while (true) {
      if (auto block_arg = llvm::dyn_cast<BlockArgument>(val)) {
        return block_arg.getArgNumber();
      }
      if (auto identity_op =
              llvm::dyn_cast<TF::IdentityOp>(val.getDefiningOp())) {
        val = identity_op.getOperand();
      } else {
        return -1;
      }
    }
  };

  for (auto call_op :

# https://github.com/tensorflow/tensorflow/issues/48919.
# Users can still include debug info for a specific kernel, e.g. with:
#     --config=dbg --per_file_copt=+tensorflow/core/kernels/identity_op.*@-g
# Since this .bazelrc file is synced between the tensorflow/tensorflow repo and
# the openxla/xla repo, also include debug info for files under xla/.
build:dbg --per_file_copt=+.*,-tensorflow.*,-xla.*@-g0

  TFE_Op* identityOp = TFE_NewOp(ctx, "IdentityN", status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  // Try to retrieve lengths before building the attributes (should fail)
  EXPECT_EQ(-1, TFE_OpGetInputLength(identityOp, "input", status));
  CHECK_NE(TF_OK, TF_GetCode(status)) << TF_Message(status);
  EXPECT_EQ(-1, TFE_OpGetOutputLength(identityOp, "output", status));

  }
};

struct ConvertIdentity : public OpConversionPattern<TF::IdentityOp> {
  using OpConversionPattern::OpConversionPattern;

  LogicalResult matchAndRewrite(
      TF::IdentityOp op, OpAdaptor adaptor,
      ConversionPatternRewriter &rewriter) const override {
    Value input = adaptor.getOperands()[0];
    rewriter.replaceOpWithNewOp<TF::IdentityOp>(
        op, input.getType(), adaptor.getOperands(), op->getAttrs());

// of Identity op is only used by TF ops.
struct RemoveIdentity : public OpRewritePattern<TF::IdentityOp> {
  using OpRewritePattern<TF::IdentityOp>::OpRewritePattern;

  LogicalResult matchAndRewrite(TF::IdentityOp identity,
                                PatternRewriter &rewriter) const override {
    // Replace the op with the input if input and result have the same type.

      tf_executor.yield %identity : tensor<i32>
    }
    %island_1_result, %island_1_control = tf_executor.island {
      %identity_n:2 = "tf.IdentityN"(%arg1, %island_0_result) : (tensor<i32>, tensor<i32>) -> (tensor<i32>, tensor<i32>)
      tf_executor.yield %identity_n#0
    }
    tf_executor.fetch %island_0_result, %island_1_result : tensor<i32>, tensor<i32>
  }