concepts.dsl.dsl_types.ScalarValueType#

class ScalarValueType[source]#

Bases: TensorValueTypeBase

Methods

`assignment_type`()	Return the value type for assignment.
`downcast_compatible`(other[, ...])	Check if the type is downcast-compatible with the other type; that is, if this type is a subtype of the other type.
`from_tensor`(tensor)	Create a value type from a pytorch tensor.
`is_intrinsically_quantized`()	Return whether the value type can be quantized.
`long_str`()	Return the long string representation of the type.
`ndim`()	Return the number of dimensions of the value type.
`set_parent_type`(parent_type)
`short_str`()	Return the short string representation of the type.
`size`()	Return the total size of the value type.
`size_tuple`()	Return the size of the value type as a tuple.
`tensor_dtype`()	Return the corresponding PyTorch tensor dtype.
`unwrap_alias`()

Attributes

`INTRINSICALLY_QUANTIZED_DTYPES`
`TENSOR_DTYPE_MAPPING`
`TENSOR_DTYPE_QUANTIZED`
`alias`	An optional alias of the type.
`base_typename`	Return the typename of the base type.
`element_type`	The element type of the type.
`is_batched_list_type`	Return whether the type is a multidimensional list type.
`is_list_type`	Return whether the type is a list type.
`is_object_type`	Return whether the type is an object type.
`is_pyobj_value_type`	Return whether the type is a Python object value type.
`is_scalar_value_type`
`is_sequence_type`	Return whether the type is a sequence type.
`is_tensor_value_type`	Return whether the type is a tensor value type.
`is_tuple_type`	Return whether the type is a tuple type.
`is_uniform_sequence_type`
`is_value_type`	Return whether the type is a value type.
`is_vector_value_type`
`is_wrapped_value_type`
`parent_type`	The parent type of the type.
`parent_typename`	Return the typename of the parent type.
`quantized`	Whether the tensor is quantized.
`typename`	The (full) typename of the type.

__init__(typename)[source]#

Initialize the type.

Parameters:

typename – The name of the type.
alias – The alias of the type.

__new__(**kwargs)#

assignment_type()#

Return the value type for assignment.

Return type:: TypeBase

downcast_compatible(other, allow_self_list=False, allow_list=False)#

Check if the type is downcast-compatible with the other type; that is, if this type is a subtype of the other type.

Parameters:

other (TypeBase) – the other type.
allow_self_list (bool) – if True, this type can be a list type derived from the other type.
allow_list (bool) – if True, the other type can be a list type derived from the type.

Return type:

bool

static from_tensor(tensor)#

Create a value type from a pytorch tensor.

Parameters:: tensor (Tensor) – the tensor.
Returns:: the tensor value type.
Return type:: TensorValueTypeBase

is_intrinsically_quantized()[source]#

Return whether the value type can be quantized. In this project, quantizable means we can transform the value into a single integer scalar. Therefore, only BOOL-valued and INTxx-valued tensors are quantizable.

Returns:: True if the value type can be quantized.
Return type:: bool

long_str()#

Return the long string representation of the type.

Return type:: str

ndim()[source]#

Return the number of dimensions of the value type.

Return type:: int

set_parent_type(parent_type)#

Parameters:: parent_type (TypeBase)

short_str()#

Return the short string representation of the type.

Return type:: str

size()[source]#

Return the total size of the value type.

Return type:: int

size_tuple()[source]#

Return the size of the value type as a tuple.

Return type:: Tuple[int]

tensor_dtype()[source]#

Return the corresponding PyTorch tensor dtype.

Return type:: dtype

unwrap_alias()#

INTRINSICALLY_QUANTIZED_DTYPES = ['bool', 'int32', 'int64']#

TENSOR_DTYPE_MAPPING = {'bool': torch.int64, 'float32': torch.float32, 'float64': torch.float64, 'int32': torch.int32, 'int64': torch.int64}#

TENSOR_DTYPE_QUANTIZED = {'bool': True, 'float32': False, 'float64': False, 'int32': True, 'int64': True}#

property alias: str | None#: An optional alias of the type.

property base_typename#: Return the typename of the base type.

property element_type: TypeBase | None#: The element type of the type.

property is_batched_list_type: bool#: Return whether the type is a multidimensional list type.

property is_list_type: bool#: Return whether the type is a list type.

property is_object_type: bool#: Return whether the type is an object type.

property is_pyobj_value_type: bool#: Return whether the type is a Python object value type.

property is_scalar_value_type#

property is_sequence_type: bool#: Return whether the type is a sequence type.

property is_tensor_value_type#: Return whether the type is a tensor value type.

property is_tuple_type: bool#: Return whether the type is a tuple type.

property is_uniform_sequence_type: bool#

property is_value_type#: Return whether the type is a value type.

property is_vector_value_type: bool#

property is_wrapped_value_type: bool#

property parent_type: TypeBase | None#: The parent type of the type.

property parent_typename#: Return the typename of the parent type.

property quantized: bool#: Whether the tensor is quantized.

property typename: str#: The (full) typename of the type.