}

	// xattr bar should always appear before others
	indices := []int{
		bytes.Index(buf.Bytes(), []byte("bar=bar")),
		bytes.Index(buf.Bytes(), []byte("baz=baz")),
		bytes.Index(buf.Bytes(), []byte("foo=foo")),
		bytes.Index(buf.Bytes(), []byte("qux=qux")),
	}
	if !slices.IsSorted(indices) {
		t.Fatal("PAX headers are not sorted")
	}
}

func TestUSTARLongName(t *testing.T) {

	// The start index is inclusive and the end index is exclusive.
	type span struct {
		start int
		end   int
	}
	spans := make([]span, 0, 32)

	// Find the field start and end indices.
	// Doing this in a separate pass (rather than slicing the string s
	// and collecting the result substrings right away) is significantly
	// more efficient, possibly due to cache effects.

    const std::vector<int>& tensors = lstm_property.restrict_scale[0];
    if (tensors.size() != 2) {
      op.emitError(
          "Unexpected restricted_scale from operator property."
          " Should only have a pair of indices.");
      return failure();
    }
    return processRestrictScale(op, tensors[0], tensors[1], rewriter);
  }

 private:
  // For LSTM's recurrent input activation and output, they are quantized with

} : (tensor<3x4x2xi32>, tensor<2x3x2xi64>) -> tensor<2x3x2x2xi32>
  func.return %2: tensor<2x3x2x2xi32>
}
// CHECK: %[[OPERAND:.*]] = stablehlo.constant
// CHECK: %[[INDICES:.*]] = stablehlo.constant
// CHECK: %[[XLA_CALL_MODULE:.*]] = "tf.XlaCallModule"(%[[OPERAND]], %[[INDICES]])
// CHECK: return %[[XLA_CALL_MODULE:.*]] : tensor<2x3x2x2xi32>
// CHECK: }

// CHECK-LABEL: private @composite_gather_fn_1

          self, input_tensor: core.Tensor
      ) -> Mapping[str, core.Tensor]:
        k = array_ops.constant(4, dtype=dtypes.int32)
        values, indices = nn_ops.top_k(input_tensor, k, name='TopK')
        adj_values = values + 2
        return {'indices': indices, 'adj_values': adj_values, 'values': values}

      @def_function.function(
          input_signature=[
              tensor_spec.TensorSpec(

      !axis.getSplatValue<llvm::APInt>().isZero()) {
    return {};
  }

  DenseIntElementsAttr indices;
  if (!matchPattern(op.getIndices(), m_Constant(&indices)) ||
      indices.getType().getRank() != 1 || port[1] >= indices.getNumElements()) {
    return {};
  }

  int64_t input_idx = indices.getValues<IntegerAttr>()[port[1]].getInt();
  if (input_idx >= params_ty.getDimSize(0)) return {};

	// we need to remove the entry in lines corresponding to the line
	// numbered <line+1>. The entry in lines corresponding to the line
	// numbered <line+1> is located at index <line>, since indices in lines
	// are 0-based and line numbers are 1-based.
	copy(f.lines[line:], f.lines[line+1:])
	f.lines = f.lines[:len(f.lines)-1]
}

// CHECK-SAME:                         %[[ARG_1:.*]]: tensor<192x256x1xui32>)
// CHECK:            %[[INDICES:.*]] = "tf.Cast"(%arg1) <{Truncate = false}> : (tensor<192x256x1xui32>) -> tensor<192x256x1xi64>
// CHECK:            %[[VAL_0:.*]] = "tf.GatherNd"(%[[ARG_0]], %[[INDICES]]) <{bad_indices_policy = ""}> : {{.*}} -> tensor<192x256xf16>
// CHECK:            return %[[VAL_0]]
// CHECK:         }

<a href="#Representability">representable</a> by a value of type
<code>int</code>; for arrays or constant strings, constant indices must also be in range.
If both indices are constant, they must satisfy <code>low &lt;= high</code>.
If the indices are out of range at run time, a <a href="#Run_time_panics">run-time panic</a> occurs.
</p>

<p>

// been decomposed and function calls have already been inlined. If `functions`
// is empty, the pass is applied to the main function by default. The pass also
// annotates the input arguments for resources with the indices of their
// aliasing output arguments.
std::unique_ptr<OperationPass<ModuleOp>> CreatePromoteResourcesToArgsPass(
    llvm::ArrayRef<std::string> functions = {});