#include "tensorflow/core/platform/strcat.h"
#include "tensorflow/core/util/debug_data_dumper.h"

using tensorflow::errors::InvalidArgument;

namespace tensorflow {
namespace {

Status ValidateNonRefOutput(const Node* node, int idx) {
  const DataType& dt = node->output_type(idx);
  return IsRefType(dt)
             ? InvalidArgument("Output ", idx, " of node '", node->name(),
                               "' has a reference type ", DataTypeString(dt))

		Code:           "InvalidArgument",
		Description:    "Argument maxKeys must be an integer between 0 and 2147483647",
		HTTPStatusCode: http.StatusBadRequest,
	},
	ErrInvalidEncodingMethod: {
		Code:           "InvalidArgument",
		Description:    "Invalid Encoding Method specified in Request",
		HTTPStatusCode: http.StatusBadRequest,
	},
	ErrInvalidMaxParts: {
		Code:           "InvalidArgument",

				VersionID: vid,
			}
		}
		if !versioned {
			return opts, InvalidArgument{
				Bucket: bucket,
				Object: object,
				Err:    fmt.Errorf("VersionID specified %s, but versioning not enabled on bucket=%s", opts.VersionID, bucket),
			}
		}
	}
	opts, err = putOptsFromHeaders(ctx, hdrs, metadata)
	if err != nil {
		return opts, InvalidArgument{
			Bucket: bucket,
			Object: object,
			Err:    err,
		}

                                      run_options->data, run_options->length)) {
      status->status = InvalidArgument("Unparseable RunOptions proto");
      return;
    }
    if (run_metadata != nullptr && run_metadata->data != nullptr) {
      status->status =
          InvalidArgument("Passing non-empty run_metadata is invalid.");
      return;
    }

    RunMetadata run_metadata_proto;

#include "tensorflow/core/protobuf/tensorflow_server.pb.h"

using tensorflow::FunctionDef;
using tensorflow::Node;
using tensorflow::NodeBuilder;
using tensorflow::Status;
using tensorflow::errors::InvalidArgument;

namespace {
typedef std::unique_ptr<TF_Function, decltype(&TF_DeleteFunction)>
    UniqueFuncPtr;
}

// struct TF_Operation { tensorflow::Node node; };
static TF_Operation* ToTF_Operation(Node* node) {

	VersionID string
	Err       error
}

// Unwrap the error to its underlying error.
func (e GenericError) Unwrap() error {
	return e.Err
}

// InvalidArgument incorrect input argument
type InvalidArgument GenericError

func (e InvalidArgument) Error() string {
	if e.Err != nil {
		return "Invalid arguments provided for " + e.Bucket + "/" + e.Object + ": (" + e.Err.Error() + ")"
	}

  if (ctx == nullptr) {
    status->status = tensorflow::errors::InvalidArgument("Invalid Context");
    return nullptr;
  }

  tensorflow::AbstractTensorInterface* t =
      tensorflow::unwrap(ctx)->CreateTensor(
          static_cast<tensorflow::DataType>(dtype), dimvec);

  if (t == nullptr) {
    status->status =
        tensorflow::errors::InvalidArgument("Unsupported dtype: ", dtype);
    return nullptr;
  }

	onlineDisks := er.getDisks()
	writeQuorum := fi.WriteQuorum(er.defaultWQuorum())

	if cs := fi.Metadata[hash.MinIOMultipartChecksum]; cs != "" {
		if r.ContentCRCType().String() != cs {
			return pi, InvalidArgument{
				Bucket: bucket,
				Object: fi.Name,
				Err:    fmt.Errorf("checksum missing, want %q, got %q", cs, r.ContentCRCType().String()),
			}
		}
	}

			s3LogIf(ctx, err)
			return opts, InvalidVersionID{
				Bucket:    bucket,
				Object:    object,
				VersionID: vid,
			}
		}
		if !versioned && !versionSuspended {
			return opts, InvalidArgument{
				Bucket: bucket,
				Object: object,
				Err:    fmt.Errorf("version-id specified %s but versioning is not enabled on %s", opts.VersionID, bucket),
			}
		}
	}
	return ObjectOptions{

			dataLen:            len(bytesData),
			accessKey:          credentials.AccessKey,
			secretKey:          credentials.SecretKey,
			expectedRespStatus: http.StatusBadRequest,
			wantAPICode:        "InvalidArgument",
		},
		// Test Case with invalid Content-Md5 value
		3: {
			bucketName:         bucketName,
			objectName:         objectName,
			headers:            invalidMD5Header,