para_gen Namespace Reference

Functions
def	convert_to_x4_weights (weights)
def	convert_q7_q15_weights (weights)

Variables
int	vec_dim = 64
int	row_dim = 32
	update_weight = np.zeros((row_dim,vec_dim), dtype=int)
	reset_weight = np.zeros((row_dim,vec_dim), dtype=int)
	hidden_weight = np.zeros((row_dim,vec_dim), dtype=int)
	update_bias = np.zeros((row_dim), dtype=int)
	reset_bias = np.zeros((row_dim), dtype=int)
	hidden_bias = np.zeros((row_dim), dtype=int)
	input_data1 = np.zeros((vec_dim-row_dim), dtype=int)
	input_data2 = np.zeros((vec_dim-row_dim), dtype=int)
	history_data = np.zeros((row_dim), dtype=int)
	outfile = open("riscv_nnexamples_gru_test_data.h", "w")
	weight = np.reshape(update_weight, (row_dim, vec_dim, 1, 1))
def	new_weight = convert_to_x4_weights(weight)
	sep
	format

Function Documentation

convert_q7_q15_weights()

def para_gen.convert_q7_q15_weights

(

weights

)

convert_to_x4_weights()

def para_gen.convert_to_x4_weights

(

weights

)

Variable Documentation

format

para_gen.format

hidden_bias

para_gen.hidden_bias = np.zeros((row_dim), dtype=int)

hidden_weight

para_gen.hidden_weight = np.zeros((row_dim,vec_dim), dtype=int)

history_data

para_gen.history_data = np.zeros((row_dim), dtype=int)

input_data1

para_gen.input_data1 = np.zeros((vec_dim-row_dim), dtype=int)

input_data2

para_gen.input_data2 = np.zeros((vec_dim-row_dim), dtype=int)

new_weight

def para_gen.new_weight = convert_to_x4_weights(weight)

outfile

para_gen.outfile = open("riscv_nnexamples_gru_test_data.h", "w")

reset_bias

para_gen.reset_bias = np.zeros((row_dim), dtype=int)

reset_weight

para_gen.reset_weight = np.zeros((row_dim,vec_dim), dtype=int)

row_dim

int para_gen.row_dim = 32

sep

para_gen.sep

update_bias

para_gen.update_bias = np.zeros((row_dim), dtype=int)

update_weight

para_gen.update_weight = np.zeros((row_dim,vec_dim), dtype=int)

vec_dim

int para_gen.vec_dim = 64

weight

para_gen.weight = np.reshape(update_weight, (row_dim, vec_dim, 1, 1))