*   Adds support for a new "distributed_epoch" processing mode. This processing
    mode distributes a dataset across all tf.data workers, instead of having
    each worker process the full dataset. See
    [the tf.data service docs](https://www.tensorflow.org/api_docs/python/tf/data/experimental/service#understand_processing_mode)
    to learn more.
*   Adds optional `exclude_cols` parameter to CsvDataset. This parameter is the

#include "xla/xla_data.pb.h"
#include "tensorflow/core/framework/graph.pb.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/io/path.h"
#include "tensorflow/core/lib/strings/proto_serialization.h"
#include "tensorflow/core/platform/env.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/regexp.h"
#include "tensorflow/core/platform/types.h"

namespace tensorflow {

  }) : () -> tensor<*xf32>
  func.return %result : tensor<*xf32>
}

// -----

// Check that a fetch with not enough data-operands but more control inputs triggers the verifier.
func.func @invalid_fetch(%arg0: tensor<*xf32>, %ctl: !tf_executor.control) -> tensor<*xf32> {
  %result = "tf_executor.graph"() ({
    "tf_executor.fetch"(%ctl) : (!tf_executor.control) -> ()

      }
    }

    // If the reshape rank is less than the number of non-unit dimensions
    // of the broadcast, then the reshape collapses non-unit dimensions.
    // TODO(rahulsp) : Handle this case with more careful checks.
    if (reshape_shape.size() < non_unit_dims.size()) return failure();

    SmallVector<int64_t, 4> old_reshape_non_unit_dims;
    SmallVector<int64_t, 4> new_reshape_dims;
    int new_reshape_dim_idx = 0;

    llvm::cl::location(use_external_constant), llvm::cl::init(false));

// TODO(b/147111261): After the importer supports generic custom ops, we should
// change the flag to a more lightwise flag, e.g.
// "import_custom_ops_as_side_effect_free_ops", and let the MLIR DCE to prune
// the operations.
// NOLINTNEXTLINE
static opt<bool, true> experimental_prune_unreachable_nodes_unconditionally_flg(

// will fail. If `prefix` is nullptr, the default prefixing behaviour takes
// place, see TF_AddGradients for more details.
//
// WARNING: This function does not yet support all the gradients that python
// supports. See
// https://www.tensorflow.org/code/tensorflow/cc/gradients/README.md
// for instructions on how to add C++ more gradients.
TF_CAPI_EXPORT void TF_AddGradientsWithPrefix(TF_Graph* g, const char* prefix,

        }
        if (any_user_is_assign) {
          VLOG(2) << "TPUMergeVariablesWithExecutePass: Skipping output "
                  << execute_output.index()
                  << " that has more than one user (including an assign):";
          for (auto result_user : result.getUsers()) {
            VLOG(2) << "  used by: " << debugString(*result_user);
          }
        }
      }
      continue;

    `[b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f]` format.

    This pass is useful to convert models that conventionally use the NCHW
    format to target hardwares that are more NHWC-friendly.
  }];
  let dependentDialects = ["mlir::stablehlo::StablehloDialect"];
}

def DeferActivationTransposePass : Pass<"stablehlo-defer-activation-transpose", "mlir::func::FuncOp"> {

#include "xla/mlir/framework/transforms/passes.h"
#include "xla/mlir_hlo/mhlo/IR/register.h"
#include "xla/mlir_hlo/mhlo/transforms/passes.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/statusor.h"

// Tool which lowers TensorFlow Graphs to StableHLO graphs.
//
// This tool is used by the ODML Programmability effort to consume input TF

#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/op_requires.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/core/refcount.h"
#include "tensorflow/core/lib/core/status.h"
#include "tensorflow/core/platform/statusor.h"