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[TF FE] Support dynamic shape Placeholder freezing and PlaceholderWithDefault (#14450)

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* [TF FE] Support dynamic shape Placeholder freezing and PlaceholderWithDefault

Also, this PR contains reorganization of python unit tests for TF FE that
covers conversion and inference of different models in pbtxt.
This mini-infrastructure will be used in the future for TF FE support.

Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>

* Revert debug info

Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>
This commit is contained in:
Roman Kazantsev authored and GitHub committed 2022-12-07 12:13:10 +04:00
1 parent a47688e593
commit d3fa858fcc
18 files changed
+665 -83
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tools/mo/openvino/tools/mo/moc_frontend/pipeline.py
+12 -4
View File
@@ -147,9 +147,6 @@ def moc_pipeline(argv: argparse.Namespace, moc_front_end: FrontEnd):
"Place (operation or tensor) with name {} is not found.".format(name))
place = node.get('node')
if node.get('shape'):
input_model.set_partial_shape(place, node['shape'])
if node.get('data_type'):
dtype = node['data_type']
ov_type = Type(dtype)
@@ -177,8 +174,19 @@ def moc_pipeline(argv: argparse.Namespace, moc_front_end: FrontEnd):
value = mo_array(casted_list, dtype=dtype)
else:
value = np_map_cast[dtype](value)
value = np.array(value, dtype=dtype)
ov_shape = input_model.get_partial_shape(place)
if node.get('shape'):
# set user defined shape
ov_shape = PartialShape(node['shape'])
input_model.set_partial_shape(place, ov_shape)
elif ov_shape.is_dynamic:
# in case of dynamic shape (dynamic rank or dynamic dimension)
# deduce it based on the value shape and set it
ov_shape = PartialShape(value.shape)
input_model.set_partial_shape(place, ov_shape)
input_model.set_tensor_value(place, value)
def shape_to_array(shape: PartialShape):
tools/mo/unit_tests/moc_tf_fe/__init__.py
View File
Whitespace-only changes.
tools/mo/unit_tests/mo/utils/freeze_placeholder_test_tf_fe.py → tools/mo/unit_tests/moc_tf_fe/conversion_basic_models.py
+67 -75
View File
@@ -68,85 +68,20 @@ except ImportError:
@generator
class TestMoFreezePlaceholderTFFE(unittest.TestCase):
def setUp(self):
try:
import tensorflow.compat.v1 as tf
except ImportError:
import tensorflow as tf
tm.Telemetry.__init__ = Mock(return_value=None)
tm.Telemetry.send_event = Mock()
FrontEnd.add_extension = Mock()
self.models = []
tf.reset_default_graph()
with tf.Session() as sess:
x = tf.placeholder(tf.float32, [2, 2], 'in1')
y = tf.placeholder(tf.float32, [2, 2], 'in2')
tf.add(x, y, name="add")
tf.global_variables_initializer()
tf.io.write_graph(sess.graph, '.', 'model_fp32.pb', as_text=False)
self.models.append("model_fp32.pb")
tf.reset_default_graph()
with tf.Session() as sess:
x = tf.placeholder(tf.int32, [2, 3], 'in1')
y = tf.placeholder(tf.int32, [2, 3], 'in2')
tf.multiply(x, y, name="add")
tf.global_variables_initializer()
tf.io.write_graph(sess.graph, '.', 'model_int32.pb', as_text=False)
self.models.append("model_int32.pb")
tf.reset_default_graph()
with tf.Session() as sess:
x = tf.placeholder(tf.bool, [2, 3], 'in1')
y = tf.placeholder(tf.bool, [2, 3], 'in2')
tf.math.logical_and(x, y)
tf.global_variables_initializer()
tf.io.write_graph(sess.graph, '.', 'model_bool.pb', as_text=False)
self.models.append("model_bool.pb")
tf.reset_default_graph()
with tf.Session() as sess:
x = tf.placeholder(tf.float32, [3], 'in1')
y = tf.placeholder(tf.float32, [3], 'in2')
cond = tf.placeholder(tf.bool, [], 'cond')
tf.where(cond, x, y)
tf.global_variables_initializer()
tf.io.write_graph(sess.graph, '.', 'model_bool2.pb', as_text=False)
self.models.append("model_bool2.pb")
tf.reset_default_graph()
with tf.Session() as sess:
x = tf.placeholder(tf.float32, [3], 'x')
y = tf.placeholder(tf.float32, [3], 'y')
z = tf.placeholder(tf.float32, [3], 'z')
add = tf.add(x, y, name="add")
tf.multiply(add, z, name="multiply")
tf.global_variables_initializer()
tf.io.write_graph(sess.graph, '.', 'model_three_inputs.pb', as_text=False)
self.models.append("model_three_inputs.pb")
def tearDown(self):
for name in self.models:
os.remove(name)
def basic(self, input_model, argv_input, inputs, dtype, expected, freeze_placeholder_with_value=None,
input_shape=None, only_conversion=False):
input_shape=None, only_conversion=False, input_model_is_text=True):
path = os.path.dirname(__file__)
input_model = os.path.join(path, "test_models", input_model)
args = base_args_config()
args.input_model = input_model
args.input = argv_input
args.freeze_placeholder_with_value = freeze_placeholder_with_value
args.input_shape = input_shape
args.input_model_is_text = input_model_is_text
try:
_, model = prepare_ir(args)
@@ -195,7 +130,7 @@ class TestMoFreezePlaceholderTFFE(unittest.TestCase):
)
def test_fp32(self, input_freezing_value, inputs, expected,
dtype):
self.basic("model_fp32.pb", input_freezing_value, inputs, dtype, expected)
self.basic("model_fp32.pbtxt", input_freezing_value, inputs, dtype, expected)
@generate(
*[
@@ -215,7 +150,7 @@ class TestMoFreezePlaceholderTFFE(unittest.TestCase):
)
def test_int32(self, input_freezing_value, inputs, expected,
dtype=None):
self.basic("model_int32.pb", input_freezing_value, inputs, dtype, expected)
self.basic("model_int32.pbtxt", input_freezing_value, inputs, dtype, expected)
@generate(
*[
@@ -241,7 +176,7 @@ class TestMoFreezePlaceholderTFFE(unittest.TestCase):
)
def test_bool(self, input_freezing_value, inputs, expected,
dtype=None):
self.basic("model_bool.pb", input_freezing_value, inputs, dtype, expected)
self.basic("model_bool.pbtxt", input_freezing_value, inputs, dtype, expected)
@generate(
*[
@@ -276,7 +211,7 @@ class TestMoFreezePlaceholderTFFE(unittest.TestCase):
)
def test_bool2(self, input_freezing_value, inputs, expected,
dtype=None, freeze_placeholder_with_value=None, input_shape=None, only_conversion=False):
self.basic("model_bool2.pb", input_freezing_value, inputs, dtype, expected, freeze_placeholder_with_value,
self.basic("model_bool2.pbtxt", input_freezing_value, inputs, dtype, expected, freeze_placeholder_with_value,
input_shape, only_conversion)
@generate(
@@ -299,6 +234,63 @@ class TestMoFreezePlaceholderTFFE(unittest.TestCase):
)
def test_cutting_fp32(self, input_freezing_value, inputs, expected,
dtype=None, freeze_placeholder_with_value=None, input_shape=None, only_conversion=False):
self.basic("model_three_inputs.pb", input_freezing_value, inputs, dtype, expected,
self.basic("model_three_inputs.pbtxt", input_freezing_value, inputs, dtype, expected,
freeze_placeholder_with_value,
input_shape, only_conversion)
input_shape, only_conversion, True)
@generate(
*[
(
"x[1,4],y[4]",
{"x": np.array([[3, 2, 1, 5]], dtype=np.int32), "y": np.array([0, -1, -7, 8], dtype=np.int32)},
np.array([[3, 1, -6, 13]], dtype=np.int32),
np.int32,
None
),
(
"x,y",
{"x": np.array([[-3, 20, 1]], dtype=np.int32), "y": np.array([[10, -11, -17]], dtype=np.int32)},
np.array([[7, 9, -16]], dtype=np.int32),
np.int32,
None
),
(
"x",
{"x": np.array([[-3, 20, 1]], dtype=np.int32)},
np.array([[-2, 22, 4], [1, 25, 7]], dtype=np.int32),
np.int32,
None
),
],
)
def test_placeholder_with_default(self, inputs, inputs_data, expected,
dtype=None, freeze_placeholder_with_value=None, input_shape=None,
only_conversion=False):
self.basic("placeholder_with_default.pbtxt", inputs, inputs_data, dtype, expected,
freeze_placeholder_with_value,
input_shape, only_conversion, True)
@generate(
*[
(
"x[4],y->2.0",
{"x": np.array([3, 2, 1, 5], dtype=np.float32)},
np.array([6, 4, 2, 10], dtype=np.float32),
np.float32,
None
),
(
"x[1],y->[2.0,3.0]",
{"x": np.array([3], dtype=np.float32)},
np.array([6, 9], dtype=np.float32),
np.float32,
None
),
],
)
def test_freeze_placeholder_with_unknown_rank(self, inputs, inputs_data, expected,
dtype=None, freeze_placeholder_with_value=None, input_shape=None,
only_conversion=False):
self.basic("mul_with_unknown_rank_y.pbtxt", inputs, inputs_data, dtype, expected,
freeze_placeholder_with_value,
input_shape, only_conversion, True)
tools/mo/unit_tests/moc_tf_fe/test_models/model_bool.pbtxt
+52
View File
@@ -0,0 +1,52 @@
node {
name: "in1"
op: "Placeholder"
attr {
key: "dtype"
value {
type: DT_BOOL
}
}
attr {
key: "shape"
value {
shape {
dim {
size: 2
}
dim {
size: 3
}
}
}
}
}
node {
name: "in2"
op: "Placeholder"
attr {
key: "dtype"
value {
type: DT_BOOL
}
}
attr {
key: "shape"
value {
shape {
dim {
size: 2
}
dim {
size: 3
}
}
}
}
}
node {
name: "LogicalAnd"
op: "LogicalAnd"
input: "in1"
input: "in2"
}
tools/mo/unit_tests/moc_tf_fe/test_models/model_bool.py
+15
View File
@@ -0,0 +1,15 @@
# Copyright (C) 2018-2022 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import tensorflow.compat.v1 as tf
tf.reset_default_graph()
with tf.Session() as sess:
x = tf.placeholder(tf.bool, [2, 3], 'in1')
y = tf.placeholder(tf.bool, [2, 3], 'in2')
tf.math.logical_and(x, y)
tf.global_variables_initializer()
tf_net = sess.graph_def
tf.io.write_graph(tf_net, './', 'model_bool.pbtxt', True)
tools/mo/unit_tests/moc_tf_fe/test_models/model_bool2.pbtxt
+70
View File
@@ -0,0 +1,70 @@
node {
name: "in1"
op: "Placeholder"
attr {
key: "dtype"
value {
type: DT_FLOAT
}
}
attr {
key: "shape"
value {
shape {
dim {
size: 3
}
}
}
}
}
node {
name: "in2"
op: "Placeholder"
attr {
key: "dtype"
value {
type: DT_FLOAT
}
}
attr {
key: "shape"
value {
shape {
dim {
size: 3
}
}
}
}
}
node {
name: "cond"
op: "Placeholder"
attr {
key: "dtype"
value {
type: DT_BOOL
}
}
attr {
key: "shape"
value {
shape {
}
}
}
}
node {
name: "Select"
op: "Select"
input: "cond"
input: "in1"
input: "in2"
attr {
key: "T"
value {
type: DT_FLOAT
}
}
}
tools/mo/unit_tests/moc_tf_fe/test_models/model_bool2.py
+16
View File
@@ -0,0 +1,16 @@
# Copyright (C) 2018-2022 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import tensorflow.compat.v1 as tf
tf.reset_default_graph()
with tf.Session() as sess:
x = tf.placeholder(tf.float32, [3], 'in1')
y = tf.placeholder(tf.float32, [3], 'in2')
cond = tf.placeholder(tf.bool, [], 'cond')
tf.where(cond, x, y)
tf.global_variables_initializer()
tf_net = sess.graph_def
tf.io.write_graph(tf_net, './', 'model_bool2.pbtxt', True)
tools/mo/unit_tests/moc_tf_fe/test_models/model_fp32.pbtxt
+58
View File
@@ -0,0 +1,58 @@
node {
name: "in1"
op: "Placeholder"
attr {
key: "dtype"
value {
type: DT_FLOAT
}
}
attr {
key: "shape"
value {
shape {
dim {
size: 2
}
dim {
size: 2
}
}
}
}
}
node {
name: "in2"
op: "Placeholder"
attr {
key: "dtype"
value {
type: DT_FLOAT
}
}
attr {
key: "shape"
value {
shape {
dim {
size: 2
}
dim {
size: 2
}
}
}
}
}
node {
name: "add"
op: "AddV2"
input: "in1"
input: "in2"
attr {
key: "T"
value {
type: DT_FLOAT
}
}
}
tools/mo/unit_tests/moc_tf_fe/test_models/model_fp32.py
+15
View File
@@ -0,0 +1,15 @@
# Copyright (C) 2018-2022 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import tensorflow.compat.v1 as tf
tf.reset_default_graph()
with tf.Session() as sess:
x = tf.placeholder(tf.float32, [2, 2], 'in1')
y = tf.placeholder(tf.float32, [2, 2], 'in2')
tf.add(x, y, name="add")
tf.global_variables_initializer()
tf_net = sess.graph_def
tf.io.write_graph(tf_net, './', 'model_fp32.pbtxt', True)
tools/mo/unit_tests/moc_tf_fe/test_models/model_int32.pbtxt
+58
View File
@@ -0,0 +1,58 @@
node {
name: "in1"
op: "Placeholder"
attr {
key: "dtype"
value {
type: DT_INT32
}
}
attr {
key: "shape"
value {
shape {
dim {
size: 2
}
dim {
size: 3
}
}
}
}
}
node {
name: "in2"
op: "Placeholder"
attr {
key: "dtype"
value {
type: DT_INT32
}
}
attr {
key: "shape"
value {
shape {
dim {
size: 2
}
dim {
size: 3
}
}
}
}
}
node {
name: "add"
op: "Mul"
input: "in1"
input: "in2"
attr {
key: "T"
value {
type: DT_INT32
}
}
}
tools/mo/unit_tests/moc_tf_fe/test_models/model_int32.py
+15
View File
@@ -0,0 +1,15 @@
# Copyright (C) 2018-2022 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import tensorflow.compat.v1 as tf
tf.reset_default_graph()
with tf.Session() as sess:
x = tf.placeholder(tf.int32, [2, 3], 'in1')
y = tf.placeholder(tf.int32, [2, 3], 'in2')
tf.multiply(x, y, name="add")
tf.global_variables_initializer()
tf_net = sess.graph_def
tf.io.write_graph(tf_net, './', 'model_int32.pbtxt', True)
tools/mo/unit_tests/moc_tf_fe/test_models/model_three_inputs.pbtxt
+84
View File
@@ -0,0 +1,84 @@
node {
name: "x"
op: "Placeholder"
attr {
key: "dtype"
value {
type: DT_FLOAT
}
}
attr {
key: "shape"
value {
shape {
dim {
size: 3
}
}
}
}
}
node {
name: "y"
op: "Placeholder"
attr {
key: "dtype"
value {
type: DT_FLOAT
}
}
attr {
key: "shape"
value {
shape {
dim {
size: 3
}
}
}
}
}
node {
name: "z"
op: "Placeholder"
attr {
key: "dtype"
value {
type: DT_FLOAT
}
}
attr {
key: "shape"
value {
shape {
dim {
size: 3
}
}
}
}
}
node {
name: "add"
op: "AddV2"
input: "x"
input: "y"
attr {
key: "T"
value {
type: DT_FLOAT
}
}
}
node {
name: "multiply"
op: "Mul"
input: "add"
input: "z"
attr {
key: "T"
value {
type: DT_FLOAT
}
}
}
tools/mo/unit_tests/moc_tf_fe/test_models/model_three_inputs.py
+17
View File
@@ -0,0 +1,17 @@
# Copyright (C) 2018-2022 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import tensorflow.compat.v1 as tf
tf.reset_default_graph()
with tf.Session() as sess:
x = tf.placeholder(tf.float32, [3], 'x')
y = tf.placeholder(tf.float32, [3], 'y')
z = tf.placeholder(tf.float32, [3], 'z')
add = tf.add(x, y, name="add")
tf.multiply(add, z, name="multiply")
tf.global_variables_initializer()
tf_net = sess.graph_def
tf.io.write_graph(tf_net, './', 'model_three_inputs.pbtxt', True)
tools/mo/unit_tests/moc_tf_fe/test_models/mul_with_unknown_rank_y.pbtxt
+50
View File
@@ -0,0 +1,50 @@
node {
name: "x"
op: "Placeholder"
attr {
key: "dtype"
value {
type: DT_FLOAT
}
}
attr {
key: "shape"
value {
shape {
dim {
size: 3
}
}
}
}
}
node {
name: "y"
op: "Placeholder"
attr {
key: "dtype"
value {
type: DT_FLOAT
}
}
attr {
key: "shape"
value {
shape {
unknown_rank: true
}
}
}
}
node {
name: "Mul"
op: "Mul"
input: "x"
input: "y"
attr {
key: "T"
value {
type: DT_FLOAT
}
}
}
tools/mo/unit_tests/moc_tf_fe/test_models/mul_with_unknown_rank_y.py
+15
View File
@@ -0,0 +1,15 @@
# Copyright (C) 2018-2022 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import tensorflow.compat.v1 as tf
tf.reset_default_graph()
with tf.Session() as sess:
x = tf.placeholder(tf.float32, [3], 'x')
keep_prob = tf.placeholder(tf.float32, None, 'y')
tf.multiply(x, keep_prob)
tf.global_variables_initializer()
tf_net = sess.graph_def
tf.io.write_graph(tf_net, './', 'mul_with_unknown_rank_y.pbtxt', True)
tools/mo/unit_tests/moc_tf_fe/test_models/placeholder_with_default.pbtxt
+86
View File
@@ -0,0 +1,86 @@
node {
name: "x"
op: "Placeholder"
attr {
key: "dtype"
value {
type: DT_INT32
}
}
attr {
key: "shape"
value {
shape {
dim {
size: -1
}
dim {
size: 3
}
}
}
}
}
node {
name: "Const"
op: "Const"
attr {
key: "dtype"
value {
type: DT_INT32
}
}
attr {
key: "value"
value {
tensor {
dtype: DT_INT32
tensor_shape {
dim {
size: 2
}
dim {
size: 3
}
}
tensor_content: "\001\000\000\000\002\000\000\000\003\000\000\000\004\000\000\000\005\000\000\000\006\000\000\000"
}
}
}
}
node {
name: "y"
op: "PlaceholderWithDefault"
input: "Const"
attr {
key: "dtype"
value {
type: DT_INT32
}
}
attr {
key: "shape"
value {
shape {
dim {
size: -1
}
dim {
size: 3
}
}
}
}
}
node {
name: "Add"
op: "AddV2"
input: "x"
input: "y"
attr {
key: "T"
value {
type: DT_INT32
}
}
}
tools/mo/unit_tests/moc_tf_fe/test_models/placeholder_with_default.py
+16
View File
@@ -0,0 +1,16 @@
# Copyright (C) 2018-2022 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import tensorflow.compat.v1 as tf
tf.reset_default_graph()
with tf.Session() as sess:
x = tf.placeholder(tf.int32, [None, 3], 'x')
y = tf.placeholder_with_default(tf.constant([[1, 2, 3], [4, 5, 6]], dtype=tf.int32),
[None, 3], 'y')
tf.add(x, y)
tf.global_variables_initializer()
tf_net = sess.graph_def
tf.io.write_graph(tf_net, './', 'placeholder_with_default.pbtxt', True)