92 lines
3.3 KiB
Python
92 lines
3.3 KiB
Python
"""
|
|
Copyright (C) 2018-2020 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.graph.perm_inputs import PermuteInputs
|
|
from mo.ops.op import Op
|
|
|
|
|
|
class Reshape(Op):
|
|
op = 'Reshape'
|
|
enabled = True
|
|
|
|
def __init__(self, graph: Graph, attrs: dict):
|
|
super().__init__(graph, {
|
|
'op': self.op,
|
|
'type': self.op,
|
|
'version': 'opset1',
|
|
|
|
'infer': self.infer,
|
|
|
|
'special_zero': True,
|
|
'reinterp_shape': True,
|
|
|
|
'in_ports_count': 2,
|
|
'out_ports_count': 1,
|
|
}, attrs)
|
|
|
|
def supported_attrs(self):
|
|
return ['special_zero']
|
|
|
|
@staticmethod
|
|
def infer(node: Node):
|
|
name = node.soft_get('name', node.id)
|
|
|
|
connected_inputs = {idx: port for idx, port in node.in_ports().items() if not port.disconnected()}
|
|
assert len(connected_inputs) == 2 and all([i in connected_inputs for i in range(2)]), \
|
|
"Reshape should have 2 connected input ports, but it doesn't for node: `{}`. Ports: {}" \
|
|
"".format(name, connected_inputs)
|
|
|
|
input_shape = node.in_port(0).data.get_shape()
|
|
assert input_shape is not None
|
|
|
|
new_shape = node.in_port(1).data.get_value()
|
|
assert new_shape is not None, 'Dynamic Reshape second input is not supported. Node {}'.format(name)
|
|
|
|
assert np.argwhere(new_shape == -1).size <= 1, \
|
|
'Reshape second input should not have several `-1` values set. ' \
|
|
'Node: {}, reshape second input value {}'.format(name, new_shape)
|
|
|
|
num_of_input_elements = np.prod(input_shape)
|
|
num_of_output_elements = 1
|
|
for index, x in enumerate(new_shape):
|
|
if x == 0 and node.has_and_set('special_zero'):
|
|
num_of_output_elements *= input_shape[index]
|
|
elif x != -1:
|
|
num_of_output_elements *= x
|
|
|
|
undefined_dim = num_of_input_elements // num_of_output_elements
|
|
output_shape = []
|
|
for index, x in enumerate(new_shape):
|
|
if x == 0 and node.has_and_set('special_zero'):
|
|
output_shape.append(input_shape[index])
|
|
elif x == -1:
|
|
output_shape.append(undefined_dim)
|
|
else:
|
|
output_shape.append(x)
|
|
|
|
assert np.prod(input_shape) == np.prod(output_shape), \
|
|
"Number of elements in input {} and output {} of reshape node {} mismatch" \
|
|
"".format(input_shape, output_shape, name)
|
|
|
|
PermuteInputs().set_input_permutation(node.in_node(1), node, 'output:0', 'shape')
|
|
|
|
if node.in_port(0).data.get_value() is not None:
|
|
node.out_port(0).data.set_value(node.in_port(0).data.get_value().reshape(output_shape))
|
|
else:
|
|
node.out_port(0).data.set_shape(output_shape)
|