"""
 Copyright (C) 2018-2020 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 unittest

import numpy as np
from google.protobuf import text_format

from mo.front.caffe.loader import caffe_pb_to_nx
from mo.front.caffe.proto import caffe_pb2
from mo.graph.graph import Graph
from mo.utils.error import Error

proto_str_one_input = 'name: "network" ' \
                      'layer { ' \
                      'name: "Input0" ' \
                      'type: "Input" ' \
                      'top: "Input0" ' \
                      'input_param { ' \
                      'shape: { ' \
                      'dim: 1 ' \
                      'dim: 3 ' \
                      'dim: 224 ' \
                      'dim: 224 ' \
                      '} ' \
                      '} ' \
                      '}'

proto_str_old_styled_multi_input = 'name: "network" ' \
                                   'input: "Input0" ' \
                                   'input_dim: 1 ' \
                                   'input_dim: 3 ' \
                                   'input_dim: 224 ' \
                                   'input_dim: 224 ' \
                                   'input: "data"' \
                                   'input_dim: 1 ' \
                                   'input_dim: 3 '

proto_str_input = 'name: "network" ' \
                  'input: "data" ' \
                  'input_shape ' \
                  '{ ' \
                  'dim: 1 ' \
                  'dim: 3 ' \
                  'dim: 224 ' \
                  'dim: 224 ' \
                  '}'

proto_str_multi_input = 'name: "network" ' \
                        'input: "data" ' \
                        'input_shape ' \
                        '{ ' \
                        'dim: 1 ' \
                        'dim: 3 ' \
                        'dim: 224 ' \
                        'dim: 224 ' \
                        '} ' \
                        'input: "data1"' \
                        'input_shape ' \
                        '{ ' \
                        'dim: 1 ' \
                        'dim: 3 ' \
                        '}'

proto_str_old_styled_input = 'name: "network" ' \
                             'input: "data" ' \
                             'input_dim: 1 ' \
                             'input_dim: 3 ' \
                             'input_dim: 224 ' \
                             'input_dim: 224 '

layer_proto_str = 'layer { ' \
                  'name: "conv1" ' \
                  'type: "Convolution" ' \
                  'bottom: "data" ' \
                  'top: "conv1" ' \
                  '}'

proto_same_name_layers = 'layer { ' \
                         'name: "conv1" ' \
                         'type: "Convolution" ' \
                         'bottom: "data" ' \
                         'top: "conv1" ' \
                         '}' \
                         'layer { ' \
                         'name: "conv1" ' \
                         'type: "Convolution" ' \
                         'bottom: "data1" ' \
                         'top: "conv1_2" ' \
                         '}'

class TestLoader(unittest.TestCase):
    def test_caffe_pb_to_nx_one_input(self):
        proto = caffe_pb2.NetParameter()
        text_format.Merge(proto_str_one_input, proto)
        input_shapes = caffe_pb_to_nx(Graph(), proto, None)
        expected_input_shapes = {
            'Input0': np.array([1, 3, 224, 224])
        }

        for i in expected_input_shapes:
            np.testing.assert_array_equal(input_shapes[i], expected_input_shapes[i])

    def test_caffe_pb_to_nx_old_styled_multi_input(self):
        proto = caffe_pb2.NetParameter()
        text_format.Merge(proto_str_old_styled_multi_input + layer_proto_str, proto)
        self.assertRaises(Error, caffe_pb_to_nx, Graph(), proto, None)

    def test_caffe_pb_to_nx_old_styled_input(self):
        proto = caffe_pb2.NetParameter()
        text_format.Merge(proto_str_old_styled_input + layer_proto_str, proto)
        input_shapes = caffe_pb_to_nx(Graph(), proto, None)
        expected_input_shapes = {
            'data': np.array([1, 3, 224, 224])
        }

        for i in expected_input_shapes:
            np.testing.assert_array_equal(input_shapes[i], expected_input_shapes[i])

    def test_caffe_pb_to_standart_input(self):
        proto = caffe_pb2.NetParameter()
        text_format.Merge(proto_str_input + layer_proto_str, proto)
        input_shapes = caffe_pb_to_nx(Graph(), proto, None)
        expected_input_shapes = {
            'data': np.array([1, 3, 224, 224])
        }

        for i in expected_input_shapes:
            np.testing.assert_array_equal(input_shapes[i], expected_input_shapes[i])

    def test_caffe_pb_to_multi_input(self):
        proto = caffe_pb2.NetParameter()
        text_format.Merge(proto_str_multi_input + layer_proto_str, proto)
        input_shapes = caffe_pb_to_nx(Graph(), proto, None)
        expected_input_shapes = {
            'data': np.array([1, 3, 224, 224]),
            'data1': np.array([1, 3])
        }

        for i in expected_input_shapes:
            np.testing.assert_array_equal(input_shapes[i], expected_input_shapes[i])

    def test_caffe_same_name_layer(self):
        proto = caffe_pb2.NetParameter()
        text_format.Merge(proto_str_multi_input + proto_same_name_layers, proto)
        graph = Graph()
        caffe_pb_to_nx(graph, proto, None)
        # 6 nodes because: 2 inputs + 2 convolutions
        np.testing.assert_equal(len(graph.nodes()), 4)
