tf.nn.conv3d_backprop_filter_v2(input, filter_sizes, out_backprop, strides, padding, name=None)

tf.nn.conv3d_backprop_filter_v2(input, filter_sizes, out_backprop, strides, padding, name=None)

See the guide: Neural Network > Convolution

Computes the gradients of 3-D convolution with respect to the filter.

Args:

  • input: A Tensor. Must be one of the following types: float32, float64, int64, int32, uint8, uint16, int16, int8, complex64, complex128, qint8, quint8, qint32, half. Shape [batch, depth, rows, cols, in_channels].
  • filter_sizes: A Tensor of type int32. An integer vector representing the tensor shape of filter, where filter is a 5-D [filter_depth, filter_height, filter_width, in_channels, out_channels] tensor.
  • out_backprop: A Tensor. Must have the same type as input. Backprop signal of shape [batch, out_depth, out_rows, out_cols, out_channels].
  • strides: A list of ints that has length >= 5. 1-D tensor of length 5. The stride of the sliding window for each dimension of input. Must have strides[0] = strides[4] = 1.
  • padding: A string from: "SAME", "VALID". The type of padding algorithm to use.
  • name: A name for the operation (optional).

Returns:

A Tensor. Has the same type as input.

Defined in tensorflow/python/ops/gen_nn_ops.py.