def __init__(self):
super().__init__()
self.name = 'full'
self.args.add_arg('shape', values.NoneValue())
self.args.add_arg('fill_value', values.NoneValue())
self.args.add_arg('dtype', values.NoneValue())
self.args.add_arg('order', values.StrValue('C'))
def __init__(self):
super().__init__()
self.name = 'array'
self.args.add_arg('object', values.NoneValue())
self.args.add_arg('dtype', values.NoneValue())
self.args.add_arg('copy', values.BoolValue(True))
self.args.add_arg('order', values.StrValue('K'))
self.args.add_arg('subok', values.BoolValue(False))
self.args.add_arg('ndmin', values.NumberValue(0))
def generate_copied_value(value: 'values.Value'):
assert(isinstance(value, values.Value))
if isinstance(value, values.NumberValue):
copied = values.NumberValue(value.internal_value)
copied.dtype = value.dtype
return copied
if isinstance(value, values.TensorValue):
copied = values.TensorValue()
copied.value = value.value
copied.shape = value.shape
copied.dtype = value.dtype
return copied
if isinstance(value, values.ListValue):
copied = values.ListValue()
copied.dtype = value.dtype
copied.vtype = value.vtype
if value.internal_value is not None:
copied.internal_value = value.internal_value.copy()
return copied
if isinstance(value, values.NoneValue):
copied = values.NoneValue()
return copied
if isinstance(value, values.BoolValue):
copied = values.BoolValue(value.internal_value)
return copied
if isinstance(value, values.StrValue):
copied = values.StrValue(value.internal_value)
return copied
if isinstance(value, values.RangeValue):
copied = values.RangeValue()
return copied
if isinstance(value, values.TupleValue):
if value.internal_value is not None:
copied = values.TupleValue(value.internal_value.copy())
else:
copied = values.TupleValue(value.internal_value)
copied.dtype = value.dtype
copied.vtype = value.vtype
return copied
if config.show_warnings:
print('Unknown type {} is copied'.format(value))
return values.Value()
def veval_ast_str(astc: 'AstContext', local_field: 'values.Field',
graph: 'Graph'):
'''
Ex. "str"
'''
assert (isinstance(astc.nast, gast.gast.Str))
lineprop = utils.LineProperty(astc.lineno, astc.filename)
value = values.StrValue(astc.nast.s)
ret = values.ValueRef(value)
name = values.create_ref_value_name_with_constant(ret)
ret.name = name
ret.get_value().name = name
return ret
def generate_value_with_same_type(value: 'values.Value', is_dummy_value = False, suffix_type = SuffixType.Unknown):
assert(isinstance(value, values.Value))
ret = None
if isinstance(value, values.TensorValue):
ret = values.TensorValue()
ret.shape = value.shape
ret.dtype = value.dtype
elif isinstance(value, values.NumberValue):
dtype = None
if value.internal_value is None:
dtype = value.dtype
elif isinstance(value.internal_value, int):
dtype = np.array(value.internal_value).dtype
elif isinstance(value.internal_value, float):
dtype = np.array(value.internal_value).dtype
ret = values.NumberValue(None)
ret.dtype = dtype
elif isinstance(value, values.StrValue):
ret = values.StrValue(None)
elif isinstance(value, values.BoolValue):
ret = values.BoolValue(None)
elif isinstance(value, values.ListValue):
ret = values.ListValue(None)
ret.dtype = value.dtype
ret.vtype = value.vtype
elif isinstance(value, values.NoneValue):
ret = values.NoneValue()
elif isinstance(value, values.TupleValue):
ret = values.TupleValue()
ret.dtype = value.dtype
ret.vtype = value.vtype
elif isinstance(value, values.RangeValue):
ret = values.RangeValue()
elif isinstance(value, values.UnknownValue):
ret = values.UnknownValue()
elif ret is None and isinstance(value, values.Value):
ret = values.Value()
else:
assert(False)
assert(ret is not None)
ret.is_dummy_value = is_dummy_value
if suffix_type == SuffixType.Unknown:
ret.name = value.name + '_st'
elif suffix_type == SuffixType.Unused:
ret.name = value.name + '_unused'
elif suffix_type == SuffixType.Dummy:
ret.name = value.name + '_dummy'
elif suffix_type == SuffixType.Input:
ret.name = value.name + '_in'
else:
assert(False)
return ret
def veval(op: 'nodes.BinOpType', left: 'values.Value', right: 'values.Value',
lineprop: 'utils.LineProperty'):
initialize_lazy()
if isinstance(left, values.ListValue):
return functions.generate_value_with_same_type(left)
if isinstance(left, values.TupleValue):
return functions.generate_value_with_same_type(left)
if isinstance(left, values.StrValue):
if not (isinstance(right, values.NumberValue) or isinstance(
right, values.StrValue) or isinstance(right, values.BoolValue)
or isinstance(right, values.TupleValue)):
assert False
if not (left.has_constant_value() or right.has_constant_value()):
assert False
if op == nodes.BinOpType.Add:
if not isinstance(right, values.StrValue):
assert False
return values.StrValue(left.internal_value + right.internal_value)
elif op == nodes.BinOpType.Mod:
right_internal_value = right.internal_value
if isinstance(right, values.TupleValue):
values_ = []
for ref in right_internal_value:
if not (isinstance(ref.get_value(), values.NumberValue)
or isinstance(ref.get_value(), values.StrValue)
or isinstance(ref.get_value(), values.BoolValue)):
assert False
if not ref.get_value().has_constant_value():
assert False
values_.append(ref.get_value())
right_internal_value = tuple(value.internal_value
for value in values_)
return values.StrValue(left.internal_value % right_internal_value)
return values.StrValue("")
if isinstance(right, values.NumberValue) or isinstance(
right, values.TensorValue):
if not isinstance(left, values.NumberValue) and not isinstance(
left, values.TensorValue):
utils.print_warning('Unestimated type is on left', lineprop)
left = values.NumberValue(0.0)
left_type = left.dtype
right_type = right.dtype
if not config.float_restrict:
if left_type == utils.dtype_float64:
left_type = utils.dtype_float32
if right_type == utils.dtype_float64:
right_type = utils.dtype_float32
if left_type is None:
left_type = np.array(0.0, np.float32).dtype
if right_type is None:
right_type = np.array(0.0, np.float32).dtype
result_type = None
for v in binop_type_table:
if v[0] == op and v[1] == left_type and v[2] == right_type:
result_type = v[3]
break
assert (result_type is not None)
if isinstance(right, values.TensorValue):
return functions.generate_value_with_type(right, type_=result_type)
else:
return functions.generate_value_with_type(left, type_=result_type)
return values.Value()
