AVhg TdZddlmZddlmZddlmZddlmZddlmZdZdZ d Z y ) zTensor shape utilities.)context)dtypes)ops) tensor_shape) tensor_utilcd}t|ttfr6|stj}n#tt t j|}tj||dS)zBConvert to an int32 or int64 tensor, defaulting to int32 if empty.Nshape)dtypename) isinstancetuplelistrint32maprdimension_valuerconvert_to_tensor)r r s P/home/dcms/DCMS/lib/python3.12/site-packages/tensorflow/python/ops/shape_util.py shape_tensorrsO %t}% lle C 44e<=e  uE @@Tc>trtjstjj rc|j jsHtj|r2t|}tj|}|j|yyyyyy)a&Sets the shape of `tensor` to the `shape`'s constant value, if inferrable. This is a temporary workaround to fix shape inference across functional op boundaries. E.g. ```python shape = tf.constant([3]) @tf.function def f(): u = tf.random_uniform(shape) return u ``` If we were to rely solely on C++ shape inference, the shape of `u` inside `f` would be unknown because C++ shape inference is not aware of the outer graph and all it sees is a Placeholder node when backtracing the captured tensor for `shape`. `maybe_set_static_shape` computes the static shape value of `shape` by traversing the `FuncGraph` boundaries and sets the correct shape. A longer term solution would be to fix C++ shape inference. Args: tensor: A tensor. shape: A shape tensor. N) _ENABLE_MAYBE_SET_STATIC_SHAPErexecuting_eagerlyrget_default_graphbuilding_functionr is_fully_definedr is_tensorrconstant_value_as_shape set_shape)tensorr const_shapes rmaybe_set_static_shaper!*s6%W-F-F-H // ,, ' ' )k.C.CE.J  E55er&s,+.+43 A "& "r