let description = [{
This operation returns the coordinates of true elements in `condition`. The
coordinates are returned in a 2-D tensor where the first dimension (rows)
represents the number of true elements, and the second dimension (columns)
represents the coordinates of the true elements. Keep in mind, the shape of
the output tensor can vary depending on how many true values there are in

	</li>
	<li>An element list that does not contain any keys must
	    list an element for each struct field in the
	    order in which the fields are declared.
	</li>
	<li>If any element has a key, every element must have a key.
	</li>
	<li>An element list that contains keys does not need to
	    have an element for each struct field. Omitted fields

static FailureOr<SmallVector<int32_t>> parseI32Array(AsmParser& parser) {
  SmallVector<int32_t> elements;
  auto elementParser = [&]() {
    int32_t element;
    if (failed(parser.parseInteger(element))) return failure();
    elements.push_back(element);
    return success();
  };
  if (parser.parseCommaSeparatedList(AsmParser::Delimiter::Square,

          <name>licenses</name>
          <version>3.0.0+</version>
          <description>
            <![CDATA[
            This element describes all the licenses for this project.
            Each license is described by a {@code license} element, which
            is then described by additional elements.
            Projects should only list the license(s) that applies to the project
            and not the licenses that apply to dependencies.

ElementsAttr ExpandTo4DForConvImpl(Attribute a, bool is_depthwise) {
  auto elements = mlir::dyn_cast<DenseElementsAttr>(a);
  auto shape = elements.getType().getShape();
  if (!shape.empty()) {
    // Checks that elements are essentially 1d.
    assert(elements.getNumElements() == shape.back());
  }
  std::vector<int64_t> shape_data = {1, 1, 1, 1};
  const int vector_length = elements.getNumElements();
  if (is_depthwise)

  return nullptr;
}

// Follow the use chain of TensorList and return true iff all elements written
// to TensorList have same static shape. If all elements have same shape, assign
// it to `potential_element_type`.
//
// This can handle multiple mutations of a TensorList object and would return
// true if across all mutations the elements written have the same shape.
bool CanInferTensorListElementType(Value tensorlist,

            "elements");

      expected_size = length;
    } else if (length != expected_size) {
      return op.emitOpError() << "requires begin, end and strides to have the "
                                 "same number of elements";
    }
  }

  // If strides are constants, verify that none of the element is zero.
  DenseIntElementsAttr strides;

	if t1 != t2 {
		panic(what + ": " + t1.String() + " != " + t2.String())
	}
}

// arrayAt returns the i-th element of p,
// an array whose elements are eltSize bytes wide.
// The array pointed at by p must have at least i+1 elements:
// it is invalid (but impossible to check here) to pass i >= len,
// because then the result will point outside the array.

/// elements of any allowed type: float or complex), rewrite the op to the
/// divisor if all the elements of the divisor are zero and to tf.Div if all the
/// elements of the divisor are non-zero.

/// Similarly, if the op is tf.MulNoNan and the multiplier is a constant tensor
/// (with all the elements of any allowed type: float or complex), rewrite the

		add element ip kube-proxy cluster-ips { 172.30.0.45 }
		add element ip kube-proxy service-ips { 172.30.0.45 . tcp . 80 : goto service-HVFWP5L3-ns5/svc5/tcp/p80 }
		add element ip kube-proxy service-ips { 5.6.7.8 . tcp . 80 : goto external-HVFWP5L3-ns5/svc5/tcp/p80 }
		add element ip kube-proxy service-nodeports { tcp . 3002 : goto external-HVFWP5L3-ns5/svc5/tcp/p80 }