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ci/official/requirements_updater/BUILD.bazel
# Copyright 2023 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS,
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RELEASE.md
dispatch to logical ops. This brings them more in line with Python and NumPy behavior. * Adds `tf.SparseTensor.with_values`. This returns a new SparseTensor with the same sparsity pattern, but with new provided values. It is similar to the `with_values` function of `RaggedTensor`. * Adds `StatelessCase` op, and uses it if none of case branches has stateful
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CONTRIBUTING.md
`--config=dbg` to Bazel will build with debugging information and without optimizations, allowing you to use GDB or other debuggers to debug C++ code. For example, you can build the pip package with debugging information by running: ```bash bazel build --config=dbg //tensorflow/tools/pip_package:build_pip_package ``` TensorFlow kernels and TensorFlow's dependencies are still not built with
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WORKSPACE
# # The cascade of load() statements and tf_workspace?() calls works around the # restriction that load() statements need to be at the top of .bzl files. # E.g. we can not retrieve a new repository with http_archive and then load() # a macro from that repository in the same file. load("@//tensorflow:workspace3.bzl", "tf_workspace3") tf_workspace3() load("@//tensorflow:workspace2.bzl", "tf_workspace2")
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tensorflow/c/BUILD
"tf_datatype.h", "tf_tensor.h", "tf_tstring.h", ], visibility = [ "//tensorflow:internal", "//tensorflow/c:__subpackages__", ], deps = selects.with_or({ "//tensorflow:android": [ "//tensorflow/core:portable_tensorflow_lib_lite", ], ("//tensorflow:chromiumos", "//tensorflow:fuchsia"): [ ":tf_attrtype",
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tensorflow/BUILD
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 # here allows us to override the behavior if needed. config_setting(
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tensorflow/c/eager/BUILD
"//tensorflow/core/common_runtime/eager:tensor_handle", "//tensorflow/core/lib/llvm_rtti", "@com_google_absl//absl/types:variant", ], }) + select({ "//tensorflow:with_xla_support": [ "//tensorflow/compiler/jit", "//tensorflow/compiler/jit:xla_device", "//tensorflow/compiler/tf2xla:xla_compiler", ], "//conditions:default": [],
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.bazelrc
# dbg: Build with debug info # # TF version options; # 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)
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ci/official/utilities/code_check_full.bats
# vim: filetype=bash # # Copyright 2022 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS,
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ci/official/envs/linux_x86_tpu
# Copyright 2023 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS,
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