model-optimizer/mo/front/kaldi/extractors/lstm_projected_streams_ext.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 from extensions.ops.lstm_cell import LSTMCell
  17 from mo.front.caffe.extractors.utils import embed_input
  18 from mo.front.extractor import FrontExtractorOp
  19 from mo.front.kaldi.loader.utils import collect_until_token, collect_until_whitespace, get_uint32
  20 from mo.front.kaldi.utils import read_binary_matrix, read_binary_vector
  21
  22
  23 class LSTMProjectedStreamsFrontExtractor(FrontExtractorOp):
  24     op = 'lstmprojectedstreams'
  25     enabled = True
  26
  27     @staticmethod
  28     def extract(node):
  29         clip_value = 50
  30         pb = node.parameters
  31         res = collect_until_whitespace(pb)
  32         if res == b'<CellClip>':
  33             clip_value = get_uint32(pb.read(4))
  34         collect_until_token(pb, b'FM')
  35         gifo_x_weights, gifo_x_weights_shape = read_binary_matrix(pb, False)
  36         gifo_r_weights, gifo_r_weights_shape = read_binary_matrix(pb)
  37         gifo_biases = read_binary_vector(pb)
  38         input_gate_weights = read_binary_vector(pb)
  39         forget_gate_weights = read_binary_vector(pb)
  40         output_gate_weights = read_binary_vector(pb)
  41
  42         projection_weights, projection_weights_shape = read_binary_matrix(pb)
  43
  44         mapping_rule = {'gifo_x_weights_shape': gifo_x_weights_shape,
  45                         'gifo_r_weights_shape': gifo_r_weights_shape,
  46                         'projection_weights_shape': projection_weights_shape,
  47                         'clip_value': clip_value
  48                         }
  49
  50         embed_input(mapping_rule, 1, 'gifo_x_weights', gifo_x_weights)
  51         embed_input(mapping_rule, 2, 'gifo_r_weights', gifo_r_weights)
  52         embed_input(mapping_rule, 3, 'gifo_biases', gifo_biases)
  53         embed_input(mapping_rule, 4, 'input_gate_weights', input_gate_weights)
  54         embed_input(mapping_rule, 5, 'forget_gate_weights', forget_gate_weights)
  55         embed_input(mapping_rule, 6, 'output_gate_weights', output_gate_weights)
  56         embed_input(mapping_rule, 7, 'projection_weights', projection_weights)
  57
  58         LSTMCell.update_node_stat(node, mapping_rule)
  59         return __class__.enabled
  60
  61
  62 class LSTMProjectedFrontExtractor(FrontExtractorOp):
  63     op = 'lstmprojected'
  64     enabled = True
  65
  66     @staticmethod
  67     def extract(node):
  68         return LSTMProjectedStreamsFrontExtractor.extract(node)