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tensorflow/api_template.__init__.py
from tensorflow.python.util.lazy_loader import KerasLazyLoader as _KerasLazyLoader # Make sure code inside the TensorFlow codebase can use tf2.enabled() at import. _os.environ["TF2_BEHAVIOR"] = "1" from tensorflow.python import tf2 as _tf2 _tf2.enable() # API IMPORTS PLACEHOLDER # WRAPPER_PLACEHOLDER # Make sure directory containing top level submodules is in # the __path__ so that "from tensorflow.foo import bar" works.
Python - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Mar 05 06:27:59 GMT 2024 - 6.7K bytes - Viewed (3) -
tensorflow/c/c_api.cc
const char* attr_name, const void* proto, size_t proto_len, TF_Status* status) { // shape.ParseFromArray takes an int as length, this function takes size_t, // make sure there is no information loss. if (proto_len > std::numeric_limits<int>::max()) { status->status = InvalidArgument( "proto_len (", proto_len,
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) -
CONTRIBUTING.md
# Contributing guidelines ## Pull Request Checklist Before sending your pull requests, make sure you do the following: - Read the [contributing guidelines](CONTRIBUTING.md). - Read the [Code of Conduct](CODE_OF_CONDUCT.md). - Ensure you have signed the [Contributor License Agreement (CLA)](https://cla.developers.google.com/). - Check if your changes are consistent with the
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ci/official/utilities/rename_and_verify_wheels.sh
# 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 [[ "$TFCI_BAZEL_COMMON_ARGS" =~ gpu|cuda ]]; then echo "Checking to make sure tensorflow[and-cuda] is installable..." "$python" -m pip install "$(echo *.whl)[and-cuda]" $TFCI_PYTHON_VERIFY_PIP_INSTALL_ARGS
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) -
tensorflow/c/eager/c_api.cc
} std::vector<int64_t> dimvec(num_dims); for (int i = 0; i < num_dims; ++i) { dimvec[i] = static_cast<int64_t>(dims[i]); } // TODO(apassos) do we need to wrap the deallocator here to make sure to sync // the device? TF_ManagedBuffer* buf = new TF_ManagedBuffer(data, len, deallocator, deallocator_arg, /*owns_memory=*/false);
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Mar 12 20:00:09 GMT 2024 - 43.9K bytes - Viewed (2) -
RELEASE.md
* DType is no longer convertible to an int. Use `dtype.as_datatype_enum` instead of `int(dtype)` to get the same result. * Support both binary and -1/1 label input in v2 hinge and squared hinge losses. * Added `LinearOperator.adjoint` and `LinearOperator.H` (alias). * Expose CriticalSection in core as `tf.CriticalSection`. * Enhanced graphviz output.
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.bazelrc
build:rbe_linux --linkopt=-lrt build:rbe_linux --host_linkopt=-lrt build:rbe_linux --linkopt=-lm build:rbe_linux --host_linkopt=-lm build:rbe_linux_cpu --config=rbe_linux # Linux cpu and cuda builds share the same toolchain now. build:rbe_linux_cpu --host_crosstool_top="@sigbuild-r2.17-clang_config_cuda//crosstool:toolchain" build:rbe_linux_cpu --crosstool_top="@sigbuild-r2.17-clang_config_cuda//crosstool:toolchain"
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