o ?e-@sdZddlmZddlmZddlmZddlmZddlmZddlmZddlm Z dd lm Z dd l m Z dd l m Z dd lmZed d dgde je ddddZedgde jdddZdS)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)v1NcCt|d||gT}tj|dd}tj|tjdd}t|}tjt ||kd||gdd}t |g|}||d }t jt||j|jj|d |}tj||||dWd S1s`wYd S) 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`. r valuenamesizedtyperNeed value.shape >= size, got Z summarizermaxvalseedN)r name_scopeconvert_to_tensorrint32rshaperAssertr reduce_allrwith_dependenciesrZrandom_uniformrmaxslicerrrrr checklimitoffsetr*f/home/www/facesmatcher.com/pyenv/lib/python3.10/site-packages/tensorflow/python/ops/random_crop_ops.pyr s*%   $zimage.stateless_random_cropcCr) aRandomly crops a tensor to a given size in a deterministic manner. Slices a shape `size` portion out of `value` at a uniformly chosen offset. Requires `value.shape >= size`. If a dimension should not be cropped, pass the full size of that dimension. For example, RGB images can be cropped with `size = [crop_height, crop_width, 3]`. Guarantees the same results given the same `seed` independent of how many times the function is called, and independent of global seed settings (e.g. `tf.random.set_seed`). Usage Example: >>> image = [[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]] >>> seed = (1, 2) >>> tf.image.stateless_random_crop(value=image, size=(1, 2, 3), seed=seed) Args: value: Input tensor to crop. size: 1-D tensor with size the rank of `value`. seed: A shape [2] Tensor, the seed to the random number generator. Must have dtype `int32` or `int64`. (When using XLA, only `int32` is allowed.) name: A name for this operation (optional). Returns: A cropped tensor of the same rank as `value` and shape `size`. r rrrrrrrrrN)rrrrrrr rr!rr"rr#r Zstateless_random_uniformrr$r%r&r*r*r+stateless_random_cropUs*#   $r,)NN)N)__doc__Ztensorflow.python.frameworkrrZtensorflow.python.opsrrrrrr Ztensorflow.python.utilr r Z tensorflow.python.util.tf_exportr Zadd_dispatch_supportZdeprecated_endpointsr r,r*r*r*r+s&            4