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[/] [artificial_neural_network/] [trunk/] [ANN_kernel/] [RTL_VHDL_files/] [layers_pkg.vhd] - Rev 7
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---------------------------------------------------------------------------------- -- Company: CEI - UPM -- Engineer: David Aledo -- -- Create Date: 01.10.2015 -- Design Name: Configurable ANN -- Pakage Name: layers_pkg -- Project Name: -- Target Devices: -- Tool Versions: -- Description: define array types for generics, functions to give them values from -- string generics, and other help functions -- Dependencies: -- -- Revision: -- Revision 0.01 - File Created -- Additional Comments: -- ---------------------------------------------------------------------------------- library IEEE; use IEEE.STD_LOGIC_1164.all; --library proc_common_v3_00_a; -- Deprecated libray from XPS tool --use proc_common_v3_00_a.proc_common_pkg.all; package layers_pkg is -- Array types for generics: type int_vector is array (natural range <>) of integer; -- Generic integer vector type ltype_vector is array (integer range <>) of string(1 to 2); -- Layer type vector type ftype_vector is array (integer range <>) of string(1 to 6); -- Activation function type vector -- Note: these strings cannot be unconstrined -- Functions to assign values to vector types from string generics: -- Arguments: -- str_v : string to be converted -- n : number of elements of the vector -- Return: assigned vector function assign_ints(str_v : string; n : integer) return int_vector; function assign_ltype(str_v : string; n : integer) return ltype_vector; function assign_ftype(str_v : string; n : integer) return ftype_vector; -- Other functions: -- Argument: c : character to be checked -- Return: TRUE if c is 0, 1, 2, 3, 4, 5, 6, 7, 8 or 9 function is_digit(c : character) return boolean; -- Base two logarithm for int_vector: -- Arguments: -- v : integer vector -- n : number of elements of the vector -- Return : integer vector of the base two logarithms of each elment of v function log2(v : int_vector; n : integer) return int_vector; -- Calculate the total weight and bias memory address length: -- Arguments: -- NumIn : number of inputs of the network -- NumN : number of neurons of each layer -- n : number of layers (number of elements of NumN) -- Return: total weight and bias memory address length (integer) function calculate_addr_l(NumIn : integer; NumN : int_vector; n : integer) return integer; -- Assign the weight and bias memory address lenght of each layer: -- Arguments: -- NumIn : number of inputs of the network -- NumN : number of neurons of each layer -- n : number of layers (number of elements of NumN and the return integer vector) -- Return: weight and bias memory address lenght of each layer (integer vector) function assign_addrl(NumIn : integer; NumN : int_vector; n : integer) return int_vector; -- Calculate the maximum of the multiplications of two vectors element by element -- Arguments: -- v1 : input vector 1 -- v2 : input vector 2 -- Return: maximum of the multiplications of two vectors element by element function calculate_max_mul(v1 : int_vector; v2 : int_vector) return integer; -- Returns the max value of the input integer vector: function calculate_max(v : int_vector) return integer; -- Adding needed functions from the deprecated libray proc_common_v3_00_a: function max2 (num1, num2 : integer) return integer; function log2(x : natural) return integer; end layers_pkg; package body layers_pkg is function max2 (num1, num2 : integer) return integer is begin if num1 >= num2 then return num1; else return num2; end if; end function max2; -- Function log2 -- returns number of bits needed to encode x choices -- x = 0 returns 0 -- x = 1 returns 0 -- x = 2 returns 1 -- x = 4 returns 2, etc. function log2(x : natural) return integer is variable i : integer := 0; variable val: integer := 1; begin if x = 0 then return 0; else for j in 0 to 29 loop -- for loop for XST if val >= x then null; else i := i+1; val := val*2; end if; end loop; -- Fix per CR520627 XST was ignoring this anyway and printing a -- Warning in SRP file. This will get rid of the warning and not -- impact simulation. -- synthesis translate_off assert val >= x report "Function log2 received argument larger" & " than its capability of 2^30. " severity failure; -- synthesis translate_on return i; end if; end function log2; function is_digit(c : character) return boolean is begin case c is when '0' | '1' | '2' | '3' | '4' | '5' | '6' | '7' | '8' | '9' => return true; when others => return false; end case; end is_digit; -- Assign values to a integer vector from a string: -- Arguments: -- str_v : string to be converted -- n : number of elements of the vector -- Return: assigned integer vector function assign_ints(str_v : string; n : integer) return int_vector is variable i : integer := n-1; ---- element counter variable d_power : integer := 1; -- decimal power variable ret : int_vector(n-1 downto 0) := (others => 0); -- return value begin for c in str_v'length downto 1 loop -- read every character in str_v if str_v(c) = ' ' then -- a space separates a new element assert i > 0 report "Error in assign_ints: number of elements in string is greater than n." severity error; i := i -1; -- decrease element counter to start calculate a new element d_power := 1; -- reset the decimal power to 1 else assert is_digit(str_v(c)) -- assert the new character is a digit report "Error in assign_ints: character " & str_v(c) & " is not a digit." severity error; -- add the value of the new charactar to the element calculation ( + ("<new_digit>" - "0") * d_power): ret(i) := ret(i) + (character'pos(str_v(c))-character'pos('0'))*d_power; d_power := d_power*10; -- increase the decimal power for the next digit end if; end loop; assert i = 0 report "Error in assign_ints: number of elements in string is less than n." severity error; return ret; end assign_ints; -- Assign values to an activation function type vector from a string: -- Arguments: -- str_v : string to be converted -- n : number of elements of the vector -- Return: assigned activation function type vector function assign_ftype(str_v : string; n : integer) return ftype_vector is variable i : integer := 0; -- element counter variable l : integer := 1; -- element length counter variable ret : ftype_vector(n-1 downto 0) := (others => "linear"); -- return value begin for c in 1 to str_v'length loop -- read every character in str_v if str_v(c) = ' ' then -- a space separates a new element i := i +1; -- increase element counter to start calculate a new element l := 1; -- reset element length counter else ret(i)(l) := str_v(c); l := l +1; -- increase element length counter end if; end loop; assert i = n-1 report "Error in assign_ftype: number of elements in string is less than n." severity error; return ret; end assign_ftype; -- Assign values to an layer type vector from a string: -- Arguments: -- str_v : string to be converted -- n : number of elements of the vector -- Return: assigned layer type vector function assign_ltype(str_v : string; n : integer) return ltype_vector is variable i : integer := 0; -- element counter variable l : integer := 1; -- element length counter variable ret : ltype_vector(n-1 downto 0) := (others => "SP"); -- return value begin for c in 1 to str_v'length loop if str_v(c) = ' ' then -- a space separates a new element i := i +1; -- increase element counter to start calculate a new element l := 1; -- reset element length counter else assert str_v(c) = 'P' or str_v(c) = 'S' report "Error in assign_ltype: character " & str_v(c) & " is not 'P' (parallel) or 'S' (serial)." severity error; ret(i)(l) := str_v(c); l := l +1; -- increase element length counter end if; end loop; assert i = n-1 report "Error in assign_ltype: number of elements do not coincide with number of introduced elements." severity error; return ret; end assign_ltype; -- Calculate the total weight and bias memory address length: -- Arguments: -- NumIn : number of inputs of the network -- NumN : number of neurons of each layer -- n : number of layers (number of elements of NumN) -- Return: total weight and bias memory address length (integer) function calculate_addr_l(NumIn : integer; NumN : int_vector; n : integer) return integer is -- matrix + b_sel variable addr_l : integer := log2(NumIn)+log2(NumN(0)); -- return value. Initialized with the weight memory length of the first layer begin -- Calculate the maximum of the weight memory length: for i in 1 to n-1 loop addr_l := max2( addr_l, log2(NumN(i-1))+log2(NumN(i)) ); end loop; addr_l := addr_l +1; -- add bias select bit return addr_l; end calculate_addr_l; -- Base two logarithm for int_vector: -- Arguments: -- v : integer vector -- n : number of elements of the vector -- Return : integer vector of the base two logarithms of each elment of v function log2(v : int_vector; n : integer) return int_vector is variable ret : int_vector(n-1 downto 0); -- return value begin -- for each element of v, calculate its base two logarithm: for i in 0 to n-1 loop ret(i) := log2(v(i)); end loop; return ret; end log2; -- Assign the weight and bias memory address lenght of each layer: -- Arguments: -- NumIn : number of inputs of the network -- NumN : number of neurons of each layer -- n : number of layers (number of elements of NumN and the return integer vector) -- Return: weight and bias memory address lenght of each layer (integer vector) function assign_addrl(NumIn : integer; NumN : int_vector; n : integer) return int_vector is variable ret : int_vector(n-1 downto 0); -- return value begin ret(0) := log2(NumIn)+log2(NumN(0)); -- Weight memory length of the first layer for i in 1 to n-1 loop ret(i) := log2(NumN(i-1))+log2(NumN(i)); end loop; return ret; end assign_addrl; -- Returns the max value of the input integer vector: function calculate_max(v : int_vector) return integer is variable ac_max : integer := 0; -- return value begin for i in 0 to v'length-1 loop ac_max := max2(ac_max,v(i)); end loop; return ac_max; end calculate_max; -- Calculate the maximum of the multiplications of two vectors element by element -- Arguments: -- v1 : input vector 1 -- v2 : input vector 2 -- Return: maximum of the multiplications of two vectors element by element function calculate_max_mul(v1 : int_vector; v2 : int_vector) return integer is variable ac_max : integer := 0; begin assert v1'length = v2'length report "Error in calculate_max_mul: vector's length do not coincide." severity error; for i in 0 to v1'length-1 loop ac_max := max2(ac_max,v1(i)*v2(i)); end loop; return ac_max; end calculate_max_mul; end layers_pkg;
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