Merge pull request tensorflow#1505 from ROCmSoftwarePlatform/develop-…

…upstream-sync-211206

Develop upstream sync 211206

.bazelrc

@@ -594,6 +594,12 @@ build:release_cpu_linux --config=avx_linux
 build:release_cpu_linux --crosstool_top="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"
 test:release_cpu_linux --test_env=LD_LIBRARY_PATH
 
+# manylinux2014 config for cpu
+build:release_cpu_linux_manylinux2014 --config=release_base
+build:release_cpu_linux_manylinux2014 --config=avx_linux
+build:release_cpu_linux_manylinux2014 --crosstool_top="@ubuntu18.04-gcc8_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"
+test:release_cpu_linux_manylinux2014 --test_env=LD_LIBRARY_PATH
+
 build:release_cpu_macos --config=release_base
 build:release_cpu_macos --config=avx_linux
 
@@ -616,6 +622,12 @@ build:release_gpu_linux_11_4 --action_env=TF_CUDA_VERSION="11.4"
 build:release_gpu_linux_11_4 --action_env=TF_CUDNN_VERSION="8.2"
 build:release_gpu_linux_11_4 --crosstool_top=@ubuntu18.04-gcc7_manylinux2010-cuda11.4-cudnn8.2-tensorrt7.2_config_cuda//crosstool:toolchain
 
+# manylinux2014 config for gpu
+build:release_gpu_linux_manylinux2014 --config=release_gpu_linux
+build:release_gpu_linux_manylinux2014 --action_env=GCC_HOST_COMPILER_PATH="/dt8/usr/bin/gcc"
+build:release_gpu_linux_manylinux2014 --crosstool_top=@ubuntu18.04-gcc8_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain
+
+
 build:release_cpu_windows --config=release_base
 build:release_cpu_windows --config=avx_win
 build:release_cpu_windows --define=no_tensorflow_py_deps=true

.bazelversion

@@ -1 +1 @@
-3.7.2
+4.2.1

LICENSE

@@ -200,31 +200,27 @@
    See the License for the specific language governing permissions and
    limitations under the License.
 
-------------------
-Files: third_party/compute_library/...
-
-MIT License
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
-
-------------------
-Files: ACKNOWLEDGEMENTS
+## Some of TensorFlow's code is derived from Caffe, which is subject to the following copyright notice:
+
+COPYRIGHT
+
+All contributions by the University of California:
+
+Copyright (c) 2014, The Regents of the University of California (Regents)
+All rights reserved.
+
+All other contributions:
+
+Copyright (c) 2014, the respective contributors
+All rights reserved.
+
+Caffe uses a shared copyright model: each contributor holds copyright over
+their contributions to Caffe. The project versioning records all such
+contribution and copyright details. If a contributor wants to further mark
+their specific copyright on a particular contribution, they should indicate
+their copyright solely in the commit message of the change when it is
+committed.
+
 LICENSE
 
 Redistribution and use in source and binary forms, with or without
@@ -248,37 +244,8 @@ modification, are permitted provided that the following conditions are met:
    (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
    SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-------------------
-Files: third_party/hexagon
+CONTRIBUTION AGREEMENT
 
-Copyright (c) 2016-2019, The Linux Foundation. All rights reserved.
-
-Redistribution and use in source and binary forms, with or without
-modification, are permitted (subject to the limitations in the
-disclaimer below) provided that the following conditions are met:
-
-   * Redistributions of source code must retain the above copyright
-     notice, this list of conditions and the following disclaimer.
-
-   * Redistributions in binary form must reproduce the above
-     copyright notice, this list of conditions and the following
-     disclaimer in the documentation and/or other materials provided
-     with the distribution.
-
-   * Neither the name of The Linux Foundation nor the names of its
-     contributors may be used to endorse or promote products derived
-     from this software without specific prior written permission.
-
-NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE
-GRANTED BY THIS LICENSE. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT
-HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED
-WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
-MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
-IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR
-ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
-DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE
-GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
-INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
-IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
-OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN
-IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+By contributing to the BVLC/caffe repository through pull-request, comment,
+or otherwise, the contributor releases their content to the
+license and copyright terms herein.

RELEASE.md

@@ -16,9 +16,12 @@
 # Major Features and Improvements
 
 *   `tf.lite`:
-    *   Where operation support is added for these data types
-        'int32/uint32/int8/uint8/int64'
-    *   Add builtin support for `Bucketize` op on CPU.
+    *   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
@@ -29,6 +32,16 @@
         `.save()` function inside `TrtGraphConverterV2`. When `False`, the
         `.save()` function won't save any TRT engines that have been built. When
         `True` (default), the original behavior is preserved.
+*   `tf.tpu.experimental.embedding`:
+    *   `tf.tpu.experimental.embedding.FeatureConfig` now takes an additional
+        argument `output_shape` which can specify the shape of the output
+        activation for the feature.
+    *   `tf.tpu.experimental.embedding.TPUEmbedding` now has the same behavior
+        as `tf.tpu.experimental.embedding.serving_embedding_lookup` which can
+        take arbitrary rank of dense and sparse tensor. For ragged tensor,
+        though the input tensor remains to be rank 2, the activations now can be
+        rank 2 or above by specifying the output shape in the feature config
+        or via the build method.
 
 *   <INSERT MAJOR FEATURE HERE, USING MARKDOWN SYNTAX>
 
@@ -42,6 +55,9 @@
 * `tf.data`:
   * The optimization `parallel_batch` now becomes default if not disabled by
     users, which will parallelize copying of batch elements.
+  * Added the ability for `TensorSliceDataset` to identify and handle inputs
+    that are files. This enables creating hermetic SavedModels when using
+    datasets created from files.
 
 * `tf.lite`:
   * GPU
@@ -161,6 +177,7 @@ This release contains contributions from many people at Google, as well as:
 * `tf.lite`:
   * Add experimental API `experimental_from_jax` to support conversion from Jax models to TensorFlow Lite.
   * Support uint32 data type for cast op.
+  * Support int8 data type for cast op.
   * Add experimental quantization debugger `tf.lite.QuantizationDebugger`
   * Add lite.experimental.authoring.compatible API
       *   A Python decorator to provide a way to check TFLite compatibility

configure.py

@@ -45,7 +45,7 @@
 _TF_WORKSPACE_ROOT = ''
 _TF_BAZELRC = ''
 _TF_CURRENT_BAZEL_VERSION = None
-_TF_MIN_BAZEL_VERSION = '3.7.2'
+_TF_MIN_BAZEL_VERSION = '4.2.1'
 _TF_MAX_BAZEL_VERSION = '4.99.0'
 
 NCCL_LIB_PATHS = [

tensorflow/BUILD

@@ -46,7 +46,6 @@ licenses(["notice"])
 
 exports_files([
     "LICENSE",
-    "ACKNOWLEDGMENTS",
     # The leakr files are used by //third_party/cloud_tpu and
     # //third_party/tensorboard/google:copybara_config_test.
     "leakr_badwords.dic",

tensorflow/c/eager/abstract_context.h

@@ -42,7 +42,7 @@ class AbstractContext {
   // Release any underlying resources, including the interface object.
   //
   // WARNING: The destructor of this class is marked as protected to disallow
-  // clients from directly destroying this object since it may manage it's own
+  // clients from directly destroying this object since it may manage its own
   // lifetime through ref counting. Thus clients MUST call Release() in order to
   // destroy an instance of this class.
   virtual void Release() = 0;

tensorflow/c/eager/c_api.h

@@ -119,7 +119,7 @@ TF_CAPI_EXPORT extern TFE_ContextDevicePlacementPolicy
 TFE_ContextGetDevicePlacementPolicy(TFE_Context* ctx);
 
 // A tensorflow.ServerDef specifies remote workers (in addition to the current
-// workers name). Operations created on this context can then be executed on
+// workers name). Operations created in this context can then be executed on
 // any of these remote workers by setting an appropriate device.
 //
 // If the following is set, all servers identified by the
@@ -134,7 +134,7 @@ TF_CAPI_EXPORT extern void TFE_ContextSetServerDef(TFE_Context* ctx,
 //
 // Like a TF_Tensor, a TFE_TensorHandle refers to a tensor with a value, shape,
 // type etc. Unlike a TF_Tensor, a TFE_TensorHandle may refer to such tensors
-// placed in memory of different devices or remote address spaces.
+// placed in the memory of different devices or remote address spaces.
 typedef struct TFE_TensorHandle TFE_TensorHandle;
 
 TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_NewTensorHandle(const TF_Tensor* t,
@@ -442,7 +442,7 @@ TF_CAPI_EXPORT extern void TFE_ContextStartStep(TFE_Context* ctx);
 
 // Ends a step. When there is no active step (that is, every started step has
 // been ended) step containers will be cleared. Note: it is not safe to call
-// TFE_ContextEndStep while ops which rely on the step container may be running.
+// TFE_ContextEndStep while ops that rely on the step container may be running.
 TF_CAPI_EXPORT extern void TFE_ContextEndStep(TFE_Context* ctx);
 
 #ifdef __cplusplus

tensorflow/c/eager/c_api_distributed_test.cc

@@ -161,7 +161,7 @@ void TestFunctionWithPackedInput(const bool remote) {
   TFE_TensorHandle* h1 = TestVariable(ctx, 2.0, task2_name);
   TFE_TensorHandle* h2 = TestVariable(ctx, 3.0, task0_name);
 
-  // Add a sync point in order to make sure that variables have been initialized
+  // Add a sync point to make sure that variables have been initialized
   // before the function execution starts.
   TFE_ContextAsyncWait(ctx, status);
   EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

tensorflow/c/eager/c_api_experimental.h

@@ -140,7 +140,7 @@ TFE_MonitoringGetCellIntGauge2(TFE_MonitoringIntGauge2* gauge,
 typedef struct TFE_MonitoringStringGaugeCell TFE_MonitoringStringGaugeCell;
 TF_CAPI_EXPORT extern void TFE_MonitoringStringGaugeCellSet(
     TFE_MonitoringStringGaugeCell* cell, const char* value);
-// Retrieves the string value and saves it in buffer.
+// Retrieves the string value and saves it in the buffer.
 TF_CAPI_EXPORT extern const void TFE_MonitoringStringGaugeCellValue(
     TFE_MonitoringStringGaugeCell* cell, TF_Buffer* buf);
 
@@ -248,7 +248,7 @@ TF_CAPI_EXPORT extern void TFE_MonitoringSamplerCellAdd(
     TFE_MonitoringSamplerCell* cell, double value);
 
 // Retrieves the current value of the cell. The return value is a HistogramProto
-// saved in buffer.
+// saved in the buffer.
 TF_CAPI_EXPORT extern void TFE_MonitoringSamplerCellValue(
     TFE_MonitoringSamplerCell* cell, TF_Buffer* buf);
 
@@ -353,7 +353,7 @@ TF_CAPI_EXPORT extern bool TFE_ExecutorIsAsync(TFE_Executor*);
 TF_CAPI_EXPORT extern void TFE_ExecutorWaitForAllPendingNodes(
     TFE_Executor*, TF_Status* status);
 
-// When an error happens, any pending operations are discarded and newly issued
+// When an error happens, any pending operations are discarded, and newly issued
 // ops return an error. This call clears the error state and re-enables
 // execution of newly issued ops.
 //
@@ -362,12 +362,12 @@ TF_CAPI_EXPORT extern void TFE_ExecutorWaitForAllPendingNodes(
 // TODO(agarwal): mark the affected handles and raise errors if they are used.
 TF_CAPI_EXPORT extern void TFE_ExecutorClearError(TFE_Executor*);
 
-// Sets a custom Executor for current thread. All nodes created by this thread
-// will be added to this Executor. It will override current executor.
+// Sets a custom Executor for the current thread. All nodes created by this
+// thread will be added to this Executor. It will override the current executor.
 TF_CAPI_EXPORT extern void TFE_ContextSetExecutorForThread(TFE_Context*,
                                                            TFE_Executor*);
 
-// Returns the Executor for current thread.
+// Returns the Executor for the current thread.
 TF_CAPI_EXPORT extern TFE_Executor* TFE_ContextGetExecutorForThread(
     TFE_Context*);
 
@@ -376,7 +376,7 @@ TF_CAPI_EXPORT extern TFE_Executor* TFE_ContextGetExecutorForThread(
 
 // Update an existing context with a new set of servers defined in a ServerDef
 // proto. Servers can be added to and removed from the list of remote workers
-// in the context. New set of servers identified by the ServerDef must be up
+// in the context. A New set of servers identified by the ServerDef must be up
 // when the context is updated.
 //
 // This API is for experimental usage and may be subject to change.
@@ -527,8 +527,8 @@ typedef struct TFE_CustomDevice {
 // names of wrapped devices.
 //
 // There are currently no graph semantics implemented for registered custom
-// devices, so executing tf.functions which contain operations placed on custom
-// devices will fail.
+// devices, so executing tf.functions which contain operations placed on the
+// custom devices will fail.
 //
 // `device_name` must not name an existing physical or custom device. It must
 // follow the format:
@@ -646,8 +646,8 @@ TF_CAPI_EXPORT extern int TFE_TensorHandleDeviceID(TFE_TensorHandle* h,
                                                    TF_Status* status);
 
 // Returns the status for the tensor handle. In TFRT, a tensor handle can carry
-// error info if error happens. If so, status will be set with the error info.
-// If not, status will be set as OK.
+// error info if error happens. If so, the status will be set with the error
+// info. If not, status will be set as OK.
 TF_CAPI_EXPORT extern void TFE_TensorHandleGetStatus(TFE_TensorHandle* h,
                                                      TF_Status* status);
 
@@ -673,7 +673,7 @@ TF_CAPI_EXPORT extern void TFE_SetLogicalCpuDevices(TFE_Context* ctx,
 // setting the same key will lead to errors.
 //
 // Note that the key-values are only expected to be used for cluster
-// configuration data, and should not be used for storing large amount of data
+// configuration data, and should not be used for storing a large amount of data
 // or being accessed very frequently.
 TF_CAPI_EXPORT extern void TFE_InsertConfigKeyValue(TFE_Context* ctx,
                                                     const char* key,