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-------------------------------------------------------------------
Tue Sep 20 00:13:13 UTC 2022 - Ben Greiner <code@bnavigator.de>

- Update to 2.10.0
  * boo#1203507 (CVE-2022-35934)
- Breaking Changes
  * Causal attention in keras.layers.Attention and
    keras.layers.AdditiveAttention is now specified in the call()
    method via the use_causal_mask argument (rather than in the
    constructor), for consistency with other layers.
  * Some files in tensorflow/python/training have been moved to
    tensorflow/python/tracking and tensorflow/python/checkpoint.
    Please update your imports accordingly, the old files will be
    removed in Release 2.11.
  * tf.keras.optimizers.experimental.Optimizer will graduate in
    Release 2.11, which means tf.keras.optimizers.Optimizer will
    be an alias of tf.keras.optimizers.experimental.Optimizer. The
    current tf.keras.optimizers.Optimizer will continue to be
    supported as tf.keras.optimizers.legacy.Optimizer,
    e.g.,tf.keras.optimizers.legacy.Adam. Most users won't be
    affected by this change, but please check the API doc if any
    API used in your workflow is changed or deprecated, and make
    adaptions. If you decide to keep using the old optimizer,
    please explicitly change your optimizer to
    tf.keras.optimizers.legacy.Optimizer.
  * RNG behavior change for tf.keras.initializers. Keras
    initializers will now use stateless random ops to generate
    random numbers.
    - Both seeded and unseeded initializers will always generate
      the same values every time they are called (for a given
      variable shape). For unseeded initializers (seed=None), a
      random seed will be created and assigned at initializer
      creation (different initializer instances get different
      seeds).
    - An unseeded initializer will raise a warning if it is reused
      (called) multiple times. This is because it would produce
      the same values each time, which may not be intended.
- Deprecations
  * The C++ tensorflow::Code and tensorflow::Status will become
    aliases of respectively absl::StatusCode and absl::Status in
    some future release.
    - Use tensorflow::OkStatus() instead of
      tensorflow::Status::OK().
    - Stop constructing Status objects from
      tensorflow::error::Code.
    - One MUST NOT access tensorflow::errors::Code fields.
      Accessing tensorflow::error::Code fields is fine.
      + Use the constructors such as
        tensorflow::errors:InvalidArgument to create status using
        an error code without accessing it.
      + Use the free functions such as
        tensorflow::errors::IsInvalidArgument if needed.
      + In the last resort, use
        e.g.static_cast<tensorflow::errors::Code>(error::Code::INVALID_ARGUMENT)
        or static_cast<int>(code) for comparisons.
  * tensorflow::StatusOr will also become in the future alias to
    absl::StatusOr, so use StatusOr::value instead of
    StatusOr::ConsumeValueOrDie.
- Major Features and Improvements
  * tf.lite:
    - New operations supported:
      + tflite SelectV2 now supports 5D.
      + tf.einsum is supported with multiple unknown shapes.
      + tf.unsortedsegmentprod op is supported.
      + tf.unsortedsegmentmax op is supported.
      + tf.unsortedsegmentsum op is supported.
    - Updates to existing operations:
      + tfl.scatter_nd now supports I1 for update arg.
    - Upgrade Flatbuffers v2.0.5 from v1.12.0
  * tf.keras:
    - EinsumDense layer is moved from experimental to core. Its
      import path is moved from
      tf.keras.layers.experimental.EinsumDense to
      tf.keras.layers.EinsumDense.
    - Added tf.keras.utils.audio_dataset_from_directory utility to
      easily generate audio classification datasets from
      directories of .wav files.
    - Added subset="both" support in
      tf.keras.utils.image_dataset_from_directory,tf.keras.utils.text_dataset_from_directory,
      and audio_dataset_from_directory, to be used with the
      validation_split argument, for returning both dataset splits
      at once, as a tuple.
    - Added tf.keras.utils.split_dataset utility to split a
      Dataset object or a list/tuple of arrays into two Dataset
      objects (e.g. train/test).
    - Added step granularity to BackupAndRestore callback for
      handling distributed training failures & restarts. The
      training state can now be restored at the exact epoch and
      step at which it was previously saved before failing.
    - Added tf.keras.dtensor.experimental.optimizers.AdamW. This
      optimizer is similar as the existing
      keras.optimizers.experimental.AdamW, and works in the
      DTensor training use case.
    - Improved masking support for
      tf.keras.layers.MultiHeadAttention.
      + Implicit masks for query, key and value inputs will
        automatically be used to compute a correct attention mask
        for the layer. These padding masks will be combined with
        any attention_mask passed in directly when calling the
        layer. This can be used with tf.keras.layers.Embedding
        with mask_zero=True to automatically infer a correct
        padding mask.
      + Added a use_causal_mask call time arugment to the layer.
        Passing use_causal_mask=True will compute a causal
        attention mask, and optionally combine it with any
        attention_mask passed in directly when calling the layer.
    - Added ignore_class argument in the loss
      SparseCategoricalCrossentropy and metrics IoU and MeanIoU,
      to specify a class index to be ignored during loss/metric
      computation (e.g. a background/void class).
    - Added
      tf.keras.models.experimental.SharpnessAwareMinimization.
      This class implements the sharpness-aware minimization
      technique, which boosts model performance on various tasks,
      e.g., ResNet on image classification.
  * tf.data:
    - Added support for cross-trainer data caching in tf.data
      service. This saves computation resources when concurrent
      training jobs train from the same dataset. See
      (https://www.tensorflow.org/api_docs/python/tf/data/experimental/service#sharing_tfdata_service_with_concurrent_trainers)
      for more details.
    - Added dataset_id to
      tf.data.experimental.service.register_dataset. If provided,
      tf.data service will use the provided ID for the dataset. If
      the dataset ID already exists, no new dataset will be
      registered. This is useful if multiple training jobs need to
      use the same dataset for training. In this case, users
      should call register_dataset with the same dataset_id.
    - Added a new field, inject_prefetch, to
      tf.data.experimental.OptimizationOptions. If it is set to
      True,tf.data will now automatically add a prefetch
      transformation to datasets that end in synchronous
      transformations. This enables data generation to be
      overlapped with data consumption. This may cause a small
      increase in memory usage due to buffering. To enable this
      behavior, set inject_prefetch=True in
      tf.data.experimental.OptimizationOptions.
    - Added a new value to
      tf.data.Options.autotune.autotune_algorithm: STAGE_BASED. If
      the autotune algorithm is set to STAGE_BASED, then it runs a
      new algorithm that can get the same performance with lower
      CPU/memory usage.
    - Added tf.data.experimental.from_list, a new API for creating
      Datasets from lists of elements.
  * tf.distribute:
    - Added tf.distribute.experimental.PreemptionCheckpointHandler
      to handle worker preemption/maintenance and cluster-wise
      consistent error reporting for
      tf.distribute.MultiWorkerMirroredStrategy. Specifically, for
      the type of interruption with advance notice, it
      automatically saves a checkpoint, exits the program without
      raising an unrecoverable error, and restores the progress
      when training restarts.
  * tf.math:
    - Added tf.math.approx_max_k and tf.math.approx_min_k which
      are the optimized alternatives to tf.math.top_k on TPU. The
      performance difference range from 8 to 100 times depending
      on the size of k. When running on CPU and GPU, a
      non-optimized XLA kernel is used.
  * tf.train:
    - Added tf.train.TrackableView which allows users to inspect
      the TensorFlow Trackable object (e.g. tf.Module, Keras
      Layers and models).
  * tf.vectorized_map:
    - Added an optional parameter: warn. This parameter controls
      whether or not warnings will be printed when operations in
      the provided fn fall back to a while loop.
  * XLA:
    - MWMS is now compilable with XLA.
    - Compute Library for the Arm® Architecture (ACL) is supported
      for aarch64 CPU XLA runtime
  * CPU performance optimizations:
    - x86 CPUs: oneDNN bfloat16 auto-mixed precision grappler
      graph optimization pass has been renamed from
      auto_mixed_precision_mkl to
      auto_mixed_precision_onednn_bfloat16. See example usage
      here.
    - aarch64 CPUs: Experimental performance optimizations from
      Compute Library for the Arm® Architecture (ACL) are
      available through oneDNN in the default Linux aarch64
      package (pip install tensorflow).
      + The optimizations are disabled by default.
      + Set the environment variable TF_ENABLE_ONEDNN_OPTS=1 to
        enable the optimizations. Setting the variable to 0 or
        unsetting it will disable the optimizations.
      + These optimizations can yield slightly different numerical
        results from when they are off due to floating-point
        round-off errors from different computation approaches and
        orders.
      + To verify that the optimizations are on, look for a
        message with "oneDNN custom operations are on" in the log.
        If the exact phrase is not there, it means they are off.
- Bug Fixes and Other Changes
  * New argument experimental_device_ordinal in
    LogicalDeviceConfiguration to control the order of logical
    devices. (GPU only)
  * tf.keras:
    - Changed the TensorBoard tag names produced by the
      tf.keras.callbacks.TensorBoard callback, so that summaries
      logged automatically for model weights now include either a
      /histogram or /image suffix in their tag names, in order to
      prevent tag name collisions across summary type
  * When running on GPU (with cuDNN version 7.6.3 or
    later),tf.nn.depthwise_conv2d backprop to filter (and
    therefore also tf.keras.layers.DepthwiseConv2D) now operate
    deterministically (and tf.errors.UnimplementedError is no
    longer thrown) when op-determinism has been enabled via
    tf.config.experimental.enable_op_determinism. This closes
    issue 47174.
  * tf.random
    - Added tf.random.experimental.stateless_shuffle, a stateless
      version of tf.random.shuffle.
- Security
  * Fixes a CHECK failure in tf.reshape caused by overflows
    (CVE-2022-35934)
  * Fixes a CHECK failure in SobolSample caused by missing
    validation (CVE-2022-35935)
  * Fixes an OOB read in Gather_nd op in TF Lite (CVE-2022-35937)
  * Fixes a CHECK failure in TensorListReserve caused by missing
    validation (CVE-2022-35960)
  * Fixes an OOB write in Scatter_nd op in TF Lite
    (CVE-2022-35939)
  * Fixes an integer overflow in RaggedRangeOp (CVE-2022-35940)
  * Fixes a CHECK failure in AvgPoolOp (CVE-2022-35941)
  * Fixes a CHECK failures in UnbatchGradOp (CVE-2022-35952)
  * Fixes a segfault TFLite converter on per-channel quantized
    transposed convolutions (CVE-2022-36027)
  * Fixes a CHECK failures in AvgPool3DGrad (CVE-2022-35959)
  * Fixes a CHECK failures in FractionalAvgPoolGrad
    (CVE-2022-35963)
  * Fixes a segfault in BlockLSTMGradV2 (CVE-2022-35964)
  * Fixes a segfault in LowerBound and UpperBound (CVE-2022-35965)
  * Fixes a segfault in QuantizedAvgPool (CVE-2022-35966)
  * Fixes a segfault in QuantizedAdd (CVE-2022-35967)
  * Fixes a CHECK fail in AvgPoolGrad (CVE-2022-35968)
  * Fixes a CHECK fail in Conv2DBackpropInput (CVE-2022-35969)
  * Fixes a segfault in QuantizedInstanceNorm (CVE-2022-35970)
  * Fixes a CHECK fail in FakeQuantWithMinMaxVars (CVE-2022-35971)
  * Fixes a segfault in Requantize (CVE-2022-36017)
  * Fixes a segfault in QuantizedBiasAdd (CVE-2022-35972)
  * Fixes a CHECK fail in FakeQuantWithMinMaxVarsPerChannel
    (CVE-2022-36019)
  * Fixes a segfault in QuantizedMatMul (CVE-2022-35973)
  * Fixes a segfault in QuantizeDownAndShrinkRange
    (CVE-2022-35974)
  * Fixes segfaults in QuantizedRelu and QuantizedRelu6
    (CVE-2022-35979)
  * Fixes a CHECK fail in FractionalMaxPoolGrad (CVE-2022-35981)
  * Fixes a CHECK fail in RaggedTensorToVariant (CVE-2022-36018)
  * Fixes a CHECK fail in QuantizeAndDequantizeV3 (CVE-2022-36026)
  * Fixes a segfault in SparseBincount (CVE-2022-35982)
  * Fixes a CHECK fail in Save and SaveSlices (CVE-2022-35983)
  * Fixes a CHECK fail in ParameterizedTruncatedNormal
    (CVE-2022-35984)
  * Fixes a CHECK fail in LRNGrad (CVE-2022-35985)
  * Fixes a segfault in RaggedBincount (CVE-2022-35986)
  * Fixes a CHECK fail in DenseBincount (CVE-2022-35987)
  * Fixes a CHECK fail in tf.linalg.matrix_rank (CVE-2022-35988)
  * Fixes a CHECK fail in MaxPool (CVE-2022-35989)
  * Fixes a CHECK fail in Conv2DBackpropInput (CVE-2022-35999)
  * Fixes a CHECK fail in EmptyTensorList (CVE-2022-35998)
  * Fixes a CHECK fail in tf.sparse.cross (CVE-2022-35997)
  * Fixes a floating point exception in Conv2D (CVE-2022-35996)
  * Fixes a CHECK fail in AudioSummaryV2 (CVE-2022-35995)
  * Fixes a CHECK fail in CollectiveGather (CVE-2022-35994)
  * Fixes a CHECK fail in SetSize (CVE-2022-35993)
  * Fixes a CHECK fail in TensorListFromTensor (CVE-2022-35992)
  * Fixes a CHECK fail in TensorListScatter and
    TensorListScatterV2 (CVE-2022-35991)
  * Fixes a CHECK fail in
    FakeQuantWithMinMaxVarsPerChannelGradient (CVE-2022-35990)
  * Fixes a CHECK fail in FakeQuantWithMinMaxVarsGradient
    (CVE-2022-36005)
  * Fixes a CHECK fail in tf.random.gamma (CVE-2022-36004)
  * Fixes a CHECK fail in RandomPoissonV2 (CVE-2022-36003)
  * Fixes a CHECK fail in Unbatch (CVE-2022-36002)
  * Fixes a CHECK fail in DrawBoundingBoxes (CVE-2022-36001)
  * Fixes a CHECK fail in Eig (CVE-2022-36000)
  * Fixes a null dereference on MLIR on empty function attributes
    (CVE-2022-36011)
  * Fixes an assertion failure on MLIR empty edge names
    (CVE-2022-36012)
  * Fixes a null-dereference in
    mlir::tfg::GraphDefImporter::ConvertNodeDef (CVE-2022-36013)
  * Fixes a null-dereference in mlir::tfg::TFOp::nameAttr
    (CVE-2022-36014)
  * Fixes an integer overflow in math ops (CVE-2022-36015)
  * Fixes a CHECK-fail in
    tensorflow::full_type::SubstituteFromAttrs (CVE-2022-36016)
  * Fixes an OOB read in Gather_nd op in TF Lite Micro
    (CVE-2022-35938)

-------------------------------------------------------------------
Fri May 27 23:01:40 UTC 2022 - Ben Greiner <code@bnavigator.de>

- tensorflow2 has been removed from Tumbleweed. Provide a separate
  Tensorflow Lite package in version 2.9.1
- Now includes the tflite_runtime python3 package
- Add tensorflow-lite-cmake-find-python.patch

-------------------------------------------------------------------
Fri Feb  4 21:37:07 UTC 2022 - Ben Greiner <code@bnavigator.de>

- restore larger memory per job constraint

-------------------------------------------------------------------
Fri Feb  4 16:28:12 UTC 2022 - Ben Greiner <code@bnavigator.de>

- Update to 2.7.1 -- boo#1195545 security update
  * 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 a null-dereference when specializing tensor type
    (CVE-2022-23570)
  * Fixes a crash when type cannot be specialized (CVE-2022-23572)
  * Fixes a heap OOB read/write in SpecializeType (CVE-2022-23574)
  * 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)
  * Fixes a use after free in DecodePng kernel (CVE-2022-23584)
  * Fixes a memory leak in decoding PNG images (CVE-2022-23585)
  * Fixes multiple CHECK-fails in function.cc (CVE-2022-23586)
  * Fixes multiple CHECK-fails due to attempting to build a
    reference tensor (CVE-2022-23588)
  * Fixes an integer overflow in Grappler cost estimation of crop
    and resize operation (CVE-2022-23587)
  * Fixes a null pointer dereference in Grappler's IsConstant
    (CVE-2022-23589)
  * Fixes a CHECK failure in constant folding (CVE-2021-41197)
  * Fixes a stack overflow due to self-recursive function in
    GraphDef (CVE-2022-23591)
  * Fixes a crash due to erroneous StatusOr (CVE-2022-23590)
  * Fixes multiple crashes and heap OOB accesses in TFG dialect
    (MLIR) (CVE-2022-23594)
  * Fixes a null pointer dereference in BuildXlaCompilationCache
    (XLA) (CVE-2022-23595)
  * Updates icu to 69.1 to handle CVE-2020-10531

-------------------------------------------------------------------
Tue Feb  1 17:44:12 UTC 2022 - Ben Greiner <code@bnavigator.de>

- Remove URLs from github zip archives for xnnpack transitive
  dependencies: The GitHub archiver produces unreliable files

-------------------------------------------------------------------
Sat Jan 22 20:52:02 UTC 2022 - Ben Greiner <code@bnavigator.de>

- Update to 2.7.0
  * Big changelog: at
    https://github.com/tensorflow/tensorflow/releases/tag/v2.7.0
- Security references:
  * Fixes a code injection issue in saved_model_cli
    (CVE-2021-41228)
  * Fixes a vulnerability due to use of uninitialized value in
    Tensorflow (CVE-2021-41225)
  * Fixes a heap OOB in FusedBatchNorm kernels (CVE-2021-41223)
  * Fixes an arbitrary memory read in ImmutableConst
    (CVE-2021-41227)
  * Fixes a heap OOB in SparseBinCount (CVE-2021-41226)
  * Fixes a heap OOB in SparseFillEmptyRows (CVE-2021-41224)
  * Fixes a segfault due to negative splits in SplitV
    (CVE-2021-41222)
  * Fixes segfaults and vulnerabilities caused by accesses to
    invalid memory during shape inference in Cudnn* ops
    (CVE-2021-41221)
  * Fixes a null pointer exception when Exit node is not preceded
    by Enter op (CVE-2021-41217)
  * Fixes an integer division by 0 in tf.raw_ops.AllToAll
    (CVE-2021-41218)
  * Fixes a use after free and a memory leak in CollectiveReduceV2
    (CVE-2021-41220)
  * Fixes an undefined behavior via nullptr reference binding in
    sparse matrix multiplication (CVE-2021-41219)
  * Fixes a heap buffer overflow in Transpose (CVE-2021-41216)
  * Prevents deadlocks arising from mutually recursive tf.function
    objects (CVE-2021-41213)
  * Fixes a null pointer exception in DeserializeSparse
    (CVE-2021-41215)
  * Fixes an undefined behavior arising from reference binding to
    nullptr in tf.ragged.cross (CVE-2021-41214)
  * Fixes a heap OOB read in tf.ragged.cross (CVE-2021-41212)
  * Fixes a heap OOB in shape inference for QuantizeV2
    (CVE-2021-41211)
  * Fixes a heap OOB read in all tf.raw_ops.QuantizeAndDequantizeV*
    ops (CVE-2021-41205)
  * Fixes an FPE in ParallelConcat (CVE-2021-41207)
  * Fixes FPE issues in convolutions with zero size filters
    (CVE-2021-41209)
  * Fixes a heap OOB read in tf.raw_ops.SparseCountSparseOutput
    (CVE-2021-41210)
  * Fixes vulnerabilities caused by incomplete validation in
    boosted trees code (CVE-2021-41208)
  * Fixes vulnerabilities caused by incomplete validation of shapes
    in multiple TF ops (CVE-2021-41206)
  * Fixes a segfault produced while copying constant resource
    tensor (CVE-2021-41204)
  * Fixes a vulnerability caused by unitialized access in
    EinsumHelper::ParseEquation (CVE-2021-41201)
  * Fixes several vulnerabilities and segfaults caused by missing
    validation during checkpoint loading (CVE-2021-41203)
  * Fixes an overflow producing a crash in tf.range
    (CVE-2021-41202)
  * Fixes an overflow producing a crash in tf.image.resize when
    size is large (CVE-2021-41199)
  * Fixes an overflow producing a crash in tf.tile when tiling
    tensor is large (CVE-2021-41198)
  * Fixes a vulnerability produced due to incomplete validation in
    tf.summary.create_file_writer (CVE-2021-41200)
  * Fixes multiple crashes due to overflow and CHECK-fail in ops
    with large tensor shapes (CVE-2021-41197)
  * Fixes a crash in max_pool3d when size argument is 0 or negative
    (CVE-2021-41196)
  * Fixes a crash in tf.math.segment_* operations (CVE-2021-41195)
  * Updates curl to 7.78.0 to handle CVE-2021-22922,
    CVE-2021-22923, CVE-2021-22924, CVE-2021-22925, and
    CVE-2021-22926.
- This drops support for Python 3.6 and thus for SLE/Leap 15
  See also https://code.opensuse.org/leap/features/issue/35
- Closes boo#1195295
  * Note that tensorflow2 (non-lite) will be removed from
    Tumbleweed soon if there are no volunteers, see leap feature
    issue above.
- Have to migrate tensorflow-lite build to CMake as old Makefile
  was dropped
- Drop patches no longer necessary or applicable
  * tensorflow-2.6.0-remove-weakref.patch
  * tensorflow-2.6.0-fix-lite.patch
  * tensorflow-2.6.0-tf-keras-hdf5-3.patch
  * tensorflow-2.6.0-removed-clog-build-as-included-in-cpuinfo.patch
  * tensorflow-2.6.0-numpy-tensor-small.patch
- fix double nested unpacking and refresh patches, migrate to -p1
  * tensorflow-2.6.0-removed-external-toolchains.patch
  * tensorflow-2.6.0-compile-with-protobuf-3.16.patch
- Add #tensorflow-2.7.0-fix-lite.patch
  * https://github.com/tensorflow/tensorflow/commit/fb1dcbd9
  * gh#tensorflow/tensorflow#54216
- Have to use grpc and upb from bazelcache, pulls in go
  * Add tensorflow-2.7.0-go_host_sdk.patch -- use system SDK
    instead of downloading a binary blob

-------------------------------------------------------------------
Tue Jan 11 09:41:07 UTC 2022 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Remove more python dependencies for tensorflow2-lite

-------------------------------------------------------------------
Mon Jan 10 14:03:05 UTC 2022 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- tensorflow2-lite version does not need all the python dependencies
  listed for tensorflow2

-------------------------------------------------------------------
Fri Jan  7 10:15:53 UTC 2022 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Leap 15.x / Backports: Do not build non-Lite versions since python3-numpy
  and python3-scipy are too old for Keras/TF2

-------------------------------------------------------------------
Tue Nov  9 13:26:21 UTC 2021 - Christian Goll <cgoll@suse.com>

- updated to 2.6.2 which is bug fix release which just fixes an issue where
  keras, tensorflow_estimator and tensorboard were missing proper upper bounds
  and resulted in broken installs after Keras 2.7 release for all packages in
  TensorFlow ecosystem
- Fixes from 2.6.1 (boo#1192447):
  * Fixes a code injection issue in saved_model_cli (CVE-2021-41228)
  * Fixes a vulnerability due to use of uninitialized value in Tensorflow (CVE-2021-41225)
  * Fixes a heap OOB in FusedBatchNorm kernels (CVE-2021-41223)
  * Fixes an arbitrary memory read in ImmutableConst (CVE-2021-41227)
  * Fixes a heap OOB in SparseBinCount (CVE-2021-41226)
  * Fixes a heap OOB in SparseFillEmptyRows (CVE-2021-41224)
  * Fixes a segfault due to negative splits in SplitV (CVE-2021-41222)
  * Fixes segfaults and vulnerabilities caused by accesses to invalid memory
    during shape inference in Cudnn* ops (CVE-2021-41221)
  * Fixes a null pointer exception when Exit node is not preceded by Enter op (CVE-2021-41217)
  * Fixes an integer division by 0 in tf.raw_ops.AllToAll (CVE-2021-41218)
  * Fixes a use after free and a memory leak in CollectiveReduceV2 (CVE-2021-41220)
  * Fixes an undefined behavior via nullptr reference binding in sparse matrix
    multiplication (CVE-2021-41219)
  * Fixes a heap buffer overflow in Transpose (CVE-2021-41216)
  * Prevents deadlocks arising from mutually recursive tf.function objects (CVE-2021-41213)
  * Fixes a null pointer exception in DeserializeSparse (CVE-2021-41215)
  * Fixes an undefined behavior arising from reference binding to nullptr in
    tf.ragged.cross (CVE-2021-41214)
  * Fixes a heap OOB read in tf.ragged.cross (CVE-2021-41212)
  * Fixes a heap OOB in shape inference for QuantizeV2 (CVE-2021-41211)
  * Fixes a heap OOB read in all tf.raw_ops.QuantizeAndDequantizeV* ops (CVE-2021-41205)
  * Fixes an FPE in ParallelConcat (CVE-2021-41207)
  * Fixes FPE issues in convolutions with zero size filters (CVE-2021-41209)
  * Fixes a heap OOB read in tf.raw_ops.SparseCountSparseOutput (CVE-2021-41210)
  * Fixes vulnerabilities caused by incomplete validation in boosted trees code (CVE-2021-41208)
  * Fixes vulnerabilities caused by incomplete validation of shapes in multiple TF ops (CVE-2021-41206)
  * Fixes a segfault produced while copying constant resource tensor (CVE-2021-41204)
  * Fixes a vulnerability caused by unitialized access in EinsumHelper::ParseEquation (CVE-2021-41201)
  * Fixes several vulnerabilities and segfaults caused by missing validation
    during checkpoint loading (CVE-2021-41203)
  * Fixes an overflow producing a crash in tf.range (CVE-2021-41202)
  * Fixes an overflow producing a crash in tf.image.resize when size is large (CVE-2021-41199)
  * Fixes an overflow producing a crash in tf.tile when tiling tensor is large (CVE-2021-41198)
  * Fixes a vulnerability produced due to incomplete validation in
    tf.summary.create_file_writer (CVE-2021-41200)
  * Fixes multiple crashes due to overflow and CHECK-fail in ops with large
    tensor shapes (CVE-2021-41197)
  * Fixes a crash in max_pool3d when size argument is 0 or negative (CVE-2021-41196)
  * Fixes a crash in tf.math.segment_* operations (CVE-2021-41195)

-------------------------------------------------------------------
Sat Oct 23 09:56:33 UTC 2021 - Egbert Eich <eich@suse.com>

- Make sure tensorflow/core/public/version.h is installed in the
  'lite' version (bsc#1191805).

-------------------------------------------------------------------
Fri Sep 24 15:57:58 UTC 2021 - Ben Greiner <code@bnavigator.de>

- Add missing python requirements -- boo#1190856

-------------------------------------------------------------------
Wed Sep  1 10:30:38 UTC 2021 - Egbert Eich <eich@suse.com>

- Limit BuildRequires for bazel-skylib-source to versions >= 1.0.3.

-------------------------------------------------------------------
Thu Aug 19 03:51:15 UTC 2021 - Fusion Future <qydwhotmail@gmail.com>

- Update to 2.6.0
  Major changes are:
  * Keras been split into a separate PIP package (keras), and its
    code has been moved to the GitHub repositorykeras-team/keras.
    The API endpoints for tf.keras stay unchanged, but are now
    backed by the keras PIP package. The existing code in
    tensorflow/python/keras is a staled copy and will be removed in
    future release (2.7). Please remove any imports to
    tensorflow.python.keras and replace them with public tf.keras
    API instead.
  * tf.train.experimental.enable_mixed_precision_graph_rewrite is
    removed, as the API only works in graph mode and is not
    customizable. The function is still accessible under
    tf.compat.v1.mixed_precision.enable_mixed_precision_graph_rewrite,
    but it is recommended to use the Keras mixed precision API
    instead.
  * tf.lite: Remove experimental.nn.dynamic_rnn,
    experimental.nn.TfLiteRNNCell and
    experimental.nn.TfLiteLSTMCell since they're no
    longer supported. It's recommended to just use keras lstm
    instead.
  * tf.keras: The methods Model.to_yaml() and
    keras.models.model_from_yaml have been replaced to raise a
    RuntimeError as they can be abused to cause arbitrary code
    execution. It is recommended to use JSON serialization instead
    of YAML, or, a better alternative, serialize to H5.
- Major changes from 2.5.x:
  * Support for Python3.9 has been added.
  * The TF_CPP_MIN_VLOG_LEVEL environment variable has been renamed
    to to TF_CPP_MAX_VLOG_LEVEL which correctly describes its
    effect.
- Fixed multiple CVEs (boo#1189423):
  * CVE-2021-37635
  * CVE-2021-37636
  * CVE-2021-37637
  * CVE-2021-37638
  * CVE-2021-37639
  * CVE-2021-37640
  * CVE-2021-37642
  * CVE-2021-37641
  * CVE-2021-37644
  * CVE-2021-37643
  * CVE-2021-37645
  * CVE-2021-37646
  * CVE-2021-37647
  * CVE-2021-37648
  * CVE-2021-37649
  * CVE-2021-37650
  * CVE-2021-37651
  * CVE-2021-37652
  * CVE-2021-37653
  * CVE-2021-37654
  * CVE-2021-37655
  * CVE-2021-37656
  * CVE-2021-37657
  * CVE-2021-37658
  * CVE-2021-37659
  * CVE-2021-37660
  * CVE-2021-37661
  * CVE-2021-37662
  * CVE-2021-37664
  * CVE-2021-37663
  * CVE-2021-37665
  * CVE-2021-37666
  * CVE-2021-37667
  * CVE-2021-37668
  * CVE-2021-37669
  * CVE-2021-37670
  * CVE-2021-37671
  * CVE-2021-37672
  * CVE-2021-37673
  * CVE-2021-37674
  * CVE-2021-37676
  * CVE-2021-37675
  * CVE-2021-37677
  * CVE-2021-37678
  * CVE-2021-37679
  * CVE-2021-37680
  * CVE-2021-37681
  * CVE-2021-37682
  * CVE-2021-37683
  * CVE-2021-37684
  * CVE-2021-37686
  * CVE-2021-37685
  * CVE-2021-37687
  * CVE-2021-37688
  * CVE-2021-37689
  * CVE-2021-37691
  * CVE-2021-37692
  * CVE-2021-37690
- Updated sources:
  * abseil-cpp.tar.gz
  * cpuinfo.zip
  * dill-0.3.2.zip
  * eigen.tar.gz
  * google-cloud-cpp.tar.gz
  * libxsmm_1.14.tar.gz
  * llvm.tar.gz
  * oneDNN.tar.gz
  * rules_cc.tar.gz
  * rules_closure.tar.gz
  * rules_docker-0.18.0.tar.gz
  * ruy.zip
  * tblib-1.7.0.tar.gz
- Added sources:
  * ComputeLibrary.tar.gz
  * oneDNN-v2.3-rc2.tar.gz
  * platforms-0.0.2.tar.gz
  * rules_proto.tar.gz
  * tf_runtime.tar.gz
  * tf_toolchains.tar.gz
- Removed sources:
  * kafka-v0.11.5.tar.gz
- Add "tensorflow-2.6.0" prefix to existing patches to indicate
  that patches are likely to be only applicable to a specific
  version.
  * fix-lite.patch -> tensorflow-2.6.0-fix-lite.patch
  * numpy-tensor-small.patch -> tensorflow-2.6.0-numpy-tensor-small.patch
  * removed-clog-build-as-included-in-cpuinfo.patch -> tensorflow-2.6.0-removed-clog-build-as-included-in-cpuinfo.patch
  * removed-external-toolchains.patch -> tensorflow-2.6.0-removed-external-toolchains.patch
  * remove-weakref.patch -> tensorflow-2.6.0-remove-weakref.patch
  * tf-keras-hdf5-3.patch -> tensorflow-2.6.0-tf-keras-hdf5-3.patch
- Rebase all existing patches.
- Add tensorflow-2.6.0-compile-with-protobuf-3.16.patch to fix
  build error with protobuf >= 3.16.0. (boo#1186860)
  (https://github.com/protocolbuffers/protobuf/pull/8354)
- Update bazel version requirement to 3.7.2.
- Drop pcre-devel build requirement as it is not used anymore.
- Drop --incompatible_no_support_tools_in_action_inputs=false as it
  is removed in bazel >= 3.6.

-------------------------------------------------------------------
Wed May 19 12:02:57 UTC 2021 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Update _constraints to use host with 'asimdrdm' cpu flag to avoid
  slow CPU and be scheduled on faster systems

-------------------------------------------------------------------
Wed Apr 14 15:01:22 UTC 2021 - Ferdinand Thiessen <rpm@fthiessen.de>

- Update to version 2.4.1
  * Bugfixes
  * Drops requirement of AVX2

-------------------------------------------------------------------
Tue Apr  6 16:27:29 UTC 2021 - Ben Greiner <code@bnavigator.de>

- Don't BuildRequire keras_applications. Tensorflow provides it
  itself: https://github.com/tensorflow/tensorflow/commit/23c3bdaa
- These were discovered by Keras test suite:
  * add numpy-tensor-small.patch for Numpy >= 1.20
    gh#tensorflow/tensorflow#47691
  * add tf-keras-hdf5-3.patch for hdf5 >= 3.0
    gh#tensorflow/tensorflow#44467

-------------------------------------------------------------------
Thu Feb 18 14:26:20 UTC 2021 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Generate and install pkgconfig files for tensorflow-lite and
  tensorflow (non-hpc)

-------------------------------------------------------------------
Wed Jan 27 10:54:57 UTC 2021 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Do not install bazel tools to build Lite version. This will allow
  to build for armv7 where bazel 3.x is not available - boo#1178564

-------------------------------------------------------------------
Fri Jan 15 08:05:09 UTC 2021 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Fix packaging for libiomp5

-------------------------------------------------------------------
Mon Jan 11 01:49:52 UTC 2021 - Dirk Müller <dmueller@suse.com>

- build verbose to not fail on the obs stall detection

-------------------------------------------------------------------
Fri Jan  8 07:30:53 UTC 2021 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- libiomp5 is x86_64 only

-------------------------------------------------------------------
Wed Jan  6 13:25:31 UTC 2021 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Fix build on aarch64 and on hpc variants

-------------------------------------------------------------------
Wed Oct 21 13:48:26 UTC 2020 - Christian Goll <cgoll@suse.com>
- Updated to version 2.4.0 which fixes several bugs (bsc#1173128)
  (bsc#1173314)i, (bsc#1179455) and (bsc#1178287)
- Security fixes for CVE-2020-26266, CVE-2020-26267, CVE-2020-26268,
  CVE-2020-26270 and CVE-2020-26271
- updated sources:
  * abseil-cpp.tar.gz
  * eigen.tar.gz
  * gemmlowp.zip
  * googleapis.zip
  * llvm.tar.gz
- added sources:
  * DouraFFT.tar.gz
  * cpuinfo.zip
  * dill-0.3.1.1.tar.gz (aarch64 only)
  * dlpack.tar.gz
  * oneDNN.tar.gz
  * openmp-10.0.1.src.tar.xz
  * python-license-astunparse
  * re2.tar.gz
  * rules_android.zip
  * rules_cc.tar.gz
  * rules_docker-0.15.0.tar.gz
  * ruy.zip
  * sobol_data.tar.gz
  * tblib-1.3.2.tar.gz (aarch64 only)
  * typing_extensions-3.7.4.2.tar.gz (aarch64 only)
- removed sources:
  * boring_ssl.tar.gz
  * cub_1.8.0.zip
  * mkl-v0.21.2.tar.gz
  * pybind11-v2.3.0.tar.gz
  * right-json-location.patch
  * rules_docker.tar.gz
- removed patches:
  * Provide-overload-to-cope-with-const-ness-change-of-N.patch
  * fix-google-absl-memory.patch
  * json-feature-name.patch
  * libjpeg_turbo-name.patch
  * removed-docker-tools.patch
- added patches:
  * removed-clog-build-as-included-in-cpuinfo.patch
  * removed-external-toolchains.patch
- Major changes are:
  * tf.distribute introduces experimental support for asynchronous training of 
    models via the tf.distribute.experimental.ParameterServerStrategy API.
  * MultiWorkerMirroredStrategy is now a stable API and is no longer considered 
    experimental.
  * Introduces experimental support for a new module named tf.experimental.numpy 
    which is a NumPy-compatible API for writing TF programs.
  * A major refactoring of the internals of the Keras Functional API has been 
    completed, that should improve the reliability, stability, and performance 
    of constructing Functional models.
  * Keras mixed precision API tf.keras.mixed_precision is no longer experimental 
    and allows the use of 16-bit floating point formats during training, 
    improving performance by up to 3x on GPUs and 60% on TPUs.
  * TensorFlow Profiler now supports profiling MultiWorkerMirroredStrategy and 
    tracing multiple workers using the sampling mode API.

-------------------------------------------------------------------
Tue Oct 13 10:02:55 UTC 2020 - Christian Goll <cgoll@suse.com>

- fixed hpc flavor and Leap15.2 builds

-------------------------------------------------------------------
Mon Sep 28 13:06:00 UTC 2020 - Christian Goll <cgoll@suse.com>

- updated to 2.1.2 with following fixes (bsc#1177022):
  * Fixes an undefined behavior causing a segfault in tf.raw_ops.Switch (CVE-2020-15190)
  * Fixes three vulnerabilities in conversion to DLPack format 
    (CVE-2020-15191, CVE-2020-15192, CVE-2020-15193)
  * Fixes two vulnerabilities in SparseFillEmptyRowsGrad 
    (CVE-2020-15194, CVE-2020-15195)
  * Fixes an integer truncation vulnerability in code using the 
    work sharder API (CVE-2020-15202)
  * Fixes a format string vulnerability in tf.strings.as_string (CVE-2020-15203)
  * Fixes segfault raised by calling session-only ops in eager mode (CVE-2020-15204)
  * Fixes data leak and potential ASLR violation from tf.raw_ops.StringNGrams (CVE-2020-15205)
  * Fixes segfaults caused by incomplete SavedModel validation (CVE-2020-15206)
  * Fixes a data corruption due to a bug in negative indexing support in TFLite (CVE-2020-15207)
  * Fixes a data corruption due to dimension mismatch in TFLite (CVE-2020-15208)
  * Fixes several vulnerabilities in TFLite saved model format 
    (CVE-2020-15209, CVE-2020-15210, CVE-2020-15211)
- using fft2d.tgz instead of fft.tar.gz
- removed fft.tar.gz

-------------------------------------------------------------------
Mon Sep 14 11:53:55 UTC 2020 - Christian Goll <cgoll@suse.com>

- fixed json-feature-name.patch for leap15.2 builds

-------------------------------------------------------------------
Thu Sep 10 09:04:46 UTC 2020 - Christian Goll <cgoll@suse.com>

- updated disk constraints, as sometimes the build fails with too
  low disk space

-------------------------------------------------------------------
Wed Sep  9 13:09:19 UTC 2020 - Christian Goll <cgoll@suse.com>

- Package C-headers for standard tensorflow (boo#1175789)
- fixed build gcc10.1 errors for Tumbleweed with following 
  upstream patch:
  * added file Provide-overload-to-cope-with-const-ness-change-of-N.patch

-------------------------------------------------------------------
Tue Sep  8 14:46:31 UTC 2020 - Christian Goll <cgoll@suse.com>

- Package header files for Tensoflow2 Lite - boo#1175099

-------------------------------------------------------------------
Thu Sep  3 15:37:56 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Revert memoryperjob constraint support and use again 
  %limit_build macro to avoid OOM errors

-------------------------------------------------------------------
Thu Aug 20 15:06:34 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Lower memoryperjob to 1300 MB (as done for tensorflow)

-------------------------------------------------------------------
Thu Aug 20 09:06:46 UTC 2020 - Martin Liška <mliska@suse.cz>

- Use memoryperjob constraint instead of %limit_build macro.

-------------------------------------------------------------------
Thu Jun 25 12:00:33 UTC 2020 - Christian Goll <cgoll@suse.com>

- fixed build with json_cpp 1.9.3 (bsc#1173314)

-------------------------------------------------------------------
Fri Jun 19 11:21:59 UTC 2020 - Christian Goll <cgoll@suse.com>

- fixed local CUDA builds

-------------------------------------------------------------------
Tue Jun 16 09:27:33 UTC 2020 - Christian Goll <cgoll@suse.com>

- updated to 2.1.1 which is a bug fix release mostly for external
  sources which are not part of this package (sqlite,libjpeg-turbo,
  Apache Spark)
  * Fixes a versioning bug which causes Keras layers from TF 1.x to 
  be used instead of those from TF 2.x

-------------------------------------------------------------------
Mon May 25 15:44:40 UTC 2020 - Christian Goll <cgoll@suse.com>

- fixed broken builds which were caused due to missing dependency
  on @com_google_absl//absl/strings in various BUILD files
- added patch: fix-google-absl-memory.patch

-------------------------------------------------------------------
Tue Apr  7 09:43:28 UTC 2020 - Christian Goll <cgoll@suse.com>

- added mkl-ddn as source and do not use system mkl-dnn (bsc#1168839)
- removed patches:
  * fixed-mkl-sgemm-call.patch
  * added-mkl_dnn-as-syslib.patch
- added source:
  mkl-v0.21.2.tar.gz

-------------------------------------------------------------------
Fri Mar 27 09:44:32 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- tensorflow2-lite-devel does not requires libtensorflow*

-------------------------------------------------------------------
Thu Mar 26 08:41:54 UTC 2020 - Christian Goll <cgoll@suse.com>

- removed hpc-mvapich2 build (bsc#1167735)

-------------------------------------------------------------------
Tue Mar 24 04:16:57 UTC 2020 - Bernhard Wiedemann <bwiedemann@suse.com>

- Use pip install --no-compile (boo#1094323)

-------------------------------------------------------------------
Fri Mar 20 07:00:40 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Lite flavor should not provide python3-tensorflow nor tensorflow

-------------------------------------------------------------------
Fri Mar 13 15:25:38 UTC 2020 - Christian Goll <cgoll@suse.com>

- removed sources of bazel sources and replaced them by internal packages
 * rules-cc.zip removed
 * bazel-toolchains.tar.gz removed
 * bazel-skylib.0.8.0.tar.gz removed

-------------------------------------------------------------------
Mon Mar  9 21:22:29 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Lite flavor should not provide "tensorflow", otherwise 
  tensorlfow2-devel and tensorlfow2-lite-devel conflict and break
  armnn

-------------------------------------------------------------------
Thu Mar  5 16:49:47 UTC 2020 - Christian Goll <cgoll@suse.com>

- added Provides: tensorflow, so that Kerase works with this package
  and fixed Leap 15.2 build

-------------------------------------------------------------------
Fri Feb 28 10:55:43 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Fix name for libtensorflow* sub-packages

-------------------------------------------------------------------
Thu Feb 20 08:46:19 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- openSUSE has no CUDA package, so disable cuda build for
  openSUSE

-------------------------------------------------------------------
Fri Feb 14 15:03:03 UTC 2020 - Christian Goll <cgoll@suse.com>

- addding changes for CUDA builds

-------------------------------------------------------------------
Thu Feb 13 19:41:17 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Add 'Provides' only for hpc flavors, otherwise it matches the
  package name

-------------------------------------------------------------------
Tue Feb 11 14:41:45 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Add provides/conflicts to avoid to install tensorflow and 
  tensorflow2 as some files are provided by both packages

-------------------------------------------------------------------
Wed Feb  5 14:14:06 UTC 2020 - Christian Goll <cgoll@suse.com>

-  removed mkl-dnn as sourc and force usage of system mkl-dnn 
   for x86_64 builds
   * removed file mkl-dnn-v021.2.tar.gz
   * added patch: added-mkl_dnn-as-syslib.patch
   * added patch: fixed-mkl-sgemm-call.patch

-------------------------------------------------------------------
Sun Feb  2 19:32:32 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Add 1.25.0 as minimal version for grpc-devel

-------------------------------------------------------------------
Fri Jan 31 10:33:05 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Add 3.1.5 as a minimal version for double-conversion-devel
  (2.0.1 from SLE15SP2/Leap15.2 is too old)
- Lower required version for protobuf (3.9.1 from SLE15SP2/Leap15.2
  is fine)

-------------------------------------------------------------------
Thu Jan 30 14:27:58 UTC 2020 - Christian Goll <cgoll@suse.com>

- removed AVX2 flavor, this should be fixed via mkl-dnn

-------------------------------------------------------------------
Thu Jan 30 13:18:12 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Fix build on hpc targets

-------------------------------------------------------------------
Tue Jan 28 11:15:24 UTC 2020 - Christian Goll <cgoll@suse.com>

- added shared library packages libtensorflow2, 
  libtensorflow_cc2 and libtensorflow_framework2
- removed the AWS sdk support as this forces a SEGFAULT
  * remobed file aws-sdk-cpp-1.5.8.tar.gz
- dropped following source files as they are not needed any more
  * removed file backports.weakref-1.0rc1.tar.gz
  * removed file gettid.patch
  * removed file grpc-v1.24.2.gz
  * removed file libjpeg-turbo-2.0.0.tar.gz
  * removed file nsync_1.20.0.tar.gz

-------------------------------------------------------------------
Tue Jan 28 09:33:03 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Do not try to install *.pb.* files in Lite flavor

-------------------------------------------------------------------
Tue Jan 28 09:13:58 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Define package name at 'tensorflow2' instead of 'tensorflow'

-------------------------------------------------------------------
Fri Jan 24 16:52:52 UTC 2020 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Generate *.pb.* files and package them, to be used by ArmNN
- Do not build on %ix86
- Do not build %arm, except for Lite flavor

-------------------------------------------------------------------
Thu Jan 23 10:23:01 UTC 2020 - Christian Goll <cgoll@suse.com>
- updated to tensorflow 2.1.0 which is a stable release and has
  following breaking changes:
  * Deletes Operation.traceback_with_start_lines for which we 
    know of no usages.
  * Removed id from tf.Tensor.__repr__() as id is not useful other 
    than internal debugging.
  * Some tf.assert_* methods now raise assertions at operation 
    creation time if the input tensors' values are known at that 
    time, not during the session.run(). This only changes behavior 
    when the graph execution would have resulted in an error. When 
    this happens, a noop is returned and the input tensors are 
    marked non-feedable. In other words, if they are used as keys 
    in feed_dict argument to session.run(), an error will be raised. 
    Also, because some assert ops don't make it into the graph, the 
    graph structure changes. A different graph can result in 
    different per-op random seeds when they are not given 
    explicitly (most often).
  * The following APIs are not longer experimental: 
    tf.config.list_logical_devices, tf.config.list_physical_devices, 
    tf.config.get_visible_devices, tf.config.set_visible_devices, 
    tf.config.get_logical_device_configuration, 
    tf.config.set_logical_device_configuration.
  * tf.config.experimentalVirtualDeviceConfiguration has been 
    renamed to tf.config.LogicalDeviceConfiguration.
  * tf.config.experimental_list_devices has been removed, 
    please use tf.config.list_logical_devices.
- renamed the project to tensorflow2 so that the original tensorflow
  v1 API compatible release can stay in factory. Following
  changes were made to achive this:
  * added tensorflow-v2.1.0.tar.gz
  * added tensforflow2.spec
  * added tensforflow2.changes
  * removed tensorflow-v1.13.2.tar.gz
  * removed tensorflow.spec
  * removed tensorflow.chnages
- following source files had to be updated
  * updated abseil-cpp.tar.gz
  * updated bazel-toolchains.tar.gz
  * updated eigen.tar.gz
  * updated gemmlowp.zip
  * updated license.rst.txt
  * updated rules_closure.tar.gz
- following new souces had to be updated
  * added aws-sdk-cpp-1.5.8.tar.gz
  * added bazel-skylib.0.8.0.tar.gz
  * added fft2d.tgz
  * added rules_cc.zip
- for the following souces the system libraries are now ues
  * removed aws-sdk-cpp-1.3.15.tar.gz
  * removed double_conversion.zip
  * removed file unicode-org-icu.tar.gz
  * removed file 816a4ae622e964763ca0862d9dbd19324a1eaf45.tar.gz
- these patches were removed
  * removed file support-new-bazel.patch
  * removed file tensorflow-make_aws_sdk_work_on_aarch64.patch
  * removed file tensorflow-fix_lite.patch
  * removed file remove-keras.patch
  * removed file grpc-namespace-corrections.patch
- these new patches were added
  * added fix-lite.patch
  * added removed-docker-tools.patch
  * added right-json-location.patch

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Tue Oct 15 19:24:06 UTC 2019 - Christian Goll <cgoll@suse.com>

- updated to tensorflow 0.13.2
- dropped grpc.tar.gz and grpc-v1.13.0.gz as system grpc is used, this
  fixes the broken builds which were introduced with gcc9 (bsc#1152671)
  * added grpc-namespace-corrections.patch in order to use system grpc
- dropped re2-2018-10-01.tar.gz as system re2 is used now

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Wed Sep 25 14:18:48 UTC 2019 - Christian Goll <cgoll@suse.com>

- added remove-keras.patch which removes keras sources and uses
  distribution keras libaries
  * removed keras-applications-1.0.6.tar.gz
  * removed keras-preprocessing-1.0.9.tar.gz

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Mon Sep 23 09:25:08 UTC 2019 - Christian Goll <cgoll@suse.com>

- using now system protobuf instead of building it (bsc#1151150)

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Tue Sep 17 21:08:12 UTC 2019 - guillaume.gardet@opensuse.org

- Ajust %limit_build to avoid OOM errors
- Do not use %limit_build for lite flavor

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Mon Jul 29 13:51:16 UTC 2019 - Christian Goll <cgoll@suse.com>

- added additonal dependencies

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Wed Jul 17 08:18:34 UTC 2019 - Christian Goll <cgoll@suse.com>

- fixed installation location of shared library

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Mon Jul  8 14:04:17 UTC 2019 - Christian Goll <cgoll@suse.com>

- removed bazel mirror from as much source links as possible 
- added support-new-bazel.patch support newer upcoming bazel
  versions

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Tue Jun  4 14:16:10 UTC 2019 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Fix build for lite flavor:
  * tensorflow-fix_lite.patch

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Wed May 29 16:11:36 UTC 2019 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Call ldconfig for devel package in post/postun

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Mon May 27 15:00:28 UTC 2019 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Fix aarch64 build with upstream patch:
  * tensorflow-make_aws_sdk_work_on_aarch64.patch

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Mon May 27 04:08:54 UTC 2019 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Add Lite flavor

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Fri Apr 26 08:27:55 UTC 2019 - Christian Goll <cgoll@suse.com>

- updated to 1.13.1 fixes boo#1133490

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Fri Mar 29 13:06:28 UTC 2019 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Update _constraints to avoid OOM errors

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Fri Mar 29 08:18:09 UTC 2019 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Build and package libtensorflow_cc and libtensorflow_framework

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Tue Mar 19 15:40:25 UTC 2019 - Christian Goll <cgoll@suse.com>

- added fix_mvapich_mpi_bzl.patch which fixes detection of 
  mvapich2 mpi library
- fixed python3 build

-------------------------------------------------------------------
Tue Mar 12 20:33:56 UTC 2019 - Adrian Schröter <adrian@suse.de>

- update to version 1.13.1
  * Major Features and Improvements
  * TensorFlow Lite has moved from contrib to core. This means that Python modules are under tf.lite and source code is now under tensorflow/lite rather than tensorflow/contrib/lite.
  * TensorFlow GPU binaries are now built against CUDA 10 and TensorRT 5.0.
  * Support for Python3.7 on all operating systems.
  * Moved NCCL to core.
- drop merged patch mpilibpath_configure_py.patch
- drop obsolete pyton3.7 patches
- disabled jemalloc for now

-------------------------------------------------------------------
Tue Feb 12 08:39:57 UTC 2019 - cgoll@suse.com

- enabled aws and googlecloud support
  * removed no_aws_and_googlecloud.patch

-------------------------------------------------------------------
Mon Feb 11 16:27:20 UTC 2019 - Christian Goll <cgoll@suse.com>

- Fixed build issues with python 3.7 what introduced the patches
  * python3_7_compatibility.patch backported from upstream
  * python3.7_unicode.patch fixes a minor function call
  * python3.7_async_keyword.patch avoids the new keyword async

-------------------------------------------------------------------
Thu Jan 31 11:44:21 UTC 2019 - Bernhard Wiedemann <bwiedemann@suse.com>

- Fix build with python 3.7

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Fri Jan 18 16:45:48 UTC 2019 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Build and package libtensorflow.so as some packages may link to it

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Fri Jan 11 13:52:51 UTC 2019 - Guillaume GARDET <guillaume.gardet@opensuse.org>

- Add constraints on HDD size to avoid no space-left error

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Mon Nov 26 19:38:35 UTC 2018 - Todd R <toddrme2178@gmail.com>

- Fix python3 provides
- Minor spec file cleanups

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Sat Nov 24 09:03:12 UTC 2018 - Todd R <toddrme2178@gmail.com>

- Provide python3-tensorflow

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Thu Nov  8 15:54:04 UTC 2018 - cgoll@suse.com

- updated build command to fit bazel-0.19

-------------------------------------------------------------------
Thu Oct 18 22:11:23 UTC 2018 - Jan Engelhardt <jengelh@inai.de>

- Trim pad wording from descriptions.

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Tue Oct 16 10:26:54 UTC 2018 - cgoll@suse.com

- Updated to Tensorflow 1.10 as with this release it supports 
  the partial use of systemlibs. Still a lot additional sources are
  included which are
  * closure
  * weakref
  * double-conversion
  * gast
  * farmhash
  * nsync
  * gemmlowp
  * abseil-cpp
  * boring-ssl
  * google-apis
  * cub
  * highwayhash
  * abseil-pypi
  * eigen
  * arm_neon_x86_sse
  * fft
  * grpc
  * re2
  Although some of these libraries are available in factory they could 
  not be used as explicit versions are needed or bazel or the build
  system links them in the wrong way.
- mpilibpath_configure_py.patch changes the search path for the mpi 
  to also include lib64/
- no_aws_and_googlecloud.patch removes the dependence of aws, 
  googlecloud and kafaka apis, as this version is not compiled with
  the support of this apis.

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Thu Jan  4 11:00:55 UTC 2018 - cgoll@suse.com

- Initial commit of Tensorflow 1.4 not all requirement could be met
  by the distribution packages and the sources have to be included. 
  This is true for
  - Eigen
  - protobuf
  - grpc
  - lmdb
  - json-cpp
  The build itself is now based on bazel and creates the pip package which 
  is then extracted from the build environment

Places

File tensorflow-lite.changes of Package tensorflow-lite (Revision 6e7b7363097ec18497df4f3bf8dad065)

Places