th task: DotNetCoreCLI@2 (displayName: Build .NET Core Projects) is to build the .csproj files. The repo has 2 .cs projects, one "xxxAPI" another "xxxAPITests".

The bug shows the $(outputPath) changes the build task's both projects' DLL output path, although the $(outputPath) is not not used in anywhere of the task. The Log shows DLL Output (in the above Log output) are affected by the $(outputPath) variable, you can see the path section "PublishOutput\API" is added in the log's DLL build output path.

Workaround: change $(outputPath) to a different name fixes the issue. However I expect either the bug could be fixed, or there are documents provide a list of reserved variable names, or there could be warning messages in the log to indicate the Task does not like the variable with name outputPath.

######################################################################3
name: $(Build.DefinitionName)_$(SourceBranchName)_$(Date:yyyyMMdd)_$(Rev:r)

trigger:
- main

pool:
  vmImage: 'windows-latest'

variables:
  solution: '**/*.sln'
  buildPlatform: 'Any CPU'
  outputPath: $(Build.ArtifactStagingDirectory)/bin/PublishOutput/API # I created this variable for a step after dotnet build

steps:
- task: NuGetToolInstaller@1
  retryCountOnTaskFailure: 3
- task: NuGetCommand@2
  retryCountOnTaskFailure: 3
  inputs:
    restoreSolution: '$(solution)'
- task: UseDotNet@2
  displayName: "Use .Net Core sdk"
  inputs:
    packageType: sdk
    version: 6.0.x
    installationPath: $(Agent.ToolsDirectory)/dotnet
- task: DotNetCoreCLI@2
  displayName: Build .NET Core Projects # should not be affected by outputPath variable as it is not used in the input arguments
  inputs:
    command: 'build'
    arguments: '--configuration $(buildConfiguration)'
    projects: |
      **/*.csproj
      !**/*SQLTests*.csproj
#################################################################

I think this is a side effect of how MSBuild works.
Variables become environment variables in all steps.  MSBuild will take the default value for a property from the environment variable with the same name.  The property MSBuild uses to determine where to output files to is OutputPath, and so the outputPath variable becomes where msbuild emits the files to.
If you run set the OutputPath environment variable locally and then try dotnet build locally, you'll encounter the same thing.
$env:OutputDir = 'c:\temp\`
dotnet build

You'll need to pick a variable name that doesn't conflict with an msbuild property
https://learn.microsoft.com/en-us/visualstudio/msbuild/common-msbuild-project-properties?view=vs-2022

OutputPath
All
Specifies the path to the output directory, relative to the project directory, for example, bin\Debug or bin\Debug$(Platform) in non-AnyCPU builds.

You can use this behaviour to your advantage - if you've got multiple dotnet steps, and you're passing the same arguments to them, rather than repeatedly passing to several dotnet steps, you can set the values as variables and the various dotnet steps will pick them up.  (e.g. configuration, versionPrefix, versionSuffix)

I think this is a side effect of how MSBuild works.
Variables become environment variables in all steps. MSBuild will take the default value for a property from the environment variable with the same name. The property MSBuild uses to determine where to output files to is OutputPath, and so the outputPath variable becomes where msbuild emits the files to.
If you run set the OutputPath environment variable locally and then try dotnet build locally, you'll encounter the same thing.
$env:OutputDir = 'c:\temp\`
dotnet build

You'll need to pick a variable name that doesn't conflict with an msbuild property https://learn.microsoft.com/en-us/visualstudio/msbuild/common-msbuild-project-properties?view=vs-2022
OutputPath	All	Specifies the path to the output directory, relative to the project directory, for example, bin\Debug or bin\Debug$(Platform) in non-AnyCPU builds.
You can use this behaviour to your advantage - if you've got multiple dotnet steps, and you're passing the same arguments to them, rather than repeatedly passing to several dotnet steps, you can set the values as variables and the various dotnet steps will pick them up. (e.g. configuration, versionPrefix, versionSuffix)

Thanks afscrome and it makes sense to me. However, this is very indirect and difficult for me to work out the root cause and it relies on prior knowledge of MSBuild. Also, we have to assume the "DotNetCoreCLI@2 build" relies on MSBuild (I don't find a document confirming this). And users should have experience with MSBuild to be able to suspect the name "outputPath" could be a variable used in the build process (so no way could workaround this issue like me). The document you shared is related to MSBuild, which also does not mention Azure Pipeline and "DotNetCoreCLI@2 build".
As I have suggested in the "Additional Info" section, I expect its documents should provide a link from the Azure Pipeline Dot Net CLI task's page to point to this MSBuild page that you shared so that users could easily figure out this issue and be clearer about the underlying mechanism.


Getting clear on how it works in real world as local url is appearing in live staging site

Have this working locally ok DDev, Craft 4 latest plugin
Question
The tag:  {{ craft.vite.script("assets/js/app.js", false) }} - is this intended for dev, staging, and production?
When pushed to staging server (ENV=dev) what is getting output is:

Is this because of DEV env or something else?
Also is vite config only used in dev? Does it need changing for each ENV?
Any light welcome:)

Yes, you use the same tag in all environments.
What it should do in each environment is determined in the config/vite.php file:
https://nystudio107.com/docs/vite/#the-config-php-file

Just to add - I wasnt ready for this to close :(
So my issue appears to be devServerPublic settings - great.
But what determines 'when not using the dev server' ?
Is this by env variable in .env?
'devServerPublic' => 'http://localhost:5173/',
/**
 * @var string The public URL to use when not using the dev server
 */
'serverPublic' => App::env('PRIMARY_SITE_URL') . '/dist/',


inference script not working

applied tools/inference.py on DOTA Test set 2 images, still no bounding boxes. Adjusted libs/configs/cfgs.py VIS_SCORE to 0.0, still no bounding boxes.
Here's the code I used
python inference.py --data_dir '/dir/of/2/test/images/' --save_dir '/my/chosen/folder/' --gpu 0 --draw_imgs
Here's the output running inference script on DOTA Test set P0034.png

Originally posted by @ncdejito in https://github.com/Thinklab-SJTU/R3Det_Tensorflow/issues/7#issuecomment-637639110

weights and folder locations

infinference.py is used for small images. @ncdejito

tried test_dota_r3det_plusplus.py, still no bounding boxes.
cd ~/R3Det_Tensorflow/tools
python test_dota_r3det_plusplus.py --test_dir='/dir/of/2/test/images/' --gpus=0 --show_box
cd test_dota/RetinaNet_DOTA_R3Det_2x_20200501/dota_img_vis

ran with gpus param 0-7, still no bounding boxes.
cd ~/R3Det_Tensorflow/tools
python test_dota_r3det_plusplus.py --test_dir='/dir/of/2/test/images/' --gpus=0,1,2,3,4,5,6,7 -s
cd test_dota/RetinaNet_DOTA_R3Det_2x_20200501/dota_img_vis

python: 3.5.6
cuda: 10.0.130
cv2: 4.2.0
tfplot: 0.2.0
tf: 1.13.2
OS: Ubuntu 16.04

tried cropping to 600x600 images, still no bounding boxes

This line of code needs to be adjusted according to the model you use

This line of code needs to be adjusted according to the model you use

I have met the same question,and the picture cannot be opened so I cannot see the solution in the picture, would you please describe how can I fix this bug? Thanks!

Hello, I'm having the same issue as above. For any config file I use, I get no predictions. I'm using the docker image, the DOTA training set, and cropped images. (1024x1024). Anyone have any luck getting this working?

I am facing a similar Issues when trying to run the ResNet152_v1d MS model
I have loaded the pre-trained model in the output/trained_weights as shown below

I have also loaded the pre-trained weights in the data/pretrained_weights as shown below

I have also modified the cfgs.py code with the cfgs_res152_dota_r3det_plusplus_v1.py code.
I execute the code using python test_dota_r3det_plusplus_ms.py --test_dir='../data/dataset/test/' --gpus=0 -s
The model runs, but the output images have no bounding boxes. Am I doing something wrong?

Need to be modified to the following
from libs.networks import build_whole_network_r3det_plusplus

Yes I have made the modification in test_dota_r3det_plusplus_ms.py file

Is there any other file in which this modification needs to be done?


Change install path of mamba env in container

Changes install path of mamba env in container due to conflict when mounting code on nautilius
Adds documentation on mounting local code into containers at runtime

@deepchatterjeeligo gonna merge this in to get the container build updated so I can test out tuning, but let me know if anything looks off.


Cloud Vision API - Authentication using API Key

Using an API key with the https://vision.googleapis.com/v1/images:annotate endpoint via curl works as expected which means API keys can be used with the cloud vision API.
As per discussion here https://github.com/googleapis/google-cloud-java/issues/1405 supplying a GOOGLE_API_KEY environment variable while ensuring no GOOGLE_APPLICATION_CREDENTIALS variable is set should mean that API key based authentication should be used by the client lib. However the following code:
class GCPCloudVisionClient {

    public void initialiseClient() throws IOException {
        ImageAnnotatorClient imageAnnotatorClient = ImageAnnotatorClient.create();
    }

    public static void main(String[] args) {
        GCPCloudVisionClient gcpCloudVisionClient = new GCPCloudVisionClient();
        try {
            gcpCloudVisionClient.initialiseClient();
        } catch (IOException e) {
            e.printStackTrace();
        }
    }
}

fails with the following exception
java.io.IOException: The Application Default Credentials are not available. They are available if running in Google Compute Engine. Otherwise, the environment variable GOOGLE_APPLICATION_CREDENTIALS must be defined pointing to a file defining the credentials. See https://developers.google.com/accounts/docs/application-default-credentials for more information.
	at com.google.auth.oauth2.DefaultCredentialsProvider.getDefaultCredentials(DefaultCredentialsProvider.java:131)
	at com.google.auth.oauth2.GoogleCredentials.getApplicationDefault(GoogleCredentials.java:127)
	at com.google.auth.oauth2.GoogleCredentials.getApplicationDefault(GoogleCredentials.java:100)
	at com.google.api.gax.core.GoogleCredentialsProvider.getCredentials(GoogleCredentialsProvider.java:59)
	at com.google.api.gax.rpc.ClientContext.create(ClientContext.java:132)
	at com.google.cloud.vision.v1.stub.GrpcImageAnnotatorStub.create(GrpcImageAnnotatorStub.java:84)
	at com.google.cloud.vision.v1.stub.ImageAnnotatorStubSettings.createStub(ImageAnnotatorStubSettings.java:120)
	at com.google.cloud.vision.v1.ImageAnnotatorClient.<init>(ImageAnnotatorClient.java:136)
	at com.google.cloud.vision.v1.ImageAnnotatorClient.create(ImageAnnotatorClient.java:117)
	at com.google.cloud.vision.v1.ImageAnnotatorClient.create(ImageAnnotatorClient.java:108)

Does this indicate a bug in the client library where in it doesn't use the API key supplied as expected?

Translate is apiary based client(also that solution only applied to translate don't know why), while vision uses grpc transport. GRPC transport needs proper authentication as described in readme Closing this issue for now. Please reopen if you need further help.


update vscode directory

closes #916
Even if we ignore the directory, because we added the files to the index, it'll keep tracking changes if users make changes. With this, users must copy the config files over to their .vscode directory where changes will not be tracked.

This is certainly an improvement, but it begs the question, what is preventing me from modifying the files in .vscode-config and accidentally pushing a commit with my sas key or client_secret?

@ahsonkhan its a good question. In theory, nothing. However in this case, because the files are useless in this new directory, it's less likely to happen; someone has to copy them over to get any use out of them. An alternative might be to take what is in these JSON files and put them in a README somewhere where someone could copy and paste from there, but it adds a bit of friction.

An alternative might be to take what is in these JSON files and put them in a README somewhere where someone could copy and paste from there, but it adds a bit of friction.

That might be better given the potential info disclosure issue, but I don't have a good sense of how much friction doing so would add, so don't have a strong preference one way or another atm.