}]>;
}

def TFL_ArgMinOp : TFL_Op<"arg_min", [
    QuantizableResult,
    Pure]> {
  let summary = "ArgMin operator";

  let description = [{
    Returns the index with the smallest value across dimensions of a tensor.
      a = [1, 10, 26.9, 2.8, 166.32, 62.3]
      b = tf.math.argmin(input = a)
      c = tf.keras.backend.eval(b)
  }];

  let arguments = (

	"fixedbugs/issue10700.go", // types2 should give hint about ptr to interface
	"fixedbugs/issue18331.go", // missing error about misuse of //go:noescape (irgen needs code from noder)
	"fixedbugs/issue18419.go", // types2 reports no field or method member, but should say unexported
	"fixedbugs/issue20233.go", // types2 reports two instead of one error (preference: 1.17 compiler)

//                 must either have the same length as `outputs`
//                 (i.e. `noutputs`) or be null. In the former case,
//                 the names should match the regular expression for ArgDef
//                 names - "[a-z][a-z0-9_]*". In the latter case,
//                 names for outputs will be generated automatically.
//  opts - various options for the function, e.g. XLA's inlining control.

	{0x0ff00f7f, 0x0e000a10, 4, VMOV_EQ, 0x1c04, instArgs{arg_Sn, arg_R_12}},                                      // VMOV<c> <Sn>, <Rt> cond:4|1|1|1|0|0|0|0|0|Vn:4|Rt:4|1|0|1|0|N|0|0|1|0|0|0|0
	{0x0ff00f7f, 0x0e100a10, 4, VMOV_EQ, 0x1c04, instArgs{arg_R_12, arg_Sn}},                                      // VMOV<c> <Rt>, <Sn> cond:4|1|1|1|0|0|0|0|1|Vn:4|Rt:4|1|0|1|0|N|0|0|1|0|0|0|0

      For anything tougher than suet;
    Yet you finished the goose, with the bones and the beak--
      Pray how did you manage to do it?'

    `In my youth,' said his father, `I took to the law,
      And argued each case with my wife;
    And the muscular strength, which it gave to my jaw,
      Has lasted the rest of my life.'

    `You are old,' said the youth, `one would hardly suppose

  // Sets operand_segment_sizes or result_segment_sizes attribute to the op.
  const auto set_segment_sizes_attr =
      [&](const NameRangeMap& arg_ranges,
          const protobuf::RepeatedPtrField<OpDef::ArgDef>& args,
          llvm::StringRef attr_name) {
        std::vector<int32_t> values;
        values.reserve(args.size());
        for (const auto& arg : args) {
          auto range = arg_ranges.at(arg.name());

        for more details about DTensor.

*   `tf.lite`:

    *   Added TFLite builtin op support for the following TF ops:
        *   `tf.math.argmin`/`tf.math.argmax` for input data type `tf.bool` on
            CPU.
        *   `tf.nn.gelu` op for output data type `tf.float32` and quantization
            on CPU.

const argsEl=root.querySelector('#args');if(Object.keys(timeSlice.args).length>0){const argsView=document.createElement('tr-ui-a-generic-object-view');argsView.object=timeSlice.args;argsEl.parentElement.style.display='';Polymer.dom(argsEl).textContent='';Polymer.dom(argsEl).appendChild(argsView);}else{argsEl.parentElement.style.display='none';}}});tr.ui.analysis.AnalysisSubView.register('tr-ui-a-single-th...

}

def TF_ArgMinOp : TF_Op<"ArgMin", [Pure]> {
  let summary = [{
Returns the index with the smallest value across dimensions of a tensor.
  }];

  let description = [{
Note that in case of ties the identity of the return value is not guaranteed.

Usage:
  ```python
  import tensorflow as tf
  a = [1, 10, 26.9, 2.8, 166.32, 62.3]
  b = tf.math.argmin(input = a)
  c = tf.keras.backend.eval(b)