#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright (c) 2021 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

import onnx
from .base_operator import QuantOperatorBase
from onnxruntime.quantization.quant_utils import QuantizedValueType
from onnx import onnx_pb as onnx_proto
from neural_compressor.adaptor.ox_utils.util import QuantizedValue
'''
    Quantize Gather
'''


class GatherQuant(QuantOperatorBase):
    def __init__(self, onnx_quantizer, onnx_node):
        super().__init__(onnx_quantizer, onnx_node)

    def quantize(self):
        node = self.node
        assert (node.op_type == "Gather")
        if (not self.quantizer.is_valid_quantize_weight(node.input[0])):
            super().quantize()
            return

        (quantized_input_names, zero_point_names, scale_names, nodes) = \
            self.quantizer.quantize_inputs(node, [0])

        node.name = node.name + "_quant" if node.name != "" else ""
        gather_new_output = node.output[0] + "_quantized"

        # Create an entry for this quantized value
        q_output = QuantizedValue(node.output[0], gather_new_output, scale_names[0], 
                                  zero_point_names[0],
                                  QuantizedValueType.Input)
        self.quantizer.quantized_value_map[node.output[0]] = q_output

        gather_original_output = node.output[0]
        node.output[0] = gather_new_output
        node.input[0] = quantized_input_names[0]
        nodes.append(node)

        self.quantizer.new_nodes += nodes
