* This allows adding extra code after a dependency is done. It can be used, for example, to close database connections.
    * Dependencies with `yield` can be normal or `async`, **FastAPI** will run normal dependencies in a threadpool.
    * They can be combined with normal dependencies.
    * It's possible to have arbitrary trees/levels of dependencies with `yield` and exit steps are handled in the correct order automatically.

$font-family-base;\n  // We deliberately do NOT reset font-size or word-wrap.\n  font-style: normal;\n  font-weight: $font-weight-normal;\n  line-height: $line-height-base;\n  text-align: left; // Fallback for where `start` is not supported\n  text-align: start;\n  text-decoration: none;\n  text-shadow: none;\n  text-transform: none;\n  letter-spacing: normal;\n  word-break: normal;\n  white-space: normal;\n  word-spacing: normal;\n  line-break: auto;\n}\n",".popover {\n  position: absolute;\n  top: 0;\n  left:...

are in bit reversed order. var productTable [16]gcmFieldElement // We precompute 16 multiples of H. However, when we do lookups // into this table we'll be using bits from a field element and // therefore the bits will be in the reverse order. So normally one // would expect, say, 4*H to be in index 4 of the table but due to // this bit ordering it will actually be in index 0010 (base 2) = 2. x := gcmFieldElement{ byteorder.BEUint64(H[:8]), byteorder.BEUint64(H[8:]), } productTable[reverseBits(1)]...

deliberately do NOT reset font-size or overflow-wrap / word-wrap.\n  font-style: normal;\n  font-weight: $font-weight-normal;\n  line-height: $line-height-base;\n  text-align: left; // Fallback for where `start` is not supported\n  text-align: start;\n  text-decoration: none;\n  text-shadow: none;\n  text-transform: none;\n  letter-spacing: normal;\n  word-break: normal;\n  white-space: normal;\n  word-spacing: normal;\n  line-break: auto;\n}\n",".popover {\n  // scss-docs-start popover-css-vars\n...

        *   `tf.raw_ops.Bucketize` op on CPU.
        *   `tf.where` op for data types
            `tf.int32`/`tf.uint32`/`tf.int8`/`tf.uint8`/`tf.int64`.
        *   `tf.random.normal` op for output data type `tf.float32` on CPU.
        *   `tf.random.uniform` op for output data type `tf.float32` on CPU.
        *   `tf.random.categorical` op for output data type `tf.int64` on CPU.