def get_default_args(**kw):
default_dict = {
"precision":
fixed_point(32, 0),
"target":
VHDLBackend(),
"output_file":
"mult_array.vhd",
"entity_name":
"mult_array",
"language":
VHDL_Code,
"Method":
ReductionMethod.Wallace_4to2,
"pipelined":
False,
"dummy_mode":
False,
"booth_mode":
False,
"method":
ReductionMethod.Wallace,
"op_expr":
multiplication_descriptor_parser("FS9.0xFS13.0"),
"stage_height_limit": [None],
"passes": [
("beforepipelining:size_datapath"),
("beforepipelining:rtl_legalize"),
("beforepipelining:unify_pipeline_stages"),
],
}
default_dict.update(kw)
return DefaultEntityArgTemplate(**default_dict)
def get_default_args(**kw):
default_mapping = {
"extra_digit": 0,
"sign_magnitude": False,
"pipelined": False
}
default_mapping.update(kw)
return DefaultEntityArgTemplate(**default_mapping)
def get_default_args(**kw):
root_arg = {
"entity_name": "new_entity_pass",
"output_file": "ut_entity_pass.c",
"width": 32,
"precision": ML_Int32
}
root_arg.update(kw)
return DefaultEntityArgTemplate(**root_arg)
def get_default_args(width=32, entity_name="my_lzc", **kw):
return DefaultEntityArgTemplate(precision=ML_Int32,
debug_flag=False,
target=vhdl_backend.VHDLBackend(),
output_file="my_lzc.vhd",
entity_name=entity_name,
language=VHDL_Code,
width=width,
**kw)
def get_default_args(**kw):
default_dict = {
"precision": ML_Binary32,
"target": VHDLBackend(),
"output_file": "my_fp_div.vhd",
"entity_name": "my_fp_div",
"language": VHDL_Code,
"pipelined": False,
}
default_dict.update(kw)
return DefaultEntityArgTemplate(**default_dict)
def get_default_args(**kw):
default_dict = {
"precision": ML_Int32,
"debug_flag": False,
"target": VHDLBackend(),
"output_file": "ut_rtl_report.vhd",
"entity_name": "ut_rtl_report",
"language": VHDL_Code,
}
default_dict.update(kw)
return DefaultEntityArgTemplate(**default_dict)
def get_default_args(**kw):
default_arg_map = {
"precision": HdlVirtualFormat(ML_Binary32),
"pipelined": False,
"output_file": "fp_adder.vhd",
"entity_name": "fp_adder",
"language": VHDL_Code,
"passes": [("beforecodegen:size_datapath")],
}
default_arg_map.update(**kw)
return DefaultEntityArgTemplate(**default_arg_map)
def get_default_args(width=32, **kw):
""" generate default argument template """
return DefaultEntityArgTemplate(
precision=ML_Int32,
debug_flag=False,
target=VHDLBackend(),
output_file="ut_fixed_point_position.vhd",
entity_name="ut_fixed_point_position",
language=VHDL_Code,
width=width,
passes=[("beforecodegen:size_datapath")],
)
def get_default_args(width=32, **kw):
""" generate default argument template """
return DefaultEntityArgTemplate(
precision=ML_Int32,
debug_flag=False,
target=VHDLBackend(),
output_file="my_adapative_entity.vhd",
entity_name="my_adaptative_entity",
language=VHDL_Code,
width=width,
passes=[("beforecodegen:size_datapath"),
("beforecodegen:rtl_legalize"), ("beforecodegen:dump")],
)
def get_default_args(**kw):
default_arg_map = {
"io_formats": {
"scale": HdlVirtualFormat(ML_Binary32),
"quantized_input": FIX32,
"offset_input": FIX32,
"result": FIX32
},
"pipelined": False,
"output_file": "dequantizer.vhd",
"entity_name": "dequantizer",
"language": VHDL_Code,
"passes": ["beforecodegen:size_datapath", "beforecodegen:rtl_legalize"],
}
default_arg_map.update(**kw)
return DefaultEntityArgTemplate(**default_arg_map)
def get_default_args(width=32, **kw):
""" generate default argument template """
return DefaultEntityArgTemplate(
precision=ML_Int32,
debug_flag=False,
target=VHDLBackend(),
output_file="ut_sub_component.vhd",
entity_name="ut_sub_component",
language=VHDL_Code,
width=width,
passes=[
("beforepipelining:size_datapath"),
("beforepipelining:rtl_legalize"),
("beforepipelining:unify_pipeline_stages"),
],
)
def get_default_args(**kw):
""" generate default argument structure for BipartiteApprox """
default_dict = {
"target":
VHDLBackend(),
"output_file":
"my_bipartite_approx.vhd",
"entity_name":
"my_bipartie_approx",
"language":
VHDL_Code,
"function":
lambda x: 1.0 / x,
"interval":
Interval(1, 2),
"pipelined":
False,
"precision":
fixed_point(1, 15, signed=False),
"disable_sub_testing":
False,
"disable_sv_testing":
False,
"alpha":
6,
"beta":
5,
"gamma":
5,
"guard_bits":
3,
"passes": [
"beforepipelining:size_datapath",
"beforepipelining:rtl_legalize",
"beforepipelining:unify_pipeline_stages"
],
}
default_dict.update(kw)
return DefaultEntityArgTemplate(**default_dict)