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SECURITY.md
`ModelServer` collates all computation graphs exposed to it (from multiple `SavedModel`) and executes them in parallel on available executors. Running TensorFlow in a multitenant design mixes the risks described above with the inherent ones from multitenant configurations. The primary areas of concern are tenant isolation, resource allocation, model sharing and hardware attacks. ### Tenant isolation
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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/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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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/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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tensorflow/c/experimental/next_pluggable_device/tensor_pjrt_buffer_util.cc
if (av_tensor == nullptr) { TF_ASSIGN_OR_RETURN( *tensor, MakeTensorFromPjRtBuffer(tensor->dtype(), tensor->shape(), std::move(buffer))); } else { av_tensor->SetBuffer(std::move(buffer)); } return absl::OkStatus(); } absl::StatusOr<xla::PjRtCApiClient*> GetPjRtCApiClient( const DeviceType& device_type) {
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.github/workflows/trusted-partners.yml
# ============================================================================== name: Trusted Partner PR on: pull_request_target: permissions: contents: read jobs: assign-partner-tags: runs-on: ubuntu-latest permissions: # Needed to attach tags into the PR issues: write contents: write pull-requests: write if: |
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tensorflow/c/c_api_experimental_test.cc
TEST(CAPI_EXPERIMENTAL, IsStateful) { std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status( TF_NewStatus(), TF_DeleteStatus); int assign = TF_OpIsStateful("AssignAddVariableOp", status.get()); ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get()); EXPECT_EQ(assign, 1); int id = TF_OpIsStateful("Identity", status.get()); ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get()); EXPECT_EQ(id, 0);
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tensorflow/c/eager/c_api_test_util.cc
TFE_Execute(op, &var_handle, &num_retvals, status); if (TF_GetCode(status) != TF_OK) return nullptr; TFE_DeleteOp(op); if (TF_GetCode(status) != TF_OK) return nullptr; CHECK_EQ(1, num_retvals); // Assign 'value' to it. op = TFE_NewOp(ctx, "AssignVariableOp", status); if (TF_GetCode(status) != TF_OK) return nullptr; TFE_OpSetAttrType(op, "dtype", TF_FLOAT); TFE_OpAddInput(op, var_handle, status);
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RELEASE.md
[guide on input distribution](https://www.tensorflow.org/tutorials/distribute/input). * Allow var.assign on MirroredVariables with aggregation=NONE in replica context. Previously this would raise an error. We now allow this because many users and library writers find using `.assign` in replica context to be more convenient, instead of having to use `Strategy.extended.update` which
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