#!/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.
"""MaxPool Operator."""

from neural_compressor.adaptor.ox_utils.operators.ops import op_registry, Operator, QOperator, qop_registry

@op_registry(op_types="MaxPool")
class MaxPoolOperator(Operator):
    """MaxPool Operator."""

    def __init__(self, onnx_quantizer, onnx_node):
        """Initialization."""
        super(MaxPoolOperator, self).__init__(onnx_quantizer, onnx_node)
    
    def quantize_check(self):
        """Check if quantizaion can be done."""
        node = self.node
        # if opset version is less than 12, just no change
        if self.quantizer.opset_version < 12: # pragma: no cover
            return False

        if not self.quantizer.is_valid_quantize_weight(node.input[0]): # pragma: no cover
            return False
            
        return True

    def quantize(self):
        """Do quantizaion."""
        node = self.node
        self.quantizer.quantize_inputs(self.node, direct_int8=True)
        if not self.disable_qdq_for_node_output or self.quantizer.mode != 'qdq':
            self.quantizer.quantize_outputs(self.node, direct_int8=True)
        node.name = node.name + "_quant"

    def convert_check(self, convert_format):
        """Check if conversion can be done."""
        node = self.node
        assert convert_format in ['static'], \
            "convert format for {} should be in ['static']".format(node.op_type)

        children = self.quantizer.model.get_children(node)
        if len(children) == 0 or not node.name.endswith('_quant'): # pragma: no cover
            return False
        return True

    def convert(self, convert_format):
        """Convert to QOperator format."""
        node = self.node
        parent = self.quantizer.model.get_parents(node)[0]
        children = self.quantizer.model.get_children(node)
        if parent.op_type != 'DequantizeLinear' or \
            all([i.op_type != 'QuantizeLinear' for i in children]): # pragma: no cover
            return
        node.input[0] = parent.input[0]
        node.output[0] = node.output[0] + '_quantized'
        for child in children:
            if child.op_type == 'QuantizeLinear':
                self.quantizer.remove_nodes.append(child)
                for n in self.quantizer.model.get_children(child):
                    self.quantizer.model.replace_node_input(n,
                                    child.output[0], node.output[0])

        self.quantizer.remove_nodes.append(parent)

@qop_registry(op_types="MaxPool")
class QMaxPoolOperator(QOperator):
    """QMaxPool Operator."""

    def __init__(self, onnx_node, children, initializers):
        """Initialization."""
        super().__init__(onnx_node, children, initializers)