A central task in drug discovery is searching, screening, and organizing large chemical databases

Overview

Cheminformatics Clustering


Introduction

A central task in drug discovery is searching, screening, and organizing large chemical databases. Here, we implement clustering on molecular similarity. We support multiple methods to provide a interactive exploration of chemical space.

  • Compute Morgan circular fingerprints, cluster using k-means, and perform dimensionality reduction using PCA and UMAP. Distributed GPU-accelerated algorithms with multi-GPU support are used in this method. This allows processing very large datasets.
  • Compute Morgan circular fingerprints, Sparse Random Projection and cluster using k-means.
  • Generate new molecules either by exploring the latent space between two molecules or sampling around a molecule

screenshot

Preparing the Environment (optional)

A launch script, launch.sh, is provided to perform all tasks.

Customization

The environment can be customized for control of the container, to create your own repo, or to store the data in a custom location. However, if this is not needed, skip to Getting Started to use the defaults.

To customize your local environment, edit the appropriate section of launch.sh or provide a ~/.env file with the following information below. To generate a template for .env, just run ./launch.sh with no arguments. If .env does not exist, then a template will be written for you.

CONT=nvcr.io/nvidia/clara/cheminformatics_demo:0.0.1
JUPYTER_PORT=8888
PLOTLY_PORT=5000
DASK_PORT=9001
PROJECT_PATH=/path/to/local/repo/dir
DATA_PATH=/path/to/scratch/space
DATA_MOUNT_PATH=/data

Getting Started

Once your environment is setup, the following commands should be all you need.

Build your container:

./launch.sh build

Download the ChEMBL database (version 27):

./launch.sh dbSetup

Launch the interactive ChEMBL exploration tool:

./launch.sh start
optional arguments:
  -h, --help            show this help message and exit
  --cpu                 Use CPU
  -b, --benchmark       Execute for benchmark
  -p PCA_COMPS, --pca_comps PCA_COMPS
                        Number of PCA components
  -n NUM_CLUSTERS, --num_clusters NUM_CLUSTERS
                        Numer of clusters
  -c CACHE_DIRECTORY, --cache_directory CACHE_DIRECTORY
                        Location to pick fingerprint from
  -m N_MOL, --n_mol N_MOL
                        Number of molecules for analysis. Use negative numbers
                        for using the whole dataset.
  --batch_size BATCH_SIZE
                        Chunksize.
  -o OUTPUT_DIR, --output_dir OUTPUT_DIR
                        Output directory for benchmark results
  --n_gpu N_GPU         Number of GPUs to use
  --n_cpu N_CPU         Number of CPU workers to use
  -d, --debug           Show debug message

Navigate a browser to:

https://0.0.0.0:5000

Tutorial

See the tutorial for an example walkthrough.

Advanced Setup

Caching Fingerprints

Users can generate Morgan Fingerprints and store it in HDF5 files for later use. Please use the following command to generate fingerprint cache.

./launch.sh cache -c /data/fp

It is best to create the cache at DATA_MOUNT_PATH property defined in ~/.env. Default value of this property is /data/. This is a mounted volumne from host and available for reuse beyond the container's lifetime.

Once generated, the cached fingerprints can be used for analysis using -c option.

./launch.sh start -c /data/fp

Conda

Conda environment support is available for user wanting to use the tool outside of containers. Please find the setup file in setup directory.

Acceleration

The latest benchmarks reside in the benchmark directory.

Benchmark tests run on A100:

Benchmark tests run on V100:

Features

  • Cluster molecules from ChEMBL using the embedding generated from Morgan Fingerprints --> PCA --> UMAP
  • Ability to color the clustered molecules based on molecular properties
  • Ability to recluster on user selected subsets of molecules or specific clusters
  • Designate and track molecules of interest during the analysis
  • Generate new molecules by linearly interpolating the latent space between two selected molecules or sampling arround a selected molecule
  • Export generated molecules in SDF format
Comments
  • Unable to use megamolbart model

    Unable to use megamolbart model

    I tried following the instructions shown in themegamolbart/README, but that does not work for me:

    --(Wed Apr 06|15:25 [master]$)- ./launch.sh dev 2
    sourcing environment from ./.env
    + local CONTAINER_OPTION=2
    + local CONT=nvcr.io/nvstaging/clara/cheminformatics_demo:latest
    + [[ 2 -eq 2 ]]
    + DOCKER_CMD='docker run     --rm     --network host     --runtime=nvidia     -p :8888     -p 9001:9001     -p 5000:5000     -v /home/muammar/git/cheminformatics:/workspace     -v /home/muammar/git/cheminformatics/data/data:/data     -u 1000:1000     --shm-size=1g     --ulimit memlock=-1     --ulimit stack=67108864     -e HOME=/workspace     -e TF_CPP_MIN_LOG_LEVEL=3     -w /workspace -v /home/muammar/git/cheminformatics/megamolbart/models:/models/megamolbart/'
    + DOCKER_CMD='docker run     --rm     --network host     --runtime=nvidia     -p :8888     -p 9001:9001     -p 5000:5000     -v /home/muammar/git/cheminformatics:/workspace     -v /home/muammar/git/cheminformatics/data/data:/data     -u 1000:1000     --shm-size=1g     --ulimit memlock=-1     --ulimit stack=67108864     -e HOME=/workspace     -e TF_CPP_MIN_LOG_LEVEL=3     -w /workspace -v /home/muammar/git/cheminformatics/megamolbart/models:/models/megamolbart/ -w /workspace/megamolbart/'
    + CONT=nvcr.io/nvstaging/clara/megamolbart:latest
    + docker run --rm --network host --runtime=nvidia -p :8888 -p 9001:9001 -p 5000:5000 -v /home/muammar/git/cheminformatics:/workspace -v /home/muammar/git/cheminformatics/data/data:/data -u 1000:1000 --shm-size=1g --ulimit memlock=-1 --ulimit stack=67108864 -e HOME=/workspace -e TF_CPP_MIN_LOG_LEVEL=3 -w /workspace -v /home/muammar/git/cheminformatics/megamolbart/models:/models/megamolbart/ -w /workspace/megamolbart/ -it nvcr.io/nvstaging/clara/megamolbart:latest bash
    WARNING: Published ports are discarded when using host network mode
    
    =============
    == PyTorch ==
    =============
    
    NVIDIA Release 20.11 (build 17345815)
    PyTorch Version 1.8.0a0+17f8c32
    
    Container image Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
    
    Copyright (c) 2014-2020 Facebook Inc.
    Copyright (c) 2011-2014 Idiap Research Institute (Ronan Collobert)
    Copyright (c) 2012-2014 Deepmind Technologies    (Koray Kavukcuoglu)
    Copyright (c) 2011-2012 NEC Laboratories America (Koray Kavukcuoglu)
    Copyright (c) 2011-2013 NYU                      (Clement Farabet)
    Copyright (c) 2006-2010 NEC Laboratories America (Ronan Collobert, Leon Bottou, Iain Melvin, Jason Weston)
    Copyright (c) 2006      Idiap Research Institute (Samy Bengio)
    Copyright (c) 2001-2004 Idiap Research Institute (Ronan Collobert, Samy Bengio, Johnny Mariethoz)
    Copyright (c) 2015      Google Inc.
    Copyright (c) 2015      Yangqing Jia
    Copyright (c) 2013-2016 The Caffe contributors
    All rights reserved.
    
    NVIDIA Deep Learning Profiler (dlprof) Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
    
    Various files include modifications (c) NVIDIA CORPORATION.  All rights reserved.
    NVIDIA modifications are covered by the license terms that apply to the underlying project or file.
    ERROR: No supported GPU(s) detected to run this container
    
    NOTE: MOFED driver for multi-node communication was not detected.
          Multi-node communication performance may be reduced.
    
    (base) bash-4.4$
    

    After getting in the SHELL, I do:

    (base) bash-4.4$ python launch.py &
    [1] 54
    (base) bash-4.4$ INFO:megamolbart:Maximum decoded sequence length is set to 512
    INFO:megamolbart:Triggering model download...
    Downloading model megamolbart to /models/megamolbart...
    ++ wget -q --show-progress --content-disposition https://api.ngc.nvidia.com/v2/models/nvidia/clara/megamolbart/versions/0.1/zip -O /models/megamolbart/megamolbart_0.1.zip
    /models/megamolbart/megamolbart_0.1.zip: Permission denied
    ++ mkdir /models/megamolbart
    mkdir: cannot create directory ‘/models/megamolbart’: File exists
    ++ unzip -q /models/megamolbart/megamolbart_0.1.zip -d /models/megamolbart
    unzip:  cannot find or open /models/megamolbart/megamolbart_0.1.zip, /models/megamolbart/megamolbart_0.1.zip.zip or /models/megamolbart/megamolbart_0.1.zip.ZIP.
    INFO:megamolbart:Model download result: None
    INFO:megamolbart:Model download result: None
    Traceback (most recent call last):
      File "launch.py", line 98, in <module>
        main()
      File "launch.py", line 94, in main
        Launcher()
      File "launch.py", line 71, in __init__
        self.download_megamolbart_model()
      File "launch.py", line 92, in download_megamolbart_model
        raise Exception('Error downloading model')
    Exception: Error downloading model
    

    The user created in the container does not have permission to write on /models/megamolbart. I am looking to feed some SMILES strings to megamolbart and generate embeddings. How can I achieve that? I would appreciate any help you could provide me. Thanks.

    opened by muammar 8
  • Bump tensorflow-gpu from 1.15.5 to 2.7.2 in /cuchem

    Bump tensorflow-gpu from 1.15.5 to 2.7.2 in /cuchem

    Bumps tensorflow-gpu from 1.15.5 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

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    dependencies 
    opened by dependabot[bot] 3
  • Bump tensorflow-gpu from 1.15.5 to 2.6.4 in /cuchem

    Bump tensorflow-gpu from 1.15.5 to 2.6.4 in /cuchem

    Bumps tensorflow-gpu from 1.15.5 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

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    dependencies 
    opened by dependabot[bot] 2
  • Bump tensorflow-gpu from 1.15.5 to 2.5.3 in /cuchem

    Bump tensorflow-gpu from 1.15.5 to 2.5.3 in /cuchem

    Bumps tensorflow-gpu from 1.15.5 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
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    dependencies 
    opened by dependabot[bot] 2
  • Bump tensorflow-gpu from 1.15.5 to 2.5.1 in /cuchem

    Bump tensorflow-gpu from 1.15.5 to 2.5.1 in /cuchem

    Bumps tensorflow-gpu from 1.15.5 to 2.5.1.

    Release notes

    Sourced from tensorflow-gpu's releases.

    TensorFlow 2.5.1

    Release 2.5.1

    This release introduces several vulnerability fixes:

    • Fixes a heap out of bounds access in sparse reduction operations (CVE-2021-37635)
    • Fixes a floating point exception in SparseDenseCwiseDiv (CVE-2021-37636)
    • Fixes a null pointer dereference in CompressElement (CVE-2021-37637)
    • Fixes a null pointer dereference in RaggedTensorToTensor (CVE-2021-37638)
    • Fixes a null pointer dereference and a heap OOB read arising from operations restoring tensors (CVE-2021-37639)
    • Fixes an integer division by 0 in sparse reshaping (CVE-2021-37640)
    • Fixes a division by 0 in ResourceScatterDiv (CVE-2021-37642)
    • Fixes a heap OOB in RaggedGather (CVE-2021-37641)
    • Fixes a std::abort raised from TensorListReserve (CVE-2021-37644)
    • Fixes a null pointer dereference in MatrixDiagPartOp (CVE-2021-37643)
    • Fixes an integer overflow due to conversion to unsigned (CVE-2021-37645)
    • Fixes a bad allocation error in StringNGrams caused by integer conversion (CVE-2021-37646)
    • Fixes a null pointer dereference in SparseTensorSliceDataset (CVE-2021-37647)
    • Fixes an incorrect validation of SaveV2 inputs (CVE-2021-37648)
    • Fixes a null pointer dereference in UncompressElement (CVE-2021-37649)
    • Fixes a segfault and a heap buffer overflow in {Experimental,}DatasetToTFRecord (CVE-2021-37650)
    • Fixes a heap buffer overflow in FractionalAvgPoolGrad (CVE-2021-37651)
    • Fixes a use after free in boosted trees creation (CVE-2021-37652)
    • Fixes a division by 0 in ResourceGather (CVE-2021-37653)
    • Fixes a heap OOB and a CHECK fail in ResourceGather (CVE-2021-37654)
    • Fixes a heap OOB in ResourceScatterUpdate (CVE-2021-37655)
    • Fixes an undefined behavior arising from reference binding to nullptr in RaggedTensorToSparse (CVE-2021-37656)
    • Fixes an undefined behavior arising from reference binding to nullptr in MatrixDiagV* ops (CVE-2021-37657)
    • Fixes an undefined behavior arising from reference binding to nullptr in MatrixSetDiagV* ops (CVE-2021-37658)
    • Fixes an undefined behavior arising from reference binding to nullptr and heap OOB in binary cwise ops (CVE-2021-37659)
    • Fixes a division by 0 in inplace operations (CVE-2021-37660)
    • Fixes a crash caused by integer conversion to unsigned (CVE-2021-37661)
    • Fixes an undefined behavior arising from reference binding to nullptr in boosted trees (CVE-2021-37662)
    • Fixes a heap OOB in boosted trees (CVE-2021-37664)
    • Fixes vulnerabilities arising from incomplete validation in QuantizeV2 (CVE-2021-37663)
    • Fixes vulnerabilities arising from incomplete validation in MKL requantization (CVE-2021-37665)
    • Fixes an undefined behavior arising from reference binding to nullptr in RaggedTensorToVariant (CVE-2021-37666)
    • Fixes an undefined behavior arising from reference binding to nullptr in unicode encoding (CVE-2021-37667)
    • Fixes an FPE in tf.raw_ops.UnravelIndex (CVE-2021-37668)
    • Fixes a crash in NMS ops caused by integer conversion to unsigned (CVE-2021-37669)
    • Fixes a heap OOB in UpperBound and LowerBound (CVE-2021-37670)
    • Fixes an undefined behavior arising from reference binding to nullptr in map operations (CVE-2021-37671)
    • Fixes a heap OOB in SdcaOptimizerV2 (CVE-2021-37672)
    • Fixes a CHECK-fail in MapStage (CVE-2021-37673)
    • Fixes a vulnerability arising from incomplete validation in MaxPoolGrad (CVE-2021-37674)
    • Fixes an undefined behavior arising from reference binding to nullptr in shape inference (CVE-2021-37676)
    • Fixes a division by 0 in most convolution operators (CVE-2021-37675)
    • Fixes vulnerabilities arising from missing validation in shape inference for Dequantize (CVE-2021-37677)
    • Fixes an arbitrary code execution due to YAML deserialization (CVE-2021-37678)
    • Fixes a heap OOB in nested tf.map_fn with RaggedTensors (CVE-2021-37679)

    ... (truncated)

    Changelog

    Sourced from tensorflow-gpu's changelog.

    Release 2.5.1

    This release introduces several vulnerability fixes:

    • Fixes a heap out of bounds access in sparse reduction operations (CVE-2021-37635)
    • Fixes a floating point exception in SparseDenseCwiseDiv (CVE-2021-37636)
    • Fixes a null pointer dereference in CompressElement (CVE-2021-37637)
    • Fixes a null pointer dereference in RaggedTensorToTensor (CVE-2021-37638)
    • Fixes a null pointer dereference and a heap OOB read arising from operations restoring tensors (CVE-2021-37639)
    • Fixes an integer division by 0 in sparse reshaping (CVE-2021-37640)
    • Fixes a division by 0 in ResourceScatterDiv (CVE-2021-37642)
    • Fixes a heap OOB in RaggedGather (CVE-2021-37641)
    • Fixes a std::abort raised from TensorListReserve (CVE-2021-37644)
    • Fixes a null pointer dereference in MatrixDiagPartOp (CVE-2021-37643)
    • Fixes an integer overflow due to conversion to unsigned (CVE-2021-37645)
    • Fixes a bad allocation error in StringNGrams caused by integer conversion (CVE-2021-37646)
    • Fixes a null pointer dereference in SparseTensorSliceDataset (CVE-2021-37647)
    • Fixes an incorrect validation of SaveV2 inputs (CVE-2021-37648)
    • Fixes a null pointer dereference in UncompressElement (CVE-2021-37649)
    • Fixes a segfault and a heap buffer overflow in {Experimental,}DatasetToTFRecord (CVE-2021-37650)
    • Fixes a heap buffer overflow in FractionalAvgPoolGrad (CVE-2021-37651)
    • Fixes a use after free in boosted trees creation (CVE-2021-37652)
    • Fixes a division by 0 in ResourceGather (CVE-2021-37653)
    • Fixes a heap OOB and a CHECK fail in ResourceGather (CVE-2021-37654)
    • Fixes a heap OOB in ResourceScatterUpdate (CVE-2021-37655)
    • Fixes an undefined behavior arising from reference binding to nullptr in RaggedTensorToSparse

    ... (truncated)

    Commits
    • 8222c1c Merge pull request #51381 from tensorflow/mm-fix-r2.5-build
    • d584260 Disable broken/flaky test
    • f6c6ce3 Merge pull request #51367 from tensorflow-jenkins/version-numbers-2.5.1-17468
    • 3ca7812 Update version numbers to 2.5.1
    • 4fdf683 Merge pull request #51361 from tensorflow/mm-update-relnotes-on-r2.5
    • 05fc01a Put CVE numbers for fixes in parentheses
    • bee1dc4 Update release notes for the new patch release
    • 47beb4c Merge pull request #50597 from kruglov-dmitry/v2.5.0-sync-abseil-cmake-bazel
    • 6f39597 Merge pull request #49383 from ashahab/abin-load-segfault-r2.5
    • 0539b34 Merge pull request #48979 from liufengdb/r2.5-cherrypick
    • Additional commits viewable in compare view

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    dependencies 
    opened by dependabot[bot] 2
  • docker build fails

    docker build fails

    The FROM statement points to an image that appears to be private. Please advise on the location of a public alternative

    https://github.com/NVIDIA/cheminformatics/blob/a86ed80cf47d5f8ea7a0e4af3478c649da4b412b/Dockerfile.megamolbart#L2

    opened by ARekesh 2
  • Bugfix: Multiple bugs from first round of feedback...

    Bugfix: Multiple bugs from first round of feedback...

    • Docker COPY Command Does Not Transfer Necessary Files Into Container Now git clone is used to copy everything from master branch. TODO: Further changes are required to align development and production deployment.

    • Incorrectly Set GPU Flag Issue Still Exists Now while creating list of available GPUs casting exception are managed to avoid this issue.

    • UMAP Bug with CPU Pipeline in UI This was a ripple effect of changes to Dockerfile and conda env. file.

    • Changing the Number of Clusters Does not Seem to Impact Plot Additional changes to event handling callbacks are make to pick the value from the textbox is working. Now, the changed 'Number of Clusters' is picked on Recluster or Reload event

    • Reclustering on Two Clusters Produces an Error Reclustering with no 'Number of cluster' was the underlying reason for this issue. Now, 'Number of cluster' is not set to null or ''. In cases were 'Number of cluster is invalid, the default value (7) is used.

    • Cluster Color Palette Seems to Change Now the colors are generated only when 'Number of Clusters' is changed.

    opened by rilango 2
  • CPU version for benchmarking and bugfixes...

    CPU version for benchmarking and bugfixes...

    Changes to switch between CPU and GPU. This change is only limited to dash (not yet implemented in notebook).

    Switching between CPU and GPU can be done from line 101 in startdash.py.
    

    Bugfix: New MoI does not always add it to dataset and recluster

    Root cause for this was complex event hierarchy. Following were the events in
    question:
     - Onblur event from MoI input and click event from 'Highlight' button does the
       same thing(Re-cluster dataset and highlight MoI molecules).
     - Onblur event of MoI input was also used to manage 'Add to MoI' in the
       Molecular structure table.
    
    To fix this issue, onblur event is removed from MoI input. Now, the only way to
    recluster and highlight is by clicking 'Highlight' button. 'Add to MoI' is
    handled thru an onChange event emmitted from an hidden input element. This
    eliminates the race condition between onblur from MoI input and onclick from
    Highlight button.
    
    Another change in this PR, adds clusters with MoI to the top of the figure.
    

    Bugfix: Adding MoI not in the origitnal dataset...

    On entering a new MoI the selection of the molecule was performed onblur event
    and reclustering was happeing on hitting 'Highlight' button. Due to these
    different event trying to complete this one task, the molecule does did not
    get highlighted.
    
    With this change both these event can perform this task such that reclustering
    is always performed before highlighting the molecule.
    
    This bug was hiding few other issues in the application.
     - Copying kmeans label was merging based on index. Since, index changes
       between every recluster event, new MoI got aligned with incorrect cluster
    
    Other changes include issues with reload. Post reload similar, issues were
    causing inconsistent behavior around clustering and highlighting molecule.
    
    opened by rilango 2
  • Bump waitress from 2.1.1 to 2.1.2 in /cuchem

    Bump waitress from 2.1.1 to 2.1.2 in /cuchem

    Bumps waitress from 2.1.1 to 2.1.2.

    Changelog

    Sourced from waitress's changelog.

    2.1.2

    Bugfix

    
    - When expose_tracebacks is enabled waitress would fail to properly encode
      unicode thereby causing another error during error handling. See
      https://github.com/Pylons/waitress/pull/378
    
    • Header length checking had a calculation that was done incorrectly when the data was received across multple socket reads. This calculation has been corrected, and no longer will Waitress send back a 413 Request Entity Too Large. See Pylons/waitress#376

    Security Bugfix

    • in 2.1.0 a new feature was introduced that allowed the WSGI thread to start sending data to the socket. However this introduced a race condition whereby a socket may be closed in the sending thread while the main thread is about to call select() therey causing the entire application to be taken down. Waitress will no longer close the socket in the WSGI thread, instead waking up the main thread to cleanup. See Pylons/waitress#377
    Commits
    • 0aa4879 Remove change of default for clear_untrusted_proxy_headers
    • 2784628 Revert "Merge pull request #370 from Yourun-proger/del_warnings"
    • 479df63 Prep 2.1.2
    • 4f6789b Merge pull request #377 from Pylons/bugfix/select-closed-socket-race
    • 1952050 Merge pull request #379 from Pylons/enhancement/pyupgrade-3.7
    • 8f5b473 pyupgrade 3.7
    • c7a3d7e Only close socket in the main thread
    • 7c3739b Merge pull request #376 from Pylons/bugfix/header-calculation
    • 3066fdd Merge pull request #378 from Pylons/bugfix/expose_tracebacks-encode-error
    • 4467d76 Fix tests to assume body is bytes
    • Additional commits viewable in compare view

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    dependencies 
    opened by dependabot[bot] 1
  • Improve application startup time...

    Improve application startup time...

    With this change startup time for 100k molecules is down abount one min. Time to process 1K molecule from 43 sec to 8 sec.

    Other changes are mostly formatting and comments cleanup.

    opened by rilango 1
  • Bump waitress from 1.4.3 to 2.1.1 in /cuchem

    Bump waitress from 1.4.3 to 2.1.1 in /cuchem

    Bumps waitress from 1.4.3 to 2.1.1.

    Changelog

    Sourced from waitress's changelog.

    2.1.1

    Security Bugfix

    
    - Waitress now validates that chunked encoding extensions are valid, and don't
      contain invalid characters that are not allowed. They are still skipped/not
      processed, but if they contain invalid data we no longer continue in and
      return a 400 Bad Request. This stops potential HTTP desync/HTTP request
      smuggling. Thanks to Zhang Zeyu for reporting this issue. See
      https://github.com/Pylons/waitress/security/advisories/GHSA-4f7p-27jc-3c36
    
    • Waitress now validates that the chunk length is only valid hex digits when parsing chunked encoding, and values such as 0x01 and +01 are no longer supported. This stops potential HTTP desync/HTTP request smuggling. Thanks to Zhang Zeyu for reporting this issue. See https://github.com/Pylons/waitress/security/advisories/GHSA-4f7p-27jc-3c36

    • Waitress now validates that the Content-Length sent by a remote contains only digits in accordance with RFC7230 and will return a 400 Bad Request when the Content-Length header contains invalid data, such as +10 which would previously get parsed as 10 and accepted. This stops potential HTTP desync/HTTP request smuggling Thanks to Zhang Zeyu for reporting this issue. See https://github.com/Pylons/waitress/security/advisories/GHSA-4f7p-27jc-3c36

    2.1.0

    Python Version Support

    • Python 3.6 is no longer supported by Waitress

    • Python 3.10 is fully supported by Waitress

    Bugfix

    
    - ``wsgi.file_wrapper`` now sets the ``seekable``, ``seek``, and ``tell``
      attributes from the underlying file if the underlying file is seekable. This
      allows WSGI middleware to implement things like range requests for example
    

    See Pylons/waitress#359 and Pylons/waitress#363

    • In Python 3 OSError is no longer subscriptable, this caused failures on Windows attempting to loop to find an socket that would work for use in the trigger.

    </tr></table>

    ... (truncated)

    Commits
    • 9e0b8c8 Merge pull request from GHSA-4f7p-27jc-3c36
    • b28c9e8 Prep for 2.1.1
    • bd22869 Remove extraneous calls to .strip() in Chunked Encoding
    • d9bdfa0 Validate chunk size in Chunked Encoding are HEXDIG
    • d032a66 Error when receiving back Chunk Extension
    • 884bed1 Update tests to remove invalid chunked encoding chunk-size
    • 1f6059f Be more strict in parsing Content-Length
    • e75b0d9 Add new regular expressions for Chunked Encoding
    • 22c0394 Merge pull request #367 from Pylons/fixup/collect-wasyncore-tests
    • dc15d9f Make sure to collect all wasyncore tests
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    dependencies 
    opened by dependabot[bot] 1
  • Bump tensorflow-gpu from 1.15.5 to 2.9.3 in /cuchem

    Bump tensorflow-gpu from 1.15.5 to 2.9.3 in /cuchem

    Bumps tensorflow-gpu from 1.15.5 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
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    dependencies 
    opened by dependabot[bot] 1
  • Bump protobuf from 3.15.0 to 3.18.3 in /cuchem

    Bump protobuf from 3.15.0 to 3.18.3 in /cuchem

    Bumps protobuf from 3.15.0 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)

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    dependencies 
    opened by dependabot[bot] 1
  • Fixed bugs in memcache.py and embedding.py, updated readme

    Fixed bugs in memcache.py and embedding.py, updated readme

    Updated readme to reflect current workflow

    Changed how dictionary is paged in memcache.py to remove ambiguity when the item stored is a NumPy/CuPy array

    Fixed imports

    Lowered default batch_size

    opened by gagank1 0
  • Stale GPG Key in CUCHEM base docker file

    Stale GPG Key in CUCHEM base docker file

    Fixes issue https://github.com/NVIDIA/cheminformatics/issues/163.

    When attempting to build the containers you get this issue building cuchem

    W: GPG error: https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64  InRelease: The following signatures couldn't be verified because the public key is not available: NO_PUBKEY A4B469963BF863CC
    E: The repository 'https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64  InRelease' is not signed.
    

    It seems related to this issue, about NVIDIA rotating their gpg keys. One can either remove the sources.list or possibly upgrade the base container.

    opened by lilleswing 1
  • GPG Key Rotation Breaking First Build

    GPG Key Rotation Breaking First Build

    When attempting to build the containers you get this issue building cuchem

    W: GPG error: https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64  InRelease: The following signatures couldn't be verified because the public key is not available: NO_PUBKEY A4B469963BF863CC
    E: The repository 'https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64  InRelease' is not signed.
    

    It seems related to this issue, about NVIDIA rotating their gpg keys. One can either remove the sources.list or possibly upgrade the base container.

    opened by lilleswing 0
Releases(0.1.2)
  • 0.1.2(Sep 17, 2021)

    • Upgrade to RAPIDS 21.08
    • Bug Fix
    • Hightlight Molecule of interest when the input size is one
    • Fix docker image version to ensure latest image is downloaded
    Source code(tar.gz)
    Source code(zip)
  • 0.1.1(Aug 20, 2021)

  • 0.1(Jul 27, 2021)

    New features in this release include:

    • The initial release of MegaMolBART, a transformer seq2seq model based on the BART architecture and co-developed with AstraZeneca
    • A new gRPC web-service to perform inference using MegaMolBART for de novo similarity sampling
    • Addition of docker-compose to allow orchestration of multiple containers in the application
    • Upgrade to latest version of RDKit
    Source code(tar.gz)
    Source code(zip)
  • 0.0.1(Apr 28, 2021)

    New features in this release include:

    • In-the-loop deep generative model enabling real-time interactive molecular generation
    • Interpolation molecular generation pipeline enabling de novo transformation between two user-selected molecules
    • Neighborhood molecular generation pipeline enabling de novo similarity sampling for one user-selected molecule
    • New hybrid clustering workflow that uses best of Single and Multi-GPU behavior
    • Ability to color the clustered molecules based on molecular properties
    • Designate and track molecules of interest during the analysis
    • Export generated molecules in SDF format

    Software Upgrade:

    • RAPIDS 0.17
    Source code(tar.gz)
    Source code(zip)
  • 0.0.1-rc1(Mar 30, 2021)

    Features includes:

    • Cluster molecules loaded from ChEMBL database using Morgan Fingerprints generated from SMILES
    • Dimensionality reduction is done using PCA and UMAP and Clustering is done using K-Means
    • A UI tool for selection of molecules or clusters for re-clustering
    • Table visualization of selected molecules

    Software:

    • Rapids 0.15
    • Dash
    • Plotly
    Source code(tar.gz)
    Source code(zip)
Owner
NVIDIA Corporation
NVIDIA Corporation
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