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.bazelrc
build:rbe_cross_compile_base --remote_instance_name=projects/tensorflow-testing/instances/default_instance # XLA depends on some local Python headers that are configured as Genrule. They # are present on the local host machine but not on the remote execution machine, # leading to build failures. To resolve the issue, the following line is added # to make sure all Genrule targets are excuted locally. build:rbe_cross_compile_base_xla --config=rbe_cross_compile_base
Plain Text - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Thu May 02 19:34:20 GMT 2024 - 52.8K bytes - Viewed (2) -
tensorflow/BUILD
# Description: # TensorFlow is a computational framework, primarily for use in machine # learning applications. load("@bazel_skylib//lib:selects.bzl", "selects") load("@bazel_skylib//rules:common_settings.bzl", "bool_flag", "bool_setting") load("@local_config_cuda//cuda:build_defs.bzl", "if_cuda") load( "//tensorflow:tensorflow.bzl", "VERSION", "VERSION_MAJOR", "check_deps", "if_google", "if_oss",
Plain Text - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Apr 09 18:15:11 GMT 2024 - 53.4K bytes - Viewed (8) -
configure.py
def is_linux(): return platform.system() == 'Linux' def is_macos(): return platform.system() == 'Darwin' def is_ppc64le(): return platform.machine() == 'ppc64le' def is_s390x(): return platform.machine() == 's390x' def is_cygwin(): return platform.system().startswith('CYGWIN_NT') def get_input(question): try: try: answer = raw_input(question)
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/c_api.cc
// DT_RESOURCE. The string serialization is converted back to a // ResourceHandle during Session run where the TF_Tensor is converted to a // Tensor. // TFv2 does not depend on this conversion. There is no matching // TF_TensorFromTensorV1 because the conversion to string is performed by the // python side of Session. static Status TF_TensorToTensorV1(const TF_Tensor* src, Tensor* dst) { Status status = TF_TensorToTensor(src, dst);
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 03:35:10 GMT 2024 - 102.3K bytes - Viewed (0) -
ci/official/utilities/rename_and_verify_wheels.sh
fi # VERY basic check to ensure the [and-cuda] package variant is installable. # Checks TFCI_BAZEL_COMMON_ARGS for "gpu" or "cuda", implying that the test is # relevant. All of the GPU test machines have CUDA installed via other means, # so I am not sure how to verify that the dependencies themselves are valid for # the moment. if [[ "$TFCI_BAZEL_COMMON_ARGS" =~ gpu|cuda ]]; then
Shell Script - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Wed Mar 27 21:16:27 GMT 2024 - 3.4K bytes - Viewed (0) -
RELEASE.md
`InvalidArgumentError,` as documented. * Update Getting Started docs and API intro. * Google Cloud Storage (GCS): * Add userspace DNS caching for the GCS client. * Customize request timeouts for the GCS filesystem. * Improve GCS filesystem caching. * Bug Fixes: * Fix bug where partitioned integer variables got their wrong shapes. Before
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.github/workflows/update-rbe.yml
echo -n "Trying to map name $1 to tag $2... " digest=$(curl -s --head "https://gcr.io/v2/tensorflow-sigs/build/manifests/$2" | egrep -o "sha256:[[:alnum:]]*") # Find the line matching the regex "sigbuild-r2.9" (with quotes) and # replace just the digest portion in it sed -i"" "/\"$1\"/ s/sha256:[[:alnum:]]*/$digest/g" tensorflow/tools/toolchains/remote_config/configs.bzl
Others - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Wed Apr 10 15:40:34 GMT 2024 - 7.2K bytes - Viewed (0) -
ci/official/utilities/code_check_full.bats
setup_file() { bazel version # Start the bazel server } # Do a bazel query specifically for the licenses checker. It searches for # targets matching the provided query, which start with // or @ but not # //tensorflow (so it looks for //third_party, //external, etc.), and then # gathers the list of all packages (i.e. directories) which contain those # targets.
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tensorflow/c/eager/tape.h
for (auto accumulated : accumulated_gradients_) { vspace_.DeleteGradient(accumulated.second); } } // Tell the forward accumulator to watch tensor_id, with a Tensor tangent // vector `tangent` of matching shape and dtype. Tangents are the "vector" in // "Jacobian-vector product"; `Watch`ing a new Tensor and immediately calling // FetchJVP for it would return `tangent`. void Watch(int64_t tensor_id, Gradient* tangent);
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