Lines Matching refs:inputs
122 * Inputs:
151 * Inputs (explicit padding):
166 * Inputs (implicit padding):
195 * Inputs:
197 * For inputs of {@link ANEURALNETWORKS_TENSOR_QUANT8_ASYMM} type, all
231 * Inputs (explicit padding):
252 * Inputs (implicit padding):
305 * Inputs (explicit padding):
327 * Inputs (explicit padding):
373 * Inputs:
395 * Inputs:
423 * Inputs:
443 * Inputs:
456 * outputs = activation(inputs * weights? + bias)
464 * Inputs:
513 * Inputs:
546 * Inputs:
570 * Inputs (explicit padding):
585 * Inputs (implicit padding):
607 * each component is divided by the weighted, squared sum of inputs within depth_radius.
620 * Inputs:
644 * Inputs:
657 * Inputs:
706 * The class has the following independently optional inputs:
717 * Inputs:
807 * Inputs (explicit padding):
822 * Inputs (implicit padding):
858 * Inputs:
883 * Inputs:
903 * Inputs:
923 * Inputs:
942 * Inputs:
963 * Inputs:
977 * outputs = state = activation(inputs * input_weights + state * recurrent_weights + bias)
980 * * ?input_weights? is a weight matrix that multiplies the inputs;
991 * Inputs:
1036 * Inputs:
1065 * Inputs:
1096 * memory = push(conv1d(inputs, weights_feature, feature_dim,
1101 * * ?weights_feature? is a weights matrix that processes the inputs (by
1118 * Inputs:
1158 * Inputs:
1338 * learning model to a set of inputs.
1343 * <li>Associate data to the model inputs with
1500 * To build a model that can accomodate inputs of various sizes, as you may want
1589 * @param inputCount The number of entries in the inputs array.
1590 * @param inputs An array of indexes identifying each operand.
1594 * The operands specified by inputs and outputs must have been
1606 const uint32_t* inputs, uint32_t outputCount,
1610 * Specfifies which operands will be the model's inputs and outputs.
1616 * @param inputCount The number of entries in the inputs array.
1617 * @param inputs An array of indexes identifying the input operands.
1621 * The operands specified by inputs and outputs must have been
1631 const uint32_t* inputs, uint32_t outputCount,
