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"""
Copyright (c) 2018 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 numpy as np
from mo.front.common.partial_infer.squeeze import tf_squeeze_infer
from mo.ops.op import Op
class Unsqueeze(Op):
op = 'Unsqueeze'
enabled = False
def __init__(self, graph, attrs: dict):
super().__init__(graph, {
'axis': 0,
'num_axes': -1,
'kind': 'op',
'type': 'Reshape',
'op': __class__.op,
'infer': __class__.infer
}, attrs)
def supported_attrs(self):
return ['axis', ('dim', lambda node: ', '.join(map(str, node['dim']))), 'num_axes']
@staticmethod
def infer(node):
unsqueeze_dims = np.array(node.unsqueeze_dims)
value = node.in_node(0).value
shape = node.in_node(0).shape
for dim in unsqueeze_dims:
shape = np.insert(shape, dim, 1)
node.out_node().shape = np.array(shape)
if value is not None:
value = np.reshape(value, shape)
node.out_node().value = np.array(value)
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