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ci/official/envs/linux_x86_tpu
# ============================================================================== source ci/official/envs/linux_x86 TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_cpu_linux --config=tpu" TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_tpu TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow_tpu" TFCI_LIB_SUFFIX="-tpu-linux-x86_64" TFCI_WHL_BAZEL_TEST_ENABLE=0
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ci/official/envs/macos_arm64
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=macos_arm64 TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_INDEX_HTML_ENABLE=1 TFCI_LIB_SUFFIX="-cpu-darwin-arm64" TFCI_MACOS_BAZEL_TEST_DIR_ENABLE=1 TFCI_MACOS_BAZEL_TEST_DIR_PATH="/Volumes/BuildData/bazel_output" TFCI_OUTPUT_DIR=build_output TFCI_WHL_BAZEL_TEST_ENABLE=1 TFCI_WHL_SIZE_LIMIT=240M
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tensorflow/c/c_api_experimental.h
// b) ConfigProto.gpu_options.allow_growth is set to `gpu_memory_allow_growth`. // c) ConfigProto.device_count is set to `num_cpu_devices`. TF_CAPI_EXPORT extern TF_Buffer* TF_CreateConfig( unsigned char enable_xla_compilation, unsigned char gpu_memory_allow_growth, unsigned int num_cpu_devices); // Create a serialized tensorflow.RunOptions proto, where RunOptions.trace_level
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tensorflow/c/c_test_util.cc
TF_SetAttrType(desc, "T", TF_INT32); // Set device to CPU since there is no version of split for int32 on GPU // TODO(iga): Convert all these helpers and tests to use floats because // they are usually available on GPUs. After doing this, remove TF_SetDevice // call in c_api_function_test.cc TF_SetDevice(desc, "/cpu:0"); *op = TF_FinishOperation(desc, s); ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
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ci/official/containers/linux_arm64/devel.usertools/code_check_full.bats
EOF # grep patterns for files and targets which don't need to be in the pip # package, ever. cat > $BATS_TEST_TMPDIR/ignore_these_deps <<EOF benchmark _test$ _test.py$ _test_cpu$ _test_cpu.py$ _test_gpu$ _test_gpu.py$ _test_lib$ //tensorflow/cc/saved_model:saved_model_test_files //tensorflow/cc/saved_model:saved_model_half_plus_two //tensorflow:no_tensorflow_py_deps
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ci/official/README.md
These "env" files match up with an environment matrix that roughly covers: - 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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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
# This bazelrc can build a CPU-supporting TF package. # Convenient cache configurations # Use a cache directory mounted to /tf/cache. Very useful! build:sigbuild_local_cache --disk_cache=/tf/cache # Use the public-access TF DevInfra cache (read only) build:sigbuild_remote_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/manylinux2014" --remote_upload_local_results=false
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RELEASE.md
* `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`:
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tensorflow/c/eager/BUILD
"//tensorflow/c:tf_buffer_internal", "//tensorflow/c:tf_status_internal", "//tensorflow/c:tf_tensor_internal", "//tensorflow/core:core_cpu", "//tensorflow/core:core_cpu_internal", "//tensorflow/core:framework", "//tensorflow/core:framework_internal", "//tensorflow/core:lib", "//tensorflow/core:lib_internal",
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tensorflow/c/eager/c_api_remote_test.cc
TFE_TensorHandle* h0_task0 = TestMatrixTensorHandle(ctx); TFE_TensorHandle* h1_task0 = TestMatrixTensorHandle(ctx); const char remote_device_name[] = "/job:localhost/replica:0/task:1/device:CPU:0"; auto* h0_task1 = TFE_TensorHandleCopyToDevice(h0_task0, ctx, remote_device_name, status); ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status); auto* h1_task1 =
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