%dense_value =
    "tf.ParseExampleV2"(%serialized, %names, %sparse_keys, %dense_keys, %ragged_keys, %dense_default)
    // CHECK: Tdense = [i64]
    // CHECK-SAME: dense_shapes = [#corert.shape<>]
    { device = "/device:CPU:0", num_sparse = 0 : i64, dense_shapes = [#tf_type.shape<>], resultSegmentSizes = array<i32: 0, 0, 0, 1, 0, 0>}

func.func @no_operand_replicate() {
  tf_device.replicate {n = 2 : i32} {
    %0 = "tf.Const"() { value = dense<0> : tensor<i64> } : () -> tensor<i64>
    %1 = "tf.Const"() { value = dense<1> : tensor<i64> } : () -> tensor<i64>
    tf_device.return %0, %1 : tensor<i64>, tensor<i64>
  }
  func.return
  // CHECK:      tf_device.replicate
  // CHECK-SAME: n = 2
  // CHECK:   tf_device.return
}

// -----

    %0 = stablehlo.convolution(%arg0, %arg1) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {pad = [[0, 1], [1, 1]]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x3x4x3xf32>, tensor<2x3x3x2xf32>) -> tensor<1x3x4x2xf32>
    return %0 : tensor<1x3x4x2xf32>
  }
}

// CHECK-LABEL: quantize_conv_fn
// CHECK-SAME: %[[ARG0:.+]]: tensor<1x3x4x3xf32>

include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.td"
include "mhlo/IR/hlo_ops.td"

def SignedIntTensor : TensorOf<[I1, I8, I16, I32, I64]>;
def UnsignedIntTensor : TensorOf<[UI8, UI16, UI32, UI64]>;

// IEEE compliant floating point tensors.
def IEEEFloatTensor : TensorOf<[F16, F32, F64]>;

//===----------------------------------------------------------------------===//
// BatchNorm op patterns.

     %3 = "tf.ReadVariableOp"(%arg3) {device = ""} : (tensor<*x!tf_type.resource<tensor<8xf32>>>) -> tensor<8xf32>
     "tf.LoadTPUEmbeddingAdagradParameters"(%2, %3) {config = "", num_shards = 1 : i64, shard_id = 0 : i64, table_id = -1 : i64, table_name = "table2"} : (tensor<8xf32>, tensor<8xf32>) -> ()

    %3 = "tf.XlaCallModule"(%2) <{Sout = [#tf_type.shape<6x5>], dim_args_spec = [], disabled_checks = [], has_token_input_output = false, module = "", platforms = ["CPU"], version = 9 : i64}> {_entry_function = @main_1, _stablehlo_module_attrs = {}, device = ""} : (tensor<3x10xf32>)...

          "Failed at tf.StridedSlice op\nsee current operation: %2 = "
          "\"tf.StridedSlice\"(%arg0, %1, %1, %0) <{begin_mask = 11 : "
          "i64, ellipsis_mask = 0 : i64, end_mask = 11 : i64, new_axis_mask = "
          "4 : i64, shrink_axis_mask = 0 : i64}> {device = \"\"} : "
          "(tensor<*xf32>, tensor<4xi32>, tensor<4xi32>, tensor<4xi32>) "
          "-> tensor<*xf32>\nError code: ERROR_NEEDS_FLEX_OPS",

    %0:3 = "tf.Unpack"(%arg0) {axis = 0 : i64} : (tensor<3xi64>) -> (tensor<i64>, tensor<i64>, tensor<i64>)
    return
  }
})";

  %0 = "tf.FakeQuantWithMinMaxArgs"(%arg1) {device = "", max = 2.000000e+00 : f32, min = -1.000000e+00 : f32, narrow_range = false, num_bits = 8 : i64} : (tensor<2x3x3x2xf32>) -> tensor<*xf32>
  %1 = "tf.FakeQuantWithMinMaxArgs"(%arg0) {device = "", max = 2.000000e-01 : f32, min = -1.000000e-01 : f32, narrow_range = false, num_bits = 8 : i64} : (tensor<1x3x4x3xf32>) -> tensor<*xf32>

        "bin/x86",
        "Bin"
    };
    private static final String[] BINPATHS_AMD64 = {
        "bin/x64"
    };
    private static final String[] BINPATHS_IA64 = {
        "bin/IA64"
    };
    private static final String[] BINPATHS_ARM = {
        "bin/arm"
    };
    private static final String LIBPATH_SDK8 = "Lib/win8/um/";
    private static final String LIBPATH_SDK81 = "Lib/winv6.3/um/";