make([]byte, k) em[1] = 1 for i := 2; i < k-len(prefix)-len(hashed)-1; i++ { em[i] = 0xff } copy(em[k-len(prefix)-len(hashed):], prefix) copy(em[k-len(hashed):], hashed) return em, nil } // VerifyPKCS1v15 verifies an RSASSA-PKCS1-v1.5 signature. // // hash is the name of the hash function as returned by [crypto.Hash.String] // or the empty string to indicate that the message is signed directly. func VerifyPKCS1v15(pub *PublicKey, hash string, hashed []byte, sig []byte) error { fipsSelfTest() fips140.RecordApproved()...

SignPKCS1v15 calculates an RSASSA-PKCS1-v1.5 signature. // // hash is the name of the hash function as returned by [crypto.Hash.String] // or the empty string to indicate that the message is signed directly. func SignPKCS1v15(priv *PrivateKey, hash string, hashed []byte) ([]byte, error) { fipsSelfTest() fips140.RecordApproved() checkApprovedHashNam(hash) return signPKCS1v15(priv, hash, hashed) } func signPKCS1v15(priv *PrivateKey, hash string, hashed []byte) ([]byte, error) { em, err := pkcs1v15ConstructEM(&priv.pub,...

      maintains a hash table to track the most up-to-date vocabulary based on
      the inputs received by the layer and the eviction policy. When this layer
      is used with an `UpdateEmbeddingCallback`, which is a time-based callback,
      the vocabulary lookup tensor is updated at the time interval set in the
      `UpdateEmbeddingCallback` based on the most up-to-date vocabulary hash

FE48          ; disallowed_STD3_mapped ; 005D          # 4.0  PRESENTATION FORM FOR VERTICAL RIGHT SQUARE BRACKET
FE49..FE4C    ; disallowed_STD3_mapped ; 0020 0305     # 1.1  DASHED OVERLINE..DOUBLE WAVY OVERLINE
FE4D..FE4F    ; disallowed_STD3_mapped ; 005F          # 1.1  DASHED LOW LINE..WAVY LOW LINE
FE50          ; disallowed_STD3_mapped ; 002C          # 1.1  SMALL COMMA

## Dependencies

### Added
_Nothing has changed._

### Changed
_Nothing has changed._

### Removed
_Nothing has changed._



# v1.19.15


## Downloads for v1.19.15

### Source Code

filename | sha512 hash
-------- | -----------

        * Before this, the return content was first passed through `jsonable_encoder` to ensure it was a "jsonable" object, like a `dict`, instead of an arbitrary object with attributes (like an ORM model). That's why you should make sure to update your Pydantic models for objects with attributes to use `orm_mode = True`.
        * If you don't have a `response_model`, the return object will still be passed through `jsonable_encoder` first.