## Scope

This Code of Conduct applies to all content on tensorflow.org, TensorFlow’s GitHub organization, or any other official TensorFlow web presence allowing for community interactions, as well as at all official TensorFlow events, whether offline or online.

#### Debug builds

When [building Tensorflow](https://www.tensorflow.org/install/source), passing
`--config=dbg` to Bazel will build with debugging information and without
optimizations, allowing you to use GDB or other debuggers to debug C++ code. For
example, you can build the pip package with debugging information by running:

```bash
bazel build --config=dbg //tensorflow/tools/pip_package:build_pip_package

    TFE_Context* ctx, const char* serialized_function_def, size_t size,
    TF_Status* status);

// Adds a function (created from TF_GraphToFunction or
// TF_FunctionImportFunctionDef) to the context, allowing it to be executed with
// TFE_Execute by creating an op with the same name as the function.
TF_CAPI_EXPORT extern void TFE_ContextAddFunction(TFE_Context* ctx,

# limitations under the License.
# ==============================================================================
# Run any CI script and env configuration to bisect a failing target in some
# build configuration. You must set the following variables to control this
# script:
#
#   TF_BISECT_GOOD: Last known good commit (e.g. commit from the last passing job)
#   TF_BISECT_BAD: First bad commit (e.g. commit from the first failing job)

Example: `/tmp/tensorflow-2.14.0-cp311-cp311-linux_x86_64.whl`

`python_version`: The target Python version, replacing `.` with `_`.
Example: For Python 3.11, use `3_11`

The script performs the following steps:

1. Navigates to the `../requirements_updater` directory.
2. Creates a `requirements_wheel_test.in` file and specifies the path
to the actual TensorFlow wheel.

                                   absl::Span<AbstractTensorHandle*>)>;

// Runs `model` maybe wrapped in a function call op. This can be thought as
// being equivalent to the following python code.
//
// if use_function:
//   outputs = tf.function(model)(inputs)
// else:
//   outputs = model(inputs)
Status RunModel(Model model, AbstractContext* ctx,

    const char* msg = "Matrix size-incompatible: In[0]: [2,2], In[1]: [3,2]";
    EXPECT_TRUE(strstr(TF_Message(status), msg) != nullptr)
        << TF_Message(status);
    // Since error is not cleared, the following copy with correct device will
    // still fail.
    TF_SetStatus(status, TF_OK, "");
    TFE_DeleteTensorHandle(retvals[0]);
    TFE_Executor* executor = TFE_ContextGetExecutorForThread(ctx);

    outputs[0] = TF_Output{nograd, 0};
    EXPECT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  }

  void BuildSuccessGraph(TF_Output* inputs, TF_Output* outputs) {
    // Construct the following graph:
    //            |
    //           z|
    //            |
    //          MatMul
    //         /       \
    //        ^         ^
    //        |         |
    //       x|        y|

#if defined(PLATFORM_WINDOWS)
// Make mkdir resolve to _mkdir to create the test temporary directory.
#include <direct.h>
#define mkdir(name, mode) _mkdir(name)

// Windows defines the following macros to convert foo to fooA or fooW,
// depending on the type of the string argument. We don't use these macros, so
// undefine them here.
#undef CopyFile
#undef DeleteFile
#undef TranslateName

        // broadcast, i.e. set as the input to each parallel operation. This
        // allows code like "tf.constant(1.)" or "tf.reduce_sum(..., axis=1)"
        // (where the value starts on the host), without allowing other implicit
        // copies/broadcasts. Other implicit copies may be supported eventually,
        // but need special handling for gradients (gradient of copy-on is not