U ʹj@sddlmZddlmZddlmZmZddlZddlm m Z ddl m Z dZddd d d d d gZddZddZddZdddZdd Zddd ZGdd d ZGdddeeZd ejeejddd Zd!ejeejddd ZdS)")update_wrapper)Number)AnyDictNis_tensor_likegox? broadcast_alllogits_to_probs clamp_probsprobs_to_logits lazy_propertytril_matrix_to_vecvec_to_tril_matrixcstdd|Dstdtdd|Dsttd|D]$}t|tjr>t|j|jdqdq>fdd|D}tj |Stj |S) a Given a list of values (possibly containing numbers), returns a list where each value is broadcasted based on the following rules: - `torch.*Tensor` instances are broadcasted as per :ref:`_broadcasting-semantics`. - numbers.Number instances (scalars) are upcast to tensors having the same size and type as the first tensor passed to `values`. If all the values are scalars, then they are upcasted to scalar Tensors. Args: values (list of `numbers.Number`, `torch.*Tensor` or objects implementing __torch_function__) Raises: ValueError: if any of the values is not a `numbers.Number` instance, a `torch.*Tensor` instance, or an instance implementing __torch_function__ css |]}t|pt|tVqdSN)r isinstancer.0vrX/var/www/html/bwave/python/venv/lib/python3.8/site-packages/torch/distributions/utils.py &sz broadcast_all..zqInput arguments must all be instances of numbers.Number, torch.Tensor or objects implementing __torch_function__.css|]}t|VqdSrrrrrrr+s)dtyperdevicecs&g|]}t|r|n tj|fqSr)rtorchZtensorroptionsrr 1sz!broadcast_all..) all ValueErrordictrZget_default_dtyperTensorrrZbroadcast_tensors)valuesvalue new_valuesrrrrs   cCsBtjr.ttj|||dtj|||dStj|||dS)Nr)r_C_get_tracing_statenormalZzerosZonesemptyZnormal_)shaperrrrr_standard_normal8s  r*cCs0|dkr |S|jd| d}||dS)z Sum out ``dim`` many rightmost dimensions of a given tensor. Args: value (Tensor): A tensor of ``.dim()`` at least ``dim``. dim (int): The number of rightmost dims to sum out. rN)r+)r)Zreshapesum)r#dimZrequired_shaperrr_sum_rightmostBsr.FcCs|rt|Stj|ddS)a Converts a tensor of logits into probabilities. Note that for the binary case, each value denotes log odds, whereas for the multi-dimensional case, the values along the last dimension denote the log probabilities (possibly unnormalized) of the events. r+)r-)rZsigmoidFZsoftmax)Zlogits is_binaryrrrr Ps cCs t|jj}|j|d|dS)N)minmax)rfinforepsclamp)probsr5rrrr \scCs,t|}|r"t|t| St|S)a$ Converts a tensor of probabilities into logits. For the binary case, this denotes the probability of occurrence of the event indexed by `1`. For the multi-dimensional case, the values along the last dimension denote the probabilities of occurrence of each of the events. )r rloglog1p)r7r0Z ps_clampedrrrr asc@s"eZdZdZddZdddZdS)r z Used as a decorator for lazy loading of class attributes. This uses a non-data descriptor that calls the wrapped method to compute the property on first call; thereafter replacing the wrapped method into an instance attribute. cCs||_t||dSr)wrappedrselfr:rrr__init__vszlazy_property.__init__Nc CsD|dkrt|jSt||}W5QRXt||jj||Sr)_lazy_property_and_propertyr:rZ enable_gradsetattr__name__)r<instanceobj_typer#rrr__get__zs   zlazy_property.__get__)N)r@ __module__ __qualname____doc__r=rCrrrrr nsc@seZdZdZddZdS)r>zWe want lazy properties to look like multiple things. * property when Sphinx autodoc looks * lazy_property when Distribution validate_args looks cCst||dSr)propertyr=r;rrrr=sz$_lazy_property_and_property.__init__N)r@rDrErFr=rrrrr>sr>)matdiagreturncCs|jd}tjsH|| ks&||krHtd|d| d|ddtj||jd}||dd|dk}|d|f}|S) z Convert a `D x D` matrix or a batch of matrices into a (batched) vector which comprises of lower triangular elements from the matrix in row order. r+zdiag (z) provided is outside [z, r1z].r.)r)rr%r&rarangerview)rHrInrL tril_maskvecrrrr s " )rPrIrJcCsdd| dd|dd|jddt||ddd}t|jj}tjst|||krt d|jddd t |tj rt| nt|}| |jd dt||f}tj||jd }||dd|dk}||d |f<|S) z Convert a vector or a batch of vectors into a batched `D x D` lower triangular matrix containing elements from the vector in row order. r1r+g?zThe size of last dimension is z which cannot be expressed as z3the lower triangular part of a square D x D matrix.NrK.)r)absrr4rr5r%r&roundrrr!itemZ new_zerosSizerLrrM)rPrIrNr5rHrLrOrrrrs$ 4 " )F)F)r)r) functoolsrnumbersrtypingrrrZtorch.nn.functionalnnZ functionalr/Ztorch.overridesrZeuler_constant__all__rr*r.r r r r rGr>r!intr rrrrrs0    "