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SECURITY.md
reachable and exploitable through production-grade, benign models. ### Compilation Compiling models via the recommended entry points described in [XLA](https://www.tensorflow.org/xla) and [JAX](https://jax.readthedocs.io/en/latest/jax-101/02-jitting.html) documentation should be safe, while some of the testing and debugging tools that come with the compiler are not designed to be used with untrusted data and
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tensorflow/c/c_api_test.cc
std::unique_ptr<CSession> expected_csession( new CSession(expected_graph_, s_)); std::vector<TF_Output> grad_outputs_vec; grad_outputs_vec.assign(grad_outputs, grad_outputs + 2); csession->SetOutputs(grad_outputs_vec); csession->Run(s_); ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_); TF_Tensor* out0 = csession->output_tensor(0);
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 03:35:10 GMT 2024 - 96.9K bytes - Viewed (3) -
tensorflow/c/c_api.h
// // Questions left to address: // * Might at some point need a way for callers to provide their own Env. // * Maybe add TF_TensorShape that encapsulates dimension info. // // Design decisions made: // * Backing store for tensor memory has an associated deallocation // function. This deallocation function will point to client code // for tensors populated by the client. So the client can do things
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tensorflow/c/experimental/next_pluggable_device/tensor_pjrt_buffer_util_test.cc
tensorflow::Tensor tensor(allocator.get(), DT_FLOAT, {1}); TF_ASSERT_OK_AND_ASSIGN( auto pjrt_client, xla::GetTfrtCpuClient(/*asynchronous=*/true, /*cpu_device_count=*/1)); std::vector<int32_t> data(1, 0); xla::Shape shape = xla::ShapeUtil::MakeShape(xla::S32, {1}); TF_ASSERT_OK_AND_ASSIGN( auto buffer, pjrt_client->BufferFromHostBuffer(
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ci/official/containers/linux_arm64/setup.packages.sh
# # setup.packages.sh: Given a list of Ubuntu packages, install them and clean up. # Usage: setup.packages.sh <package_list.txt> set -e # Prevent apt install tzinfo from asking our location (assumes UTC) export DEBIAN_FRONTEND=noninteractive apt-get update # Remove commented lines and blank lines apt-get install -y --no-install-recommends $(sed -e '/^\s*#.*$/d' -e '/^\s*$/d' "$1" | sort -u)
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ci/official/containers/linux_arm64/setup.sources.sh
# Usage: setup.python.sh <pyversion> <requirements.txt> # Sets up custom apt sources for our TF images. # Prevent apt install tzinfo from asking our location (assumes UTC) export DEBIAN_FRONTEND=noninteractive # Set up shared custom sources apt-get update apt-get install -y gnupg ca-certificates # Deadsnakes: https://launchpad.net/~deadsnakes/+archive/ubuntu/ppa
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configure.py
ld_version_int = convert_version_to_int(ld_version[4]) # Enable if 'ld' version >= 2.35 if ld_version_int >= 2035000: write_to_bazelrc( 'build --copt="-DEIGEN_ALTIVEC_ENABLE_MMA_DYNAMIC_DISPATCH=1"') with_xla_support = environ_cp.get('TF_ENABLE_XLA', None) if with_xla_support is not None: write_to_bazelrc('build --define=with_xla_support=%s' %
Python - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 18:25:36 GMT 2024 - 53.8K bytes - Viewed (0) -
tensorflow/c/eager/c_api_experimental.h
TFE_Context* ctx, TF_Tensor* t, TF_Status* status); // Create a packed TensorHandle with the given list of TensorHandles. // If `handles` are on the same device, assign the same device to the packed // handle; if `handles` are on different deivces, assign a CompositeDevice to // it. TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_CreatePackedTensorHandle( TFE_Context* ctx, TFE_TensorHandle** handles, int* num_handles,
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CONTRIBUTING.md
* If you work for a company that wants to allow you to contribute your work, then you'll need to sign a [corporate CLA](https://code.google.com/legal/corporate-cla-v1.0.html).
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tensorflow/BUILD
# kernel registration - REGISTER_OP, REGISTER_KERNEL_BUILDER, etc. # # This setting is currently experimental. The 'v2' implementation does _not_ # correspond to a particular, finalized design; rather, it relates to # developing one. # # The current aim of the 'v2' implementation is to allow 'unused' ops and # kernels to be discarded by the linker (to the benefit of binary size). bool_flag(
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