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[TF FE] Refactor OneHot translator and add layer test (#15763)

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Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>
This commit is contained in:
Roman Kazantsev
2023-02-17 13:54:40 +04:00
committed by GitHub
parent 50090ed03a
commit bd0dfbcd7a
2 changed files with 33 additions and 143 deletions
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17
src/frontends/tensorflow_common/src/op/one_hot.cpp
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@@ -14,15 +14,16 @@ namespace tensorflow {
namespace op {
OutputVector translate_one_hot_op(const NodeContext& node) {
auto ng_features = node.get_input(0);
auto ng_depth = node.get_input(1);
auto ng_on = node.get_input(2);
auto ng_off = node.get_input(3);
default_op_checks(node, 4, {"OneHot"});
auto indices = node.get_input(0);
auto depth = node.get_input(1);
auto on_value = node.get_input(2);
auto off_value = node.get_input(3);
auto one_hot_axis = node.get_attribute<int64_t>("axis");
auto res = make_shared<OneHot>(ng_features, ng_depth, ng_on, ng_off, one_hot_axis);
set_node_name(node.get_name(), res);
return res->outputs();
auto axis = node.get_attribute<int64_t>("axis", -1);
auto one_hot = make_shared<OneHot>(indices, depth, on_value, off_value, axis);
set_node_name(node.get_name(), one_hot);
return {one_hot};
}
} // namespace op
} // namespace tensorflow

159
tests/layer_tests/tensorflow_tests/test_tf_OneHot.py
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@@ -3,161 +3,50 @@
import pytest
from common.tf_layer_test_class import CommonTFLayerTest
from common.utils.tf_utils import permute_nchw_to_nhwc
class TestOneHot(CommonTFLayerTest):
@staticmethod
def create_one_hot_net(shape, depth, on_value, off_value, axis, ir_version, use_new_frontend):
"""
Tensorflow net
Input -> OneHot
IR net (can contain Permutes for input/output of OneHot, depending on shapes), all cases are:
Input (< 3D) -> OneHot
Input (3D) -> OneHot -> Permute (NHWC -> NCHW)
Input (> 3D) -> Permute (NCHW -> NHWC) -> OneHot -> Permute (NHWC -> NCHW)
"""
def create_one_hot_net(shape, depth, on_value, off_value, axis):
import tensorflow as tf
tf.compat.v1.reset_default_graph()
# Create the graph and model
with tf.compat.v1.Session() as sess:
# Permute NCHW -> NHWC for TF network creation
net_shape = permute_nchw_to_nhwc(shape)
indices = tf.compat.v1.placeholder(tf.int32, shape=net_shape, name='input_indices')
result = tf.one_hot(indices,
depth,
on_value,
off_value,
axis,
name='Operation')
indices = tf.compat.v1.placeholder(tf.int32, shape, name='input_indices')
tf.raw_ops.OneHot(indices=indices,
depth=depth,
on_value=on_value,
off_value=off_value,
axis=axis,
name='Operation')
tf.compat.v1.global_variables_initializer()
tf_net = sess.graph_def
#
# Create reference IR net
#
return tf_net, None
ref_net = None
return tf_net, ref_net
test_data_1D = [
# check for default on/off value, axis params
dict(shape=[5], depth=7, on_value=None, off_value=None, axis=None),
dict(shape=[5], depth=7, on_value=2.0, off_value=-1.0, axis=0)]
@pytest.mark.parametrize("params", test_data_1D)
@pytest.mark.nightly
def test_OneHot_1D(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend,
use_old_api):
self._test(*self.create_one_hot_net(**params, ir_version=ir_version,
use_new_frontend=use_new_frontend),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_new_frontend=use_new_frontend, use_old_api=use_old_api)
test_data_2D = [
dict(shape=[5, 6], depth=7, on_value=None, off_value=None, axis=None),
# check for default on/off value, axis params
dict(shape=[5, 6], depth=7, on_value=5.0, off_value=None, axis=None),
# check for default on/off value, axis params
dict(shape=[5, 6], depth=7, on_value=None, off_value=-1.0, axis=None),
# check for default on/off value, axis params
dict(shape=[5, 6], depth=7, on_value=None, off_value=None, axis=1),
# check for default on/off value, axis params
dict(shape=[5, 6], depth=7, on_value=2.0, off_value=-3.0, axis=0),
dict(shape=[5, 6], depth=7, on_value=2.0, off_value=-3.0, axis=1),
test_data_basic = [
dict(shape=[2], depth=3, on_value=1.0, off_value=-1.0, axis=None),
dict(shape=[2, 3], depth=4, on_value=5.0, off_value=10.0, axis=1),
]
@pytest.mark.parametrize("params", test_data_2D)
@pytest.mark.parametrize("params", test_data_basic)
@pytest.mark.precommit_tf_fe
@pytest.mark.nightly
def test_OneHot_2D(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend,
use_old_api):
self._test(*self.create_one_hot_net(**params, ir_version=ir_version,
use_new_frontend=use_new_frontend),
def test_one_hot_basic(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend,
use_old_api):
self._test(*self.create_one_hot_net(**params),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_new_frontend=use_new_frontend, use_old_api=use_old_api)
test_data_3D = [
dict(shape=[5, 6, 7], depth=8, on_value=None, off_value=None, axis=None),
# check for default on/off value, axis params
dict(shape=[5, 6, 7], depth=8, on_value=6.0, off_value=None, axis=None),
# check for default on/off value, axis params
dict(shape=[5, 6, 7], depth=8, on_value=None, off_value=4.0, axis=None),
# check for default on/off value, axis params
dict(shape=[5, 6, 7], depth=8, on_value=None, off_value=None, axis=1),
# check for default on/off value, axis params
dict(shape=[5, 6, 7], depth=8, on_value=None, off_value=None, axis=0),
dict(shape=[5, 6, 7], depth=8, on_value=None, off_value=None, axis=1),
pytest.param(dict(shape=[5, 6, 7], depth=8, on_value=None, off_value=None, axis=2),
marks=pytest.mark.precommit_tf_fe),
test_data_complex = [
dict(shape=[3, 4], depth=1, on_value=1.0, off_value=-5.0, axis=-2),
dict(shape=[3, 4, 2, 1], depth=4, on_value=3.0, off_value=5.0, axis=2),
]
@pytest.mark.parametrize("params", test_data_3D)
@pytest.mark.parametrize("params", test_data_basic)
@pytest.mark.nightly
def test_OneHot_3D(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend,
use_old_api):
self._test(*self.create_one_hot_net(**params, ir_version=ir_version,
use_new_frontend=use_new_frontend),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_new_frontend=use_new_frontend, use_old_api=use_old_api)
test_data_4D = [
dict(shape=[5, 6, 7, 8], depth=9, on_value=None, off_value=None, axis=None),
# check for default on/off value, axis params
dict(shape=[5, 6, 7, 8], depth=9, on_value=None, off_value=None, axis=2),
# check for default on/off value, axis params
dict(shape=[5, 6, 7, 8], depth=9, on_value=5.0, off_value=None, axis=None),
# check for default on/off value, axis params
dict(shape=[5, 6, 7, 8], depth=9, on_value=None, off_value=6.0, axis=None),
# check for default on/off value, axis params
dict(shape=[5, 6, 7, 8], depth=9, on_value=None, off_value=None, axis=0),
dict(shape=[5, 6, 7, 8], depth=9, on_value=None, off_value=None, axis=1),
dict(shape=[5, 6, 7, 8], depth=9, on_value=None, off_value=None, axis=2),
dict(shape=[5, 6, 7, 8], depth=9, on_value=None, off_value=None, axis=3),
]
@pytest.mark.parametrize("params", test_data_4D)
@pytest.mark.nightly
@pytest.mark.precommit
def test_OneHot_4D(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend,
use_old_api):
self._test(*self.create_one_hot_net(**params, ir_version=ir_version,
use_new_frontend=use_new_frontend),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_new_frontend=use_new_frontend, use_old_api=use_old_api)
test_data_5D = [
dict(shape=[4, 5, 6, 7, 8], depth=9, on_value=None, off_value=None, axis=None),
# check for default on/off value, axis params
dict(shape=[4, 5, 6, 7, 8], depth=9, on_value=2.0, off_value=None, axis=None),
# check for default on/off value, axis params
dict(shape=[4, 5, 6, 7, 8], depth=9, on_value=None, off_value=4.0, axis=None),
# check for default on/off value, axis params
dict(shape=[4, 5, 6, 7, 8], depth=9, on_value=None, off_value=None, axis=1),
# check for default on/off value, axis params
dict(shape=[4, 5, 6, 7, 8], depth=9, on_value=None, off_value=None, axis=0),
dict(shape=[4, 5, 6, 7, 8], depth=9, on_value=None, off_value=None, axis=1),
dict(shape=[4, 5, 6, 7, 8], depth=9, on_value=None, off_value=None, axis=2),
dict(shape=[4, 5, 6, 7, 8], depth=9, on_value=None, off_value=None, axis=3),
dict(shape=[4, 5, 6, 7, 8], depth=9, on_value=None, off_value=None, axis=4),
]
@pytest.mark.parametrize("params", test_data_5D)
@pytest.mark.nightly
def test_OneHot_5D(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend,
use_old_api):
self._test(*self.create_one_hot_net(**params, ir_version=ir_version,
use_new_frontend=use_new_frontend),
def test_one_hot_complex(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend,
use_old_api):
self._test(*self.create_one_hot_net(**params),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_new_frontend=use_new_frontend, use_old_api=use_old_api)