Agrave "&#192;"> <!ENTITY Aacute "&#193;"> <!ENTITY Acirc "&#194;"> <!ENTITY Atilde "&#195;"> <!ENTITY Auml "&#196;"> <!ENTITY Aring "&#197;"> <!ENTITY AElig "&#198;"> <!ENTITY Ccedil "&#199;"> <!ENTITY Egrave "&#200;"> <!ENTITY Eacute "&#201;"> <!ENTITY Ecirc "&#202;"> <!ENTITY Euml "&#203;"> <!ENTITY Igrave "&#204;"> <!ENTITY Iacute "&#205;"> <!ENTITY Icirc "&#206;"> <!ENTITY Iuml "&#207;"> <!ENTITY ETH "&#208;"> <!ENTITY Ntilde "&#209;"> <!ENTITY Ograve "&#210;"> <!ENTITY Oacute "&#211;"> <!ENTITY Ocirc...

			}
		// Unreserved according to RFC 3986 sec 2.3
		// "For consistency, percent-encoded octets in the ranges of
		// ALPHA (%41-%5A and %61-%7A), DIGIT (%30-%39), hyphen (%2D),
		// period (%2E), underscore (%5F), or tilde (%7E) should not be
		// created by URI producers
		case '-', '.', '_', '~':
			continue
		case '%':
			// When normalizing do not re-encode valid escapes.

		x = t
	}
	return x
}

func (p *parser) embeddedTerm() ast.Expr {
	if p.trace {
		defer un(trace(p, "EmbeddedTerm"))
	}
	if p.tok == token.TILDE {
		t := new(ast.UnaryExpr)
		t.OpPos = p.pos
		t.Op = token.TILDE
		p.next()
		t.X = p.parseType()
		return t
	}

	t := p.tryIdentOrType()
	if t == nil {
		pos := p.pos
		p.errorExpected(pos, "~ term or type")

  pymdownx.superfences:
    custom_fences:
    - name: mermaid
      class: mermaid
      format: !!python/name:pymdownx.superfences.fence_code_format ''
  pymdownx.tabbed:
    alternate_style: true
  pymdownx.tilde: null
  attr_list: null
  md_in_html: null
extra:
  analytics:
    provider: google
    property: G-YNEVN69SC3
  social:
  - icon: fontawesome/brands/github-alt

	case *ast.Ident:
		// nothing to do
	case *ast.ParenExpr:
		r.filterType(nil, t.X)
	case *ast.StarExpr: // possibly an embedded type literal
		r.filterType(nil, t.X)
	case *ast.UnaryExpr:
		if t.Op == token.TILDE { // approximation element
			r.filterType(nil, t.X)
		}
	case *ast.BinaryExpr:
		if t.Op == token.OR { // union
			r.filterType(nil, t.X)
			r.filterType(nil, t.Y)
		}
	case *ast.ArrayType:

    "StopGradient",
    "StridedSlice",
    "StridedSliceGrad",
    "TensorScatterAdd",
    "TensorScatterMax",
    "TensorScatterMin",
    "TensorScatterSub",
    "TensorStridedSliceUpdate",
    "Tile",
    "TileGrad",
    "Transpose",
    "Unique",
    "UniqueV2",
    "UniqueWithCounts",
    "UniqueWithCountsV2",
    "Unpack",
    "UnravelIndex",
    "Where",
    "ZerosLike",

    func.return %1, %3 : tensor<*xi32>, tensor<*xi1>
  }
}

// -----

// Tests inputs are correctly split and fed into TPU computation for tiled input
// sharding.

// The following OpSharding is used for TPU computation inputs in below test:
// Proto debug string:
//  input 0
//   type: OTHER
//   tile_assignment_dimensions: 1

}

// EmbeddedTerm = [ "~" ] Type .
func (p *parser) embeddedTerm() Expr {
	if trace {
		defer p.trace("embeddedTerm")()
	}

	if p.tok == _Operator && p.op == Tilde {
		t := new(Operation)
		t.pos = p.pos()
		t.Op = Tilde
		p.next()
		t.X = p.type_()
		return t
	}

	t := p.typeOrNil()
	if t == nil {
		t = p.badExpr()
		p.syntaxError("expected ~ term or type")

 Minimum 1
 Mul 3
 Pack 2
 Pad 1
 Range 1
 RealDiv 1
 Reshape 8
 Shape 7
 Size 1
 Slice 2
 Snapshot 5
 SparseSoftmaxCrossEntropyWithLogits 1
 StridedSlice 2
 Sub 3
 Sum 1
 Tile 1
 Transpose 2
 Unpack 1
cluster 2 size 44
 Cast 2
 ConcatV2 2
 Const 18
 ExpandDims 1
 GatherV2 2
 Less 1
 MatMul 1
 Mul 1
 Pack 1
 Prod 2
 Range 1
 Reshape 3

		// parameters.
		reportReason := len(m.seen) == 1

		for _, term := range terms {
			if !m.match(term.Type(), topLevel) {
				if reportReason {
					if term.Tilde() {
						m.reason = fmt.Sprintf("contains ~%s", term.Type())
					} else {
						m.reason = fmt.Sprintf("contains %s", term.Type())
					}
				}
				return false
			}
		}
		return true
	}