Merge pull request #30544 from tensorflow:mm-fix-release-notes

PiperOrigin-RevId: 257440629

RELEASE.md

@@ -1,3 +1,274 @@
+# Release 1.14.0
+
+## Major Features and Improvements
+
+*   This is the first 1.x release containing the compat.v2 module. This module
+    is required to allow libraries to publish code which works in both 1.x and
+    2.x. After this release, no backwards incompatible changes are allowed in
+    the 2.0 Python API.
+*   Turn on MKL-DNN contraction kernels by default. MKL-DNN dynamically
+    dispatches the best kernel implementation based on CPU vector architecture.
+    To disable them, build with --define=tensorflow_mkldnn_contraction_kernel=0.
+
+## Behavioral changes
+
+*   Set default loss reduction as `AUTO` for improving reliability of loss
+    scaling with distribution strategy and custom training loops. `AUTO`
+    indicates that the reduction option will be determined by the usage context.
+    For almost all cases this defaults to `SUM_OVER_BATCH_SIZE`. When used in
+    distribution strategy scope, outside of built-in training loops such as
+    `tf.keras` `compile` and `fit`, we expect reduction value to be 'None' or
+    'SUM'. Using other values will raise an error.
+*   Wraps losses passed to the `compile` API (strings and v1 losses) which are
+    not instances of v2 `Loss` class in `LossWrapper` class. => All losses will
+    now use `SUM_OVER_BATCH_SIZE` reduction as default.
+*   Disable `run_eagerly` and distribution strategy if there are symbolic
+    tensors added to the model using `add_metric` or `add_loss`.
+*   tf.linspace(start, stop, num) now always uses "stop" as last value (for
+    num > 1)
+*   `ResourceVariable` and `Variable` no longer accepts `constraint` in the
+    constructor, nor expose it as a @property.
+*   The behavior of tf.gather is now correct when axis=None and batch_dims<0.
+*   Only create a GCS directory object if the object does not already exist.
+*   In `map_vectorization` optimization, reduce the degree of parallelism in the
+    vectorized map node.
+*   Bug fix: loss and gradients should now more reliably be correctly scaled
+    w.r.t. the global batch size when using a tf.distribute.Strategy.
+*   Updating cosine similarity loss - removed the negate sign from cosine
+    similarity.
+*   DType is no longer convertible to an int. Use dtype.as_datatype_enum instead
+    of int(dtype) to get the same result.
+*   Changed default for gradient accumulation for TPU embeddings to true.
+*   Callbacks now log values in eager mode when a deferred build model is used.
+*   Transitive dependencies on :pooling_ops were removed. Some users may need to
+    add explicit dependencies on :pooling_ops if they reference the operators
+    from that library.
+
+## Bug Fixes and Other Changes
+
+*   Documentation
+*   Deprecations and Symbol renames.
+    *   Remove unused StringViewVariantWrapper
+    *   Delete unused Fingerprint64Map op registration
+    *   SignatureDef util functions have been deprecated.
+    *   Renamed tf.image functions to remove duplicate "image" where it is
+        redundant.
+    *   tf.keras.experimental.export renamed to
+        tf.keras.experimental.export_saved_model
+    *   Standardize the LayerNormalization API by replacing the args `norm_axis`
+        and `params_axis` with `axis`.
+    *   Tensor::UnsafeCopyFromInternal deprecated in favor Tensor::BitcastFrom
+*   Keras & Python API
+    *   Add v2 module aliases for:
+    *   tf.initializers => tf.keras.initializers
+    *   tf.losses => tf.keras.losses & tf.metrics => tf.keras.metrics
+    *   tf.optimizers => tf.keras.optimizers
+    *   Add tf.keras.layers.AbstractRNNCell as the preferred implementation of
+        RNN cell for TF v2. User can use it to implement RNN cell with custom
+        behavior.
+    *   Adding `clear_losses` API to be able to clear losses at the end of
+        forward pass in a custom training loop in eager.
+    *   Add support for passing list of lists to the `metrics` param in Keras
+        `compile`.
+    *   Added top-k to precision and recall to keras metrics.
+    *   Adding public APIs for `cumsum` and `cumprod` keras backend functions.
+    *   Fix: model.add_loss(symbolic_tensor) should work in ambient eager.
+    *   Add name argument to tf.string_split and tf.strings_split
+    *   Minor change to SavedModels exported from Keras using
+        tf.keras.experimental.export. (SignatureDef key for evaluation mode is
+        now "eval" instead of "test"). This will be reverted back to "test" in
+        the near future.
+    *   Updates binary cross entropy logic in Keras when input is probabilities.
+        Instead of converting probabilities to logits, we are using the cross
+        entropy formula for probabilities.
+    *   Raw TensorFlow functions can now be used in conjunction with the Keras
+        Functional API during model creation. This obviates the need for users
+        to create Lambda layers in most cases when using the Functional API.
+        Like Lambda layers, TensorFlow functions that result in Variable
+        creation or assign ops are not supported.
+    *   Keras training and validation curves are shown on the same plot.
+    *   Introduce `dynamic` constructor argument in Layer and Model, which
+        should be set to True when using imperative control flow in the `call`
+        method.
+    *   Removing of dtype in the constructor of initializers and partition_info
+        in call.
+*   New ops and improved op functionality
+    *   Add OpKernels for some stateless maps
+    *   Add v2 APIs for AUCCurve and AUCSummationMethod
+        enums. #tf-metrics-convergence
+    *   Add tf.math.nextafter op.
+    *   Add CompositeTensor base class.
+    *   Add tf.linalg.tridiagonal_solve op.
+    *   Add opkernel templates for common table operations.
+    *   Added support for TFLite in TensorFlow 2.0.
+    *   Adds summary trace API for collecting graph and profile information.
+    *   Add batch_dims argument to tf.gather.
+    *   Add support for `add_metric` in the graph function mode.
+    *   Add C++ Gradient for BatchMatMulV2.
+    *   Added tf.random.binomial
+    *   Added gradient for SparseToDense op.
+    *   Add legacy string flat hash map op kernels
+    *   Add a ragged size op and register it to the op dispatcher
+    *   Add broadcasting support to tf.matmul.
+    *   Add ellipsis (...) support for tf.einsum()
+    *   Added LinearOperator.adjoint and LinearOperator.H (alias).
+    *   Added GPU implementation of tf.linalg.tridiagonal_solve.
+    *   Added strings.byte_split
+    *   Add RaggedTensor.placeholder()
+    *   Add a new "result_type" parameter to tf.strings.split
+    *   `add_update` can now be passed a zero-arg callable in order to support
+        turning off the update when setting `trainable=False` on a Layer of a
+        Model compiled with `run_eagerly=True`.
+    *   Add variant wrapper for absl::string_view
+    *   Add expand_composites argument to all nest.* methods.
+    *   Add pfor converter for Squeeze.
+    *   Bug fix for tf.tile gradient
+    *   Expose CriticalSection in core as tf.CriticalSection.
+    *   Update Fingerprint64Map to use aliases
+    *   ResourceVariable support for gather_nd.
+    *   ResourceVariable's gather op supports batch dimensions.
+    *   Variadic reduce is supported on CPU
+    *   Extend tf.function with basic support for CompositeTensors arguments
+        (such as SparseTensor and RaggedTensor).
+    *   Add templates and interfaces for creating lookup tables
+    *   Post-training quantization tool supports quantizing weights shared by
+        multiple operations. The models made with versions of this tool will use
+        INT8 types for weights and will only be executable interpreters from
+        this version onwards.
+    *   Malformed gif images could result in an access out of bounds in the
+        color palette of the frame. This has been fixed now
+    *   image.resize now considers proper pixel centers and has new kernels
+        (incl. anti-aliasing).
+*   Performance
+    *   Turn on MKL-DNN contraction kernels by default. MKL-DNN dynamically
+        dispatches the best kernel implementation based on CPU vector
+        architecture. To disable them, build with
+        --define=tensorflow_mkldnn_contraction_kernel=0.
+    *   Support for multi-host ncclAllReduce in Distribution Strategy.
+    *   Expose a flag that allows the number of threads to vary across Python
+        benchmarks.
+*   TensorFlow 2.0 Development
+    *   Add v2 sparse categorical crossentropy metric.
+    *   Allow non-Tensors through v2 losses.
+    *   Add UnifiedGRU as the new GRU implementation for tf2.0. Change the
+        default recurrent activation function for GRU from 'hard_sigmoid' to
+        'sigmoid', and 'reset_after' to True in 2.0. Historically recurrent
+        activation is 'hard_sigmoid' since it is fast than 'sigmoid'. With new
+        unified backend between CPU and GPU mode, since the CuDNN kernel is
+        using sigmoid, we change the default for CPU mode to sigmoid as well.
+        With that, the default GRU will be compatible with both CPU and GPU
+        kernel. This will enable user with GPU to use CuDNN kernel by default
+        and get a 10x performance boost in training. Note that this is
+        checkpoint breaking change. If user want to use their 1.x pre-trained
+        checkpoint, please construct the layer with
+        GRU(recurrent_activation='hard_sigmoid', reset_after=False) to fallback
+        to 1.x behavior.
+    *   TF 2.0 - Update metric name to always reflect what the user has given in
+        compile. Affects following cases 1. When name is given as
+        'accuracy'/'crossentropy' 2. When an aliased function name is used eg.
+        'mse' 3. Removing the `weighted` prefix from weighted metric names.
+    *   Begin adding Go wrapper for C Eager API
+    *   image.resize in 2.0 now supports gradients for the new resize kernels.
+    *   removed tf.string_split from v2 API
+    *   Expose tf.contrib.proto.* ops in tf.io (they will exist in TF2)
+    *   "Updates the TFLiteConverter API in 2.0. Changes from_concrete_function
+        to from_concrete_functions."
+    *   Enable tf.distribute.experimental.MultiWorkerMirroredStrategy working in
+        eager mode.
+    *   Support both binary and -1/1 label input in v2 hinge and squared hinge
+        losses.
+*   TensorFlow Lite
+    *   "Adds support for tflite_convert in 2.0."
+    *   "Remove lite.OpHint, lite.experimental, and lite.constant from 2.0 API."
+*   tf.contrib
+    *   Added Neural Turing Implementation as described in
+        https://arxiv.org/abs/1807.08518.
+    *   Remove tf.contrib.timeseries dependency on TF distributions.
+*   tf.data
+    *   Add num_parallel_reads and passing in a Dataset containing filenames
+        into TextLineDataset and FixedLengthRecordDataset
+    *   Going forward we operate in TF 2.0, this change is part of the effort to
+        slowly converting XYZDataset to DatasetV2 type which is the official
+        version going to be used in TF 2.0 and motivated by some compatibility
+        issue found, _BigtableXYZDataset (of type DatasetV2) does not implement
+        the _as_variant_tensor() of DatasetV1, when moving contrib.bigtable to
+        tensorflow_io. Converting into DatasetV2 removes the overheads to
+        maintain V1 while we are moving into TF 2.0.
+    *   Add dataset ops to the graph (or create kernels in Eager execution)
+        during the python Dataset object creation instead doing it during
+        Iterator creation time.
+    *   Add support for TensorArrays to tf.data Dataset.
+    *   Switching tf.data functions to use `defun`, providing an escape hatch to
+        continue using the legacy `Defun`.
+*   Toolchains
+    *   CUDNN_INSTALL_PATH, TENSORRT_INSTALL_PATH, NCCL_INSTALL_PATH,
+        NCCL_HDR_PATH are deprecated. Use TF_CUDA_PATHS instead which supports a
+        comma-separated list of base paths that are searched to find CUDA
+        libraries and headers.
+    *   TF code now resides in `tensorflow_core` and `tensorflow` is just a
+        virtual pip package. No code changes are needed for projects using
+        TensorFlow, the change is transparent
+*   XLA
+    *   XLA HLO graphs can be inspected with interactive_graphviz tool now.
+*   Estimator
+    *   Use tf.compat.v1.estimator.inputs instead of tf.estimator.inputs
+    *   Replace contrib references with tf.estimator.experimental.* for apis in
+        early_stopping.py
+
+## Thanks to our Contributors
+
+This release contains contributions from many people at Google, as well as:
+
+1e100, 4d55397500, a6802739, abenmao, Adam Weiss, Ag Ramesh, Alan Du, Albin Joy,
+Alex, Aman Patel, Amit, Amit Kumar Jaiswal, Amit Srivastava, Andreas Eberle,
+Andy Craze, Anthony Platanios, Armen Poghosov, armenpoghosov, arp95, Arpit Shah,
+Ashwin Ramaswami, Aurelien Geron, AuréLien Geron, aweers, awesomealex1, Ayush
+Agrawal, Ben Barsdell, Bharat Raghunathan, Bhavani Subramanian, blairhan,
+BléNesi Attila, Brandon Carter, candy.dc, Chao Liu, chenchc, chie8842, Christian
+Hansen, Christian Sigg, Clayne Robison, crafet, csukuangfj, ctiijima, Dan
+Jarvis, Dan Lazewatsky, Daniel Ingram, Daniel Salvadori, Dave Airlie, David
+Norman, Dayananda V, Dayananda-V, delock, Denis Khalikov, Deven Desai, Dheeraj
+Rajaram Reddy, dmitrievanthony, Donovan Ong, Drew Szurko, Duncan Riach, Dustin
+Neighly, Edward Forgacs, EFanZh, Fei Hu, Felix Lemke, Filip Matzner, fo40225,
+frreiss, Gautam, gehring, Geoffrey Irving, Grzegorz George Pawelczak, Grzegorz
+Pawelczak, Gyoung-Yoon Ryoo, HanGuo97, Hanton Yang, Hari Shankar, hehongliang,
+Heungsub Lee, Hoeseong Kim, I-Hong Jhuo, Ilango R, Innovimax, Irene Dea, Jacky
+Ko, Jakub Lipinski, Jason Zaman, jcf94, Jeffrey Poznanovic, Jens Elofsson,
+Jeroen BéDorf, Jia Qingtong, Jiankang, Joe Q, Joe Quadrino, Joeran Beel, Jonas
+Rauber, Jonathan, Jonathan Kyl, Joppe Geluykens, Joseph Friedman, jtressle, jwu,
+K Yasaswi Sri Chandra Gandhi, K. Hodges, Kaixi Hou, Karl Lessard, Karl
+Weinmeister, Karthik Muthuraman, Kashif Rasul, KDR, Keno Fischer, Kevin Mader,
+kjopek, Koan-Sin Tan, kouml, ktaebum, Lakshay Tokas, Laurent Le Brun, Letian
+Kang, Li, Guizi, Loo Rong Jie, Lucas Hendren, Lukas Geiger, Luke Han, luxupu,
+Ma, Guokai, Mahmoud Abuzaina, Mandar Deshpande, manhyuk, Marco Gaido, Marek
+Drozdowski, Mark Collier, Mark Ryan, mars20, Mateusz Chudyk, Matt Conley,
+MattConley, mbhuiyan, mdfaijul, Melissa Grueter, Michael KäUfl, MickaëL
+Schoentgen, Miguel Morin, Mihail Salnikov, Mike Arpaia, Mike Holcomb, monklof,
+Moses Marin, Mshr-H, nammbash, Natalia Gimelshein, Nayana-Ibm, neargye, Neeraj
+Pradhan, Nehal J Wani, Nick, Niels Ole Salscheider, Niranjan Hasabnis, nlewycky,
+Nuka-137, Nutti, olicht, P Sudeepam, Palmer Lao, Pan Daoxin, Pariksheet Pinjari,
+Pavel Samolysov, PENGWA, Pooya Davoodi, R S Nikhil Krishna, Rohit Gupta, Roman
+Soldatow, rthadur, Ruizhe, Ryan Jiang, Samantha Andow, Sami Kama, Sana-Damani,
+Saurabh Deoras, sdamani, seanshpark, Sebastien Iooss, Serv-Inc, Shahzad Lone,
+Shashank Gupta, Shashi, shashvat, shashvatshahi1998, Siju, Siju Samuel,
+Snease-Abq, Spencer Schaber, sremedios, srinivasan.narayanamoorthy, Steve Lang,
+Steve Nesae, Sumesh Udayakumaran, Supriya Rao, Taylor Jakobson, Taylor Thornton,
+Ted Chang, ThisIsPIRI, Thomas Deegan, Thomas Hagebols, tianyapiaozi, Tim Zaman,
+tomguluson92, Tongxuan Liu, TungJerry, v1incent, Vagif, vcarpani, Vikram Tiwari,
+Vishwak Srinivasan, Vitor-Alves, wangsiyu, wateryzephyr, WeberXie, WeijieSun,
+Wen-Heng (Jack) Chung, wenxizhu, Will Battel, William D. Irons, wyzhao, Xin,
+Yasuhiro Matsumoto, ymodak, Yong Tang, Younes Khoudli, Yuan Lin, Yves-Noel
+Weweler, Zantares, zjjott, 卜居, 王振华 (Wang Zhenhua), 黄鑫
+
+# Release 1.12.3
+
+## Bug Fixes and Other Changes
+
+*   Updates `png_archive` dependency to 1.6.37 to not be affected by
+    CVE-2019-7317, CVE-2018-13785, and CVE-2018-14048.
+*   Updates `sqlite` depenency to 3.28.0 to not be affected by CVE-2018-20506,
+    CVE-2018-20346, and CVE-2018-20505.
+
 # Release 1.12.2
 
 ## Bug Fixes and Other Changes