AVh-:dZddlmZddlmZddlmZddlmZddlmZddlmZddlm Z dd lm Z dd l m Z dd l m Z dd lmZed d dge j e j"dddZedge j ddZy)z&Operations for random tensor cropping.)dtypes)ops) array_ops)control_flow_assert)control_flow_ops)math_ops) random_ops)stateless_random_ops) deprecation)dispatch) tf_exportzimage.random_crop random_crop)v1Ncptj|d||g5}tj|d}tj|tjd}t j |}tjtj||k\d||gd}tj|g|}||z d z}tjt j ||j|jj | |z}t j"||||cd d d S#1swYy xYw) aRandomly crops a tensor to a given size. Slices a shape `size` portion out of `value` at a uniformly chosen offset. Requires `value.shape >= size`. If a dimension should not be cropped, pass the full size of that dimension. For example, RGB images can be cropped with `size = [crop_height, crop_width, 3]`. Example usage: >>> image = [[1, 2, 3], [4, 5, 6]] >>> result = tf.image.random_crop(value=image, size=(1, 3)) >>> result.shape.as_list() [1, 3] For producing deterministic results given a `seed` value, use `tf.image.stateless_random_crop`. Unlike using the `seed` param with `tf.image.random_*` ops, `tf.image.stateless_random_*` ops guarantee the same results given the same seed independent of how many times the function is called, and independent of global seed settings (e.g. tf.random.set_seed). Args: value: Input tensor to crop. size: 1-D tensor with size the rank of `value`. seed: Python integer. Used to create a random seed. See `tf.random.set_seed` for behavior. name: A name for this operation (optional). Returns: A cropped tensor of the same rank as `value` and shape `size`. rvaluenamesizedtyperNeed value.shape >= size, got  summarizermaxvalseedN)r name_scopeconvert_to_tensorrint32rshaperAssertr reduce_allrwith_dependenciesr random_uniformrmaxslicerrrrr"checklimitoffsets U/home/dcms/DCMS/lib/python3.12/site-packages/tensorflow/python/ops/random_crop_ops.pyrrs J ~~dME4=9;T  ! !%g 6E  V\\ GD OOE "E  & &ETM* )5$7 E  . .w >E DL1 E  & &jjzz~~   F ??5&$T :;;; DD,,D5zimage.stateless_random_cropcptj|d||g5}tj|d}tj|tjd}t j |}tjtj||k\d||gd}tj|g|}||z d z}tjt j ||j|jj | |z}t j"||||cd d d S#1swYy xYw) aRandomly crops a tensor to a given size in a deterministic manner. Slices a shape `size` portion out of `value` at a uniformly chosen offset. Requires `value.shape >= size`. If a dimension should not be cropped, pass the full size of that dimension. For example, RGB images can be cropped with `size = [crop_height, crop_width, 3]`. Guarantees the same results given the same `seed` independent of how many times the function is called, and independent of global seed settings (e.g. `tf.random.set_seed`). Usage Example: >>> image = [[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]] >>> seed = (1, 2) >>> tf.image.stateless_random_crop(value=image, size=(1, 2, 3), seed=seed) Args: value: Input tensor to crop. size: 1-D tensor with size the rank of `value`. seed: A shape [2] Tensor, the seed to the random number generator. Must have dtype `int32` or `int64`. (When using XLA, only `int32` is allowed.) name: A name for this operation (optional). Returns: A cropped tensor of the same rank as `value` and shape `size`. rrrrrrrrrrN)rrr rr!rr"rr#rr$rr%r stateless_random_uniformrr'r(r)s r-stateless_random_cropr1Us F ~~dME4=9;T  ! !%g 6E  V\\ GD OOE "E  & &ETM* )5$7 E  . .w >E DL1 E ! : :jjzz~~   F ??5&$T :;;;r.)NN)N)__doc__tensorflow.python.frameworkrrtensorflow.python.opsrrrrr r tensorflow.python.utilr r tensorflow.python.util.tf_exportr add_dispatch_supportdeprecated_endpointsrr1r-r;s-.++52*,6.+6 $7#GH !!!-01;1I1;h (R0 0;10;r: