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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 logging as log
import numpy as np
def tf_reshape_shape_infer(node):
# TODO Make sure that all -1 are handled correctly
# We cannot simply copy shape argument to the output,
# because if -1 appears, it should be substituted by a real
# value from input shape if input shape is completely defined.
if node.in_node(0).shape is None:
return None
input_shape = node.in_node(0).shape
reshape_output = node.in_node(1).value if len(node.in_nodes()) > 1 else node.dim
if node.in_node(0).shape is None:
return None
total = 1
for index, i in enumerate(input_shape):
total *= i
res = 1
for index, x in enumerate(reshape_output):
if x == 0:
res *= input_shape[index]
elif x != -1:
res *= x
new_dim = total // res
output_shape = []
for index, x in enumerate(reshape_output):
if x == 0:
output_shape.append(input_shape[index])
elif x == -1:
output_shape.append(new_dim)
else:
output_shape.append(x)
out_shape_total = 1
for index, i in enumerate(output_shape):
assert i != -1
out_shape_total *= i
if total != out_shape_total:
log.error(
"Number of elements in input {} and output {} of reshape node {} mismatch".format(input_shape, output_shape,
node.name))
return None
return np.array(output_shape, dtype=np.int64)
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