/external/tensorflow/tensorflow/contrib/rnn/ops/ |
gru_ops.cc | 26 .Input("h_prev: T") 36 ShapeHandle x, h_prev; 38 TF_RETURN_IF_ERROR(c->WithRank(c->input(1), 2, &h_prev)); 41 DimensionHandle cell_size = c->Dim(h_prev, 1); 53 h_prev: State input from the previous GRU cell. 79 x_h_prev = [x, h_prev] 86 h_prevr = h_prev \circ r 93 h = (1-u) \circ c + u \circ h_prev 100 .Input("h_prev: T") 114 ShapeHandle x, h_prev, w_ru [all...] |
lstm_ops.cc | 28 .Input("h_prev: T") 67 xh = [x, h_prev] 92 h_prev: Output of the previous cell at previous time step. 111 .Input("h_prev: T") 158 h_prev: The previous h state. 183 .Input("h_prev: T") 226 x1, cs_prev, h_prev, w, wci, wcf, wco, b) 228 h_prev = h1 247 h_prev: Initial output of cell (to be used for peephole). 267 .Input("h_prev: T" [all...] |
/external/tensorflow/tensorflow/contrib/rnn/python/ops/ |
gru_ops.py | 82 x, h_prev, w_ru, w_c, b_ru, b_c = op.inputs 87 x, h_prev, w_ru, w_c, b_ru, b_c, r, u, c, d_h) 89 x_h_prev = array_ops.concat([x, h_prev], 1) 93 x_h_prevr = array_ops.concat([x, h_prev * r], 1) 116 x_h_prev = [x, h_prev] 123 h_prevr = h_prev \circ r 130 h = (1-u) \circ c + u \circ h_prev 196 def call(self, inputs, h_prev): 198 # Check cell_size == state_size from h_prev. 199 cell_size = h_prev.get_shape().with_rank(2)[1 [all...] |
lstm_ops.py | 43 h_prev, 61 xh = [x, h_prev] 85 h_prev: A `Tensor`. Must have the same type as `x`. 127 h_prev=h_prev, 145 h_prev=None, 161 h_prev: A `Tensor`. Must have the same type as `x`. 196 if cs_prev is None or h_prev is None: 201 if h_prev is None: 202 h_prev = zero_stat [all...] |
rnn_cell.py | [all...] |
/external/tensorflow/tensorflow/contrib/rnn/kernels/ |
gru_ops.h | 76 typename TTypes<T>::ConstMatrix h_prev, 83 // Concat x_h_prev = [x, h_prev]. 85 x_h_prev.slice(h_offsets(), h_extends()).device(d) = h_prev; 102 // Concat x_h_prevr = [x,h_prev*r] 104 x_h_prevr.slice(h_offsets(), h_extends()).device(d) = h_prev * r; 116 // h= u*h_prev + (1-u)*c 117 h.device(d) = u * (h_prev - c) + c; 129 typename TTypes<T>::ConstMatrix h_prev, 146 d_u_bar.device(d) = d_h * (h_prev - c) * u * (u.constant(T(1)) - u); 156 d_r_bar.device(d) = (d_hr * h_prev * r) * (r.constant(T(1)) - r) [all...] |
lstm_ops_gpu.cu.cc | 148 __global__ void concat_xh(T* xh, const T* x, const T* h_prev, 171 xh[gid] = h_prev[output_row * cell_size + output_col - input_size]; 180 typename TTypes<T>::ConstMatrix h_prev, typename TTypes<T>::ConstMatrix w, 200 xh.data(), x.data(), h_prev.data(), batch_size, cell_size, input_size); 232 const T* h_prev, // [batch_size, cell_size] 310 typename TTypes<T>::ConstMatrix h_prev, typename TTypes<T>::ConstMatrix w, 331 cs_prev.data(), h_prev.data(), w.data(), wci.data(), wcf.data(), 363 typename TTypes<T>::ConstMatrix h_prev, \ 372 x, cs_prev, h_prev, w, wci, wcf, wco, b, xh, i, \ 381 typename TTypes<T>::ConstMatrix h_prev, \ [all...] |
lstm_ops.h | 161 typename TTypes<T>::ConstMatrix h_prev, typename TTypes<T>::ConstMatrix w, 183 typename TTypes<T>::ConstMatrix h_prev, typename TTypes<T>::ConstMatrix w, 208 typename TTypes<T>::ConstMatrix h_prev, typename TTypes<T>::ConstMatrix w, 268 xh.slice(xh_h_offsets(), xh_h_extents()).device(d) = h_prev;
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lstm_ops.cc | 49 typename TTypes<T>::ConstMatrix h_prev, typename TTypes<T>::ConstMatrix w, 59 xh.slice(cell.xh_h_offsets(), cell.xh_h_extents()).device(d) = h_prev; 129 typename TTypes<T>::ConstMatrix h_prev, typename TTypes<T>::ConstMatrix w, 186 typename TTypes<T>::ConstMatrix h_prev, \ 196 h_prev, w, wci, wcf, wco, b, xh, i, cs, f, o, ci, co, icfo, h); \ 203 typename TTypes<T>::ConstMatrix h_prev, \ 219 *this, ctx, d, use_peephole, x, cs_prev, h_prev, w, wci, wcf, wco, b, \ 248 OP_REQUIRES_OK(ctx, ctx->input("h_prev", &h_prev_tensor)); 280 errors::InvalidArgument("h_prev.dims(0) != batch_size: ", 285 "h_prev.dims(1) != cell_size: ", h_prev_tensor->dim_size(1) [all...] |
gru_ops.cc | 38 OP_REQUIRES_OK(ctx, ctx->input("h_prev", &h_prev_tensor)); 60 errors::InvalidArgument("h_prev.dims(0) != batch_size: ", 65 "h_prev.dims(1) != cell_size: ", h_prev_tensor->dim_size(1), 126 {"h_prev"}, "h", 181 OP_REQUIRES_OK(ctx, ctx->input("h_prev", &h_prev_tensor)); 213 // Shape of 'h_prev' must be [batch_size, cell_size] 215 errors::InvalidArgument("h_prev.dims(0) != batch_size: ", 220 "h_prev.dims(1) != cell_size: ", h_prev_tensor->dim_size(1), 314 {"h_prev"}, "d_h_prev", TensorShape({batch_size, cell_size}), 393 typename TTypes<T>::ConstMatrix h_prev, \ [all...] |
/external/opencv/cvaux/src/ |
extendededges.cpp | 83 new_seq->h_prev = tail_seq;
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cvbgfg_gaussmix.cpp | 331 prev_seq = seq->h_prev; 335 if( seq->h_next ) seq->h_next->h_prev = prev_seq; 340 if( seq->h_next ) seq->h_next->h_prev = NULL;
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cvsegment.cpp | 462 seq->h_next->h_prev = seq; 558 tmpseq->h_prev = prev_seq;
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cvbgfg_acmmm2003.cpp | 447 prev_seq = seq->h_prev; 451 if( seq->h_next ) seq->h_next->h_prev = prev_seq; 456 if( seq->h_next ) seq->h_next->h_prev = NULL;
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cvlee.cpp | [all...] |
/external/libedit/src/ |
history.c | 72 history_gfun_t h_prev; /* Get the previous element */ local 83 #define HPREV(h, ev) (*(h)->h_prev)((h)->h_ref, ev) 584 h->h_prev = history_def_prev; 691 nh->h_prev == NULL || nh->h_curr == NULL || nh->h_set == NULL || 700 h->h_prev = history_def_prev; 717 h->h_prev = nh->h_prev; 993 case H_PREV: 1047 hf.h_prev = va_arg(va, history_gfun_t);
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/external/opencv/cv/src/ |
cvapprox.cpp | 462 contour->h_prev = prev_contour; 1023 contour->h_prev = prev_contour;
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cvcontours.cpp | [all...] |
/external/opencv/cxcore/src/ |
cxdatastructs.cpp | 3812 struct CvTreeNode* h_prev; \/* previous sequence *\/ member in struct:CvTreeNode [all...] |
cxpersistence.cpp | [all...] |
/external/opencv/cxcore/include/ |
cxtypes.h | 1201 struct node_type* h_prev; /* Previous sequence. */ \ [all...] |