}

void TF_SetDevice(TF_OperationDescription* desc, const char* device) {
  desc->node_builder.Device(device);
}

void TF_AddInput(TF_OperationDescription* desc, TF_Output input) {
  desc->node_builder.Input(&input.oper->node, input.index);
}

void TF_AddInputList(TF_OperationDescription* desc, const TF_Output* inputs,
                     int num_inputs) {
  std::vector<NodeBuilder::NodeOut> input_list;

        }

        for (final Pattern pattern : includedDocUrlPatterns) {
            if (pattern.matcher(input).matches()) {
                return Constants.TRUE;
            }
        }

        for (final Pattern pattern : excludedDocUrlPatterns) {
            if (pattern.matcher(input).matches()) {
                return Constants.FALSE;
            }
        }

        return Constants.TRUE;
    }

        {
            "detail": [
                {
                    "type": "missing",
                    "loc": ["body", "file"],
                    "msg": "Field required",
                    "input": None,
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [
                {

        {
            "detail": [
                {
                    "type": "int_parsing",
                    "loc": ["path", "item_id"],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "foo",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [

                        updater.write("# " + line);
                    }
                    continue;
                }

                final String input = m.group(1).trim();
                final String output = m.group(2).trim();

                if (input == null || output == null) {
                    logger.warn("Failed to parse {} to {}", line, path);
                    if (updater != null) {

        {
            "detail": [
                {
                    "type": "int_parsing",
                    "loc": ["path", "item_id"],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "foo",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [

}

// Returns always a same erasure coded set for a given input.
func (s *erasureSets) getHashedSetIndex(input string) int {
	return hashKey(s.distributionAlgo, input, len(s.sets), s.deploymentID)
}

// Returns always a same erasure coded set for a given input.
func (s *erasureSets) getHashedSet(input string) (set *erasureObjects) {
	return s.sets[s.getHashedSetIndex(input)]
}

			d := divisibleSize / cnt
			if d <= prevD {
				prevD = d
				setSize = cnt
			}
		}
	}
	return setSize
}

// possibleSetCountsWithSymmetry returns symmetrical setCounts based on the
// input argument patterns, the symmetry calculation is to ensure that
// we also use uniform number of drives common across all ellipses patterns.

TF_Operation* RandomUniform(TF_Operation* shape, TF_DataType dtype,
                            TF_Graph* graph, TF_Status* s);

// Split `input` along the first dimension into 3 tensors
TF_Operation* Split3(TF_Operation* input, TF_Graph* graph, TF_Status* s,
                     const char* name = "split3");

bool IsPlaceholder(const tensorflow::NodeDef& node_def);

    TF_Status* status);

// Controls how to act when we try to run an operation on a given device but
// some input tensors are not on that device.
// LINT.IfChange
// Note: Keep in sync with internal copy of enum in eager/context.h.
typedef enum TFE_ContextDevicePlacementPolicy {
  // Running operations with input tensors on the wrong device will fail.
  TFE_DEVICE_PLACEMENT_EXPLICIT = 0,