tf.FixedLenFeature.__getstate__()

tf.FixedLenFeature.__getstate__() Exclude the OrderedDict from pickling

tf.FixedLenFeature.__getnewargs__()

tf.FixedLenFeature.__getnewargs__() Return self as a plain tuple. Used by copy and pickle.

tf.FixedLenFeature.shape

tf.FixedLenFeature.shape Alias for field number 0

tf.FixedLenFeature.dtype

tf.FixedLenFeature.dtype Alias for field number 1

tf.FixedLenFeature.default_value

tf.FixedLenFeature.default_value Alias for field number 2

tf.FixedLenFeature

class tf.FixedLenFeature Configuration for parsing a fixed-length input feature. To treat sparse input as dense, provide a default_value; otherwise, the parse functions will fail on any examples missing this feature. Fields: shape: Shape of input data. dtype: Data type of input. default_value: Value to be used if an example is missing this feature. It must be compatible with dtype.

tf.fill()

tf.fill(dims, value, name=None) Creates a tensor filled with a scalar value. This operation creates a tensor of shape dims and fills it with value. For example: # Output tensor has shape [2, 3]. fill([2, 3], 9) ==> [[9, 9, 9] [9, 9, 9]] Args: dims: A Tensor of type int32. 1-D. Represents the shape of the output tensor. value: A Tensor. 0-D (scalar). Value to fill the returned tensor. name: A name for the operation (optional). Returns: A Tensor. Has the same type a

tf.FIFOQueue.__init__()

tf.FIFOQueue.__init__(capacity, dtypes, shapes=None, names=None, shared_name=None, name='fifo_queue') Creates a queue that dequeues elements in a first-in first-out order. A FIFOQueue has bounded capacity; supports multiple concurrent producers and consumers; and provides exactly-once delivery. A FIFOQueue holds a list of up to capacity elements. Each element is a fixed-length tuple of tensors whose dtypes are described by dtypes, and whose shapes are optionally described by the shapes argumen

tf.FIFOQueue

class tf.FIFOQueue A queue implementation that dequeues elements in first-in first-out order. See tf.QueueBase for a description of the methods on this class.

tf.fft3d()

tf.fft3d(input, name=None) Compute the 3-dimensional discrete Fourier Transform over the inner-most 3 dimensions of input. Args: input: A Tensor of type complex64. A complex64 tensor. name: A name for the operation (optional). Returns: A Tensor of type complex64. A complex64 tensor of the same shape as input. The inner-most 3 dimensions of input are replaced with their 3D Fourier Transform.