{
		"define without value",
		"#define A",
		"",
	},
	{
		"macro without arguments",
		"#define A() 1234\n" + "A()\n",
		"1234.\n",
	},
	{
		"macro with just parens as body",
		"#define A () \n" + "A\n",
		"(.).\n",
	},
	{
		"macro with parens but no arguments",
		"#define A (x) \n" + "A\n",
		"(.x.).\n",
	},
	{
		"macro with arguments",
		"#define A(x, y, z) x+z+y\n" + "A(1, 2, 3)\n",

#ifndef TENSORFLOW_C_C_API_MACROS_INTERNAL_H_
#define TENSORFLOW_C_C_API_MACROS_INTERNAL_H_

#ifdef __cplusplus
#include "tensorflow/core/platform/status.h"

// Macro to verify that the field `struct_size` of STRUCT_OBJ is initialized.
// `struct_size` is used for struct member compatibility check between core TF
// and plug-ins with the same C API minor version. More info here:

}

func (s *Slice) Line() int {
	return s.line
}

func (s *Slice) Col() int {
	// TODO: Col is only called when defining a macro and all it cares about is increasing
	// position to discover whether there is a blank before the parenthesis.
	// We only get here if defining a macro inside a macro.
	// This imperfect implementation means we cannot tell the difference between
	//	#define A #define B(x) x
	// and

KIND, either express or implied.  See the License for the
specific language governing permissions and limitations
under the License.
-->

]]#

#macro(yesno $val)
  #if ($val) Yes #else No #end
#end

#macro(value $val)
#if ($val) `$val` #else - #end
#end

| No | Key | Type | Description | Default Value | Since | Source |
| --- | --- | --- | --- | --- | --- | --- |
#foreach($key in $keys)

#endif  // _WIN32
#endif  // SWIG

// TF_Bool is the C API typedef for unsigned char, while TF_BOOL is
// the datatype for boolean tensors.
#ifndef TF_Bool
#define TF_Bool unsigned char
#endif  // TF_Bool

// Macro used to calculate struct size for maintaining ABI stability across
// different struct implementations.
#ifndef TF_OFFSET_OF_END
#define TF_OFFSET_OF_END(TYPE, MEMBER) \
  (offsetof(TYPE, MEMBER) + sizeof(((TYPE *)0)->MEMBER))

*.htm           text diff=html
*.html          text diff=html
*.java          text diff=java
*.sh            text eol=lf


# These files are binary and should be left untouched
# (binary is a macro for -text -diff)
*.a             binary
*.lib           binary
*.icns          binary
*.png           binary
*.jpg           binary
*.jpeg          binary
*.gif           binary
*.ico           binary

    }

    void sleepMicros(String caption, long micros) {
      instant += MICROSECONDS.toNanos(micros);
      events.add(caption + String.format(Locale.ROOT, "%3.2f", (micros / 1000000.0)));
    }

    @Override
    protected void sleepMicrosUninterruptibly(long micros) {
      sleepMicros("R", micros);
    }

    String readEventsAndClear() {
      try {

    }

    void sleepMicros(String caption, long micros) {
      instant += MICROSECONDS.toNanos(micros);
      events.add(caption + String.format(Locale.ROOT, "%3.2f", (micros / 1000000.0)));
    }

    @Override
    protected void sleepMicrosUninterruptibly(long micros) {
      sleepMicros("R", micros);
    }

    String readEventsAndClear() {
      try {

        micros = (long) (permitsAboveThresholdToTake * length / 2.0);
        permitsToTake -= permitsAboveThresholdToTake;
      }
      // measuring the integral on the left part of the function (the horizontal line)
      micros += (long) (stableIntervalMicros * permitsToTake);
      return micros;
    }

    private double permitsToTime(double permits) {

# The cascade of load() statements and tf_workspace?() calls works around the
# restriction that load() statements need to be at the top of .bzl files.
# E.g. we can not retrieve a new repository with http_archive and then load()
# a macro from that repository in the same file.
load("@//tensorflow:workspace3.bzl", "tf_workspace3")

tf_workspace3()

# Initialize hermetic Python
load("@local_tsl//third_party/py:python_init_rules.bzl", "python_init_rules")