TensorFlow 2.0 Beta is available Learn more

tf.keras.backend.local_conv2d

Apply 2D conv with un-shared weights.

Aliases:

  • tf.compat.v1.keras.backend.local_conv2d
  • tf.compat.v2.keras.backend.local_conv2d
  • tf.keras.backend.local_conv2d
tf.keras.backend.local_conv2d(
    inputs,
    kernel,
    kernel_size,
    strides,
    output_shape,
    data_format=None
)
View source on GitHub

Arguments:

  • inputs: 4D tensor with shape: (batch_size, filters, new_rows, new_cols) if data_format='channels_first' or 4D tensor with shape: (batch_size, new_rows, new_cols, filters) if data_format='channels_last'.
  • kernel: the unshared weight for convolution, with shape (output_items, feature_dim, filters).
  • kernel_size: a tuple of 2 integers, specifying the width and height of the 2D convolution window.
  • strides: a tuple of 2 integers, specifying the strides of the convolution along the width and height.
  • output_shape: a tuple with (output_row, output_col).
  • data_format: the data format, channels_first or channels_last.

Returns:

A 4D tensor with shape: (batch_size, filters, new_rows, new_cols) if data_format='channels_first' or 4D tensor with shape: (batch_size, new_rows, new_cols, filters) if data_format='channels_last'.