tf.keras.backend.local_conv2d
Apply 2D conv with un-shared weights.
tf.keras.backend.local_conv2d(
inputs, kernel, kernel_size, strides, output_shape, data_format=None
)
| 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'. |