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[MO]Implement additional shape extraction for TF Placeholder operation (#8817)

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* Implement additional shape extraction for TF placeholder operation

* Update checks and add comments

* Use more accurate check

* Extract _output_shapes attr only if we have problems with shape attr

* Add missed import

* Apply suggestions from code review

Update code comments

Co-authored-by: Anastasia Popova <anastasia.popova@intel.com>

* Add update condition to avoid unnecessary checks

* Remove unnecessary checks

Co-authored-by: Anastasia Popova <anastasia.popova@intel.com>
This commit is contained in:
Anton Chetverikov 2021-12-18 19:55:06 +03:00 committed by GitHub
parent 526fe3098d
commit 6b0d1525fd
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1 changed files with 25 additions and 2 deletions
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27
tools/mo/openvino/tools/mo/front/tf/placeholder_ext.py
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@ -1,10 +1,13 @@
# Copyright (C) 2018-2021 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
from openvino.tools.mo.ops.parameter import Parameter
import logging as log
from openvino.tools.mo.front.common.partial_infer.utils import shape_array
from openvino.tools.mo.front.extractor import FrontExtractorOp
from openvino.tools.mo.front.tf.extractors.utils import tf_dtype_extractor, tf_tensor_shape
from openvino.tools.mo.ops.op import PermuteAttrs
from openvino.tools.mo.ops.parameter import Parameter
class PlaceholderFrontExtractor(FrontExtractorOp):
@ -13,9 +16,29 @@ class PlaceholderFrontExtractor(FrontExtractorOp):
@classmethod
def extract(cls, node):
shape = shape_array([])
# Extract output shape from `shape` attribute
extracted_shape = tf_tensor_shape(node.pb.attr["shape"].shape)
if len(extracted_shape) != 0:
shape = extracted_shape
else:
# Extract output shape from `_output_shapes` attribute if it is possible
extracted_output_shapes = node.pb.attr["_output_shapes"].list.shape
if len(extracted_output_shapes) == 1: # check if attribute not empty
extracted_output_shapes = tf_tensor_shape(extracted_output_shapes[0])
# Check equality of extracted shapes. We know some cases then Placeholder operation has empty `shape`
# attribute value and non-empty `_output_shapes` attribute value and need co handle and support it.
if len(extracted_output_shapes) > len(extracted_shape):
log.warning('Extracted shapes for Placeholder operation {} have different lengths: `shape` {} and '
'`_output_shapes` {}. Please, check if model is consistent'.format(
node.pb.name, extracted_shape, extracted_output_shapes))
if len(extracted_output_shapes) != 0:
shape = extracted_output_shapes
attrs = {
'data_type': tf_dtype_extractor(node.pb.attr["dtype"].type),
'shape': tf_tensor_shape(node.pb.attr["shape"].shape),
'shape': shape,
'permute_attrs': PermuteAttrs().update_attrs(attrs=[('shape', 'output:0')])
}
if node.pb.attr["shape"].shape.unknown_rank: