parallel Planes of a Looking-glass, and BD the Plane of the Diamond-cut,
making at B a very obtuse Angle with the Plane AB. And let all the Light
between the Rays ENI and FBM pass directly through the parallel Planes
of the Glass, and fall upon the Paper between I and M, and all the Light
between the Rays GO and HD be refracted by the oblique Plane of the

                                    purposely left undefined, since different data planes have different
                                    capabilities. However, it is *recommended* that implementations should
                                    match against the first value of the param if the data plane supports it,
                                    as this behavior is expected in other load balancing contexts outside of

capitalization.)\n\n<decimalExponent> ::= \"e\" <signedNumber> | \"E\" <signedNumber> ```\n\nNo matter which of the three exponent forms is used, no quantity may represent a number greater than 2^63-1 in magnitude, nor may it have more than 3 decimal places. Numbers larger or more precise will be capped or rounded up. (E.g.: 0.1m will rounded up to 1m.) This may be extended in the future if we require larger or smaller quantities.\n\nWhen a Quantity is parsed from a string, it will remember the type...

            calling this op is typically not necessary, as it is automatically
            used when computing the gradient of `tf.sparse.segment_sum`.
    *   Renaming of tensorflow::int64 to int_64_t in numerous places (the former
        is an alias for the latter) which could result in needing to regenerate
        selective op registration headers else execution would fail with
        unregistered kernels error.

capitalization.)\n\n<decimalExponent> ::= \"e\" <signedNumber> | \"E\" <signedNumber> ```\n\nNo matter which of the three exponent forms is used, no quantity may represent a number greater than 2^63-1 in magnitude, nor may it have more than 3 decimal places. Numbers larger or more precise will be capped or rounded up. (E.g.: 0.1m will rounded up to 1m.) This may be extended in the future if we require larger or smaller quantities.\n\nWhen a Quantity is parsed from a string, it will remember the type...

returns `f(inputs)`, where `f`'s body is placed and partitioned.
  }];

  let description = [{
Asynchronously executes a function, potentially across multiple devices but
within a single process. The kernel places and partitions a given function's
underlying graph, and executes each of the partitioned subgraphs as a function.
  }];

  let arguments = (ins
    Arg<Variadic<TF_Tensor>, [{A list of input tensors.}]>:$args,

1FA87..1FA88  ; valid                  ;      ; NV8    # 15.0 MARACAS..FLUTE
1FA89..1FA8F  ; disallowed                             # NA   <reserved-1FA89>..<reserved-1FA8F>
1FA90..1FA95  ; valid                  ;      ; NV8    # 12.0 RINGED PLANET..BANJO
1FA96..1FAA8  ; valid                  ;      ; NV8    # 13.0 MILITARY HELMET..ROCK
1FAA9..1FAAC  ; valid                  ;      ; NV8    # 14.0 MIRROR BALL..HAMSA

variants\n//\n\n.nav-fill {\n  .nav-item {\n    flex: 1 1 auto;\n    text-align: center;\n  }\n}\n\n.nav-justified {\n  .nav-item {\n    flex-basis: 0;\n    flex-grow: 1;\n    text-align: center;\n  }\n}\n\n\n// Tabbable tabs\n//\n// Hide tabbable panes to start, show them when `.active`\n\n.tab-content {\n  > .tab-pane {\n    display: none;\n  }\n  > .active {\n    display: block;\n  }\n}\n","// Contents\n//\n// Navbar\n// Navbar brand\n// Navbar nav\n// Navbar text\n// Navbar divider\n// Responsive...