W3cubDocs

/TensorFlow 2.3

tf.keras.backend.local_conv2d

View source on GitHub

Apply 2D conv with un-shared weights.

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'.

© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/keras/backend/local_conv2d