o * i)@s UddlmZddlmZddlZddlmZddlZddlm Z ddl m Z m Z ddl mZddlmZddlmZdd lmZer{dd lmZdd lmZdd lmZdd lmZddlmZeeeeeeejeejej fefZ!de"d<Gdddej#Z$dS)) annotations) TYPE_CHECKINGN)_C_ops) check_type convert_dtype)Variable) distribution)in_dynamic_mode)random)Sequence)Union) TypeAlias)Tensor)NestedSequencer _UniformBoundarycsfeZdZUdZded<ded< ddfd d Zgd fdddZdddZdddZdddZ Z S) Uniformaj Uniform distribution with `low` and `high` parameters. Mathematical Details The probability density function (pdf) is .. math:: pdf(x; a, b) = \frac{1}{Z}, \ a <=x >> import paddle >>> from paddle.distribution import Uniform >>> paddle.seed(2023) >>> # Without broadcasting, a single uniform distribution [3, 4]: >>> u1 = Uniform(low=3.0, high=4.0) >>> # 2 distributions [1, 3], [2, 4] >>> u2 = Uniform(low=[1.0, 2.0], high=[3.0, 4.0]) >>> # 4 distributions >>> u3 = Uniform(low=[[1.0, 2.0], [3.0, 4.0]], ... high=[[1.5, 2.5], [3.5, 4.5]]) ... >>> # With broadcasting: >>> u4 = Uniform(low=3.0, high=[5.0, 6.0, 7.0]) >>> # Complete example >>> value_tensor = paddle.to_tensor([0.8], dtype="float32") >>> uniform = Uniform([0.], [2.]) >>> sample = uniform.sample([2]) >>> # a random tensor created by uniform distribution with shape: [2, 1] >>> entropy = uniform.entropy() >>> print(entropy) Tensor(shape=[1], dtype=float32, place=Place(cpu), stop_gradient=True, [0.69314718]) >>> lp = uniform.log_prob(value_tensor) >>> print(lp) Tensor(shape=[1], dtype=float32, place=Place(cpu), stop_gradient=True, [-0.69314718]) >>> p = uniform.probs(value_tensor) >>> print(p) Tensor(shape=[1], dtype=float32, place=Place(cpu), stop_gradient=True, [0.50000000]) rlowhighNrname str | NonereturnNonec szts%t|dtttjttjj t t fdt|dtttjttjj t t fdd|_ d|_ |dur1|nd|_d|_t|tr@t|}t|trIt|}|||r\||_||_t|j|_nWt|trit|trid|_ t|tjr{t|jdvr{|j|_nt|tjrt|jdvr|j|_|||\|_|_|jt|jjkrtj|j|jd|_tj|j|jd|_t|jjdS) NrrrFfloat32T)rfloat64dtype)r rintfloatnpZndarrayrpaddleZpirValuelisttupleall_arg_is_floatZbatch_size_unknownrr isinstanceZ_validate_argsrrrstrZ _to_tensorcastsuper__init__shape)selfrrr __class__g/home/app/PaddleOCR-VL-test/.venv_paddleocr/lib/python3.10/site-packages/paddle/distribution/uniform.pyr(sd      zUniform.__init__rr) Sequence[int]seedrc CsVtst|dttfdt|dtdt|}|jd}t|j|jj}d|vrx||}t||}t |j|jd |d<t |d|j }t j||j|j dd|d }t ||} t ||} | | |j|j} t j| |j|d } | S||}t j||j dd|d t j||j d |j|j} t j| |j|d } |jrt j| ||d S| S) aSGenerate samples of the specified shape. Args: shape (Sequence[int], optional): 1D `int32`. Shape of the generated samples. Defaults to []. seed (int): Python integer number. Returns: Tensor, A tensor with prepended dimensions shape. The data type is float32. r)sampler0Z_samplergg?)rminmaxr0rr)r rr!r"rrrrr)ritemfullrr Zuniform_random_batch_size_likeZreshapeadduniformZzerosr#) r*r)r0rZ batch_shapeZ output_shapeZ fill_shapeZzero_tmpZuniform_random_tmpZzero_tmp_reshapeZuniform_random_tmp_reshapeoutputr-r-r.r1sP      zUniform.samplevaluecCs||j|}tr2|j|k}||jk}t||j}t||j}t||t|j|jS|j d}|j|k}||jk}tj||jd}tj||jd}tj t||t|j|j|dS)zLog probability density/mass function. Args: value (Tensor): The input tensor. Returns: Tensor, log probability.The data type is same with value. Z _log_probrr5) _check_values_dtype_in_probsrr rrr&rrlogrsubtractr*r;Zlb_boolZub_boolZlbZubrr-r-r.log_probs       zUniform.log_probcCs||j|}tr,|j|k}||jk}t||j}t||j}|||j|jS|jd}|j|k}||jk}tj||jd}tj||jd}tj |||j|j|dS)zProbability density/mass function. Args: value (Tensor): The input tensor. Returns: Tensor, probability. The data type is same with value. Z_probsrr5) r<rr rrr&rrrdivider?r-r-r.probss      z Uniform.probscCs |jd}tj|j|j|dS)zShannon entropy in nats. The entropy is .. math:: entropy(low, high) = \\log (high - low) Returns: Tensor, Shannon entropy of uniform distribution.The data type is float32. Z_entropyr5)rrr=rr)r*rr-r-r.entropy1s zUniform.entropy)N)rrrrrrrr)r)r/r0rrr)r;rrr)rr) __name__ __module__ __qualname____doc____annotations__r(r1r@rBrC __classcell__r-r-r+r.r/s LF 6 r)% __future__rtypingrnumpyrZ numpy.typingZnptrrZpaddle.base.data_feederrrZpaddle.base.frameworkrZpaddle.distributionrZpaddle.frameworkr Z paddle.tensorr collections.abcr r Ztyping_extensionsr rZpaddle._typingrrZNDArrayrrrrH Distributionrr-r-r-r.s4