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  1. CONTRIBUTING.md

    ```
    
    TensorFlow kernels and TensorFlow's dependencies are still not built with
    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
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  2. RELEASE.md

            on Ampere based GPUs.TensorFloat-32, or TF32 for short, is a math mode
            for NVIDIA Ampere based GPUs which causes certain float32 ops, such as
            matrix multiplications and convolutions, to run much faster on Ampere
            GPUs but with reduced precision. This reduced precision has not been
            found to effect convergence quality of deep learning models in practice.
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  3. tensorflow/c/c_api.cc

            return;
          }
          // We have a convoluted scheme here: Using the C++ graph construction API
          // to add potentially many nodes to the graph without running the checks
          // (such as uniqueness of the names of nodes) we run with other functions
          // that add a node to the graph (like TF_FinishOperation).
          if (!g->name_map.insert(std::make_pair(n->name(), n)).second) {
    C++
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  4. tensorflow/BUILD

    # New rules should be added above this target.
    # -------------------------------------------
    
    # TensorFlow uses several libraries that may also be used by applications
    # linking against the C and C++ APIs (such as libjpeg).  When we create
    # the shared library, only export the core TF API functions to avoid
    # causing library conflicts (e.g., those reported in github issue 1924).
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  5. tensorflow/c/eager/tape.h

        std::unordered_map<int64_t, OpTapeEntry<BackwardFunction, TapeTensor>>;
    
    // Operations the tape needs to perform on tensors to do backpropagation. Named
    // "vspace" because a subset of these are related to a vector space, such as
    // adding gradients, getting zeroes, etc. Currently cannot be implemented
    // without using tensorflow python code, hence left unspecified here.
    //
    // Gradient is the type returned by gradient functions. In Python TF it's either
    C
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  6. .bazelrc

    # END TF TEST SUITE OPTIONS
    
    # START CROSS-COMPILE CONFIGS
    # Set execution platform to Linux x86
    # Note: Lot of the "host_" flags such as "host_cpu" and "host_crosstool_top"
    # flags seem to be actually used to specify the execution platform details. It
    # seems it is this way because these flags are old and predate the distinction
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  7. tensorflow/c/c_api_function.cc

            body_nodes->push_back(node);
          } else {
            // This node is referenced in inputs. Currently, we place an
            // artificial restriction and require that when num_opers=-1, such
            // nodes must have a single output.
            if (node->num_outputs() != 1) {
              return InvalidArgument(
                  "When `num_opers` is set to -1, nodes referenced in `inputs` "
    C++
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