dec7df17ed
* Remove unnnecessary ir_version checks in the MO * Cleaned up 'backend_attrs_v2' function * Small clean up from the 'TFCustomSubgraphCall' * Clean up the MO extractor attributes mapping * Renamed PreluOp to PReLU
70 lines
2.7 KiB
Python
70 lines
2.7 KiB
Python
"""
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Copyright (C) 2018-2020 Intel Corporation
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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"""
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import logging as log
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from mo.front.common.partial_infer.elemental import copy_shape_infer
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from mo.graph.graph import Node, Graph
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from mo.middle.passes.convert_data_type import np_data_type_to_precision, convert_blob, np_data_type_to_destination_type
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from mo.ops.op import Op
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from mo.utils.utils import refer_to_faq_msg
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class Cast(Op):
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op = 'Cast'
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enabled = False
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def __init__(self, graph: Graph, attrs: dict):
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mandatory_props = {
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'op': self.op,
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'type': 'Convert',
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'version': 'opset1',
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'infer': self.infer,
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'type_infer': self.type_infer,
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'dst_type': None,
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'in_ports_count': 1,
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'out_ports_count': 1,
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}
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super().__init__(graph, mandatory_props, attrs)
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def backend_attrs(self):
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return [('destination_type', lambda node: np_data_type_to_destination_type(node.dst_type))]
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@staticmethod
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def type_infer(node: Node):
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assert node.has_valid('dst_type'), 'Destination type of "Cast" operation should be extracted earlier'
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node.out_port(0).set_data_type(node.dst_type)
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@staticmethod
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def infer(node: Node):
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assert node.has_valid('dst_type'), 'Destination type of "Cast" operation should be extracted earlier'
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dst_type = node.dst_type
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copy_shape_infer(node)
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if node.has_and_set('stop_value_propagation'):
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return
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if node.in_node(0).has_valid('value'):
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new_blob, finite_match_count, zero_match_count = convert_blob(node.in_node(0).value, dst_type)
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node.out_port(0).data.set_value(new_blob)
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if finite_match_count:
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log.error(
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("{} elements of {} were clipped to infinity while converting an input blob for node '{}' to {}. " +
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refer_to_faq_msg(76)).format(finite_match_count, new_blob.size, node.name, dst_type))
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if zero_match_count:
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log.warning(
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("{} elements of {} were clipped to zero while converting an input blob for node '{}' to {}. " +
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refer_to_faq_msg(77)).format(zero_match_count, new_blob.size, node.name, dst_type))
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