Class RegexFullMatch

java.lang.Object
org.tensorflow.op.RawOp
org.tensorflow.op.strings.RegexFullMatch
All Implemented Interfaces:
Shaped, Op, Operand<TBool>

@Operator(group="strings") public final class RegexFullMatch extends RawOp implements Operand<TBool>
Check if the input matches the regex pattern. The input is a string tensor of any shape. The pattern is a scalar string tensor which is applied to every element of the input tensor. The boolean values (True or False) of the output tensor indicate if the input matches the regex pattern provided.

The pattern follows the re2 syntax (https://github.com/google/re2/wiki/Syntax)

Examples:

tf.strings.regex_full_match(["TF lib", "lib TF"], ".*lib$") <tf.Tensor: shape=(2,), dtype=bool, numpy=array([ True, False])> tf.strings.regex_full_match(["TF lib", "lib TF"], ".*TF$") <tf.Tensor: shape=(2,), dtype=bool, numpy=array([False, True])>

  • Field Details

  • Constructor Details

    • RegexFullMatch

      public RegexFullMatch(Operation operation)
  • Method Details

    • create

      @Endpoint(describeByClass=true) public static RegexFullMatch create(Scope scope, Operand<TString> input, Operand<TString> pattern)
      Factory method to create a class wrapping a new RegexFullMatch operation.
      Parameters:
      scope - current scope
      input - A string tensor of the text to be processed.
      pattern - A scalar string tensor containing the regular expression to match the input.
      Returns:
      a new instance of RegexFullMatch
    • output

      public Output<TBool> output()
      Gets output. A bool tensor with the same shape as input.
      Returns:
      output.
    • asOutput

      public Output<TBool> asOutput()
      Description copied from interface: Operand
      Returns the symbolic handle of the tensor.

      Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

      Specified by:
      asOutput in interface Operand<TBool>
      See Also: