P/j6E<dZddlZddlZddlmZmZddlZddlmZddgZGddejjZ Gdd ejjZ Gd d ejjZ Gd dejjZy) z We will recreate all the RNN modules as we require the modules to be decomposed into its building blocks to be able to observe. N)OptionalTuple)TensorLSTMCellLSTMc eZdZdZej j Z ddedede ddffd Z dde d e e e e fde e e ffd Z dd ed e de e e ffd ZdZeddZeddZxZS)raA quantizable long short-term memory (LSTM) cell. For the description and the argument types, please, refer to :class:`~torch.nn.LSTMCell` Examples:: >>> import torch.ao.nn.quantizable as nnqa >>> rnn = nnqa.LSTMCell(10, 20) >>> input = torch.randn(6, 10) >>> hx = torch.randn(3, 20) >>> cx = torch.randn(3, 20) >>> output = [] >>> for i in range(6): ... hx, cx = rnn(input[i], (hx, cx)) ... output.append(hx) N input_dim hidden_dimbiasreturnc||d}t|||_||_||_t j j|d|zfd|i||_t j j|d|zfd|i||_ t jj jj|_ t j j|_t j j|_t j j#|_t j j|_t jj jj|_t jj jj|_t jj jj|_t jj jj|_d|_d|_t j4|_t j4|_y)Ndevicedtyper )?r)super__init__ input_size hidden_sizer torchnnLinearigateshgatesao quantizedFloatFunctionalgatesSigmoid input_gate forget_gateTanh cell_gate output_gatefgate_cx igate_cgatefgate_cx_igate_cgateogate_cyinitial_hidden_state_qparamsinitial_cell_state_qparamsquint8hidden_state_dtypecell_state_dtypeselfr r r rrfactory_kwargs __class__s f/root/repos/pocs/video-evals/.venv/lib/python3.12/site-packages/torch/ao/nn/quantizable/modules/rnn.pyrzLSTMCell.__init__&s%+U; #% hhoo q:~ ,0 4B  hhoo J -1 5C  XX[[**::< ((**, 88++- 88++- --==?  88;;00@@B$)HHKK$9$9$I$I$K! --==? ?G)=E'/4||-2\\xhiddenc| |d|d)|j|jd|j}|\}}|j|}|j |}|j j ||}|jdd\}} } } |j|}|j| } |j| } |j| } |jj| |} |jj|| } |jj | | }|}t!j"|}|j$j| |}||fS)Nrr)initialize_hiddenshape is_quantizedrrraddchunkr!r"r$r%r&mulr'r(rtanhr))r0r5r6hxcxrrrr!r"r$out_gater&r'r(cytanh_cyhys r3forwardzLSTMCell.forwardLs? >VAY.&)2C++AGGAJGFBQR vv.7<{{1a7H4 KH__Z0 &&{3 NN9- ##H-==$$["5&&**:yA #88<