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tensorflow/c/BUILD
":checkpoint_reader", ":tf_buffer", ":tf_buffer_internal", "//tensorflow/c/eager:c_api", "//tensorflow/c/eager:c_api_internal", "//tensorflow/c/eager:tfe_context_internal", "//tensorflow/c/eager:tfe_op_internal", "//tensorflow/c/eager:tfe_tensorhandle_internal", "//tensorflow/compiler/jit:flags", "//tensorflow/compiler/jit:get_compiler_ir",
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CONTRIBUTING.md
debugging information with `--config=dbg`, as issues occur on Linux if there is too much debug info (see [this GitHub issue](https://github.com/tensorflow/tensorflow/issues/48919) for context). If you want to debug a kernel, you can compile specific files with `-g` using the `--per_file_copt` bazel option. For example, if you want to debug the Identity op, which are in files starting with `identity_op`, you can run
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tensorflow/c/eager/gradients.cc
void MarkAsResult(AbstractTensorHandle* gradient) const override; void DeleteGradient(AbstractTensorHandle* gradient) const override; private: // The context where the aggregation op `Add` is to be created. AbstractContext* ctx_; }; // Returns the number of elements in the gradient tensor. int64_t TapeVSpace::NumElements(AbstractTensorHandle* tensor) const {
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.github/workflows/sigbuild-docker-presubmit.yml
- '!tensorflow/tools/tf_sig_build_dockerfiles/README.md' permissions: contents: read jobs: docker: if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks runs-on: ubuntu-latest strategy: matrix: python-version: [python3.9, python3.10, python3.11, python3.12] permissions: contents: read pull-requests: write steps:
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tensorflow/c/eager/c_api.cc
/*jit_compile_rewrite=*/opts->jit_compile_rewrite); #if !defined(IS_MOBILE_PLATFORM) eager_context->SetDistributedManager( std::make_unique<tensorflow::EagerContextDistributedManager>( eager_context)); #endif // !IS_MOBILE_PLATFORM return tensorflow::wrap(eager_context); } void TFE_DeleteContext(TFE_Context* ctx) { if (ctx == nullptr) { return; }
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tensorflow/c/eager/c_api_test_util.cc
#include "tensorflow/core/protobuf/rewriter_config.pb.h" #include "tensorflow/core/util/port.h" using tensorflow::string; using tensorflow::tstring; TFE_TensorHandle* TestScalarTensorHandle(TFE_Context* ctx, float value) { float data[] = {value}; TF_Status* status = TF_NewStatus(); TF_Tensor* t = TFE_AllocateHostTensor(ctx, TF_FLOAT, nullptr, 0, status); memcpy(TF_TensorData(t), &data[0], TF_TensorByteSize(t));
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tensorflow/c/eager/c_api_unified_experimental_internal.h
} }; // An abstract operation describes an operation by its type, name, and // attributes. It can be "executed" by the context with some input tensors. // It is allowed to reusing the same abstract operation for multiple execution // on a given context, with the same or different input tensors. class TracingOperation : public AbstractOperation { protected: explicit TracingOperation(AbstractOperationKind kind)
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tensorflow/c/c_api_experimental_test.cc
protected: ShapeInferenceTest() : status_(TF_NewStatus()), tfe_context_options_(TFE_NewContextOptions()) { tfe_context_ = TFE_NewContext(tfe_context_options_, status_); CHECK_EQ(TF_OK, TF_GetCode(status_)) << TF_Message(status_); } ~ShapeInferenceTest() override { TFE_DeleteContextOptions(tfe_context_options_); TFE_DeleteContext(tfe_context_); TF_DeleteStatus(status_); }
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tensorflow/c/eager/BUILD
"//tensorflow/core:protos_all_cc", ], ) cc_library( name = "immediate_execution_context", hdrs = ["immediate_execution_context.h"], visibility = [ "//tensorflow:internal", ], deps = [ ":abstract_context", ":immediate_execution_distributed_manager", ":immediate_execution_operation", ":immediate_execution_tensor_handle",
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RELEASE.md
* It is available for immediate use. * See the `TF_RUN_EAGER_OP_AS_FUNCTION` environment variable in [eager context](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/eager/context.py). * Eager performance should be similar with this feature enabled. * A roughly 5us per-op overhead may be observed when running many
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