tf.keras.backend.local_conv2d

Apply 2D conv with un-shared weights.

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.

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'.