# "pip tests" run a similar suite of tests the "nonpip" tests, but do something
# odd to attempt to validate the quality of the pip package. The wheel is
# installed into a virtual environment, and then that venv is used to run all
# bazel tests with a special flag "--define=no_tensorflow_py_deps=true", which

      // We have to join path for non-local filesystem manually to make sure
      // that this test will run on Windows since `tensorflow::io::JoinPath`
      // behaves differently on Windows. `tmp_dir` should be something like
      // `path/to/tmp/dir/`. After joining path, we will have
      // /path/to/tmp/dir/tf_fs_rng_name/`
      root_dir_ = tensorflow::strings::StrCat(
          "/", tmp_dir_,

// This file extends/implements core graph optimizer base classes in terms of
// the C API defined in grappler.h. A class "CSomething" represents a
// "Something" that can be manipulated via calls in the C interface and a C
// struct called "TP_Something".

#include "tensorflow/c/experimental/grappler/grappler.h"

#include <algorithm>
#include <cstddef>
#include <cstring>
#include <string>

  // appropriate.
  virtual tensorflow::FullTypeDef FullType() const = 0;

  // The default debug string includes a shape, dtype and FullType.
  // Implementations are free to override it with something more informative.
  virtual std::string DebugString() const;

  AbstractTensorHandleKind getKind() const { return kind_; }

 private:
  const AbstractTensorHandleKind kind_;
};

namespace internal {

# "pip tests" run a similar suite of tests the "nonpip" tests, but do something
# odd to attempt to validate the quality of the pip package. The wheel is
# installed into a virtual environment, and then that venv is used to run all
# bazel tests with a special flag "--define=no_tensorflow_py_deps=true", which

TEST_F(CApiFunctionTest, Description) {
  DefineFunction(func_name_, &func_, "Return something");
  tensorflow::FunctionDef fdef;
  ASSERT_TRUE(GetFunctionDef(func_, &fdef));
  ASSERT_EQ(string("Return something"), fdef.signature().description());
}

TEST_F(CApiFunctionTest, Name) {
  DefineFunction("long_func_name", &func_, "Return something",
                 /*append_hash=*/false);
  tensorflow::FunctionDef fdef;

# checks for cross-file issues like bad includes or missing BUILD definitions.
#
# We can't test on the windows toolchains because they're using a legacy
# toolchain format (or something) that specifies the toolchain directly instead
# of as a "repository". They can't be valid on Linux because Linux can't do
# anything with a Windows-only toolchain, and bazel errors if trying to build
# that directory.

# checks for cross-file issues like bad includes or missing BUILD definitions.
#
# We can't test on the windows toolchains because they're using a legacy
# toolchain format (or something) that specifies the toolchain directly instead
# of as a "repository". They can't be valid on Linux because Linux can't do
# anything with a Windows-only toolchain, and bazel errors if trying to build
# that directory.

      # Sharded tests have target names like this:
      # WindowOpsTest.test_tflite_convert0 (<function hann_window at
      #     0x7fc61728dd40>, 10, False, tf.float32)
      # Where 0x... is a thread ID (or something) that is not important for
      # debugging, but breaks this "number of failures" counter because it's
      # different for repetitions of the same test. We use re.sub(r"0x\w+")
      # to remove it.

/// paths (although this has a security risk if two plugins register for the
/// same filesystem and the malicious one loads before the legimitate one -
/// but we consider this to be something that users should care about and
/// manage themselves). In both of these cases, core TensorFlow looks for
/// the `TF_InitPlugin` symbol and calls this function.
///