super(ProjectDependency.class);
            this.instantiator = instantiator;
        }

        @Override
        protected DependencyConstraint parseType(ProjectDependency notation) {
            return instantiator.newInstance(DefaultProjectDependencyConstraint.class, notation);
        }
    }

        StringNotationParser(boolean versionIsRequired) {
            super(CharSequence.class);
            this.versionIsRequired = versionIsRequired;
        }

        @Override
        protected Capability parseType(CharSequence notation) {
            String stringNotation = notation.toString();
            String[] parts = stringNotation.split(":");
            if (parts.length != 3) {

  static StringRef getDialectNamespace() { return "tf"; }

  // Overrides to redirect to tf_type dialect.
  Attribute parseAttribute(DialectAsmParser &parser, Type type) const override;
  Type parseType(DialectAsmParser &parser) const override;

  // Gradient attribute ("tf.gradient") in the list of NamedAttributes in a
  // function references to its gradient function. This attribute in TensorFlow

	cfg.Enable = env.Get(EnvEnable, kvs.GetWithDefault(Enable, DefaultKVS)) == config.EnableOn

	if d := env.Get(EnvBlockSize, kvs.GetWithDefault(BlockSize, DefaultKVS)); d != "" {
		objectSize, err := humanize.ParseBytes(d)
		if err != nil {
			return cfg, err
		}
		cfg.BlockSize = int64(objectSize)
	}

	cfg.Endpoint = env.Get(EnvEndpoint, kvs.GetWithDefault(Endpoint, DefaultKVS))

		return Config{}, err
	}

	cfg.Optimize = env.Get(OptimizeEnv, kvs.Get(Optimize))

	inlineBlockStr := env.Get(InlineBlockEnv, kvs.Get(InlineBlock))
	if inlineBlockStr != "" {
		inlineBlock, err := humanize.ParseBytes(inlineBlockStr)
		if err != nil {
			return cfg, err
		}
		if inlineBlock > 128*humanize.KiByte {

  for (auto &hook : GetAdditionalOperationHooks()) {
    hook.second(*this);
  }
}

TensorFlowDialect::~TensorFlowDialect() {
  delete fallback_effect_op_interface_;
}

Type TensorFlowDialect::parseType(DialectAsmParser &parser) const {
  StringRef spec = parser.getFullSymbolSpec();
  llvm::SMLoc loc = parser.getCurrentLocation();
  parser.emitError(
      loc, "tf dialect has no types, potentially meant !tf_type." + spec);

	if ctx.IsSet("memlimit") || ctx.GlobalIsSet("memlimit") {
		memlimit := ctx.String("memlimit")
		if memlimit == "" {
			memlimit = ctx.GlobalString("memlimit")
		}
		mlimit, err := humanize.ParseBytes(memlimit)
		if err != nil {
			return err
		}
		if mlimit > memAvailable {
			logger.Info("WARNING: maximum memory available (%s) smaller than specified --memlimit=%s, ignoring --memlimit value",

//                 | `tensor<` (string-literal | string_list)  '>'
//   tensor_list_type ::= `tensor_list`
//                      | `tensor_list<` (string-literal | string_list)  '>'
//   attr_type ::= `attr`
Type TFRDialect::parseType(DialectAsmParser &parser) const {
  Location loc = parser.getEncodedSourceLoc(parser.getNameLoc());
  MLIRContext *ctx = loc.getContext();

  StringRef typeNameSpelling;

      >();

  addInterfaces<TensorFlowExecutorInlinerInterface,
                TensorFlowExecutorDialectFoldInterface>();

  addTypes<ControlType, TokenType>();
}

Type TensorFlowExecutorDialect::parseType(DialectAsmParser &parser) const {
  StringRef data_type;
  if (parser.parseKeyword(&data_type)) return Type();

  if (data_type == "control") return ControlType::get(getContext());

				BucketLookup: lookupStyle(r.Target.Path),
			})
			if err != nil {
				batchLogIf(ctx, err)
				return
			}

			// Already validated before arriving here
			smallerThan, _ := humanize.ParseBytes(*r.Source.Snowball.SmallerThan)

			batch := make([]ObjectInfo, 0, *r.Source.Snowball.Batch)
			writeFn := func(batch []ObjectInfo) {
				if len(batch) > 0 {