<pre>
Description of the input(s).
</pre>

<code>repeated .tensorflow.OpDef.ArgDef input_arg = 2;</code>
180932
public org.tensorflow.framework.OpDef.ArgDefOrBuilder getInputArgOrBuilder(
      int index) {
    return inputArg_.get(index);
  }
283729
public org.tensorflow.framework.OpDeprecation getDeprecation() {
    return deprecation_ == null ? org.tensorflow.framework.OpDeprecation.getDefaultInstance() : deprecation_;
  }
897716
public org.tensorflow.framework.ValuesDef getValuesDef() {
    return valuesDef_ == null ? org.tensorflow.framework.ValuesDef.getDefaultInstance() : valuesDef_;
  }
120483
private String typeParameters(Options opt, ParameterizedType t) {
	if (t == null)
	    return "";
	StringBuffer tp = new StringBuffer(1000).append("&lt;");
	Type args[] = t.typeArguments();
	for (int i = 0; i < args.length; i++) {
	    tp.append(type(opt, args[i], true));
	    if (i != args.length - 1)
		tp.append(", ");
	}
	return tp.append("&gt;").toString();
    }
73865
public java.util.List<? extends org.tensorflow.framework.OpDef.ArgDefOrBuilder> 
      getOutputArgOrBuilderList() {
    return outputArg_;
  }
9825
def _get_description(arg):
    """"""
    desc = []
    otherwise = False
    if arg.can_be_inferred:
        desc.append('If left unspecified, it will be inferred automatically.')
        otherwise = True
    elif arg.is_flag:
        desc.append('This argument defaults to '
                    '<code>None</code> and can be omitted.')
        otherwise = True

    if arg.type in {'InputPeer', 'InputUser', 'InputChannel',
                    'InputNotifyPeer', 'InputDialogPeer'}:
        desc.append(
            'Anything entity-like will work if the library can find its '
            '<code>Input</code> version (e.g., usernames, <code>Peer</code>, '
            '<code>User</code> or <code>Channel</code> objects, etc.).'
        )

    if arg.is_vector:
        if arg.is_generic:
            desc.append('A list of other Requests must be supplied.')
        else:
            desc.append('A list must be supplied.')
    elif arg.is_generic:
        desc.append('A different Request must be supplied for this argument.')
    else:
        otherwise = False  # Always reset to false if no other text is added

    if otherwise:
        desc.insert(1, 'Otherwise,')
        desc[-1] = desc[-1][:1].lower() + desc[-1][1:]

    return ' '.join(desc).replace(
        'list',
        '<span class="tooltip" title="Any iterable that supports len() '
        'will work too">list</span>'
    )
719161
public static String humanReadableCommandLineOutput(List<String> arguments) {
        //TODO investigate removing this, only used in tests
        StringBuilder debugOutput = new StringBuilder();
        for (String argument : arguments) {
            debugOutput.append(argument).append(" ");
        }
        return debugOutput.toString().trim();
    }
162088
public org.tensorflow.framework.TensorInfo getOutputsOrDefault(
      java.lang.String key,
      org.tensorflow.framework.TensorInfo defaultValue) {
    if (key == null) { throw new java.lang.NullPointerException(); }
    java.util.Map<java.lang.String, org.tensorflow.framework.TensorInfo> map =
        internalGetOutputs().getMap();
    return map.containsKey(key) ? map.get(key) : defaultValue;
  }
872478
def _parse_execution_args(execution_args):
        
        if not isinstance(execution_args, (list, tuple)):
            raise ValueError("Parameter 'execution_args' should be a list")

        return [EOWorkflow.parse_input_args(input_args) for input_args in execution_args]
826478
public java.util.List<? extends org.tensorflow.framework.OpDef.AttrDefOrBuilder> 
      getAttrOrBuilderList() {
    return attr_;
  }
544124
@Override
    public InputType getOutputType(InputType... inputType) throws InvalidKerasConfigurationException {
        if (inputType.length > 1)
            throw new InvalidKerasConfigurationException(
                    "Keras Convolution layer accepts only one input (received " + inputType.length + ")");
        return this.getDeconvolution2DLayer().getOutputType(-1, inputType[0]);
    }
764863
@java.lang.Deprecated
  public java.util.Map<java.lang.String, org.tensorflow.framework.TensorInfo> getInputs() {
    return getInputsMap();
  }
554094
def InputSplines1D(seq_length, n_bases=10, name=None, **kwargs):
    
    return Input((seq_length, n_bases), name=name, **kwargs)
1266702
public Collection<Tuple> getTuples( FunctionInputDef inputDef)
    {
    List<VarDef> combinedVars = getCombinedVars( inputDef);
    return getCombinedTuples( combinedVars, getTuples( combinedVars, getTupleSize()));
    }
326428
public INDArray ndArrayFromTensor(TF_Tensor tensor) {
        int rank = TF_NumDims(tensor);

        int[] ndShape;
        if (rank == 0) {
            // scalar
            ndShape = new int[] { 1 };
        } else {
            ndShape = new int[rank];
            for (int i = 0; i < ndShape.length; i++) {
                ndShape[i] = (int) TF_Dim(tensor,i);
            }
        }

        int tfType = TF_TensorType(tensor);
        DataType nd4jType = typeFor(tfType);

        int length = ArrayUtil.prod(ndShape);
        INDArray array;
        if (nd4jType == DataType.UTF8) {
            String[] strings = new String[length];
            BytePointer data = new BytePointer(TF_TensorData(tensor)).capacity(TF_TensorByteSize(tensor));
            BytePointer str = new BytePointer((Pointer)null);
            SizeTPointer size = new SizeTPointer(1);
            TF_Status status = TF_NewStatus();
            for (int i = 0; i < length; i++) {
                long offset = data.position(8 * i).getLong();
                TF_StringDecode(data.position(8 * length + offset), data.capacity() - data.position(), str, size, status);
                if (TF_GetCode(status) != TF_OK) {
                    throw new IllegalStateException("ERROR: Unable to convert tensor " + TF_Message(status).getString());
                }
                strings[i] = str.position(0).capacity(size.get()).getString();
            }
            TF_DeleteStatus(status);
            array = Nd4j.create(strings);
        } else {
            Pointer pointer = TF_TensorData(tensor).capacity(length);
            Indexer indexer = indexerForType(nd4jType,pointer);
            DataBuffer d = Nd4j.createBuffer(indexer.pointer(),nd4jType,length,indexer);
            array = Nd4j.create(d,ndShape);
        }
        Nd4j.getAffinityManager().tagLocation(array, AffinityManager.Location.HOST);
        return array;
    }
943760
public static List<TupleValueExpression>
    getTupleValueExpressions(AbstractExpression input)
    {
        ArrayList<TupleValueExpression> tves =
            new ArrayList<TupleValueExpression>();
        // recursive stopping steps
        if (input == null)
        {
            return tves;
        } else if (input instanceof TupleValueExpression) {
            tves.add((TupleValueExpression) input);
            return tves;
        }

        // recursive calls
        tves.addAll(getTupleValueExpressions(input.m_left));
        tves.addAll(getTupleValueExpressions(input.m_right));
        if (input.m_args != null) {
            for (AbstractExpression argument : input.m_args) {
                tves.addAll(getTupleValueExpressions(argument));
            }
        }
        return tves;
    }
471534
def fromimpute2(args):
    
    p = OptionParser(fromimpute2.__doc__)
    opts, args = p.parse_args(args)

    if len(args) != 3:
        sys.exit(not p.print_help())

    impute2file, fastafile, chr = args
    fasta = Fasta(fastafile)
    print(get_vcfstanza(fastafile, fasta))
    fp = open(impute2file)
    seen = set()
    for row in fp:
        snp_id, rsid, pos, ref, alt, aa, ab, bb = row.split()
        pos = int(pos)
        if pos in seen:
            continue
        seen.add(pos)
        code = max((float(aa), "0/0"), (float(ab), "0/1"), (float(bb), "1/1"))[-1]
        tag = "PR" if snp_id == chr else "IM"
        print("\t".join(str(x) for x in \
                (chr, pos, rsid, ref, alt, ".", ".", tag, \
                "GT:GP", code + ":" + ",".join((aa, ab, bb)))))