tf.inv(x, name=None) Computes the reciprocal of x element-wise. I.e., \(y = 1 / x\). Args: x: A Tensor. Must be one of the following types: half, float32, float64, int32, int64, complex64, complex128. name: A name for the operation (optional). Returns: A Tensor. Has the same type as x.

tf.is_non_decreasing(x, name=None) Returns True if x is non-decreasing. Elements of x are compared in row-major order. The tensor [x[0],...] is non-decreasing if for every adjacent pair we have x[i] <= x[i+1]. If x has less than two elements, it is trivially non-decreasing. See also: is_strictly_increasing Args: x: Numeric Tensor. name: A name for this operation (optional). Defaults to "is_non_decreasing" Returns: Boolean Tensor, equal to True iff x is non-decreasing. Raises: TypeError

tf.invert_permutation(x, name=None) Computes the inverse permutation of a tensor. This operation computes the inverse of an index permutation. It takes a 1-D integer tensor x, which represents the indices of a zero-based array, and swaps each value with its index position. In other words, for an output tensor y and an input tensor x, this operation computes the following: y[x[i]] = i for i in [0, 1, ..., len(x) - 1] The values must include 0. There can be no duplicate values or negative values

tf.InteractiveSession.close() Closes an InteractiveSession.

tf.image.transpose_image(image) Transpose an image by swapping the first and second dimension. See also transpose(). Args: image: 3-D tensor of shape [height, width, channels] Returns: A 3-D tensor of shape [width, height, channels] Raises: ValueError: if the shape of image not supported.

class tf.InteractiveSession A TensorFlow Session for use in interactive contexts, such as a shell. The only difference with a regular Session is that an InteractiveSession installs itself as the default session on construction. The methods Tensor.eval() and Operation.run() will use that session to run ops. This is convenient in interactive shells and IPython notebooks, as it avoids having to pass an explicit Session object to run ops. For example: sess = tf.InteractiveSession() a = tf.constant

tf.InteractiveSession.__init__(target='', graph=None, config=None) Creates a new interactive TensorFlow session. If no graph argument is specified when constructing the session, the default graph will be launched in the session. If you are using more than one graph (created with tf.Graph() in the same process, you will have to use different sessions for each graph, but each graph can be used in multiple sessions. In this case, it is often clearer to pass the graph to be launched explicitly to

tf.image.sample_distorted_bounding_box(image_size, bounding_boxes, seed=None, seed2=None, min_object_covered=None, aspect_ratio_range=None, area_range=None, max_attempts=None, use_image_if_no_bounding_boxes=None, name=None) Generate a single randomly distorted bounding box for an image. Bounding box annotations are often supplied in addition to ground-truth labels in image recognition or object localization tasks. A common technique for training such a system is to randomly distort an image wh

tf.image.resize_nearest_neighbor(images, size, align_corners=None, name=None) Resize images to size using nearest neighbor interpolation. Args: images: A Tensor. Must be one of the following types: uint8, int8, int16, int32, int64, half, float32, float64. 4-D with shape [batch, height, width, channels]. size: A 1-D int32 Tensor of 2 elements: new_height, new_width. The new size for the images. align_corners: An optional bool. Defaults to False. If true, rescale input by (new_height - 1) / (

tf.image.rot90(image, k=1, name=None) Rotate an image counter-clockwise by 90 degrees. Args: image: A 3-D tensor of shape [height, width, channels]. k: A scalar integer. The number of times the image is rotated by 90 degrees. name: A name for this operation (optional). Returns: A rotated 3-D tensor of the same type and shape as image.