ёi/6SSKJr SSKJr SSKrSSKrSSKJr SSKJ r J r SSK J r J r SSKJrJr SS KJr SS KJrJr S S KJrJr \(aSS KJr /rSSjrSSjr\ "SS/05SSj5r\ "SS/5SSj5rSSjrSSSjjr SSSjjr!g)) annotations) TYPE_CHECKINGN)_C_ops)ParamAliasDecoratorparam_one_alias) check_typecheck_variable_and_dtype)in_dynamic_or_pir_mode use_pir_api)Variable) LayerHelpercore)_complex_to_real_dtypeassign)Tensorinputc[US[[RR4S5 [ UR 5n[[R"US55nU$)a Returns the number of dimensions for a tensor, which is a 0-D int32 Tensor. Args: input (Tensor): The input Tensor with shape of :math:`[N_1, N_2, ..., N_k]`, the data type is arbitrary. Returns: Tensor, the output data type is int32.: The 0-D tensor with the dimensions of the input Tensor. Examples: .. code-block:: python >>> import paddle >>> input = paddle.rand((3, 100, 100)) >>> rank = paddle.rank(input) >>> print(rank.numpy()) 3 rint32) r r paddlepirValuelenshapernparray)rndimsouts W/var/www/html/banglarbhumi/venv/lib/python3.13/site-packages/paddle/tensor/attribute.pyrankr!%sI*ug&***:*:;WE  E %) *C Jc[5(a[R"U5nSUlU$[ US/SQS5 [ S 0[ 5D6nURSS9nURSSU0SU0SS 9 SUlU$) a1 Get the shape of the input. .. code-block:: text Case1: Given N-D Tensor: input = [ [1, 2, 3, 4], [5, 6, 7, 8] ] Then: input.shape = [2, 4] Case2: Given SelectedRows: input.rows = [0, 4, 19] input.height = 20 input.value = [ [1, 2], [3, 4], [5, 6] ] # inner tensor Then: input.shape = [3, 2] Args: input (Tensor): The input can be N-D Tensor or SelectedRows with data type bool, bfloat16, float16, float32, float64, int32, int64. If input variable is type of SelectedRows, returns the shape of it's inner tensor. Returns: Tensor: The shape of the input variable. Examples: .. code-block:: pycon >>> import numpy as np >>> import paddle >>> paddle.enable_static() >>> inputs = paddle.static.data(name="x", shape=[3, 100, 100], dtype="float32") >>> output = paddle.shape(inputs) >>> exe = paddle.static.Executor(paddle.CPUPlace()) >>> exe.run(paddle.static.default_startup_program()) >>> img = np.ones((3, 100, 100)).astype(np.float32) >>> res = exe.run(paddle.static.default_main_program(), feed={'x': img}, fetch_list=[output]) >>> print(res) [array([ 3, 100, 100], dtype=int64)] Tr) booluint16float16float32float64rint64 complex64 complex128r% float8_e4m3fn float8_e5m2rrdtypeInputOut)typeinputsoutputs stop_gradient)r) r rshape64r5r rlocals"create_variable_for_type_inference append_op)rrhelpers r rrAs^nnU#      # &1177g7FU#CL  ! r"xc*[U[R[RR[R R 45(d[S[U535eURnU[RRR:H=(do U[RRR:H=(dA U[RR:H=(d U[RR:HnU$)aReturn whether x is a tensor of complex data type(complex64 or complex128). .. note:: Alias Support: The parameter name ``input`` can be used as an alias for ``x``. For example, ``input=tensor_x`` is equivalent to ``x=tensor_x``. Args: x (Tensor): The input tensor. input: An alias for ``x`` , with identical behavior. Returns: bool: True if the data type of the input is complex data type, otherwise false. Examples: .. code-block:: python >>> import paddle >>> x = paddle.to_tensor([1 + 2j, 3 + 4j]) >>> print(paddle.is_complex(x)) True >>> x = paddle.to_tensor([1.1, 1.2]) >>> print(paddle.is_complex(x)) False >>> x = paddle.to_tensor([1, 2, 3]) >>> print(paddle.is_complex(x)) False )Expected Tensor, but received type of x: ) isinstancerrstaticr rr TypeErrorr2r/rVarDescVarType COMPLEX64 COMPLEX128DataType)r;r/is_complex_dtypes r is_complexrGsB  FMM6==116::3C3C D  CDG9MNN GGE %%/// - DLL((33 3 - DMM++ + - DMM,, ,  r"ct[U[R[RR[R R 45(d[S[U535eURnU[RRR:H=(Gd U[RRR:H=(d U[RRR:H=(d U[RRR :H=(d U[R"R$:H=(de U[R"R&:H=(dA U[R"R(:H=(d U[R"R*:HnU$)a Returns whether the dtype of `x` is one of paddle.float64, paddle.float32, paddle.float16, and paddle.bfloat16. .. note:: Alias Support: The parameter name ``input`` can be used as an alias for ``x``. For example, ``is_floating_point(input=tensor_x)`` is equivalent to ``is_floating_point(x=tensor_x)``. Args: x (Tensor): The input tensor. alias: ``input``. Returns: bool: True if the dtype of `x` is floating type, otherwise false. Examples: .. code-block:: python >>> import paddle >>> x = paddle.arange(1., 5., dtype='float32') >>> y = paddle.arange(1, 5, dtype='int32') >>> print(paddle.is_floating_point(x)) True >>> print(paddle.is_floating_point(y)) False r=)r>rrr?r rrr@r2r/rrArBFP32FP64FP16BF16rEFLOAT32FLOAT64FLOAT16BFLOAT16)r;r/ is_fp_dtypes r is_floating_pointrRs>6  FMM6==116::3C3C D  CDG9MNN GGE %%*** + + DLL((-- - + DLL((-- - + DLL((-- - + DMM)) )  + DMM)) )  + DMM)) )  + DMM** * r"c.[U[R[RR[R R 45(d[S[U535eURnSn[5(dU[RRR:H=(d U[RRR:H=(d U[RRR :H=(dU U[RRR":H=(d' U[RRR$:HnU$U[R&R:H=(d U[R&R:H=(de U[R&R :H=(dA U[R&R":H=(d U[R&R$:HnU$)a,Return whether x is a tensor of integral data type. Args: x (Tensor): The input tensor. Returns: bool: True if the data type of the input is integer data type, otherwise false. Examples: .. code-block:: python >>> import paddle >>> x = paddle.to_tensor([1 + 2j, 3 + 4j]) >>> print(paddle.is_integer(x)) False >>> x = paddle.to_tensor([1.1, 1.2]) >>> print(paddle.is_integer(x)) False >>> x = paddle.to_tensor([1, 2, 3]) >>> print(paddle.is_integer(x)) True r=F)r>rrr?r rrr@r2r/r rrArBUINT8INT8INT16INT32INT64rE)r;r/ is_int_dtypes r is_integerrZs4  FMM6==116::3C3C D  CDG9MNN GGEL == T\\))// / 3 ,,111 3 ,,222 3 ,,222 3 ,,222   T]](( ( , *** , +++ , +++ , +++  r"c [5(a[R"U5$[USSS/S5 [ S 0[ 5D6nUR [UR55S9nURSSU0SU0S9 U$) aw Returns a new Tensor containing real values of the input Tensor. Args: x (Tensor): the input Tensor, its data type could be complex64 or complex128. name (str|None, optional): The default value is None. Normally there is no need for user to set this property. For more information, please refer to :ref:`api_guide_Name` . Returns: Tensor: a Tensor containing real values of the input Tensor. Examples: .. code-block:: python >>> import paddle >>> x = paddle.to_tensor( ... [[1 + 6j, 2 + 5j, 3 + 4j], [4 + 3j, 5 + 2j, 6 + 1j]]) >>> print(x) Tensor(shape=[2, 3], dtype=complex64, place=Place(cpu), stop_gradient=True, [[(1+6j), (2+5j), (3+4j)], [(4+3j), (5+2j), (6+1j)]]) >>> real_res = paddle.real(x) >>> print(real_res) Tensor(shape=[2, 3], dtype=float32, place=Place(cpu), stop_gradient=True, [[1., 2., 3.], [4., 5., 6.]]) >>> real_t = x.real() >>> print(real_t) Tensor(shape=[2, 3], dtype=float32, place=Place(cpu), stop_gradient=True, [[1., 2., 3.], [4., 5., 6.]]) r;r*r+realr.Xr1r2r3r4)r\) r rr\r rr7r8r input_dtyper9r;namer:rs r r\r\%H{{1~ C+|)DfM0vx077(););)=>8  fc1Xs|L r"c [5(a[R"U5$[USSS/S5 [ S 0[ 5D6nUR [UR55S9nURSSU0SU0S9 U$) a} Returns a new tensor containing imaginary values of input tensor. Args: x (Tensor): the input tensor, its data type could be complex64 or complex128. name (str|None, optional): The default value is None. Normally there is no need for user to set this property. For more information, please refer to :ref:`api_guide_Name` . Returns: Tensor: a tensor containing imaginary values of the input tensor. Examples: .. code-block:: python >>> import paddle >>> x = paddle.to_tensor( ... [[1 + 6j, 2 + 5j, 3 + 4j], [4 + 3j, 5 + 2j, 6 + 1j]]) >>> print(x) Tensor(shape=[2, 3], dtype=complex64, place=Place(cpu), stop_gradient=True, [[(1+6j), (2+5j), (3+4j)], [(4+3j), (5+2j), (6+1j)]]) >>> imag_res = paddle.imag(x) >>> print(imag_res) Tensor(shape=[2, 3], dtype=float32, place=Place(cpu), stop_gradient=True, [[6., 5., 4.], [3., 2., 1.]]) >>> imag_t = x.imag() >>> print(imag_t) Tensor(shape=[2, 3], dtype=float32, place=Place(cpu), stop_gradient=True, [[6., 5., 4.], [3., 2., 1.]]) r;r*r+imagr.r]r1r^)rd) r rrdr rr7r8rr_r9r`s r rdrdUrbr")rrreturnr)r;rrer$)N)r;rraz str | Nonerer)" __future__rtypingrnumpyrrrpaddle.utils.decorator_utilsrrbase.data_feederr r base.frameworkr r common_ops_importr frameworkrrcreationrrr__all__r!rrGrRrZr\rdr"r rqs#  MC@()4 8PfcG9%&+'+\#w )!)X2j-`-r"