PathTypeExact = PathType("Exact")

	// PathTypePrefix matches based on a URL path prefix split by '/'. Matching
	// is case sensitive and done on a path element by element basis. A path
	// element refers to the list of labels in the path split by the '/'
	// separator. A request is a match for path p if every p is an element-wise

				"self.val1.indexOf('o', 2) == 2":                   4,
				"self.val1.replace(' ', 'x') == 'Rookxtakesx👑'":    7,
				"self.val1.replace(' ', 'x', 1) == 'Rookxtakes 👑'": 7,
				"self.val1.split(' ') == ['Rook', 'takes', '👑']":   6,
				"self.val1.split(' ', 2) == ['Rook', 'takes 👑']":   6,
				"self.val1.substring(5) == 'takes 👑'":              5,
				"self.val1.substring(0, 4) == 'Rook'":              5,

			if !strings.HasPrefix(arg, "-g") {
				p.GccOptions = append(p.GccOptions, arg)
			}
		}
	}
	if flag == "LDFLAGS" {
		p.LdFlags = append(p.LdFlags, args...)
	}
}

// splitQuoted splits the string s around each instance of one or more consecutive
// white space characters while taking into account quotes and escaping, and
// returns an array of substrings of s or an empty list if s contains only white space.

    private static int compareModelVersions(String first, String second) {
        // we use a dedicated comparator because we control our model version scheme.
        String[] firstSegments = first.split("\\.");
        String[] secondSegments = second.split("\\.");
        for (int i = 0; i < Math.max(firstSegments.length, secondSegments.length); i++) {
            int result = Long.valueOf(i < firstSegments.length ? firstSegments[i] : "0")

  let summary = "";

  let arguments = (ins
    TF_StrTensor:$program_key,
    TF_Int32Tensor:$row_ids,
    TF_Int32Tensor:$col_ids,
    TF_Float32Tensor:$gains,
    TF_Int64Tensor:$splits,
    TF_Int32Tensor:$id_counts,

    ConfinedAttr<I64Attr, [IntMinValue<1>]>:$sample_count,
    ConfinedAttr<I64Attr, [IntMinValue<1>]>:$num_replica,

			expectedSetCost:  12,
		},
		{
			name: "extended library split",
			schemaGenerator: func(max *int64) *schema.Structural {
				strType := withMaxLength(primitiveType("string", ""), max)
				objType := objectType(map[string]schema.Structural{
					"str":       strType,
					"separator": strType,
				})
				objType = withRule(objType, "self.str.split(self.separator) == []")
				return &objType
			},

	if err != nil {
		p.Ctxt.Diag("%v: constant %d too large", p, ins.imm, err)
		return nil
	}
	if high == 0 {
		return []*instruction{ins}
	}

	// Split into two additions, if possible.
	// Do not split SP-writing instructions, as otherwise the recorded SP delta may be wrong.
	if p.Spadj == 0 && ins.as == AADDI && ins.imm >= -(1<<12) && ins.imm < 1<<12-1 {
		imm0 := ins.imm / 2

  // return the same resource (after passing it through multiple identity ops).
  // Some subsequent ops use the original resource and others use the returned
  // version. Pipelining splits these uses across loop iterations resulting in
  // terrible things.
  result = EliminateResourceLoops(builder, symbol_table, loop_body_func);
  if (failed(result)) return signalPassFailure();

	-bench regexp
	    Run only those benchmarks matching a regular expression.
	    By default, no benchmarks are run.
	    To run all benchmarks, use '-bench .' or '-bench=.'.
	    The regular expression is split by unbracketed slash (/)
	    characters into a sequence of regular expressions, and each
	    part of a benchmark's identifier must match the corresponding
	    element in the sequence, if any. Possible parents of matches

// RUN: tf-quant-opt %s -split-input-file -quant-insert-quantized-functions -quant-quantize-composite-functions | FileCheck --check-prefix=TF %s
// RUN: tf-quant-opt %s -split-input-file -quant-insert-quantized-functions -quant-quantize-composite-functions='target-opset=XLA' | FileCheck --check-prefix=XLA %s