}
  }

  const DimensionVector& batch_dimensions() const { return batch_dimensions_; }
  const DimensionVector& contracting_dimensions() const {
    return contracting_dimensions_;
  }
  // Out dimensions are any dimensions that are neither batch nor contracting
  // dimensions, hence will be propagated to output shape.
  const DimensionVector& out_dimensions() const { return out_dimensions_; }

      recurrent_to_output_weights.hasStaticShape()) {
    const int n_input = input_type.getDimSize(input_type.getRank() - 1);
    const int n_cell = input_to_output_weights.getDimSize(0);
    const int n_output = recurrent_to_output_weights.getDimSize(1);
    const int output_state_size = activation_state.getNumElements();
    const int n_batch = input_type.getRank() == 2 ? input_type.getDimSize(0)

}

bool CanFuseConvOrDepthwiseConvShapes(const ArrayRef<int64_t> filter_shape,
                                      const ArrayRef<int64_t> elements_shape,
                                      bool is_depthwise) {
  // Val tensor must be a scalar or of a shape [1, ... , 1, elements_depth].
  const int elements_rank = elements_shape.size();
  for (int i = 0; i < elements_rank - 1; ++i) {

Overview Package Class Use Tree Deprecated Index Help PREV CLASS NEXT CLASS FRAMES NO FRAMES All Classes SUMMARY: NESTED | FIELD | CONSTR | METHOD DETAIL: FIELD | CONSTR | METHOD org/hamcrest/BaseMatcher.html Overview Package Class Use Tree Deprecated Index Help PREV CLASS NEXT CLASS FRAMES NO FRAMES All Classes SUMMARY: NESTED | FIELD | CONSTR | METHOD DETAIL: FIELD | CONSTR | METHOD org.hamcrest Class BaseMatcher<T> java.lang.Object org.hamcrest.BaseMatcher<T> All Implemented Interfaces: Matcher<T>,...

// `high` if `high` is less than `val`; otherwise returns `val`.
template <class T>
constexpr const T &Clamp(const T &val, const T &low, const T &high) {
  assert(!(high < low));
  return (val < low) ? low : (high < val) ? high : val;
}

// Checks if the `index` bit of `val` is set.
template <class T>
constexpr bool IsSet(const T &val, unsigned index) {
  return (val & (1 << index)) != 0;
}

  %feature_group_count = "tf.Const"() {value = dense<1> : tensor<2xi32>} : () -> tensor<2xi32>
  %lhs_dilation = "tf.Const"() {value = dense<[4, 1, 1]> : tensor<3xi32>} : () -> tensor<3xi32>
  %rhs_dilation = "tf.Const"() {value = dense<1> : tensor<3xi32>} : () -> tensor<3xi32>
  %padding = "tf.Const"() {value = dense<0> : tensor<3x2xi32>} : () -> tensor<3x2xi32>

    llvm::SmallVectorImpl<ShapedTypeComponents>& inferredReturnShapes) {
  const int64_t num_spatial_dims = std::is_same<OpT, Conv2DOpAdaptor>() ? 2 : 3;
  const int64_t num_dims = 2 + num_spatial_dims;
  const Value input = op.getInput();
  const Value filter = op.getFilter();
  const TensorType input_ty = mlir::cast<TensorType>(input.getType());
  const TensorType filter_ty = mlir::cast<TensorType>(filter.getType());

}

func nameToKey(name *pkix.Name) string {
	return strings.Join(name.Country, ",") + "/" + strings.Join(name.Organization, ",") + "/" + strings.Join(name.OrganizationalUnit, ",") + "/" + name.CommonName
}

const gtsIntermediate = `-----BEGIN CERTIFICATE-----
MIIFljCCA36gAwIBAgINAgO8U1lrNMcY9QFQZjANBgkqhkiG9w0BAQsFADBHMQsw
CQYDVQQGEwJVUzEiMCAGA1UEChMZR29vZ2xlIFRydXN0IFNlcnZpY2VzIExMQzEU

	EI_PAD        = 9  /* Start of padding (per SVR4 ABI). */
	EI_NIDENT     = 16 /* Size of e_ident array. */
)

// Initial magic number for ELF files.
const ELFMAG = "\177ELF"

// Version is found in Header.Ident[EI_VERSION] and Header.Version.
type Version byte

const (
	EV_NONE    Version = 0
	EV_CURRENT Version = 1
)

var versionStrings = []intName{
	{0, "EV_NONE"},
	{1, "EV_CURRENT"},
}

  %1 = "tf.Const"() {device = "", dtype = f32, value = dense<0.000000e+00>: tensor<16x28xf32>} : () -> tensor<16x28xf32>
  %2 = "tf.Const"() {device = "", dtype = f32, value = dense<0.000000e+00>: tensor<16x16xf32>} : () -> tensor<16x16xf32>
  %3 = "tf.Const"() {device = "", dtype = f32, value = dense<0.000000e+00>: tensor<16xf32>} : () -> tensor<16xf32>