model-optimizer/extensions/ops/resample.py

   1 """
   2  Copyright (c) 2018-2019 Intel Corporation
   3
   4  Licensed under the Apache License, Version 2.0 (the "License");
   5  you may not use this file except in compliance with the License.
   6  You may obtain a copy of the License at
   7
   8       http://www.apache.org/licenses/LICENSE-2.0
   9
  10  Unless required by applicable law or agreed to in writing, software
  11  distributed under the License is distributed on an "AS IS" BASIS,
  12  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  13  See the License for the specific language governing permissions and
  14  limitations under the License.
  15 """
  16
  17 import logging as log
  18
  19 from extensions.ops.resize_factor_utils import factor_update
  20 from mo.front.common.layout import get_batch_dim, get_features_dim, get_height_dim, get_width_dim, shape_for_layout
  21 from mo.graph.graph import Node, Graph
  22 from mo.ops.op import Op
  23
  24
  25 class ResampleOp(Op):
  26     op = 'Resample'
  27
  28     def __init__(self, graph: Graph, attrs: dict):
  29         mandatory_props = {
  30             'type': __class__.op,
  31             'op': __class__.op,
  32             'factor': None,
  33             'in_ports_count': 2,
  34             'out_ports_count': 1,
  35             'infer': ResampleOp.resample_infer
  36         }
  37         super().__init__(graph, mandatory_props, attrs)
  38
  39     def supported_attrs(self):
  40         return [
  41             'antialias',
  42             'height',
  43             'width',
  44             'resample_type',
  45             'factor',
  46         ]
  47
  48     def backend_attrs(self):
  49         return [
  50             'antialias',
  51             'height',
  52             'width',
  53             ('type', 'resample_type'),
  54             'factor'
  55         ]
  56
  57     @staticmethod
  58     def resample_infer(node: Node):
  59         layout = node.graph.graph['layout']
  60         assert len(layout) == 4
  61
  62         input_shape = node.in_node(0).shape
  63         if input_shape is None:
  64             return
  65         in_height = input_shape[get_height_dim(layout, 4)]
  66         in_width = input_shape[get_width_dim(layout, 4)]
  67
  68         if node.has('fw') and node.fw == 'tf':
  69             dst_shape = node.in_node(1).value
  70             if dst_shape is None or len(input_shape) != 4 or len(dst_shape) != 2:
  71                 log.error(
  72                     'Node {} with op {} cannot be converted to Resample layer because there is no enough info about '
  73                     'src/dst shapes: src_shape = {}, dst_shape = {}'.format(node.name, node.op, input_shape, dst_shape))
  74                 node.type = None  # prevent translation to a valid IE layer
  75                 return
  76             out_height = dst_shape[0]
  77             out_width = dst_shape[1]
  78             node.graph.remove_edge(node.in_node(1).id, node.id)
  79         else:
  80             if len(node.in_nodes()) == 1:
  81                 if node.has('width') and node.has('height'):
  82                     out_height = node.height
  83                     out_width = node.width
  84                 else:
  85                     out_height = node.factor * in_height
  86                     out_width = node.factor * in_width
  87             else:
  88                 out_height = node.in_node(1).shape[get_height_dim(layout, 4)]
  89                 out_width = node.in_node(1).shape[get_width_dim(layout, 4)]
  90
  91         node.factor = factor_update(
  92             node.factor,
  93             [float(out_height) / in_height, float(out_width) / in_width],
  94             [in_height, in_width],
  95             [out_height, out_width],
  96             node.soft_get('name'))
  97
  98         node.out_node().shape = shape_for_layout(layout,
  99                                                  batch=input_shape[get_batch_dim(layout, 4)],
 100                                                  features=input_shape[get_features_dim(layout, 4)],
 101                                                  height=out_height,
 102                                                  width=out_width)