Searched refs:input_weights (Results 1 – 8 of 8) sorted by relevance
/external/tensorflow/tensorflow/lite/kernels/ |
D | basic_rnn.cc | 65 const TfLiteTensor* input_weights; in Prepare() local 67 context, GetInputSafe(context, node, kWeightsTensor, &input_weights)); in Prepare() 81 const int num_units = input_weights->dims->data[0]; in Prepare() 83 input_weights->dims->data[1]); in Prepare() 84 TF_LITE_ENSURE_EQ(context, input_weights->dims->data[0], bias->dims->data[0]); in Prepare() 90 TF_LITE_ENSURE_TYPES_EQ(context, input_weights->type, in Prepare() 107 const bool is_hybrid = IsHybridOp(input, input_weights); in Prepare() 120 input_quantized->type = input_weights->type; in Prepare() 131 hidden_state_quantized->type = input_weights->type; in Prepare() 201 const TfLiteTensor* input_weights, in EvalFloat() argument [all …]
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D | unidirectional_sequence_rnn.cc | 66 const TfLiteTensor* input_weights; in Prepare() local 68 context, GetInputSafe(context, node, kWeightsTensor, &input_weights)); in Prepare() 87 const int num_units = input_weights->dims->data[0]; in Prepare() 89 input_weights->dims->data[1]); in Prepare() 90 TF_LITE_ENSURE_EQ(context, input_weights->dims->data[0], bias->dims->data[0]); in Prepare() 96 TF_LITE_ENSURE_TYPES_EQ(context, input_weights->type, in Prepare() 114 const bool is_hybrid = IsHybridOp(input, input_weights); in Prepare() 127 input_quantized->type = input_weights->type; in Prepare() 138 hidden_state_quantized->type = input_weights->type; in Prepare() 208 const TfLiteTensor* input_weights, in EvalFloat() argument [all …]
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/external/rnnoise/src/ |
D | rnn_reader.c | 116 INPUT_ARRAY(name->input_weights, name->nb_inputs * name->nb_neurons); \ in rnnoise_model_from_file() 125 INPUT_ARRAY(name->input_weights, name->nb_inputs * name->nb_neurons * 3); \ in rnnoise_model_from_file() 145 free((void *) model->name->input_weights); \ in rnnoise_model_free() 152 free((void *) model->name->input_weights); \ in rnnoise_model_free()
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D | rnn.h | 46 const rnn_weight *input_weights; member 54 const rnn_weight *input_weights; member
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D | rnn.c | 92 sum += layer->input_weights[j*stride + i]*input[j]; in compute_dense() 125 sum += gru->input_weights[j*stride + i]*input[j]; in compute_gru() 135 sum += gru->input_weights[N + j*stride + i]*input[j]; in compute_gru() 145 sum += gru->input_weights[2*N + j*stride + i]*input[j]; in compute_gru()
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/external/libopus/src/ |
D | mlp.c | 92 gemm_accum(output, layer->input_weights, N, M, stride, input); in compute_dense() 119 gemm_accum(z, gru->input_weights, N, M, stride, input); in compute_gru() 127 gemm_accum(r, &gru->input_weights[N], N, M, stride, input); in compute_gru() 137 gemm_accum(h, &gru->input_weights[2*N], N, M, stride, input); in compute_gru()
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D | mlp.h | 38 const opus_int8 *input_weights; member 46 const opus_int8 *input_weights; member
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/external/tensorflow/tensorflow/lite/toco/graph_transformations/ |
D | quantize.cc | 267 const auto& input_weights = model->GetArray(op.inputs[weights_input_index]); in ChooseQuantizationForOperatorInput() local 269 !input_weights.quantization_params) { in ChooseQuantizationForOperatorInput() 276 const auto input_weights_scale = input_weights.quantization_params->scale; in ChooseQuantizationForOperatorInput()
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