Converts a plain tensor to a Python list. Returns: Python list.

* Get a pointer to the current TenSEAL context. **/

Get the wrapped low level TenSEALContext object

* Returns the size of the first dimension of the tensor. */

Get the context linked to this tensor

Return a new tensor object wrapping the low level tensor object

* Link to a TenSEAL context. **/

* Returns the size of the first dimension of the tensor. */

* Iterator utils **/

Serialize the context into a stream of bytes.

Drop secret part from the context. This is useful before sending the context for remote computation, as we don't want to send the secret-key t

Evaluate polynomial `coefficients[0] + coefficients[1] * self + .... coefficients[n] * self ^ n`

* Return information about the ciphertext. **/

* Compute the power of the EncryptedTensor<plain_data_t, encrypted_t> with *minimal multiplication depth. **/

* Return the size of the encrypted vector. **/

* Iterator utils **/

* empty() returns if the queue is empty or not. **/

* Returns the current shape of the tensor. */

Construct a context from a serialized buffer. Args: data : bytes buffer from the original context. n_threads: define

* Plain evaluation function operates on an encrypted tensors and plaintext * tensors and returns a new EncryptedTensor<plain_data_t, encrypted_t>

* Checks if the tensor is empty. */

* Returns the element at position {idx1, idx2, ..., idxn} in the current * shape * @param[in] desired position from the tensor. */

* Relinearize the ciphertext if the context has automatic relinearization *enabled. **/

* Rescale the ciphertext, if the context has automatic rescaling enabled. **/

* Split the tensor in chunks * */