Code for "Audio-driven Talking Face Video Generation with Learning-based Personalized Head Pose"

Overview

Audio-driven Talking Face Video Generation with Learning-based Personalized Head Pose

We provide PyTorch implementations for our arxiv paper "Audio-driven Talking Face Video Generation with Learning-based Personalized Head Pose"(http://arxiv.org/abs/2002.10137).

Note that this code is protected under patent. It is for research purposes only at your university (research institution) only. If you are interested in business purposes/for-profit use, please contact Prof.Liu (the corresponding author, email: [email protected]).

We provide a demo video here (please search for "Talking Face" in this page and click the "demo video" button).

Colab

Our Proposed Framework

Prerequisites

  • Linux or macOS
  • NVIDIA GPU
  • Python 3
  • MATLAB

Getting Started

Installation

  • You can create a virtual env, and install all the dependencies by
pip install -r requirements.txt

Download pre-trained models

  • Including pre-trained general models and models needed for face reconstruction, identity feature extraction etc
  • Download from BaiduYun(extract code:usdm) or GoogleDrive and copy to corresponding subfolders (Audio, Deep3DFaceReconstruction, render-to-video).

Download face model for 3d face reconstruction

Fine-tune on a target peron's short video

    1. Prepare a talking face video that satisfies: 1) contains a single person, 2) 25 fps, 3) longer than 12 seconds, 4) without large body translation (e.g. move from the left to the right of the screen). An example is here. Rename the video to [person_id].mp4 (e.g. 1.mp4) and copy to Data subfolder.

Note: You can make a video to 25 fps by

ffmpeg -i xxx.mp4 -r 25 xxx1.mp4
    1. Extract frames and lanmarks by
cd Data/
python extract_frame1.py [person_id].mp4
    1. Conduct 3D face reconstruction. First should compile code in Deep3DFaceReconstruction/tf_mesh_renderer/mesh_renderer/kernels to .so, following its readme, and modify line 28 in rasterize_triangles.py to your directory. Then run
cd Deep3DFaceReconstruction/
CUDA_VISIBLE_DEVICES=0 python demo_19news.py ../Data/[person_id]

This process takes about 2 minutes on a Titan Xp.

cd Audio/code/
python train_19news_1.py [person_id] [gpu_id]

The saved models are in Audio/model/atcnet_pose0_con3/[person_id]. This process takes about 5 minutes on a Titan Xp.

    1. Fine-tune the gan network. Run
cd render-to-video/
python train_19news_1.py [person_id] [gpu_id]

The saved models are in render-to-video/checkpoints/memory_seq_p2p/[person_id]. This process takes about 40 minutes on a Titan Xp.

Test on a target peron

Place the audio file (.wav or .mp3) for test under Audio/audio/. Run [with generated poses]

cd Audio/code/
python test_personalized.py [audio] [person_id] [gpu_id]

or [with poses from short video]

cd Audio/code/
python test_personalized2.py [audio] [person_id] [gpu_id]

This program will print 'saved to xxx.mov' if the videos are successfully generated. It will output 2 movs, one is a video with face only (_full9.mov), the other is a video with background (_transbigbg.mov).

Colab

A colab demo is here.

Acknowledgments

The face reconstruction code is from Deep3DFaceReconstruction, the arcface code is from insightface, the gan code is developed based on pytorch-CycleGAN-and-pix2pix.

Comments
  • FileNotFoundError: [Errno 2] No such file or directory: '/home/yugaljain03/audio_face_animation/audio_driven_headpose/Audio-driven-TalkingFace-HeadPose/render-to-video/../Deep3DFaceReconstruction/output/render/19_news/33/bm/frame18_renderold_bm.png'

    FileNotFoundError: [Errno 2] No such file or directory: '/home/yugaljain03/audio_face_animation/audio_driven_headpose/Audio-driven-TalkingFace-HeadPose/render-to-video/../Deep3DFaceReconstruction/output/render/19_news/33/bm/frame18_renderold_bm.png'

    @yiranran I am unable to find rederold_bm.png files in bm folder. What script I should run to generate these files? Please help me to solve this..

    PS - II am running demo colab file which is mentioned in README and I already installed octave as per given instructions in demo colab link in Readme.. Thanks

    opened by yugaljain1999 6
  • basic information about code

    basic information about code

    I run `runtest.sh', appeared errors

    Extracting Bazel installation...
    Starting local Bazel server and connecting to it...
    WARNING: Download from https://mirror.bazel.build/github.com/bazelbuild/rules_cc/archive/8bd6cd75d03c01bb82561a96d9c1f9f7157b13d0.zip failed: class java.io.IOException connect timed out
    WARNING: Download from https://mirror.bazel.build/github.com/bazelbuild/rules_java/archive/7cf3cefd652008d0a64a419c34c13bdca6c8f178.zip failed: class java.io.IOException connect timed out
    INFO: SHA256 (https://github.com/google/googletest/archive/master.zip) = dc68f063f82052444a11186a476f3ff02aeb88038e7390229ce4b773bd4ea158
    DEBUG: Rule 'com_google_googletest' indicated that a canonical reproducible form can be obtained by modifying arguments sha256 = "dc68f063f82052444a11186a476f3ff02aeb88038e7390229ce4b773bd4ea158"
    DEBUG: Repository com_google_googletest instantiated at:
      no stack (--record_rule_instantiation_callstack not enabled)
    Repository rule http_archive defined at:
      /home/puaiuc/.cache/bazel/_bazel_puaiuc/dbf87e3e58b07c8f4c9b973173f78069/external/bazel_tools/tools/build_defs/repo/http.bzl:336:16: in <toplevel>
    INFO: Repository remote_coverage_tools instantiated at:
      no stack (--record_rule_instantiation_callstack not enabled)
    Repository rule http_archive defined at:
      /home/puaiuc/.cache/bazel/_bazel_puaiuc/dbf87e3e58b07c8f4c9b973173f78069/external/bazel_tools/tools/build_defs/repo/http.bzl:336:16: in <toplevel>
    WARNING: Download from https://mirror.bazel.build/bazel_coverage_output_generator/releases/coverage_output_generator-v2.1.zip failed: class java.io.IOException connect timed out
    ERROR: An error occurred during the fetch of repository 'remote_coverage_tools':
       java.io.IOException: Error downloading [https://mirror.bazel.build/bazel_coverage_output_generator/releases/coverage_output_generator-v2.1.zip] to /home/puaiuc/.cache/bazel/_bazel_puaiuc/dbf87e3e58b07c8f4c9b973173f78069/external/remote_coverage_tools/coverage_output_generator-v2.1.zip: connect timed out
    ERROR: /home/puaiuc/.cache/bazel/_bazel_puaiuc/dbf87e3e58b07c8f4c9b973173f78069/external/bazel_tools/tools/test/BUILD:36:1: @bazel_tools//tools/test:coverage_report_generator depends on @remote_coverage_tools//:coverage_report_generator in repository @remote_coverage_tools which failed to fetch. no such package '@remote_coverage_tools//': java.io.IOException: Error downloading [https://mirror.bazel.build/bazel_coverage_output_generator/releases/coverage_output_generator-v2.1.zip] to /home/puaiuc/.cache/bazel/_bazel_puaiuc/dbf87e3e58b07c8f4c9b973173f78069/external/remote_coverage_tools/coverage_output_generator-v2.1.zip: connect timed out
    ERROR: Analysis of target '//mesh_renderer:mesh_renderer_test' failed; build aborted: Analysis failed
    

    Can you help me,thanks.

    opened by Adorablepet 4
  • No 60_net_G.pth file

    No 60_net_G.pth file

    Running this project on colab Getting error on running train19_news1.py here is colab https://colab.research.google.com/drive/1FXoqSLC_y6UpDDcbxGefwMDBh9UTipvZ

    And error

    /content/Audio-driven-TalkingFace-HeadPose/render-to-video
    19_news/11 11_bmold_win3
    sh: 1: matlab: not found
    loading models/model-r100-ii/model 0
    [20:08:28] src/nnvm/legacy_json_util.cc:209: Loading symbol saved by previous version v1.2.0. Attempting to upgrade...
    [20:08:28] src/nnvm/legacy_json_util.cc:217: Symbol successfully upgraded!
    
    Segmentation fault: 11
    
    Stack trace:
      [bt] (0) /usr/local/lib/python3.6/dist-packages/mxnet/libmxnet.so(+0x3c27360) [0x7f214559b360]
    loading models/model-r100-ii/model 0
    [20:08:30] src/nnvm/legacy_json_util.cc:209: Loading symbol saved by previous version v1.2.0. Attempting to upgrade...
    [20:08:30] src/nnvm/legacy_json_util.cc:217: Symbol successfully upgraded!
    
    Segmentation fault: 11
    
    Stack trace:
      [bt] (0) /usr/local/lib/python3.6/dist-packages/mxnet/libmxnet.so(+0x3c27360) [0x7f5400af1360]
    ----------------- Options ---------------
                           Nw: 3                             
                        alpha: 0.3                           
                    attention: 1                             
                   batch_size: 1                             
                        beta1: 0.5                           
              checkpoints_dir: ./checkpoints                 
               continue_train: True                          	[default: False]
                    crop_size: 256                           
                     dataroot: 11_bmold_win3                 	[default: None]
                 dataset_mode: aligned_feature_multi         
                    direction: AtoB                          
                  display_env: memory_seq_11                 	[default: main]
                 display_freq: 400                           
                   display_id: 1                             
                display_ncols: 4                             
                 display_port: 8097                          
               display_server: http://localhost              
              display_winsize: 256                           
             do_saturate_mask: False                         
                        epoch: 0                             	[default: latest]
                  epoch_count: 1                             
                     gan_mode: vanilla                       
                      gpu_ids: 0                             
                iden_feat_dim: 512                           
                iden_feat_dir: arcface/iden_feat/            
                   iden_thres: 0.98                          
                    init_gain: 0.02                          
                    init_type: normal                        
                     input_nc: 3                             
                      isTrain: True                          	[default: None]
                    lambda_L1: 100.0                         
                  lambda_mask: 2.0                           	[default: 0.1]
           lambda_mask_smooth: 1e-05                         
                    load_iter: 0                             	[default: 0]
                    load_size: 286                           
                           lr: 0.0001                        	[default: 0.0002]
               lr_decay_iters: 50                            
                    lr_policy: linear                        
             max_dataset_size: inf                           
                     mem_size: 30000                         
                        model: memory_seq                    	[default: cycle_gan]
                   n_layers_D: 3                             
                         name: memory_seq_p2p/11             	[default: experiment_name]
                          ndf: 64                            
                         netD: basic                         
                         netG: unetac_adain_256              
                          ngf: 64                            
                        niter: 60                            	[default: 100]
                  niter_decay: 0                             	[default: 100]
                   no_dropout: False                         
                      no_flip: False                         
                      no_html: False                         
                         norm: batch                         
                  num_threads: 4                             
                    output_nc: 3                             
                        phase: train                         
                    pool_size: 0                             
                   preprocess: resize_and_crop               
                   print_freq: 100                           
                 resizemethod: lanczos                       
                 save_by_iter: False                         
              save_epoch_freq: 5                             
             save_latest_freq: 5000                          
               serial_batches: False                         
             spatial_feat_dim: 512                           
                       suffix:                               
                        top_k: 256                           
             update_html_freq: 1000                          
                      verbose: False                         
    ----------------- End -------------------
    dataset [AlignedFeatureMultiDataset] was created
    The number of training images = 298
    initialize network with normal
    initialize network with normal
    model [MemorySeqModel] was created
    loading the model from ./checkpoints/memory_seq_p2p/0_net_G.pth
    loading the model from ./checkpoints/memory_seq_p2p/0_net_D.pth
    loading the model from ./checkpoints/memory_seq_p2p/0_net_mem.pth
    ---------- Networks initialized -------------
    [Network G] Total number of parameters : 259.056 M
    [Network D] Total number of parameters : 2.775 M
    [Network mem] Total number of parameters : 11.952 M
    -----------------------------------------------
    Setting up a new session...
    Exception in user code:
    ------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.6/dist-packages/urllib3/connection.py", line 159, in _new_conn
        (self._dns_host, self.port), self.timeout, **extra_kw)
      File "/usr/local/lib/python3.6/dist-packages/urllib3/util/connection.py", line 80, in create_connection
        raise err
      File "/usr/local/lib/python3.6/dist-packages/urllib3/util/connection.py", line 70, in create_connection
        sock.connect(sa)
    ConnectionRefusedError: [Errno 111] Connection refused
    
    During handling of the above exception, another exception occurred:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.6/dist-packages/urllib3/connectionpool.py", line 600, in urlopen
        chunked=chunked)
      File "/usr/local/lib/python3.6/dist-packages/urllib3/connectionpool.py", line 354, in _make_request
        conn.request(method, url, **httplib_request_kw)
      File "/usr/lib/python3.6/http/client.py", line 1254, in request
        self._send_request(method, url, body, headers, encode_chunked)
      File "/usr/lib/python3.6/http/client.py", line 1300, in _send_request
        self.endheaders(body, encode_chunked=encode_chunked)
      File "/usr/lib/python3.6/http/client.py", line 1249, in endheaders
        self._send_output(message_body, encode_chunked=encode_chunked)
      File "/usr/lib/python3.6/http/client.py", line 1036, in _send_output
        self.send(msg)
      File "/usr/lib/python3.6/http/client.py", line 974, in send
        self.connect()
      File "/usr/local/lib/python3.6/dist-packages/urllib3/connection.py", line 181, in connect
        conn = self._new_conn()
      File "/usr/local/lib/python3.6/dist-packages/urllib3/connection.py", line 168, in _new_conn
        self, "Failed to establish a new connection: %s" % e)
    urllib3.exceptions.NewConnectionError: <urllib3.connection.HTTPConnection object at 0x7f506009f198>: Failed to establish a new connection: [Errno 111] Connection refused
    
    During handling of the above exception, another exception occurred:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.6/dist-packages/requests/adapters.py", line 449, in send
        timeout=timeout
      File "/usr/local/lib/python3.6/dist-packages/urllib3/connectionpool.py", line 638, in urlopen
        _stacktrace=sys.exc_info()[2])
      File "/usr/local/lib/python3.6/dist-packages/urllib3/util/retry.py", line 399, in increment
        raise MaxRetryError(_pool, url, error or ResponseError(cause))
    urllib3.exceptions.MaxRetryError: HTTPConnectionPool(host='localhost', port=8097): Max retries exceeded with url: /env/memory_seq_11 (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f506009f198>: Failed to establish a new connection: [Errno 111] Connection refused',))
    
    During handling of the above exception, another exception occurred:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.6/dist-packages/visdom/__init__.py", line 711, in _send
        data=json.dumps(msg),
      File "/usr/local/lib/python3.6/dist-packages/visdom/__init__.py", line 677, in _handle_post
        r = self.session.post(url, data=data)
      File "/usr/local/lib/python3.6/dist-packages/requests/sessions.py", line 581, in post
        return self.request('POST', url, data=data, json=json, **kwargs)
      File "/usr/local/lib/python3.6/dist-packages/requests/sessions.py", line 533, in request
        resp = self.send(prep, **send_kwargs)
      File "/usr/local/lib/python3.6/dist-packages/requests/sessions.py", line 646, in send
        r = adapter.send(request, **kwargs)
      File "/usr/local/lib/python3.6/dist-packages/requests/adapters.py", line 516, in send
        raise ConnectionError(e, request=request)
    requests.exceptions.ConnectionError: HTTPConnectionPool(host='localhost', port=8097): Max retries exceeded with url: /env/memory_seq_11 (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f506009f198>: Failed to establish a new connection: [Errno 111] Connection refused',))
    [Errno 99] Cannot assign requested address
    [Errno 99] Cannot assign requested address
    [Errno 99] Cannot assign requested address
    Visdom python client failed to establish socket to get messages from the server. This feature is optional and can be disabled by initializing Visdom with `use_incoming_socket=False`, which will prevent waiting for this request to timeout.
    
    
    Could not connect to Visdom server. 
     Trying to start a server....
    Command: /usr/bin/python3 -m visdom.server -p 8097 &>/dev/null &
    create web directory ./checkpoints/memory_seq_p2p/11/web...
    Traceback (most recent call last):
      File "train.py", line 45, in <module>
        for i, data in enumerate(dataset):  # inner loop within one epoch
      File "/content/Audio-driven-TalkingFace-HeadPose/render-to-video/data/__init__.py", line 90, in __iter__
        for i, data in enumerate(self.dataloader):
      File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py", line 345, in __next__
        data = self._next_data()
      File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py", line 856, in _next_data
        return self._process_data(data)
      File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py", line 881, in _process_data
        data.reraise()
      File "/usr/local/lib/python3.6/dist-packages/torch/_utils.py", line 394, in reraise
        raise self.exc_type(msg)
    FileNotFoundError: Caught FileNotFoundError in DataLoader worker process 0.
    Original Traceback (most recent call last):
      File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/worker.py", line 178, in _worker_loop
        data = fetcher.fetch(index)
      File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
        data = [self.dataset[idx] for idx in possibly_batched_index]
      File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
        data = [self.dataset[idx] for idx in possibly_batched_index]
      File "/content/Audio-driven-TalkingFace-HeadPose/render-to-video/data/aligned_feature_multi_dataset.py", line 54, in __getitem__
        A = Image.open(AB_path).convert('RGB')
      File "/usr/local/lib/python3.6/dist-packages/PIL/Image.py", line 2809, in open
        fp = builtins.open(filename, "rb")
    FileNotFoundError: [Errno 2] No such file or directory: '/content/Audio-driven-TalkingFace-HeadPose/render-to-video/../Deep3DFaceReconstruction/output/render/19_news/11/bm/frame111_renderold_bm.png'
    
    ----------------- Options ---------------
                           Nw: 3                             
                        alpha: 0.3                           
                 aspect_ratio: 1.0                           
                    attention: 1                             
                   batch_size: 1                             
                 blinkframeid: 41                            
              checkpoints_dir: ./checkpoints                 
                    crop_size: 256                           
                     dataroot: 11_bmold_win3                 	[default: None]
                 dataset_mode: aligned_feature_multi         
                    direction: AtoB                          
              display_winsize: 256                           
             do_saturate_mask: False                         
                        epoch: 60                            	[default: latest]
                         eval: False                         
                      gpu_ids: 0                             
                iden_feat_dim: 512                           
                iden_feat_dir: arcface/iden_feat/            
                   iden_thres: 0.98                          
                  imagefolder: images60                      	[default: images]
                    init_gain: 0.02                          
                    init_type: normal                        
                     input_nc: 3                             
                      isTrain: False                         	[default: None]
                    load_iter: 0                             	[default: 0]
                    load_size: 256                           
             max_dataset_size: inf                           
                     mem_size: 30000                         
                        model: memory_seq                    	[default: test]
                            n: 26                            
                   n_layers_D: 3                             
                         name: memory_seq_p2p/11             	[default: experiment_name]
                          ndf: 64                            
                         netD: basic                         
                         netG: unetac_adain_256              
                          ngf: 64                            
                   no_dropout: False                         
                      no_flip: False                         
                         norm: batch                         
                        ntest: inf                           
                     num_test: 200                           	[default: 50]
                  num_threads: 4                             
                    output_nc: 3                             
                        phase: test                          
                   preprocess: resize_and_crop               
                 resizemethod: lanczos                       
                  results_dir: ./results/                    
               serial_batches: False                         
             spatial_feat_dim: 512                           
                       suffix:                               
              test_batch_list:                               
                  test_use_gt: 0                             
                        top_k: 256                           
                      verbose: False                         
    ----------------- End -------------------
    dataset [AlignedFeatureMultiDataset] was created
    initialize network with normal
    model [MemorySeqModel] was created
    loading the model from ./checkpoints/memory_seq_p2p/60_net_G.pth
    Traceback (most recent call last):
      File "test.py", line 47, in <module>
        model.setup(opt)               # regular setup: load and print networks; create schedulers
      File "/content/Audio-driven-TalkingFace-HeadPose/render-to-video/models/base_model.py", line 89, in setup
        self.load_networks(load_suffix)
      File "/content/Audio-driven-TalkingFace-HeadPose/render-to-video/models/base_model.py", line 202, in load_networks
        state_dict = torch.load(load_path, map_location=str(self.device))
      File "/usr/local/lib/python3.6/dist-packages/torch/serialization.py", line 525, in load
        with _open_file_like(f, 'rb') as opened_file:
      File "/usr/local/lib/python3.6/dist-packages/torch/serialization.py", line 212, in _open_file_like
        return _open_file(name_or_buffer, mode)
      File "/usr/local/lib/python3.6/dist-packages/torch/serialization.py", line 193, in __init__
        super(_open_file, self).__init__(open(name, mode))
    FileNotFoundError: [Errno 2] No such file or directory: './checkpoints/memory_seq_p2p/60_net_G.pth'
    
    opened by kryzhikov 4
  • undefined symbol: _ZN10tensorflow12OpDefBuilder4AttrESs

    undefined symbol: _ZN10tensorflow12OpDefBuilder4AttrESs

    Traceback (most recent call last): File "/root/.cache/bazel/_bazel_root/60fa6525d50100b7b5f2200eb3a7cc53/sandbox/processwrapper-sandbox/48/execroot/tf_mesh_renderer/bazel-out/k8-fastbuild/bin/mesh_renderer/mesh_renderer_test.runfiles/tf_mesh_renderer/mesh_renderer/mesh_renderer_test.py", line 26, in import mesh_renderer File "/root/audio2/Deep3DFaceReconstruction/tf_mesh_renderer/mesh_renderer/mesh_renderer.py", line 24, in import rasterize_triangles File "/root/audio2/Deep3DFaceReconstruction/tf_mesh_renderer/mesh_renderer/rasterize_triangles.py", line 29, in 'tf_mesh_renderer/mesh_renderer/kernels/rasterize_triangles_kernel.so')) File "/root/anaconda3/envs/audio2/lib/python3.7/site-packages/tensorflow/python/framework/load_library.py", line 61, in load_op_library lib_handle = py_tf.TF_LoadLibrary(library_filename) tensorflow.python.framework.errors_impl.NotFoundError: /root/audio2/Deep3DFaceReconstruction/tf_mesh_renderer/mesh_renderer/kernels/rasterize_triangles_kernel.so: undefined symbol: _ZN10tensorflow12OpDefBuilder4AttrESs

    请问有此问题的解决方法吗? tf=1.14.0,已链接.so文件 尝试过更换bazel版本和gcc版本,未解决 更改-D_GLIBCXX_USE_CXX11_ABI=1,未解决

    Can anyone offer a solution? tf=1.14.0,i have changed bazel version and GCC version , but failed. set -D_GLIBCXX_USE_CXX11_ABI=1, failed either

    opened by 15211 3
  • build tf_mesh_renderer appear unable to load packages ?

    build tf_mesh_renderer appear unable to load packages ?

    ERROR: /home/puaiuc/opensources/Audio-driven-TalkingFace-HeadPose-master/Deep3DFaceReconstruction/tf_mesh_renderer/mesh_renderer/kernels/BUILD:7:1: error loading package '@com_google_googletest//': Extension file not found. Unable to load package for '@rules_cc//cc:defs.bzl': The repository could not be resolved and referenced by '//mesh_renderer/kernels:rasterize_triangles_impl_test'
    ERROR: Analysis of target '//mesh_renderer/kernels:rasterize_triangles_impl_test' failed; build aborted: error loading package '@com_google_googletest//': Extension file not found. Unable to load package for '@rules_cc//cc:defs.bzl': The repository could not be resolved
    INFO: Elapsed time: 0.158s
    INFO: 0 processes.
    FAILED: Build did NOT complete successfully (0 packages loaded, 2 targets configured)
    FAILED: Build did NOT complete successfully (0 packages loaded, 2 targets configured)
    

    I compiled it on my own server. bazel version: 0.19.2 tensorflow version: 1.13.2 Both bazel and tf are source compiled. I've been troubled for a long time, I don't know how to solve it.Help me, please.Thanks.

    opened by Adorablepet 2
  • Bump tensorflow-gpu from 1.14.0 to 2.7.2

    Bump tensorflow-gpu from 1.14.0 to 2.7.2

    Bumps tensorflow-gpu from 1.14.0 to 2.7.2.

    Release notes

    Sourced from tensorflow-gpu's releases.

    TensorFlow 2.7.2

    Release 2.7.2

    This releases introduces several vulnerability fixes:

    TensorFlow 2.7.1

    Release 2.7.1

    This releases introduces several vulnerability fixes:

    • Fixes a floating point division by 0 when executing convolution operators (CVE-2022-21725)
    • Fixes a heap OOB read in shape inference for ReverseSequence (CVE-2022-21728)
    • Fixes a heap OOB access in Dequantize (CVE-2022-21726)
    • Fixes an integer overflow in shape inference for Dequantize (CVE-2022-21727)
    • Fixes a heap OOB access in FractionalAvgPoolGrad (CVE-2022-21730)
    • Fixes an overflow and divide by zero in UnravelIndex (CVE-2022-21729)
    • Fixes a type confusion in shape inference for ConcatV2 (CVE-2022-21731)
    • Fixes an OOM in ThreadPoolHandle (CVE-2022-21732)
    • Fixes an OOM due to integer overflow in StringNGrams (CVE-2022-21733)
    • Fixes more issues caused by incomplete validation in boosted trees code (CVE-2021-41208)
    • Fixes an integer overflows in most sparse component-wise ops (CVE-2022-23567)
    • Fixes an integer overflows in AddManySparseToTensorsMap (CVE-2022-23568)

    ... (truncated)

    Changelog

    Sourced from tensorflow-gpu's changelog.

    Release 2.7.2

    This releases introduces several vulnerability fixes:

    Release 2.6.4

    This releases introduces several vulnerability fixes:

    • Fixes a code injection in saved_model_cli (CVE-2022-29216)
    • Fixes a missing validation which causes TensorSummaryV2 to crash (CVE-2022-29193)
    • Fixes a missing validation which crashes QuantizeAndDequantizeV4Grad (CVE-2022-29192)
    • Fixes a missing validation which causes denial of service via DeleteSessionTensor (CVE-2022-29194)
    • Fixes a missing validation which causes denial of service via GetSessionTensor (CVE-2022-29191)
    • Fixes a missing validation which causes denial of service via StagePeek (CVE-2022-29195)
    • Fixes a missing validation which causes denial of service via UnsortedSegmentJoin (CVE-2022-29197)
    • Fixes a missing validation which causes denial of service via LoadAndRemapMatrix (CVE-2022-29199)
    • Fixes a missing validation which causes denial of service via SparseTensorToCSRSparseMatrix (CVE-2022-29198)
    • Fixes a missing validation which causes denial of service via LSTMBlockCell (CVE-2022-29200)
    • Fixes a missing validation which causes denial of service via Conv3DBackpropFilterV2 (CVE-2022-29196)
    • Fixes a CHECK failure in depthwise ops via overflows (CVE-2021-41197)
    • Fixes issues arising from undefined behavior stemming from users supplying invalid resource handles (CVE-2022-29207)
    • Fixes a segfault due to missing support for quantized types (CVE-2022-29205)
    • Fixes a missing validation which results in undefined behavior in SparseTensorDenseAdd (CVE-2022-29206)

    ... (truncated)

    Commits
    • dd7b8a3 Merge pull request #56034 from tensorflow-jenkins/relnotes-2.7.2-15779
    • 1e7d6ea Update RELEASE.md
    • 5085135 Merge pull request #56069 from tensorflow/mm-cp-52488e5072f6fe44411d70c6af09e...
    • adafb45 Merge pull request #56060 from yongtang:curl-7.83.1
    • 01cb1b8 Merge pull request #56038 from tensorflow-jenkins/version-numbers-2.7.2-4733
    • 8c90c2f Update version numbers to 2.7.2
    • 43f3cdc Update RELEASE.md
    • 98b0a48 Insert release notes place-fill
    • dfa5cf3 Merge pull request #56028 from tensorflow/disable-tests-on-r2.7
    • 501a65c Disable timing out tests
    • Additional commits viewable in compare view

    Dependabot compatibility score

    Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


    Dependabot commands and options

    You can trigger Dependabot actions by commenting on this PR:

    • @dependabot rebase will rebase this PR
    • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
    • @dependabot merge will merge this PR after your CI passes on it
    • @dependabot squash and merge will squash and merge this PR after your CI passes on it
    • @dependabot cancel merge will cancel a previously requested merge and block automerging
    • @dependabot reopen will reopen this PR if it is closed
    • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
    • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
    • @dependabot use these labels will set the current labels as the default for future PRs for this repo and language
    • @dependabot use these reviewers will set the current reviewers as the default for future PRs for this repo and language
    • @dependabot use these assignees will set the current assignees as the default for future PRs for this repo and language
    • @dependabot use this milestone will set the current milestone as the default for future PRs for this repo and language

    You can disable automated security fix PRs for this repo from the Security Alerts page.

    dependencies 
    opened by dependabot[bot] 1
  • Bump tensorflow-gpu from 1.14.0 to 2.6.4

    Bump tensorflow-gpu from 1.14.0 to 2.6.4

    Bumps tensorflow-gpu from 1.14.0 to 2.6.4.

    Release notes

    Sourced from tensorflow-gpu's releases.

    TensorFlow 2.6.4

    Release 2.6.4

    This releases introduces several vulnerability fixes:

    TensorFlow 2.6.3

    Release 2.6.3

    This releases introduces several vulnerability fixes:

    • Fixes a floating point division by 0 when executing convolution operators (CVE-2022-21725)
    • Fixes a heap OOB read in shape inference for ReverseSequence (CVE-2022-21728)
    • Fixes a heap OOB access in Dequantize (CVE-2022-21726)
    • Fixes an integer overflow in shape inference for Dequantize (CVE-2022-21727)
    • Fixes a heap OOB access in FractionalAvgPoolGrad (CVE-2022-21730)
    • Fixes an overflow and divide by zero in UnravelIndex (CVE-2022-21729)
    • Fixes a type confusion in shape inference for ConcatV2 (CVE-2022-21731)
    • Fixes an OOM in ThreadPoolHandle (CVE-2022-21732)
    • Fixes an OOM due to integer overflow in StringNGrams (CVE-2022-21733)
    • Fixes more issues caused by incomplete validation in boosted trees code (CVE-2021-41208)
    • Fixes an integer overflows in most sparse component-wise ops (CVE-2022-23567)
    • Fixes an integer overflows in AddManySparseToTensorsMap (CVE-2022-23568)
    • Fixes a number of CHECK-failures in MapStage (CVE-2022-21734)

    ... (truncated)

    Changelog

    Sourced from tensorflow-gpu's changelog.

    Release 2.6.4

    This releases introduces several vulnerability fixes:

    Release 2.8.0

    Major Features and Improvements

    • tf.lite:

      • Added TFLite builtin op support for the following TF ops:
        • tf.raw_ops.Bucketize op on CPU.
        • tf.where op for data types tf.int32/tf.uint32/tf.int8/tf.uint8/tf.int64.
        • tf.random.normal op for output data type tf.float32 on CPU.
        • tf.random.uniform op for output data type tf.float32 on CPU.
        • tf.random.categorical op for output data type tf.int64 on CPU.
    • tensorflow.experimental.tensorrt:

      • conversion_params is now deprecated inside TrtGraphConverterV2 in favor of direct arguments: max_workspace_size_bytes, precision_mode, minimum_segment_size, maximum_cached_engines, use_calibration and

    ... (truncated)

    Commits
    • 33ed2b1 Merge pull request #56102 from tensorflow/mihaimaruseac-patch-1
    • e1ec480 Fix build due to importlib-metadata/setuptools
    • 63f211c Merge pull request #56033 from tensorflow-jenkins/relnotes-2.6.4-6677
    • 22b8fe4 Update RELEASE.md
    • ec30684 Merge pull request #56070 from tensorflow/mm-cp-adafb45c781-on-r2.6
    • 38774ed Merge pull request #56060 from yongtang:curl-7.83.1
    • 9ef1604 Merge pull request #56036 from tensorflow-jenkins/version-numbers-2.6.4-9925
    • a6526a3 Update version numbers to 2.6.4
    • cb1a481 Update RELEASE.md
    • 4da550f Insert release notes place-fill
    • Additional commits viewable in compare view

    Dependabot compatibility score

    Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


    Dependabot commands and options

    You can trigger Dependabot actions by commenting on this PR:

    • @dependabot rebase will rebase this PR
    • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
    • @dependabot merge will merge this PR after your CI passes on it
    • @dependabot squash and merge will squash and merge this PR after your CI passes on it
    • @dependabot cancel merge will cancel a previously requested merge and block automerging
    • @dependabot reopen will reopen this PR if it is closed
    • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
    • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
    • @dependabot use these labels will set the current labels as the default for future PRs for this repo and language
    • @dependabot use these reviewers will set the current reviewers as the default for future PRs for this repo and language
    • @dependabot use these assignees will set the current assignees as the default for future PRs for this repo and language
    • @dependabot use this milestone will set the current milestone as the default for future PRs for this repo and language

    You can disable automated security fix PRs for this repo from the Security Alerts page.

    dependencies 
    opened by dependabot[bot] 1
  • Bump pillow from 4.3.0 to 9.0.1

    Bump pillow from 4.3.0 to 9.0.1

    Bumps pillow from 4.3.0 to 9.0.1.

    Release notes

    Sourced from pillow's releases.

    9.0.1

    https://pillow.readthedocs.io/en/stable/releasenotes/9.0.1.html

    Changes

    • In show_file, use os.remove to remove temporary images. CVE-2022-24303 #6010 [@​radarhere, @​hugovk]
    • Restrict builtins within lambdas for ImageMath.eval. CVE-2022-22817 #6009 [radarhere]

    9.0.0

    https://pillow.readthedocs.io/en/stable/releasenotes/9.0.0.html

    Changes

    ... (truncated)

    Changelog

    Sourced from pillow's changelog.

    9.0.1 (2022-02-03)

    • In show_file, use os.remove to remove temporary images. CVE-2022-24303 #6010 [radarhere, hugovk]

    • Restrict builtins within lambdas for ImageMath.eval. CVE-2022-22817 #6009 [radarhere]

    9.0.0 (2022-01-02)

    • Restrict builtins for ImageMath.eval(). CVE-2022-22817 #5923 [radarhere]

    • Ensure JpegImagePlugin stops at the end of a truncated file #5921 [radarhere]

    • Fixed ImagePath.Path array handling. CVE-2022-22815, CVE-2022-22816 #5920 [radarhere]

    • Remove consecutive duplicate tiles that only differ by their offset #5919 [radarhere]

    • Improved I;16 operations on big endian #5901 [radarhere]

    • Limit quantized palette to number of colors #5879 [radarhere]

    • Fixed palette index for zeroed color in FASTOCTREE quantize #5869 [radarhere]

    • When saving RGBA to GIF, make use of first transparent palette entry #5859 [radarhere]

    • Pass SAMPLEFORMAT to libtiff #5848 [radarhere]

    • Added rounding when converting P and PA #5824 [radarhere]

    • Improved putdata() documentation and data handling #5910 [radarhere]

    • Exclude carriage return in PDF regex to help prevent ReDoS #5912 [hugovk]

    • Fixed freeing pointer in ImageDraw.Outline.transform #5909 [radarhere]

    ... (truncated)

    Commits
    • 6deac9e 9.0.1 version bump
    • c04d812 Update CHANGES.rst [ci skip]
    • 4fabec3 Added release notes for 9.0.1
    • 02affaa Added delay after opening image with xdg-open
    • ca0b585 Updated formatting
    • 427221e In show_file, use os.remove to remove temporary images
    • c930be0 Restrict builtins within lambdas for ImageMath.eval
    • 75b69dd Dont need to pin for GHA
    • cd938a7 Autolink CWE numbers with sphinx-issues
    • 2e9c461 Add CVE IDs
    • Additional commits viewable in compare view

    Dependabot compatibility score

    Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


    Dependabot commands and options

    You can trigger Dependabot actions by commenting on this PR:

    • @dependabot rebase will rebase this PR
    • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
    • @dependabot merge will merge this PR after your CI passes on it
    • @dependabot squash and merge will squash and merge this PR after your CI passes on it
    • @dependabot cancel merge will cancel a previously requested merge and block automerging
    • @dependabot reopen will reopen this PR if it is closed
    • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
    • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
    • @dependabot use these labels will set the current labels as the default for future PRs for this repo and language
    • @dependabot use these reviewers will set the current reviewers as the default for future PRs for this repo and language
    • @dependabot use these assignees will set the current assignees as the default for future PRs for this repo and language
    • @dependabot use this milestone will set the current milestone as the default for future PRs for this repo and language

    You can disable automated security fix PRs for this repo from the Security Alerts page.

    dependencies 
    opened by dependabot[bot] 1
  • Bump protobuf from 3.8.0 to 3.15.0

    Bump protobuf from 3.8.0 to 3.15.0

    Bumps protobuf from 3.8.0 to 3.15.0.

    Release notes

    Sourced from protobuf's releases.

    Protocol Buffers v3.15.0

    Protocol Compiler

    • Optional fields for proto3 are enabled by default, and no longer require the --experimental_allow_proto3_optional flag.

    C++

    • MessageDifferencer: fixed bug when using custom ignore with multiple unknown fields
    • Use init_seg in MSVC to push initialization to an earlier phase.
    • Runtime no longer triggers -Wsign-compare warnings.
    • Fixed -Wtautological-constant-out-of-range-compare warning.
    • DynamicCastToGenerated works for nullptr input for even if RTTI is disabled
    • Arena is refactored and optimized.
    • Clarified/specified that the exact value of Arena::SpaceAllocated() is an implementation detail users must not rely on. It should not be used in unit tests.
    • Change the signature of Any::PackFrom() to return false on error.
    • Add fast reflection getter API for strings.
    • Constant initialize the global message instances
    • Avoid potential for missed wakeup in UnknownFieldSet
    • Now Proto3 Oneof fields have "has" methods for checking their presence in C++.
    • Bugfix for NVCC
    • Return early in _InternalSerialize for empty maps.
    • Adding functionality for outputting map key values in proto path logging output (does not affect comparison logic) and stop printing 'value' in the path. The modified print functionality is in the MessageDifferencer::StreamReporter.
    • Fixed protocolbuffers/protobuf#8129
    • Ensure that null char symbol, package and file names do not result in a crash.
    • Constant initialize the global message instances
    • Pretty print 'max' instead of numeric values in reserved ranges.
    • Removed remaining instances of std::is_pod, which is deprecated in C++20.
    • Changes to reduce code size for unknown field handling by making uncommon cases out of line.
    • Fix std::is_pod deprecated in C++20 (#7180)
    • Fix some -Wunused-parameter warnings (#8053)
    • Fix detecting file as directory on zOS issue #8051 (#8052)
    • Don't include sys/param.h for _BYTE_ORDER (#8106)
    • remove CMAKE_THREAD_LIBS_INIT from pkgconfig CFLAGS (#8154)
    • Fix TextFormatMapTest.DynamicMessage issue#5136 (#8159)
    • Fix for compiler warning issue#8145 (#8160)
    • fix: support deprecated enums for GCC < 6 (#8164)
    • Fix some warning when compiling with Visual Studio 2019 on x64 target (#8125)

    Python

    • Provided an override for the reverse() method that will reverse the internal collection directly instead of using the other methods of the BaseContainer.
    • MessageFactory.CreateProtoype can be overridden to customize class creation.

    ... (truncated)

    Commits
    • ae50d9b Update protobuf version
    • 8260126 Update protobuf version
    • c741c46 Resovled issue in the .pb.cc files
    • eef2764 Resolved an issue where NO_DESTROY and CONSTINIT were in incorrect order
    • 0040102 Updated collect_all_artifacts.sh for Ubuntu Xenial
    • 26cb6a7 Delete root-owned files in Kokoro builds
    • 1e924ef Update port_def.inc
    • 9a80cf1 Update coded_stream.h
    • a97c4f4 Merge pull request #8276 from haberman/php-warning
    • 44cd75d Merge pull request #8282 from haberman/changelog
    • Additional commits viewable in compare view

    Dependabot compatibility score

    Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


    Dependabot commands and options

    You can trigger Dependabot actions by commenting on this PR:

    • @dependabot rebase will rebase this PR
    • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
    • @dependabot merge will merge this PR after your CI passes on it
    • @dependabot squash and merge will squash and merge this PR after your CI passes on it
    • @dependabot cancel merge will cancel a previously requested merge and block automerging
    • @dependabot reopen will reopen this PR if it is closed
    • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
    • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
    • @dependabot use these labels will set the current labels as the default for future PRs for this repo and language
    • @dependabot use these reviewers will set the current reviewers as the default for future PRs for this repo and language
    • @dependabot use these assignees will set the current assignees as the default for future PRs for this repo and language
    • @dependabot use this milestone will set the current milestone as the default for future PRs for this repo and language

    You can disable automated security fix PRs for this repo from the Security Alerts page.

    dependencies 
    opened by dependabot[bot] 1
  • Bump tensorflow-gpu from 1.14.0 to 2.5.3

    Bump tensorflow-gpu from 1.14.0 to 2.5.3

    Bumps tensorflow-gpu from 1.14.0 to 2.5.3.

    Release notes

    Sourced from tensorflow-gpu's releases.

    TensorFlow 2.5.3

    Release 2.5.3

    Note: This is the last release in the 2.5 series.

    This releases introduces several vulnerability fixes:

    • Fixes a floating point division by 0 when executing convolution operators (CVE-2022-21725)
    • Fixes a heap OOB read in shape inference for ReverseSequence (CVE-2022-21728)
    • Fixes a heap OOB access in Dequantize (CVE-2022-21726)
    • Fixes an integer overflow in shape inference for Dequantize (CVE-2022-21727)
    • Fixes a heap OOB access in FractionalAvgPoolGrad (CVE-2022-21730)
    • Fixes an overflow and divide by zero in UnravelIndex (CVE-2022-21729)
    • Fixes a type confusion in shape inference for ConcatV2 (CVE-2022-21731)
    • Fixes an OOM in ThreadPoolHandle (CVE-2022-21732)
    • Fixes an OOM due to integer overflow in StringNGrams (CVE-2022-21733)
    • Fixes more issues caused by incomplete validation in boosted trees code (CVE-2021-41208)
    • Fixes an integer overflows in most sparse component-wise ops (CVE-2022-23567)
    • Fixes an integer overflows in AddManySparseToTensorsMap (CVE-2022-23568)
    • Fixes a number of CHECK-failures in MapStage (CVE-2022-21734)
    • Fixes a division by zero in FractionalMaxPool (CVE-2022-21735)
    • Fixes a number of CHECK-fails when building invalid/overflowing tensor shapes (CVE-2022-23569)
    • Fixes an undefined behavior in SparseTensorSliceDataset (CVE-2022-21736)
    • Fixes an assertion failure based denial of service via faulty bin count operations (CVE-2022-21737)
    • Fixes a reference binding to null pointer in QuantizedMaxPool (CVE-2022-21739)
    • Fixes an integer overflow leading to crash in SparseCountSparseOutput (CVE-2022-21738)
    • Fixes a heap overflow in SparseCountSparseOutput (CVE-2022-21740)
    • Fixes an FPE in BiasAndClamp in TFLite (CVE-2022-23557)
    • Fixes an FPE in depthwise convolutions in TFLite (CVE-2022-21741)
    • Fixes an integer overflow in TFLite array creation (CVE-2022-23558)
    • Fixes an integer overflow in TFLite (CVE-2022-23559)
    • Fixes a dangerous OOB write in TFLite (CVE-2022-23561)
    • Fixes a vulnerability leading to read and write outside of bounds in TFLite (CVE-2022-23560)
    • Fixes a set of vulnerabilities caused by using insecure temporary files (CVE-2022-23563)
    • Fixes an integer overflow in Range resulting in undefined behavior and OOM (CVE-2022-23562)
    • Fixes a vulnerability where missing validation causes tf.sparse.split to crash when axis is a tuple (CVE-2021-41206)
    • Fixes a CHECK-fail when decoding resource handles from proto (CVE-2022-23564)
    • Fixes a CHECK-fail with repeated AttrDef (CVE-2022-23565)
    • Fixes a heap OOB write in Grappler (CVE-2022-23566)
    • Fixes a CHECK-fail when decoding invalid tensors from proto (CVE-2022-23571)
    • Fixes an unitialized variable access in AssignOp (CVE-2022-23573)
    • Fixes an integer overflow in OpLevelCostEstimator::CalculateTensorSize (CVE-2022-23575)
    • Fixes an integer overflow in OpLevelCostEstimator::CalculateOutputSize (CVE-2022-23576)
    • Fixes a null dereference in GetInitOp (CVE-2022-23577)
    • Fixes a memory leak when a graph node is invalid (CVE-2022-23578)
    • Fixes an abort caused by allocating a vector that is too large (CVE-2022-23580)
    • Fixes multiple CHECK-failures during Grappler's IsSimplifiableReshape (CVE-2022-23581)
    • Fixes multiple CHECK-failures during Grappler's SafeToRemoveIdentity (CVE-2022-23579)
    • Fixes multiple CHECK-failures in TensorByteSize (CVE-2022-23582)
    • Fixes multiple CHECK-failures in binary ops due to type confusion (CVE-2022-23583)

    ... (truncated)

    Changelog

    Sourced from tensorflow-gpu's changelog.

    Release 2.5.3

    This releases introduces several vulnerability fixes:

    • Fixes a floating point division by 0 when executing convolution operators (CVE-2022-21725)
    • Fixes a heap OOB read in shape inference for ReverseSequence (CVE-2022-21728)
    • Fixes a heap OOB access in Dequantize (CVE-2022-21726)
    • Fixes an integer overflow in shape inference for Dequantize (CVE-2022-21727)
    • Fixes a heap OOB access in FractionalAvgPoolGrad (CVE-2022-21730)
    • Fixes an overflow and divide by zero in UnravelIndex (CVE-2022-21729)
    • Fixes a type confusion in shape inference for ConcatV2 (CVE-2022-21731)
    • Fixes an OOM in ThreadPoolHandle (CVE-2022-21732)
    • Fixes an OOM due to integer overflow in StringNGrams (CVE-2022-21733)
    • Fixes more issues caused by incomplete validation in boosted trees code (CVE-2021-41208)
    • Fixes an integer overflows in most sparse component-wise ops (CVE-2022-23567)
    • Fixes an integer overflows in AddManySparseToTensorsMap (CVE-2022-23568)
    • Fixes a number of CHECK-failures in MapStage (CVE-2022-21734)
    • Fixes a division by zero in FractionalMaxPool (CVE-2022-21735)
    • Fixes a number of CHECK-fails when building invalid/overflowing tensor shapes (CVE-2022-23569)
    • Fixes an undefined behavior in SparseTensorSliceDataset (CVE-2022-21736)
    • Fixes an assertion failure based denial of service via faulty bin count operations (CVE-2022-21737)
    • Fixes a reference binding to null pointer in QuantizedMaxPool (CVE-2022-21739)
    • Fixes an integer overflow leading to crash in SparseCountSparseOutput (CVE-2022-21738)
    • Fixes a heap overflow in SparseCountSparseOutput (CVE-2022-21740)
    • Fixes an FPE in BiasAndClamp in TFLite (CVE-2022-23557)
    • Fixes an FPE in depthwise convolutions in TFLite (CVE-2022-21741)

    ... (truncated)

    Commits
    • 959e9b2 Merge pull request #54213 from tensorflow/fix-sanity-on-r2.5
    • d05fcbc Fix sanity build
    • f2526a0 Merge pull request #54205 from tensorflow/disable-flaky-tests-on-r2.5
    • a5f94df Disable flaky test
    • 7babe52 Merge pull request #54201 from tensorflow/cherrypick-510ae18200d0a4fad797c0bf...
    • 0e5d378 Set Env Variable to override Setuptools new behavior
    • fdd4195 Merge pull request #54176 from tensorflow-jenkins/relnotes-2.5.3-6805
    • 4083165 Update RELEASE.md
    • a2bb7f1 Merge pull request #54185 from tensorflow/cherrypick-d437dec4d549fc30f9b85c75...
    • 5777ea3 Update third_party/icu/workspace.bzl
    • Additional commits viewable in compare view

    Dependabot compatibility score

    Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


    Dependabot commands and options

    You can trigger Dependabot actions by commenting on this PR:

    • @dependabot rebase will rebase this PR
    • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
    • @dependabot merge will merge this PR after your CI passes on it
    • @dependabot squash and merge will squash and merge this PR after your CI passes on it
    • @dependabot cancel merge will cancel a previously requested merge and block automerging
    • @dependabot reopen will reopen this PR if it is closed
    • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
    • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
    • @dependabot use these labels will set the current labels as the default for future PRs for this repo and language
    • @dependabot use these reviewers will set the current reviewers as the default for future PRs for this repo and language
    • @dependabot use these assignees will set the current assignees as the default for future PRs for this repo and language
    • @dependabot use this milestone will set the current milestone as the default for future PRs for this repo and language

    You can disable automated security fix PRs for this repo from the Security Alerts page.

    dependencies 
    opened by dependabot[bot] 1
  • Bump pillow from 4.3.0 to 9.0.0

    Bump pillow from 4.3.0 to 9.0.0

    Bumps pillow from 4.3.0 to 9.0.0.

    Release notes

    Sourced from pillow's releases.

    9.0.0

    https://pillow.readthedocs.io/en/stable/releasenotes/9.0.0.html

    Changes

    ... (truncated)

    Changelog

    Sourced from pillow's changelog.

    9.0.0 (2022-01-02)

    • Restrict builtins for ImageMath.eval(). CVE-2022-22817 #5923 [radarhere]

    • Ensure JpegImagePlugin stops at the end of a truncated file #5921 [radarhere]

    • Fixed ImagePath.Path array handling. CVE-2022-22815, CVE-2022-22816 #5920 [radarhere]

    • Remove consecutive duplicate tiles that only differ by their offset #5919 [radarhere]

    • Improved I;16 operations on big endian #5901 [radarhere]

    • Limit quantized palette to number of colors #5879 [radarhere]

    • Fixed palette index for zeroed color in FASTOCTREE quantize #5869 [radarhere]

    • When saving RGBA to GIF, make use of first transparent palette entry #5859 [radarhere]

    • Pass SAMPLEFORMAT to libtiff #5848 [radarhere]

    • Added rounding when converting P and PA #5824 [radarhere]

    • Improved putdata() documentation and data handling #5910 [radarhere]

    • Exclude carriage return in PDF regex to help prevent ReDoS #5912 [hugovk]

    • Fixed freeing pointer in ImageDraw.Outline.transform #5909 [radarhere]

    • Added ImageShow support for xdg-open #5897 [m-shinder, radarhere]

    • Support 16-bit grayscale ImageQt conversion #5856 [cmbruns, radarhere]

    • Convert subsequent GIF frames to RGB or RGBA #5857 [radarhere]

    ... (truncated)

    Commits

    Dependabot compatibility score

    Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


    Dependabot commands and options

    You can trigger Dependabot actions by commenting on this PR:

    • @dependabot rebase will rebase this PR
    • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
    • @dependabot merge will merge this PR after your CI passes on it
    • @dependabot squash and merge will squash and merge this PR after your CI passes on it
    • @dependabot cancel merge will cancel a previously requested merge and block automerging
    • @dependabot reopen will reopen this PR if it is closed
    • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
    • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
    • @dependabot use these labels will set the current labels as the default for future PRs for this repo and language
    • @dependabot use these reviewers will set the current reviewers as the default for future PRs for this repo and language
    • @dependabot use these assignees will set the current assignees as the default for future PRs for this repo and language
    • @dependabot use this milestone will set the current milestone as the default for future PRs for this repo and language

    You can disable automated security fix PRs for this repo from the Security Alerts page.

    dependencies 
    opened by dependabot[bot] 1
  • Bump certifi from 2019.9.11 to 2022.12.7

    Bump certifi from 2019.9.11 to 2022.12.7

    Bumps certifi from 2019.9.11 to 2022.12.7.

    Commits

    Dependabot compatibility score

    Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


    Dependabot commands and options

    You can trigger Dependabot actions by commenting on this PR:

    • @dependabot rebase will rebase this PR
    • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
    • @dependabot merge will merge this PR after your CI passes on it
    • @dependabot squash and merge will squash and merge this PR after your CI passes on it
    • @dependabot cancel merge will cancel a previously requested merge and block automerging
    • @dependabot reopen will reopen this PR if it is closed
    • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
    • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
    • @dependabot use these labels will set the current labels as the default for future PRs for this repo and language
    • @dependabot use these reviewers will set the current reviewers as the default for future PRs for this repo and language
    • @dependabot use these assignees will set the current assignees as the default for future PRs for this repo and language
    • @dependabot use this milestone will set the current milestone as the default for future PRs for this repo and language

    You can disable automated security fix PRs for this repo from the Security Alerts page.

    dependencies 
    opened by dependabot[bot] 0
  • (not an issue) The following environment.yml might help

    (not an issue) The following environment.yml might help

    One may try to use the following to reproduce the code,

    `name: <Your_environment_name> channels:

    • pytorch
    • defaults
    • conda-forge dependencies:
    • _libgcc_mutex=0.1=main
    • _openmp_mutex=5.1=1_gnu
    • _pytorch_select=0.2=gpu_0
    • _tflow_select=2.1.0=gpu
    • absl-py=0.15.0=pyhd3eb1b0_0
    • astor=0.8.1=py36h06a4308_0
    • audioread=2.1.9=py36h5fab9bb_0
    • blas=1.0=mkl
    • bzip2=1.0.8=h7b6447c_0
    • c-ares=1.18.1=h7f8727e_0
    • ca-certificates=2022.10.11=h06a4308_0
    • certifi=2021.5.30=py36h06a4308_0
    • cffi=1.14.6=py36h400218f_0
    • cudatoolkit=10.1.243=h6bb024c_0
    • cycler=0.11.0=pyhd3eb1b0_0
    • dataclasses=0.8=pyh4f3eec9_6
    • dbus=1.13.18=hb2f20db_0
    • expat=2.4.9=h6a678d5_0
    • ffmpeg=4.2.2=h20bf706_0
    • fontconfig=2.13.1=hef1e5e3_1
    • freetype=2.12.1=h4a9f257_0
    • gast=0.5.3=pyhd3eb1b0_0
    • gettext=0.21.0=hf68c758_0
    • glib=2.69.1=h4ff587b_1
    • gmp=6.2.1=h295c915_3
    • gnutls=3.6.15=he1e5248_0
    • google-pasta=0.2.0=pyhd3eb1b0_0
    • grpcio=1.31.0=py36hf8bcb03_0
    • gst-plugins-base=1.14.0=h8213a91_2
    • gstreamer=1.14.0=h28cd5cc_2
    • h5py=2.10.0=py36hd6299e0_1
    • hdf5=1.10.6=hb1b8bf9_0
    • icu=58.2=he6710b0_3
    • importlib-metadata=4.8.1=py36h06a4308_0
    • intel-openmp=2022.1.0=h9e868ea_3769
    • joblib=1.0.1=pyhd3eb1b0_0
    • jpeg=9e=h7f8727e_0
    • keras-applications=1.0.8=py_1
    • keras-preprocessing=1.1.2=pyhd3eb1b0_0
    • kiwisolver=1.3.1=py36h2531618_0
    • krb5=1.19.2=hac12032_0
    • lame=3.100=h7b6447c_0
    • lcms2=2.12=h3be6417_0
    • ld_impl_linux-64=2.38=h1181459_1
    • lerc=3.0=h295c915_0
    • libcurl=7.85.0=h91b91d3_0
    • libdeflate=1.8=h7f8727e_5
    • libedit=3.1.20210910=h7f8727e_0
    • libev=4.33=h7f8727e_1
    • libffi=3.3=he6710b0_2
    • libflac=1.3.4=h27087fc_0
    • libgcc-ng=11.2.0=h1234567_1
    • libgfortran-ng=7.5.0=ha8ba4b0_17
    • libgfortran4=7.5.0=ha8ba4b0_17
    • libgomp=11.2.0=h1234567_1
    • libidn2=2.3.2=h7f8727e_0
    • libnghttp2=1.46.0=hce63b2e_0
    • libogg=1.3.5=h27cfd23_1
    • libopus=1.3.1=h7b6447c_0
    • libpng=1.6.37=hbc83047_0
    • libprotobuf=3.17.2=h4ff587b_1
    • librosa=0.7.0=py_0
    • libsndfile=1.0.31=h9c3ff4c_1
    • libssh2=1.10.0=h8f2d780_0
    • libstdcxx-ng=11.2.0=h1234567_1
    • libtasn1=4.16.0=h27cfd23_0
    • libtiff=4.4.0=hecacb30_2
    • libunistring=0.9.10=h27cfd23_0
    • libuuid=1.41.5=h5eee18b_0
    • libuv=1.40.0=h7b6447c_0
    • libvorbis=1.3.7=h7b6447c_0
    • libvpx=1.7.0=h439df22_0
    • libwebp-base=1.2.4=h5eee18b_0
    • libxcb=1.15=h7f8727e_0
    • libxml2=2.9.14=h74e7548_0
    • llvmlite=0.29.0=py36hd408876_0
    • lz4-c=1.9.3=h295c915_1
    • markdown=3.3.4=py36h06a4308_0
    • matplotlib=3.3.4=py36h06a4308_0
    • matplotlib-base=3.3.4=py36h62a2d02_0
    • mkl=2020.2=256
    • mkl-service=2.3.0=py36he8ac12f_0
    • mkl_fft=1.3.0=py36h54f3939_0
    • mkl_random=1.1.1=py36h0573a6f_0
    • ncurses=6.3=h5eee18b_3
    • nettle=3.7.3=hbbd107a_1
    • ninja=1.10.2=h06a4308_5
    • ninja-base=1.10.2=hd09550d_5
    • numba=0.45.1=py36h962f231_0
    • numpy=1.19.2=py36h54aff64_0
    • numpy-base=1.19.2=py36hfa32c7d_0
    • olefile=0.46=py36_0
    • openh264=2.1.1=h4ff587b_0
    • openjpeg=2.4.0=h3ad879b_0
    • openssl=1.1.1s=h7f8727e_0
    • pcre=8.45=h295c915_0
    • pip=21.2.4=pyhd8ed1ab_0
    • protobuf=3.17.2=py36h295c915_0
    • pycparser=2.21=pyhd3eb1b0_0
    • pyparsing=3.0.4=pyhd3eb1b0_0
    • pyqt=5.9.2=py36h05f1152_2
    • pysoundfile=0.11.0=pyhd8ed1ab_0
    • python=3.6.13=h12debd9_1
    • python-dateutil=2.8.2=pyhd3eb1b0_0
    • python_abi=3.6=2_cp36m
    • pytorch=1.8.1=py3.6_cuda10.1_cudnn7.6.3_0
    • qt=5.9.7=h5867ecd_1
    • readline=8.2=h5eee18b_0
    • resampy=0.2.2=py_0
    • scikit-learn=0.24.2=py36ha9443f7_0
    • scipy=1.5.2=py36h0b6359f_0
    • setuptools=49.6.0=py36h5fab9bb_3
    • sip=4.19.8=py36hf484d3e_0
    • six=1.16.0=pyhd3eb1b0_1
    • sqlite=3.39.3=h5082296_0
    • tbb=2021.6.0=hdb19cb5_0
    • tensorboard=1.14.0=py36hf484d3e_0
    • tensorflow=1.14.0=hc3e5e64_0
    • tensorflow-base=1.14.0=py36hc3e5e64_0
    • tensorflow-estimator=1.14.0=py_0
    • tensorflow-gpu=1.14.0=h0d30ee6_0
    • termcolor=1.1.0=py36h06a4308_1
    • threadpoolctl=2.2.0=pyh0d69192_0
    • tk=8.6.12=h1ccaba5_0
    • torchvision=0.2.2=py_3
    • tornado=6.1=py36h27cfd23_0
    • typing_extensions=4.1.1=pyh06a4308_0
    • werkzeug=2.0.3=pyhd3eb1b0_0
    • wheel=0.37.1=pyhd3eb1b0_0
    • wrapt=1.12.1=py36h7b6447c_1
    • x264=1!157.20191217=h7b6447c_0
    • xz=5.2.6=h5eee18b_0
    • zipp=3.6.0=pyhd3eb1b0_0
    • zlib=1.2.13=h5eee18b_0
    • zstd=1.5.2=ha4553b6_0
    • pip:
      • beautifulsoup4==4.11.1
      • charset-normalizer==2.0.12
      • decorator==4.4.2
      • dlib==19.18.0
      • dominate==2.4.0
      • easydict==1.9
      • filelock==3.4.1
      • gdown==4.5.3
      • idna==3.4
      • imageio==2.15.0
      • importlib-resources==5.4.0
      • mxnet==1.5.1.post0
      • mxnet-cu101==1.5.0
      • networkx==2.5.1
      • opencv-python==4.1.0.25
      • pillow==8.4.0
      • pysocks==1.7.1
      • python-graphviz==0.8.4
      • python-speech-features==0.6
      • pywavelets==1.1.1
      • requests==2.27.1
      • scikit-image==0.15.0
      • soupsieve==2.3.2.post1
      • tqdm==4.64.1
      • urllib3==1.26.12 prefix: /<your_path>/anaconda3/envs/<your_environment>`
    opened by ArghyaPal 0
  • Bump pillow from 4.3.0 to 9.3.0

    Bump pillow from 4.3.0 to 9.3.0

    Bumps pillow from 4.3.0 to 9.3.0.

    Release notes

    Sourced from pillow's releases.

    9.3.0

    https://pillow.readthedocs.io/en/stable/releasenotes/9.3.0.html

    Changes

    ... (truncated)

    Changelog

    Sourced from pillow's changelog.

    9.3.0 (2022-10-29)

    • Limit SAMPLESPERPIXEL to avoid runtime DOS #6700 [wiredfool]

    • Initialize libtiff buffer when saving #6699 [radarhere]

    • Inline fname2char to fix memory leak #6329 [nulano]

    • Fix memory leaks related to text features #6330 [nulano]

    • Use double quotes for version check on old CPython on Windows #6695 [hugovk]

    • Remove backup implementation of Round for Windows platforms #6693 [cgohlke]

    • Fixed set_variation_by_name offset #6445 [radarhere]

    • Fix malloc in _imagingft.c:font_setvaraxes #6690 [cgohlke]

    • Release Python GIL when converting images using matrix operations #6418 [hmaarrfk]

    • Added ExifTags enums #6630 [radarhere]

    • Do not modify previous frame when calculating delta in PNG #6683 [radarhere]

    • Added support for reading BMP images with RLE4 compression #6674 [npjg, radarhere]

    • Decode JPEG compressed BLP1 data in original mode #6678 [radarhere]

    • Added GPS TIFF tag info #6661 [radarhere]

    • Added conversion between RGB/RGBA/RGBX and LAB #6647 [radarhere]

    • Do not attempt normalization if mode is already normal #6644 [radarhere]

    ... (truncated)

    Commits

    Dependabot compatibility score

    Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


    Dependabot commands and options

    You can trigger Dependabot actions by commenting on this PR:

    • @dependabot rebase will rebase this PR
    • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
    • @dependabot merge will merge this PR after your CI passes on it
    • @dependabot squash and merge will squash and merge this PR after your CI passes on it
    • @dependabot cancel merge will cancel a previously requested merge and block automerging
    • @dependabot reopen will reopen this PR if it is closed
    • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
    • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
    • @dependabot use these labels will set the current labels as the default for future PRs for this repo and language
    • @dependabot use these reviewers will set the current reviewers as the default for future PRs for this repo and language
    • @dependabot use these assignees will set the current assignees as the default for future PRs for this repo and language
    • @dependabot use this milestone will set the current milestone as the default for future PRs for this repo and language

    You can disable automated security fix PRs for this repo from the Security Alerts page.

    dependencies 
    opened by dependabot[bot] 0
  • Bump tensorflow-gpu from 1.14.0 to 2.9.3

    Bump tensorflow-gpu from 1.14.0 to 2.9.3

    Bumps tensorflow-gpu from 1.14.0 to 2.9.3.

    Release notes

    Sourced from tensorflow-gpu's releases.

    TensorFlow 2.9.3

    Release 2.9.3

    This release introduces several vulnerability fixes:

    TensorFlow 2.9.2

    Release 2.9.2

    This releases introduces several vulnerability fixes:

    ... (truncated)

    Changelog

    Sourced from tensorflow-gpu's changelog.

    Release 2.9.3

    This release introduces several vulnerability fixes:

    Release 2.8.4

    This release introduces several vulnerability fixes:

    ... (truncated)

    Commits
    • a5ed5f3 Merge pull request #58584 from tensorflow/vinila21-patch-2
    • 258f9a1 Update py_func.cc
    • cd27cfb Merge pull request #58580 from tensorflow-jenkins/version-numbers-2.9.3-24474
    • 3e75385 Update version numbers to 2.9.3
    • bc72c39 Merge pull request #58482 from tensorflow-jenkins/relnotes-2.9.3-25695
    • 3506c90 Update RELEASE.md
    • 8dcb48e Update RELEASE.md
    • 4f34ec8 Merge pull request #58576 from pak-laura/c2.99f03a9d3bafe902c1e6beb105b2f2417...
    • 6fc67e4 Replace CHECK with returning an InternalError on failing to create python tuple
    • 5dbe90a Merge pull request #58570 from tensorflow/r2.9-7b174a0f2e4
    • Additional commits viewable in compare view

    Dependabot compatibility score

    Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


    Dependabot commands and options

    You can trigger Dependabot actions by commenting on this PR:

    • @dependabot rebase will rebase this PR
    • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
    • @dependabot merge will merge this PR after your CI passes on it
    • @dependabot squash and merge will squash and merge this PR after your CI passes on it
    • @dependabot cancel merge will cancel a previously requested merge and block automerging
    • @dependabot reopen will reopen this PR if it is closed
    • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
    • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
    • @dependabot use these labels will set the current labels as the default for future PRs for this repo and language
    • @dependabot use these reviewers will set the current reviewers as the default for future PRs for this repo and language
    • @dependabot use these assignees will set the current assignees as the default for future PRs for this repo and language
    • @dependabot use this milestone will set the current milestone as the default for future PRs for this repo and language

    You can disable automated security fix PRs for this repo from the Security Alerts page.

    dependencies 
    opened by dependabot[bot] 0
  • Bump joblib from 0.13.2 to 1.2.0

    Bump joblib from 0.13.2 to 1.2.0

    Bumps joblib from 0.13.2 to 1.2.0.

    Changelog

    Sourced from joblib's changelog.

    Release 1.2.0

    • Fix a security issue where eval(pre_dispatch) could potentially run arbitrary code. Now only basic numerics are supported. joblib/joblib#1327

    • Make sure that joblib works even when multiprocessing is not available, for instance with Pyodide joblib/joblib#1256

    • Avoid unnecessary warnings when workers and main process delete the temporary memmap folder contents concurrently. joblib/joblib#1263

    • Fix memory alignment bug for pickles containing numpy arrays. This is especially important when loading the pickle with mmap_mode != None as the resulting numpy.memmap object would not be able to correct the misalignment without performing a memory copy. This bug would cause invalid computation and segmentation faults with native code that would directly access the underlying data buffer of a numpy array, for instance C/C++/Cython code compiled with older GCC versions or some old OpenBLAS written in platform specific assembly. joblib/joblib#1254

    • Vendor cloudpickle 2.2.0 which adds support for PyPy 3.8+.

    • Vendor loky 3.3.0 which fixes several bugs including:

      • robustly forcibly terminating worker processes in case of a crash (joblib/joblib#1269);

      • avoiding leaking worker processes in case of nested loky parallel calls;

      • reliability spawn the correct number of reusable workers.

    Release 1.1.0

    • Fix byte order inconsistency issue during deserialization using joblib.load in cross-endian environment: the numpy arrays are now always loaded to use the system byte order, independently of the byte order of the system that serialized the pickle. joblib/joblib#1181

    • Fix joblib.Memory bug with the ignore parameter when the cached function is a decorated function.

    ... (truncated)

    Commits
    • 5991350 Release 1.2.0
    • 3fa2188 MAINT cleanup numpy warnings related to np.matrix in tests (#1340)
    • cea26ff CI test the future loky-3.3.0 branch (#1338)
    • 8aca6f4 MAINT: remove pytest.warns(None) warnings in pytest 7 (#1264)
    • 067ed4f XFAIL test_child_raises_parent_exits_cleanly with multiprocessing (#1339)
    • ac4ebd5 MAINT add back pytest warnings plugin (#1337)
    • a23427d Test child raises parent exits cleanly more reliable on macos (#1335)
    • ac09691 [MAINT] various test updates (#1334)
    • 4a314b1 Vendor loky 3.2.0 (#1333)
    • bdf47e9 Make test_parallel_with_interactively_defined_functions_default_backend timeo...
    • Additional commits viewable in compare view

    Dependabot compatibility score

    Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


    Dependabot commands and options

    You can trigger Dependabot actions by commenting on this PR:

    • @dependabot rebase will rebase this PR
    • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
    • @dependabot merge will merge this PR after your CI passes on it
    • @dependabot squash and merge will squash and merge this PR after your CI passes on it
    • @dependabot cancel merge will cancel a previously requested merge and block automerging
    • @dependabot reopen will reopen this PR if it is closed
    • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
    • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
    • @dependabot use these labels will set the current labels as the default for future PRs for this repo and language
    • @dependabot use these reviewers will set the current reviewers as the default for future PRs for this repo and language
    • @dependabot use these assignees will set the current assignees as the default for future PRs for this repo and language
    • @dependabot use this milestone will set the current milestone as the default for future PRs for this repo and language

    You can disable automated security fix PRs for this repo from the Security Alerts page.

    dependencies 
    opened by dependabot[bot] 0
  • Bump protobuf from 3.8.0 to 3.18.3

    Bump protobuf from 3.8.0 to 3.18.3

    Bumps protobuf from 3.8.0 to 3.18.3.

    Release notes

    Sourced from protobuf's releases.

    Protocol Buffers v3.18.3

    C++

    Protocol Buffers v3.16.1

    Java

    • Improve performance characteristics of UnknownFieldSet parsing (#9371)

    Protocol Buffers v3.18.2

    Java

    • Improve performance characteristics of UnknownFieldSet parsing (#9371)

    Protocol Buffers v3.18.1

    Python

    • Update setup.py to reflect that we now require at least Python 3.5 (#8989)
    • Performance fix for DynamicMessage: force GetRaw() to be inlined (#9023)

    Ruby

    • Update ruby_generator.cc to allow proto2 imports in proto3 (#9003)

    Protocol Buffers v3.18.0

    C++

    • Fix warnings raised by clang 11 (#8664)
    • Make StringPiece constructible from std::string_view (#8707)
    • Add missing capability attributes for LLVM 12 (#8714)
    • Stop using std::iterator (deprecated in C++17). (#8741)
    • Move field_access_listener from libprotobuf-lite to libprotobuf (#8775)
    • Fix #7047 Safely handle setlocale (#8735)
    • Remove deprecated version of SetTotalBytesLimit() (#8794)
    • Support arena allocation of google::protobuf::AnyMetadata (#8758)
    • Fix undefined symbol error around SharedCtor() (#8827)
    • Fix default value of enum(int) in json_util with proto2 (#8835)
    • Better Smaller ByteSizeLong
    • Introduce event filters for inject_field_listener_events
    • Reduce memory usage of DescriptorPool
    • For lazy fields copy serialized form when allowed.
    • Re-introduce the InlinedStringField class
    • v2 access listener
    • Reduce padding in the proto's ExtensionRegistry map.
    • GetExtension performance optimizations
    • Make tracker a static variable rather than call static functions
    • Support extensions in field access listener
    • Annotate MergeFrom for field access listener
    • Fix incomplete types for field access listener
    • Add map_entry/new_map_entry to SpecificField in MessageDifferencer. They record the map items which are different in MessageDifferencer's reporter.
    • Reduce binary size due to fieldless proto messages
    • TextFormat: ParseInfoTree supports getting field end location in addition to start.

    ... (truncated)

    Commits

    Dependabot compatibility score

    Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


    Dependabot commands and options

    You can trigger Dependabot actions by commenting on this PR:

    • @dependabot rebase will rebase this PR
    • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
    • @dependabot merge will merge this PR after your CI passes on it
    • @dependabot squash and merge will squash and merge this PR after your CI passes on it
    • @dependabot cancel merge will cancel a previously requested merge and block automerging
    • @dependabot reopen will reopen this PR if it is closed
    • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
    • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
    • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
    • @dependabot use these labels will set the current labels as the default for future PRs for this repo and language
    • @dependabot use these reviewers will set the current reviewers as the default for future PRs for this repo and language
    • @dependabot use these assignees will set the current assignees as the default for future PRs for this repo and language
    • @dependabot use this milestone will set the current milestone as the default for future PRs for this repo and language

    You can disable automated security fix PRs for this repo from the Security Alerts page.

    dependencies 
    opened by dependabot[bot] 0
Owner
Ran Yi
Assistant Professor at CSE Dept, SJTU
Ran Yi
Using python to generate a bat script of repetitive lines of code that differ in some way but can sort out a group of audio files according to their common names

Batch Sorting Using python to generate a bat script of repetitive lines of code that differ in some way but can sort out a group of audio files accord

David Mainoo 1 Oct 29, 2021
Code to work with wave files!

Code to work with wave files!

Mohammad Dori 3 Jul 15, 2022
Code for csig audio deepfake detection

FMFCC Audio Deepfake Detection Solution This repo provides an solution for the 多媒体伪造取证大赛. Our solution achieve the 1st in the Audio Deepfake Detection

BokingChen 9 Jun 4, 2022
This is the official source code for SLATE. We provide the code for the model, the training code, and a dataset loader for the 3D Shapes dataset. This code is implemented in Pytorch.

SLATE This is the official source code for SLATE. We provide the code for the model, the training code and a dataset loader for the 3D Shapes dataset.

Gautam Singh 66 Dec 26, 2022
IDE allow you to refactor code, Baron allows you to write refactoring code.

Introduction Baron is a Full Syntax Tree (FST) library for Python. By opposition to an AST which drops some syntax information in the process of its c

Python Code Quality Authority 278 Dec 29, 2022
Various code metrics for Python code

Radon Radon is a Python tool that computes various metrics from the source code. Radon can compute: McCabe's complexity, i.e. cyclomatic complexity ra

Michele Lacchia 1.4k Jan 7, 2023
Code examples for my Write Better Python Code series on YouTube.

Write Better Python Code This repository contains the code examples used in my Write Better Python Code series published on YouTube: https:/

null 858 Dec 29, 2022
Django project starter on steroids: quickly create a Django app AND generate source code for data models + REST/GraphQL APIs (the generated code is auto-linted and has 100% test coverage).

Create Django App ?? We're a Django project starter on steroids! One-line command to create a Django app with all the dependencies auto-installed AND

imagine.ai 68 Oct 19, 2022
TensorFlow code for the neural network presented in the paper: "Structural Language Models of Code" (ICML'2020)

SLM: Structural Language Models of Code This is an official implementation of the model described in: "Structural Language Models of Code" [PDF] To ap

null 73 Nov 6, 2022
Code to use Augmented Shapiro Wilks Stopping, as well as code for the paper "Statistically Signifigant Stopping of Neural Network Training"

This codebase is being actively maintained, please create and issue if you have issues using it Basics All data files are included under losses and ea

Justin Terry 32 Nov 9, 2021
Inference code for "StylePeople: A Generative Model of Fullbody Human Avatars" paper. This code is for the part of the paper describing video-based avatars.

NeuralTextures This is repository with inference code for paper "StylePeople: A Generative Model of Fullbody Human Avatars" (CVPR21). This code is for

Visual Understanding Lab @ Samsung AI Center Moscow 18 Oct 6, 2022
A code generator from ONNX to PyTorch code

onnx-pytorch Generating pytorch code from ONNX. Currently support onnx==1.9.0 and torch==1.8.1. Installation From PyPI pip install onnx-pytorch From

Wenhao Hu 94 Jan 6, 2023
SCodeScanner stands for Source Code scanner where the user can scans the source code for finding the Critical Vulnerabilities.

The SCodeScanner stands for Source Code Scanner, where you can scan your source code files like PHP and get identify the vulnerabilities inside it. The tool can use by Pentester, Developer to quickly identify the weakness.

null 136 Dec 13, 2022
This is the code for our KILT leaderboard submission to the T-REx and zsRE tasks. It includes code for training a DPR model then continuing training with RAG.

KGI (Knowledge Graph Induction) for slot filling This is the code for our KILT leaderboard submission to the T-REx and zsRE tasks. It includes code fo

International Business Machines 72 Jan 6, 2023
Convert Python 3 code to CUDA code.

Py2CUDA Convert python code to CUDA. Usage To convert a python file say named py_file.py to CUDA, run python generate_cuda.py --file py_file.py --arch

Yuval Rosen 3 Jul 14, 2021
Empirical Study of Transformers for Source Code & A Simple Approach for Handling Out-of-Vocabulary Identifiers in Deep Learning for Source Code

Transformers for variable misuse, function naming and code completion tasks The official PyTorch implementation of: Empirical Study of Transformers fo

Bayesian Methods Research Group 56 Nov 15, 2022
Reference implementation of code generation projects from Facebook AI Research. General toolkit to apply machine learning to code, from dataset creation to model training and evaluation. Comes with pretrained models.

This repository is a toolkit to do machine learning for programming languages. It implements tokenization, dataset preprocessing, model training and m

Facebook Research 408 Jan 1, 2023
A python script to prefab your scripts/text files, and re create them with ease and not have to open your browser to copy code or write code yourself

Scriptfab - What is it? A python script to prefab your scripts/text files, and re create them with ease and not have to open your browser to copy code

DevNugget 3 Jul 28, 2021
Code for the Python code smells video on the ArjanCodes channel.

7 Python code smells This repository contains the code for the Python code smells video on the ArjanCodes channel (watch the video here). The example

null 55 Dec 29, 2022
Mysterium the first tool which permits you to retrieve the most part of a Python code even the .py or .pyc was extracted from an executable file, even it is encrypted with every existing encryptage. Mysterium don't make any difference between encrypted and non encrypted files, it can retrieve code from Pyarmor or .pyc files.

Mysterium the first tool which permits you to retrieve the most part of a Python code even the .py or .pyc was extracted from an executable file, even it is encrypted with every existing encryptage. Mysterium don't make any difference between encrypted and non encrypted files, it can retrieve code from Pyarmor or .pyc files.

Venax 116 Dec 21, 2022