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Results 21 - 24 of 24 for unrepresentable (0.29 sec)

  1. src/go/types/stmt.go

    		return bad("no core type")
    	case *Basic:
    		if isString(typ) {
    			return Typ[Int], universeRune, "", false, true // use 'rune' name
    		}
    		if isInteger(typ) {
    			// untyped numeric constants may be representable as integer values
    			if allowVersion != nil && !allowVersion(go1_22) {
    				return bad("requires go1.22 or later")
    			}
    			return orig, nil, "", false, true
    		}
    	case *Array:
    Registered: Wed Jun 12 16:32:35 UTC 2024
    - Last Modified: Thu May 30 19:19:55 UTC 2024
    - 30.6K bytes
    - Viewed (0)
  2. src/cmd/compile/internal/ssa/_gen/genericOps.go

    	// See issue 36399 and 36400.
    	// Encodings of +inf, -inf, and -0 are fine.
    	{name: "Const32F", aux: "Float32"}, // value is math.Float64frombits(uint64(auxint)) and is exactly representable as float 32
    	{name: "Const64F", aux: "Float64"}, // value is math.Float64frombits(uint64(auxint))
    	{name: "ConstInterface"},           // nil interface
    	{name: "ConstSlice"},               // nil slice
    
    Registered: Wed Jun 12 16:32:35 UTC 2024
    - Last Modified: Thu May 23 15:49:20 UTC 2024
    - 42.6K bytes
    - Viewed (0)
  3. tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td

    This op determines the maximum scale_factor that would map the initial
    [input_min, input_max] range to a range that lies within the representable
    quantized range.
    
    It determines the scale from one of input_min and input_max, then updates the
    other one to maximize the representable range.
    
    e.g.
    
    *   if the output is signed, num_bits = 8, [input_min, input_max] = [-10.0,
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Tue Jun 11 23:24:08 UTC 2024
    - 793K bytes
    - Viewed (0)
  4. RELEASE.md

            `tf.GradientTape` inside a `tf.function`.
        *   Changed the default step size in `gradient_checker_v2.compute_gradients`
            to be exactly representable as a binary floating point numbers. This
            avoids poluting gradient approximations needlessly, which is some cases
            leads to false negatives in op gradient tests.
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Tue Jun 11 23:24:08 UTC 2024
    - 730.3K bytes
    - Viewed (0)
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