"""
 Copyright (c) 2018-2019 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 logging as log

from extensions.ops.TensorIterator_ops import TensorIteratorCondition
from mo.graph.graph import Graph
from mo.middle.replacement import MiddleReplacementPattern
import numpy as np


class LoopConditionMatcher(MiddleReplacementPattern):
    """
    This pattern match condition for TensorIterator in while loops in TF.
    The structure of pattern without Data nodes between ops. Every node is named as op attribute of this node
    (data nodes is marked by (data)):
                                                                   Const----
                                                                            |
                                                                            v
    Const -> Enter -> Merge ---------------------> Switch -> Identity ->  Add -> NextIteration
                        |                              ^
                        ---> Less ----|                |
                                ^     |                |
    Maximum -> Minimum -> Enter-|     |                |
                 ^                    v                |
Shape -> StridedSlice -> Enter -|    LogicalAnd --> LoopCond (data)
                                v     ^                |
                        ---> Less ----|                |
                        |                              v
    Const -> Enter -> Merge ---------------------> Switch -> Identity ->  Add -> NextIteration
                                                                            ^
                                                                            |
                                                                   Const----
    """
    enabled = True
    graph_condition = [lambda graph: graph.graph['is_cyclic']]

    def run_after(self):
        return []

    def run_before(self):
        from extensions.middle.TensorIteratorMerge import TensorIteratorMerge
        return [TensorIteratorMerge]

    @staticmethod
    def pattern():
        log.debug('+++++++++++++++ ConditionMatching ++++++++++++++++')
        return dict(
            nodes=[
                ('Enter_1_less', dict(kind='op', op='Enter')),
                ('Strided_slice', dict(kind='op', op='StridedSlice')),
                ('Strided_slice_data', dict(kind='data')),
                ('Enter_1_less_data', dict(kind='data')),

                ('Less_1', dict(kind='op', op='Less')),
                ('Merge_1', dict(kind='op', op='Merge')),
                ('Merge_1_data', dict(kind='data')),
                ('Less_1_data', dict(kind='data')),

                ('Less_2', dict(kind='op', op='Less')),
                ('Merge_2', dict(kind='op', op='Merge')),
                ('Merge_2_data', dict(kind='data')),
                ('Less_2_data', dict(kind='data')),

                ('Enter_2_less', dict(kind='op', op='Enter')),
                ('Enter_2_less_data', dict(kind='data')),
                ('minimum_data', dict(kind='data')),

                ('and', dict(kind='op', op='LogicalAnd')),
                ('and_data', dict(kind='data')),
                ('loop_cond', dict(kind='op', op='LoopCond')),
                ('loop_cond_data', dict(kind='data')),

                ('init_1', dict(kind='op', op='Const')),
                ('init_1_data', dict(kind='data')),
                ('Enter_1', dict(kind='op', op='Enter')),
                ('Enter_1_data', dict(kind='data')),

                ('init_2', dict(kind='op', op='Const')),
                ('init_2_data', dict(kind='data')),
                ('Enter_2', dict(kind='op', op='Enter')),
                ('Enter_2_data', dict(kind='data')),

                ('Switch_1', dict(kind='op', op='Switch')),
                ('Switch_1_data', dict(kind='data')),
                ('Identity_1', dict(kind='op', op='Identity')),
                ('Identity_1_data', dict(kind='data')),
                ('add_1', dict(kind='op', op='Add')),
                ('add_1_y', dict(kind='op', op='Const')),
                ('add_1_y_data', dict(kind='data')),
                ('add_1_data', dict(kind='data')),
                ('NextIteration_1', dict(kind='op', op='NextIteration')),

                ('Switch_2', dict(kind='op', op='Switch')),
                ('Switch_2_data', dict(kind='data')),
                ('Identity_2', dict(kind='op', op='Identity')),
                ('Identity_2_data', dict(kind='data')),
                ('add_2', dict(kind='op', op='Add')),
                ('add_2_y', dict(kind='op', op='Const')),
                ('add_2_y_data', dict(kind='data')),
                ('add_2_data', dict(kind='data')),
                ('NextIteration_2', dict(kind='op', op='NextIteration')),

            ],
            edges=[
                ('Strided_slice', 'Strided_slice_data'),
                ('Strided_slice_data', 'Enter_1_less'),
                ('Enter_1_less', 'Enter_1_less_data'),
                ('Enter_1_less_data', 'Less_1'),
                ('Less_1', 'Less_1_data'),
                ('Less_1_data', 'and'),

                ('and', 'and_data'),
                ('and_data', 'loop_cond'),
                ('loop_cond', 'loop_cond_data'),
                ('loop_cond_data', 'Switch_1'),
                ('loop_cond_data', 'Switch_2'),

                ('init_1', 'init_1_data'),
                ('init_1_data', 'Enter_1'),
                ('Enter_1', 'Enter_1_data'),
                ('Enter_1_data', 'Merge_1'),
                ('Merge_1', 'Merge_1_data'),
                ('Merge_1_data', 'Less_1'),

                ('Merge_1_data', 'Switch_1'),
                ('Switch_1', 'Switch_1_data'),
                ('Switch_1_data', 'Identity_1'),
                ('Identity_1', 'Identity_1_data'),
                ('Identity_1_data', 'add_1'),
                ('add_1_y', 'add_1_y_data'),
                ('add_1_y_data', 'add_1'),
                ('add_1', 'add_1_data'),
                ('add_1_data', 'NextIteration_1'),

                ('Merge_2_data', 'Switch_2'),
                ('Switch_2', 'Switch_2_data'),
                ('Switch_2_data', 'Identity_2'),
                ('Identity_2', 'Identity_2_data'),
                ('Identity_2_data', 'add_2'),
                ('add_2_y', 'add_2_y_data'),
                ('add_2_y_data', 'add_2'),
                ('add_2', 'add_2_data'),
                ('add_2_data', 'NextIteration_2'),

                ('minimum_data', 'Enter_2_less'),
                ('Enter_2_less', 'Enter_2_less_data'),
                ('Enter_2_less_data', 'Less_2'),

                ('init_2', 'init_2_data'),
                ('init_2_data', 'Enter_2'),
                ('Enter_2', 'Enter_2_data'),
                ('Enter_2_data', 'Merge_2'),

                ('Merge_2', 'Merge_2_data'),
                ('Merge_2_data', 'Less_2'),
                ('Less_2', 'Less_2_data'),
                ('Less_2_data', 'and'),
            ],
        )

    @staticmethod
    def looking_for_iteration_counter(graph: Graph, match: dict):
        types = ['TensorIteratorInput', 'TensorIteratorOutput']
        candidates = np.array([match['Identity_1_data'], match['Identity_2_data']])
        results = np.array([False for i in range(len(candidates))])
        for i, candidat in enumerate(candidates):
            for node in candidat.out_nodes():
                if node['op'] in types:
                    results[i] = True
        assert not np.all(results)
        assert sum(results) == 1
        return candidates[results == True][0]

    def replace_pattern(self, graph: Graph, match: dict):
        log.debug('================== ConditionFind ===============')
        # init_1
        init_1 = match['init_1_data'].value
        assert init_1 is not None
        init_1 = int(init_1)

        # init_2
        init_2 = match['init_2_data'].value
        assert init_2 is not None
        init_2 = int(init_2)

        # step_1
        assert match['add_1_y_data'].value is not None
        step_1 = int(match['add_1_y_data'].value)

        # step_2
        assert match['add_2_y_data'].value is not None
        step_2 = int(match['add_2_y_data'].value)

        match['loop_cond_data'].value = None
        match['Identity_2_data'].value = None

        # Create condition node and delete all useless nodes from condition pattern
        loop_condiiton = match['loop_cond_data']
        iterator_data = self.looking_for_iteration_counter(graph, match)

        condition_attrs = dict(time=dict(init=init_2, step=step_2), iter=dict(init=init_1, step=step_1),
                               name=match['loop_cond'].name + '/TensorIteratorCondition_')
        condition = TensorIteratorCondition(graph, attrs=condition_attrs)
        condition.create_node_with_data(inputs=[match['Strided_slice_data'], match['minimum_data']],
                                        data_nodes=[loop_condiiton, iterator_data])

        # Delete useless nodes
        safe_nodes = ['loop_cond_data', 'Identity_1_data', 'Identity_2_data',  'Strided_slice', 'Strided_slice_data',
                      'minimum', 'minimum_data']
        nodes_for_remove = []
        for node in match.keys():
            if node not in safe_nodes:
                nodes_for_remove.append(match[node].id)
        graph.remove_nodes_from(nodes_for_remove)


class SimpleConditionMatcher(MiddleReplacementPattern):
    enabled = True
    graph_condition = [lambda graph: graph.graph['is_cyclic']]

    def run_after(self):
        return [LoopConditionMatcher]

    def run_before(self):
        from extensions.middle.TensorIteratorMerge import TensorIteratorMerge
        return [TensorIteratorMerge]

    @staticmethod
    def pattern():
        log.debug('+++++++++++++++ SimpleConditionMatching ++++++++++++++++')
        return dict(
            nodes=[
                ('Enter_1_less', dict(kind='op', op='Enter')),
                ('Strided_slice', dict(kind='op', op='StridedSlice')),
                ('Strided_slice_data', dict(kind='data')),
                ('Enter_1_less_data', dict(kind='data')),

                ('Less_1', dict(kind='op', op='Less')),
                ('Merge_1', dict(kind='op', op='Merge')),
                ('Merge_1_data', dict(kind='data')),
                ('Less_1_data', dict(kind='data')),

                ('loop_cond', dict(kind='op', op='LoopCond')),
                ('loop_cond_data', dict(kind='data')),

                ('init_1', dict(kind='op', op='Const')),
                ('init_1_data', dict(kind='data')),
                ('Enter_1', dict(kind='op', op='Enter')),
                ('Enter_1_data', dict(kind='data')),

                ('Switch_1', dict(kind='op', op='Switch')),
                ('Switch_1_data', dict(kind='data')),
                ('Identity_1', dict(kind='op', op='Identity')),
                ('Identity_1_data', dict(kind='data')),
                ('add_1', dict(kind='op', op='Add')),
                ('add_1_y', dict(kind='op', op='Const')),
                ('add_1_y_data', dict(kind='data')),
                ('add_1_data', dict(kind='data')),
                ('NextIteration_1', dict(kind='op', op='NextIteration')),
            ],
            edges=[
                ('Strided_slice', 'Strided_slice_data'),
                ('Strided_slice_data', 'Enter_1_less'),
                ('Enter_1_less', 'Enter_1_less_data'),
                ('Enter_1_less_data', 'Less_1'),
                ('Less_1', 'Less_1_data'),
                ('Less_1_data', 'loop_cond'),

                ('loop_cond', 'loop_cond_data'),
                ('loop_cond_data', 'Switch_1'),

                ('init_1', 'init_1_data'),
                ('init_1_data', 'Enter_1'),
                ('Enter_1', 'Enter_1_data'),
                ('Enter_1_data', 'Merge_1'),
                ('Merge_1', 'Merge_1_data'),
                ('Merge_1_data', 'Less_1'),

                ('Merge_1_data', 'Switch_1'),
                ('Switch_1', 'Switch_1_data'),
                ('Switch_1_data', 'Identity_1'),
                ('Identity_1', 'Identity_1_data'),
                ('Identity_1_data', 'add_1'),
                ('add_1_y', 'add_1_y_data'),
                ('add_1_y_data', 'add_1'),
                ('add_1', 'add_1_data'),
                ('add_1_data', 'NextIteration_1'),

            ],
        )

    @staticmethod
    def replace_pattern(graph: Graph, match: dict):
        log.debug('================== SimpleConditionFind ===============')
        # init_1
        init_1 = match['init_1_data'].value
        assert init_1 is not None
        init_1 = int(init_1)

        # step_1
        assert match['add_1_y_data'].value is not None
        step_1 = int(match['add_1_y_data'].value)

        match['loop_cond_data'].value = None

        # Create condition node and delete all useless nodes from condition pattern
        condition_attrs = dict(iter=dict(init=init_1, step=step_1),
                               name=match['loop_cond'].name + '/TensorIteratorCondition_')
        condition = TensorIteratorCondition(graph, attrs=condition_attrs)
        condition.create_node_with_data(inputs=[match['Strided_slice_data']],
                                        data_nodes=[match['loop_cond_data'], match['Identity_1_data']])

        # Delete useless nodes
        safe_nodes = ['loop_cond_data', 'Identity_1_data', 'Strided_slice', 'Strided_slice_data']
        nodes_for_remove = []
        for node in match.keys():
            if node not in safe_nodes:
                nodes_for_remove.append(match[node].id)
        graph.remove_nodes_from(nodes_for_remove)
