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ci/official/requirements_updater/BUILD.bazel
) compile_pip_requirements_3_9( name = "requirements_3_9_release", extra_args = [ "--allow-unsafe", "-P keras-nightly", "-P tb-nightly", ], requirements_in = "requirements.in", requirements_txt = "requirements_lock_3_9.txt", ) compile_pip_requirements_3_10( name = "requirements_3_10_release", extra_args = [ "--allow-unsafe", "-P keras-nightly",
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ci/official/envs/linux_x86_cuda
# limitations under the License. # ============================================================================== source ci/official/envs/linux_x86 TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_gpu_linux" TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cuda TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_DOCKER_ARGS="--gpus all" TFCI_LIB_SUFFIX="-gpu-linux-x86_64"
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RELEASE.md
`tf.divide()` is now the recommended division function. `tf.div()` will remain, but its semantics do not respond to Python 3 or `from future` mechanisms. * tf.reverse() now takes indices of axes to be reversed. E.g. `tf.reverse(a, [True, False, True])` must now be written as `tf.reverse(a, [0, 2])`. `tf.reverse_v2()` will remain until 1.0 final. * `tf.mul`, `tf.sub` and `tf.neg` are deprecated in favor of `tf.multiply`, `tf.subtract` and `tf.negative`. *
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ci/official/requirements_updater/release_updater.sh
do cp ../../../requirements_lock_"$VERSION".txt "requirements_lock_"$VERSION".txt" bazel run \ --experimental_convenience_symlinks=ignore \ --enable_bzlmod=false \ //:requirements_"$VERSION"_release.update sed -i '/^#/d' requirements_lock_"$VERSION".txt mv "requirements_lock_"$VERSION".txt" ../../../requirements_lock_"$VERSION".txt done
Shell Script - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 15:05:45 GMT 2024 - 1.3K bytes - Viewed (0) -
ci/official/envs/versions_upload
# Release jobs are very basic. They don't use any caching or RBE, # but they do upload logs to resultstore. # IMPORTANT: trailing slash is required on GCS URIs, as it tells gcloud to # pretend the path is a directory. TFCI_ARTIFACT_FINAL_GCS_ENABLE=1 TFCI_ARTIFACT_FINAL_GCS_SA_PATH="${KOKORO_KEYSTORE_DIR}/73361_tensorflow_release_binary_uploader_service_account"
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ci/official/envs/linux_arm64
# limitations under the License. # ============================================================================== TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_arm64_linux" 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"
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tensorflow/c/eager/c_api_unified_experimental.cc
return wrap(t); } void TF_DeleteExecutionContext(TF_ExecutionContext* c) { unwrap(c)->Release(); } TF_AbstractOp* TF_NewAbstractOp(TF_ExecutionContext* c) { return wrap((unwrap(c)->CreateOperation())); } void TF_DeleteAbstractOp(TF_AbstractOp* op) { unwrap(op)->Release(); } void TF_DeleteAbstractTensor(TF_AbstractTensor* t) { unwrap(t)->Unref(); }
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tensorflow/c/c_api.cc
tensorflow::shape_inference::InferenceContext* ic, int num_dims, const int64_t* dims) { if (num_dims != -1) { std::vector<tensorflow::shape_inference::DimensionHandle> dim_vec; dim_vec.reserve(num_dims); for (int i = 0; i < num_dims; ++i) { dim_vec.push_back(ic->MakeDim(dims[i])); } return ic->MakeShape(dim_vec); } else { return ic->UnknownShape(); } }
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ci/official/requirements_updater/README.md
requirements_in = "requirements.in", requirements_txt = "requirements_lock_3_11.txt", ) ``` ``` compile_pip_requirements_3_11( name = "requirements_3_11_release", extra_args = [ "--allow-unsafe", "-P keras-nightly", "-P tb-nightly", ], requirements_in = "requirements.in",
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tensorflow/c/eager/gradients.cc
for (int i = 0; i < inputs.size(); i++) { input_ids[i] = ToId(inputs[i]); input_dtypes[i] = inputs[i]->DataType(); } std::vector<TapeTensor> tape_tensors; tape_tensors.reserve(outputs.size()); for (auto t : outputs) { tape_tensors.push_back(TapeTensor(t)); } GradientTape::RecordOperation( op_name, tape_tensors, input_ids, input_dtypes,
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