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        "author": "Ben Reynwar",
        "author_email": "ben@reynwar.net",
        "bugtrack_url": null,
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        "description": "\nslvcodec\n========\n\nslvcodec is a tool that analyzes VHDL and generates:\n\n  * Functions to convert arbitrary VHDL types to and from std_logic_vector.\n\n  * Generate testbenches for entities that read inputs from a file, and\n    write outputs to a file.\n\n  * Utilities so that unit tests for VHDL code can easily to be written\n    in python.\n\n\nGeneration of functions to convert to and from std_logic_vector\n---------------------------------------------------------------\n\nHere's an example VHDL package.\n\n.. code:: vhdl\n\n    library ieee;\n    use ieee.numeric_std.all;\n\n    package complex is\n\n      constant FIXED_WIDTH: natural := 8;\n      subtype fixed_t is unsigned(FIXED_WIDTH-1 downto 0);\n\n      type complex_t is record\n        real: fixed_t;\n        imag: fixed_t;\n      end record;\n\n      type array_of_complex is array(natural range <>) of complex_t;\n\n    end package;\n\nThe following python script is used to generate a helper package that contains\nfunctions to convert the types to and from std_logic_vector.\n\n.. code:: python\n\n    import os\n\n    from slvcodec import filetestbench_generator\n\n\n    thisdir = os.path.dirname(__file__)\n\n\n    def make_slvcodec_package():\n        complex_pkg_fn = os.path.join(thisdir, 'complex_pkg.vhd')\n        directory = os.path.join(thisdir, 'generated')\n        os.mkdir(directory)\n        filetestbench_generator.add_slvcodec_files(directory, [complex_pkg_fn])\n\n\n    if __name__ == '__main__':\n        make_slvcodec_package()\n\nHere is what the generated VHDL looks like.\n\n.. code:: vhdl\n\n    library ieee;\n    use ieee.std_logic_1164.all;\n    use ieee.numeric_std.all;\n    use work.complex.all;\n    use work.slvcodec.all;\n\n    package complex_slvcodec is\n\n\n      function to_slvcodec (constant data: array_of_complex) return std_logic_vector;\n      function from_slvcodec (constant slv: std_logic_vector) return array_of_complex;\n      constant fixed_t_slvcodecwidth: natural := fixed_width;\n      constant complex_t_slvcodecwidth: natural := 2*fixed_width;\n      function to_slvcodec (constant data: complex_t) return std_logic_vector;\n      function from_slvcodec (constant slv: std_logic_vector) return complex_t;\n\n    end package;\n\n    package body complex_slvcodec is\n\n      function to_slvcodec (constant data: array_of_complex) return std_logic_vector is\n        constant W: natural := complex_t_slvcodecwidth;\n        constant N: natural := data'length;\n        variable slv: std_logic_vector(N*W-1 downto 0);\n      begin\n        for ii in 0 to N-1 loop\n          slv((ii+1)*W-1 downto ii*W) := to_slvcodec(data(ii));\n        end loop;\n        return slv; \n      end function;\n\n      function from_slvcodec (constant slv: std_logic_vector) return array_of_complex is\n        constant W: natural := complex_t_slvcodecwidth;\n        constant N: natural := slv'length/W;\n        variable mapped: std_logic_vector(slv'length-1 downto 0);\n        variable output: array_of_complex(N-1 downto 0);\n      begin\n        mapped := slv;\n        for ii in 0 to N-1 loop\n          output(ii) := from_slvcodec(mapped((ii+1)*W-1 downto ii*W));\n        end loop;\n        return output; \n      end function;\n\n      function to_slvcodec (constant data: complex_t) return std_logic_vector is\n        constant W0: natural := 0;\n        constant W1: natural := W0 + fixed_width;\n        constant W2: natural := W1 + fixed_width;\n        variable slv: std_logic_vector(complex_t_slvcodecwidth-1 downto 0);\n      begin\n        slv(W1-1 downto W0) := to_slvcodec(data.real);\n        slv(W2-1 downto W1) := to_slvcodec(data.imag);\n        return slv; \n      end function;\n\n      function from_slvcodec (constant slv: std_logic_vector) return complex_t is\n        constant W0: natural := 0;\n        constant W1: natural := W0 + fixed_width;\n        constant W2: natural := W1 + fixed_width;\n        variable data: complex_t;\n        variable mapped: std_logic_vector(complex_t_slvcodecwidth-1 downto 0);\n      begin\n        mapped := slv;\n        data.real := from_slvcodec(mapped(W1-1 downto W0)); \n        data.imag := from_slvcodec(mapped(W2-1 downto W1)); \n        return data; \n      end function;\n\n    end package body;\n\n\nGeneration of file-based testbenches\n------------------------------------\n\nHere's an example entity that just returns the magnitude squared of a complex data type\nthat we defined earlier.\n\n.. code:: vhdl\n\n    library ieee;\n    use ieee.numeric_std.all;\n    use work.complex.all;\n\n    entity complex_mag2 is\n      port (\n        i: in complex_t;\n        o: out unsigned(FIXED_WIDTH+1-1 downto 0)\n        );\n    end entity;\n\n    architecture arch of complex_mag2 is\n\n      signal real2: signed(FIXED_WIDTH*2-1 downto 0);\n      signal imag2: signed(FIXED_WIDTH*2-1 downto 0);\n      signal mag2: unsigned(FIXED_WIDTH*2-1 downto 0);\n      signal scaled_mag2: unsigned(FIXED_WIDTH+1-1 downto 0);\n\n    begin\n\n      real2 <= i.real * i.real;\n      imag2 <= i.imag * i.imag;\n      mag2 <= unsigned(real2) + unsigned(imag2);\n\n      scaled_mag2 <= mag2(FIXED_WIDTH*2-1-1 downto FIXED_WIDTH-2);\n\n      o <= scaled_mag2;\n\n    end architecture;\n\nWe can use slvcodec to generate a testbench that reads input data from a file,\nand writes output data to another file.\n\n.. code:: python\n\n    import os\n\n    from slvcodec import filetestbench_generator\n\n\n    thisdir = os.path.dirname(__file__)\n\n\n    def make_slvcodec_package():\n        complex_pkg_fn = os.path.join(thisdir, 'complex_pkg.vhd')\n        directory = os.path.join(thisdir, 'generated')\n        os.mkdir(directory)\n        slvcodec_files = filetestbench_generator.add_slvcodec_files(directory, [complex_pkg_fn])\n        return slvcodec_files\n\n\n    def make_complex_mag2_testbench():\n        base_filenames = [\n            os.path.join(thisdir, 'complex_pkg.vhd'),\n            os.path.join(thisdir, 'complex_mag2.vhd'),\n            ]\n        slvcodec_fns = make_slvcodec_package()\n        with_slvcodec_fns = base_filenames + slvcodec_fns\n        directory = os.path.join(thisdir, 'generated')\n        generated_fns, generated_wrapper_fns, resolved = filetestbench_generator.prepare_files(\n            directory=directory, filenames=with_slvcodec_fns,\n            top_entity='complex_mag2')\n        return generated_fns\n\n\n    if __name__ == '__main__':\n        make_complex_mag2_testbench()\n\n\nThis will generate the following VHDL testbench.\n\n.. code:: vhdl\n\n    library ieee;\n    use ieee.std_logic_1164.all;\n    use work.slvcodec.all;\n    use ieee.numeric_std.all;\n    use work.complex.all;\n    use work.complex_slvcodec.all;\n\n    entity complex_mag2_tb is\n      generic (\n\n        CLOCK_PERIOD: time := 10 ns;\n        RUNNER_CFG: string;\n        OUTPUT_PATH: string\n      );\n    end entity;\n\n    architecture arch of complex_mag2_tb is\n      type t_input is\n    record\n        i: complex_t;\n    end record;\n    type t_output is\n    record\n        o: unsigned((1+fixed_width)-1 downto 0);\n    end record;\n      constant t_input_slvcodecwidth: natural := 2*fixed_width;\n      function to_slvcodec (constant data: t_input) return std_logic_vector;\n      function from_slvcodec (constant slv: std_logic_vector) return t_input;\n      function to_slvcodec (constant data: t_input) return std_logic_vector is\n        constant W0: natural := 0;\n        constant W1: natural := W0 + 2*fixed_width;\n        variable slv: std_logic_vector(t_input_slvcodecwidth-1 downto 0);\n      begin\n        slv(W1-1 downto W0) := to_slvcodec(data.i);\n        return slv; \n      end function;\n\n      function from_slvcodec (constant slv: std_logic_vector) return t_input is\n        constant W0: natural := 0;\n        constant W1: natural := W0 + 2*fixed_width;\n        variable data: t_input;\n        variable mapped: std_logic_vector(t_input_slvcodecwidth-1 downto 0);\n      begin\n        mapped := slv;\n        data.i := from_slvcodec(mapped(W1-1 downto W0)); \n        return data; \n      end function;\n      constant t_output_slvcodecwidth: natural := (1+fixed_width);\n      function to_slvcodec (constant data: t_output) return std_logic_vector;\n      function from_slvcodec (constant slv: std_logic_vector) return t_output;\n      function to_slvcodec (constant data: t_output) return std_logic_vector is\n        constant W0: natural := 0;\n        constant W1: natural := W0 + (1+fixed_width);\n        variable slv: std_logic_vector(t_output_slvcodecwidth-1 downto 0);\n      begin\n        slv(W1-1 downto W0) := to_slvcodec(data.o);\n        return slv; \n      end function;\n\n      function from_slvcodec (constant slv: std_logic_vector) return t_output is\n        constant W0: natural := 0;\n        constant W1: natural := W0 + (1+fixed_width);\n        variable data: t_output;\n        variable mapped: std_logic_vector(t_output_slvcodecwidth-1 downto 0);\n      begin\n        mapped := slv;\n        data.o := from_slvcodec(mapped(W1-1 downto W0)); \n        return data; \n      end function;\n      signal input_data: t_input;\n      signal output_data: t_output;\n      signal input_slv: std_logic_vector(t_input_slvcodecwidth-1 downto 0);\n      signal output_slv: std_logic_vector(t_output_slvcodecwidth-1 downto 0);\n      signal clk: std_logic;\n      signal read_clk: std_logic;\n      signal write_clk: std_logic;\n    begin\n\n      input_data <= from_slvcodec(input_slv);\n      output_slv <= to_slvcodec(output_data);\n\n      file_reader: entity work.ReadFile\n        generic map(FILENAME => OUTPUT_PATH & \"/indata.dat\",\n                    PASSED_RUNNER_CFG => RUNNER_CFG,\n                    WIDTH => t_input_slvcodecwidth)\n        port map(clk => read_clk,\n                 out_data => input_slv);\n\n      file_writer: entity work.WriteFile\n        generic map(FILENAME => OUTPUT_PATH & \"/outdata.dat\",\n                    WIDTH => t_output_slvcodecwidth)\n        port map(clk => write_clk,\n                 in_data => output_slv);\n\n      clock_generator: entity work.ClockGenerator\n        generic map(CLOCK_PERIOD => CLOCK_PERIOD,\n                    CLOCK_OFFSET => 0 ns\n                    )\n        port map(clk => clk);\n\n      read_clock_generator: entity work.ClockGenerator\n        generic map(CLOCK_PERIOD => CLOCK_PERIOD,\n                    CLOCK_OFFSET => CLOCK_PERIOD/10\n                    )\n        port map(clk => read_clk);\n\n      write_clock_generator: entity work.ClockGenerator\n        generic map(CLOCK_PERIOD => CLOCK_PERIOD,\n                    CLOCK_OFFSET => 4*CLOCK_PERIOD/10\n                    )\n        port map(clk => write_clk);\n\n      dut: entity work.complex_mag2\n        port map(\n                 i => input_data.i,\n    o => output_data.o\n                 );\n\n    end architecture;\n\n\nBut generating a test bench that just reads and writes the input and output data\nto and from files isn't particularly useful unless we have a way of generating the\ninput data, and checking the output data.  Slvcodec include tools to do this\nwith python.\n\nPython-based testing\n--------------------\n\nWe define a python class with a ``make_input_data`` method that returns an iterable of\ndictionaries specifying the input data, and a ``check_output_data`` method that receives\na list of input_data dictionaries and a list of output data dictionaries, that raises an\nexeception is the output data is incorrect.\n\n.. code:: python\n\n    class ComplexMag2Test:\n\n        def __init__(self, resolved, generics, top_params):\n            # Here we're taking advantage of the fact that when the test is intialized it\n            # has access to the parsed VHDL.  We use that to get the value of the constant\n            # FIXED_WIDTH that is defined in complex_pkg.vhd.\n            self.fixed_width = resolved['packages']['complex'].constants['fixed_width'].value()\n            self.max_fixed = pow(2, self.fixed_width-1)-1\n            self.min_fixed = -pow(2, self.fixed_width-1)\n            self.n_data = 100\n\n        def fixed_to_float(self, f):\n            r = f / pow(2, self.fixed_width-2)\n            return r\n\n        def make_input_data(self, seed=None, n_data=3000):\n            input_data = [{\n                'i': {'real': random.randint(self.min_fixed, self.max_fixed),\n                      'imag': random.randint(self.min_fixed, self.max_fixed)},\n            } for i in range(self.n_data)]\n\n            return input_data\n\n        def check_output_data(self, input_data, output_data):\n            inputs = [self.fixed_to_float(d['i']['real']) + self.fixed_to_float(d['i']['imag']) * 1j\n                      for d in input_data]\n            input_float_mag2s = [abs(v)*abs(v) for v in inputs] \n            outputs = [self.fixed_to_float(d['o']) for d in output_data]\n            differences = [abs(expected - actual) for expected, actual in zip(input_float_mag2s, outputs)]\n            allowed_error = 1/pow(2, self.fixed_width-2)\n            assert all([d < allowed_error for d in differences])\n\n\nWe then use ``slvcodec.test_utils.register_test_with_vunit`` to generate an appropriate testbench and input\ndata file, and register the produced test with vunit.  VUnit can then be run as normal.\n\n\n.. code:: python\n\n    from slvcodec import test_utils, config\n    import os\n\n    if __name__ == '__main__':\n        random.seed(0)\n        # Initialize vunit with command line parameters.\n        vu = config.setup_vunit()\n        # Set up logging.\n        config.setup_logging(vu.log_level)\n        # Get filenames for test\n        this_dir = os.path.dirname(os.path.realpath(__file__))\n        filenames = [\n            os.path.join(this_dir, 'complex_pkg.vhd'),\n            os.path.join(this_dir, 'complex_mag2.vhd'),\n            ]\n        # Register the test with VUnit.\n        test_output_directory = os.path.join(this_dir, 'generated')\n        test_utils.register_test_with_vunit(\n            vu=vu,\n            directory=test_output_directory,\n            filenames=filenames,\n            top_entity='complex_mag2',\n            all_generics=[{}],\n            test_class=ComplexMag2Test,\n            top_params={},\n            )\n        # Run the tests with VUnit\n        vu.set_sim_option('disable_ieee_warnings', True)\n        vu.main()\n\n\n",
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