aesara.tensor.TensorType

class aesara.tensor.TensorType(dtype: str | dtype, shape: Iterable[bool | int | None] | None = None, name: str | None = None, broadcastable: Iterable[bool] | None = None)

Symbolic Type representing numpy.ndarrays.

__init__(dtype: str | dtype, shape: Iterable[bool | int | None] | None = None, name: str | None = None, broadcastable: Iterable[bool] | None = None)

Parameters:

• dtype – A NumPy dtype (e.g. "int64").

• shape – The static shape information. Nones are used to indicate unknown shape values for their respective dimensions. If shape is a list of bools, the True elements of are converted to 1s and the False values are converted to Nones.

• name – Optional name for this type.

Methods

__init__(dtype[, shape, name, broadcastable])	param dtype: A NumPy dtype (e.g. "int64").
c_cleanup(name, sub)	Return C code to clean up after CLinkerType.c_extract().
c_code_cache_version()	Return a tuple of integers indicating the version of this type.
c_compile_args(**kwargs)	Return a list of recommended compile arguments for code returned by other methods in this class.
c_declare(name, sub[, check_input])	Return C code to declare variables that will be instantiated by CLinkerType.c_extract().
c_element_type()	Return the name of the primitive C type of items into variables handled by this type.
c_extract(name, sub[, check_input])	Return C code to extract a PyObject * instance.
c_extract_out(name, sub[, check_input])	Return C code to extract a PyObject * instance.
c_header_dirs(**kwargs)	Return a list of header search paths required by code returned by this class.
c_headers(**kwargs)	Return a list of header files required by code returned by this class.
c_init(name, sub)	Return C code to initialize the variables that were declared by CLinkerType.c_declare().
c_init_code(**kwargs)	Return a list of code snippets to be inserted in module initialization.
c_is_simple()	Return True for small or builtin C types.
c_lib_dirs(**kwargs)	Return a list of library search paths required by code returned by this class.
c_libraries(**kwargs)	Return a list of libraries required by code returned by this class.
c_literal(data)	Provide a C literal string value for the specified data.
c_no_compile_args(**kwargs)	Return a list of incompatible gcc compiler arguments.
c_support_code(**kwargs)	Return utility code for use by a Variable or Op.
c_sync(name, sub)	Return C code to pack C types back into a PyObject.
clone([dtype, shape, broadcastable])	Clone a copy of this type with the given arguments/keyword values, if any.
convert_variable(var)	Produce a Variable that's compatible with both self and var.type, if possible.
dtype_specs()	Return a tuple (python type, c type, numpy typenum) that corresponds to self.dtype.
filter(data[, strict, allow_downcast])	Convert data to something which can be associated to a TensorVariable.
filter_inplace(value, storage[, strict, ...])	Return data or an appropriately wrapped/converted data by converting it in-place.
filter_variable(other[, allow_convert])	Convert a other into a Variable with a Type that's compatible with self.
get_shape_info(obj)	Return the information needed to compute the memory size of obj.
get_size(shape_info)	Number of bytes taken by the object represented by shape_info.
in_same_class(otype)	Determine if otype is in the same class of fixed broadcastable types as self.
is_super(otype)	Determine if self is a supertype of otype.
is_valid_value(data[, strict])	Return True for any python object that would be a legal value for a Variable of this Type.
make_constant(value[, name])	Return a new Constant instance of this Type.
make_variable([name])	Return a new Variable instance of this Type.
may_share_memory(a, b)
to_scalar_type()
values_eq(a, b[, force_same_dtype])	Return True if a and b can be considered exactly equal.
values_eq_approx(a, b[, allow_remove_inf, ...])	Return True if a and b can be considered approximately equal.

Attributes

broadcastable	A boolean tuple indicating which dimensions have a shape equal to one.
context_name
dtype_specs_map
filter_checks_isfinite	When this is True, strict filtering rejects data containing numpy.nan or numpy.inf entries.
ndim	The number of dimensions that a Variable`'s values will have at evaluation time.
dtype
shape