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tf.keras.backend.local_conv2d

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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'.

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Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/keras/backend/local_conv2d