Pavel Esir
d2a23680f2
* Initial support of GatherElements in MO and nGraph * apply_style * added lost extractor for GatherElements * Corrected GatherElements::validate_and_infer_types * updated package_BOM.txt * Type_t added * started to implement ngraph shape_type_infer unit-tests * finally implemented all ngraph shape_inference unit-tests * updated Supported_Frameworks_Layers.md * added correct handling of dynamic shapes in nGraph, added unit-tests for dynamic cases, fixed dump typos in MO, replaced axis type from int -> int64_t * implemented shape infer for dynamic shapes with intervals * finalized MO implementation * applied comment from review * style-apply * spec correction * removed conflict * fixed typos * removed obsolete comments form type_prop * significant corrections in validate_and_infer_types * style-apply * data_rank check for axis
76 lines
2.9 KiB
Python
76 lines
2.9 KiB
Python
"""
|
|
Copyright (C) 2017-2020 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 numpy as np
|
|
|
|
from mo.graph.graph import Node, Graph
|
|
from mo.ops.op import Op, PermuteAttrs
|
|
|
|
|
|
class GatherElements(Op):
|
|
op = 'GatherElements'
|
|
|
|
def __init__(self, graph: Graph, attrs: dict):
|
|
super().__init__(graph, {
|
|
'op': self.op,
|
|
'type': self.op,
|
|
'version': 'opset6',
|
|
'infer': self.infer,
|
|
'in_ports_count': 2,
|
|
'out_ports_count': 1,
|
|
'axis': 0,
|
|
}, attrs)
|
|
|
|
def backend_attrs(self):
|
|
return ['axis']
|
|
|
|
@staticmethod
|
|
def infer(node: Node):
|
|
data_shape = node.in_port(0).data.get_shape()
|
|
indices_shape = node.in_port(1).data.get_shape()
|
|
axis = node.axis
|
|
data_rank = len(data_shape)
|
|
|
|
assert data_rank >= 1, 'data_rank must be >= 1'
|
|
assert data_rank == len(indices_shape), 'data and indices inputs for node {} must be of the ' \
|
|
'same rank. Instead got {} and {}'.\
|
|
format(node.name, data_rank, len(indices_shape))
|
|
assert -data_rank <= axis < data_rank, 'axis for node {0} must be within interval ' \
|
|
'[-{1}}, {1} - 1]. Instead got: axis={2}'.\
|
|
format(node.name, data_rank, axis)
|
|
if axis < 0:
|
|
axis += data_rank
|
|
|
|
for idx, (data_sz, ind_sz) in enumerate(zip(data_shape, indices_shape)):
|
|
if idx != axis and data_sz != ind_sz:
|
|
raise ValueError('Sizes along axis {} for node {} do not match. data and indices must have '
|
|
'equal size along all axes except for axis {}'.format(idx, node.name, axis))
|
|
|
|
data = node.in_port(0).data.get_value()
|
|
indices = node.in_port(1).data.get_value()
|
|
|
|
if data is not None and indices is not None:
|
|
out_value = np.empty(indices_shape, dtype=data.dtype)
|
|
for idx in np.ndindex(*indices_shape):
|
|
data_idx = list(idx)
|
|
data_idx[node.axis] = indices[idx]
|
|
out_value[idx] = data[tuple(data_idx)]
|
|
node.out_port(0).data.set_value(out_value)
|
|
else:
|
|
node.out_port(0).data.set_shape(indices_shape)
|
|
|
|
PermuteAttrs.create_permute_attrs(node, attrs=[('axis', 'input:0')])
|