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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _construct_w(self, inputs):
 """Construct the convolution weight matrix. Figures out the shape of the weight matrix, initialize it, and return it. Args: inputs: A Tensor of shape `data_format` and of type `tf.float16`, `tf.bfloat16` or `tf.float32`. Returns: w: A weight matrix of the same type as `inputs` and of shape [kernel_shape, 1, 1]. """

    weight_shape = self._kernel_shape + (1, 1)

    if "w" not in self._initializers:
      self._initializers["w"] = create_weight_initializer(weight_shape[:2],
                                                          dtype=inputs.dtype)

    w = tf.get_variable("w",
                        shape=weight_shape,
                        dtype=inputs.dtype,
                        initializer=self._initializers["w"],
                        partitioner=self._partitioners.get("w", None),
                        regularizer=self._regularizers.get("w", None))
    return w