// Exact CPU pad specialization: copy contiguous blocks instead of converting
// every scalar index to/from coordinates. Complex tensors use the original.
module.exports = function install(face) {
  var backend = face.tf.backend(), original = backend.pad, enabled = false;
  backend.pad = function (input, paddings, constantValue) {
    if (!enabled || input.dtype === 'complex64' || !input.shape.length) return original.call(this, input, paddings, constantValue);
    var rank = input.shape.length, outShape = [], lastPadded = -1;
    for (var axis = 0; axis < rank; axis++) {
      if (!paddings[axis] || paddings[axis].length !== 2) return original.call(this, input, paddings, constantValue);
      var before = paddings[axis][0], after = paddings[axis][1];
      if (before < 0 || after < 0 || Math.floor(before) !== before || Math.floor(after) !== after) return original.call(this, input, paddings, constantValue);
      if (before || after) lastPadded = axis;
      outShape.push(input.shape[axis] + before + after);
    }
    var output = face.tf.buffer(outShape, input.dtype), source = this.readSync(input.dataId), target = output.values;
    if (constantValue !== 0) target.fill(constantValue);
    var firstBlockAxis = lastPadded < 0 ? 0 : lastPadded;
    var blockSize = 1, padOffset = 0;
    for (var dimension = 0; dimension < rank; dimension++) {
      padOffset += paddings[dimension][0] * (dimension === rank - 1 ? 1 : output.strides[dimension]);
      if (dimension >= firstBlockAxis) blockSize *= input.shape[dimension];
    }
    var blocks = input.size / blockSize;
    for (var block = 0; block < blocks; block++) {
      var remainder = block, destination = padOffset;
      for (var outer = firstBlockAxis - 1; outer >= 0; outer--) {
        var coordinate = remainder % input.shape[outer]; remainder = Math.floor(remainder / input.shape[outer]);
        destination += coordinate * output.strides[outer];
      }
      target.set(source.subarray(block * blockSize, (block + 1) * blockSize), destination);
    }
    return output.toTensor();
  };
  return { setEnabled: function (value) { enabled = value === true; } };
};