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RELEASE.md
* <NOTES SHOULD BE GROUPED PER AREA> * `tf.lite` * Added support for `stablehlo.gather`. * Added support for `stablehlo.add`. * Added support for `stablehlo.multiply`. * Added support for `stablehlo.maximum`. * Added support for `stablehlo.minimum`. * Added boolean parameter support for `tfl.gather_nd`. * C API: * New API functions:
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ci/official/envs/linux_arm64
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_arm64 # Note: this is not set to "--cpu", because that changes the package name # to tensorflow_cpu. These ARM builds are supposed to have the name "tensorflow" # despite lacking Nvidia CUDA support. TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_DOCKER_ENABLE=1 TFCI_DOCKER_IMAGE=gcr.io/tensorflow-sigs/build-arm64:tf-2-16-multi-python TFCI_DOCKER_PULL_ENABLE=1
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tensorflow/BUILD
config_setting( name = "stackdriver_support", define_values = {"stackdriver_support": "true"}, visibility = ["//visibility:public"], ) config_setting( name = "with_xla_support", define_values = {"with_xla_support": "true"}, visibility = ["//visibility:public"], ) # By default, XLA GPU is compiled into tensorflow when building with # --config=cuda even when `with_xla_support` is false. The config setting
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.bazelrc
# v2: Build TF v2 # # Feature and Third party library support options: # xla: Build TF with XLA # tpu: Build TF with TPU support # cuda: Build with CUDA support. # cuda_clang Build with CUDA Clang support. # rocm: Build with AMD GPU support (rocm) # mkl: Enable full mkl support. # tensorrt: Enable Tensorrt support. # noaws: Disable AWS S3 storage support
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tensorflow/c/experimental/filesystem/BUILD
srcs = ["modular_filesystem_test.cc"], linkopts = ["-ldl"], tags = [ "manual", # Requires DSOs as arguments, eventual setup "notap", # b/139060984, requires implementing modular support for Google filesystem ], deps = [ ":modular_filesystem", "//tensorflow/core:framework_internal", "//tensorflow/core/lib/io:path", "//tensorflow/core/platform:env",
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ci/official/README.md
- Different Python versions - Linux, MacOS, and Windows machines (these pool definitions are internal) - x86 and arm64 - CPU-only, or with NVIDIA CUDA support (Linux only), or with TPUs ## How to Test Your Changes to TensorFlow You may check how your changes will affect TensorFlow by: 1. Creating a PR and observing the presubmit test results
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configure.py
write_to_bazelrc( 'build --copt="-DEIGEN_ALTIVEC_ENABLE_MMA_DYNAMIC_DISPATCH=1"') with_xla_support = environ_cp.get('TF_ENABLE_XLA', None) if with_xla_support is not None: write_to_bazelrc('build --define=with_xla_support=%s' % ('true' if int(with_xla_support) else 'false')) set_action_env_var( environ_cp, 'TF_NEED_ROCM', 'ROCm', False, bazel_config_name='rocm')
Python - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 18:25:36 GMT 2024 - 53.8K bytes - Viewed (1) -
tensorflow/c/eager/dlpack.cc
tensorflow::TensorHandleFromInterface(tensorflow::unwrap(h)); if (handle->Type() != TensorHandle::LOCAL) { status->status = tensorflow::errors::InvalidArgument( "DLPack doesn't support ", handle->TypeString(), " tensor"); return nullptr; } const tensorflow::Tensor* tensor; status->status = handle->Tensor(&tensor); if (!status->status.ok()) { return nullptr; } return tensor;
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ci/official/utilities/setup_macos.sh
chmod +x "/usr/local/bin/bazel" fi # "TFCI_MACOS_UPGRADE_PYENV_ENABLE" is used to decide if we need to upgrade the # Pyenv version. We enable this for macOS x86 builds as the default Pyenv on # those VMs does not support installing Python 3.12 and above which we need # for running smoke tests in nightly/release wheel builds. if [[ "${TFCI_MACOS_UPGRADE_PYENV_ENABLE}" == 1 ]]; then
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tensorflow/c/eager/gradients.cc
for (int i = 0; i < *num_retvals; i++) { // TODO(srbs): Manage refcount of ForwardOperation's inputs/outputs. forward_op_->outputs.push_back(retvals[i]); } // TODO(b/166669239): This is needed to support AttrBuilder::Get for string // attributes. Number type attrs and DataType attrs work fine without this. // Consider getting rid of this and making the behavior between number types // and string consistent.
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