108 lines
4.5 KiB
Python
108 lines
4.5 KiB
Python
# Copyright (C) 2018-2022 Intel Corporation
|
|
# SPDX-License-Identifier: Apache-2.0
|
|
|
|
import pytest
|
|
|
|
from common.tf_layer_test_class import CommonTFLayerTest
|
|
from common.utils.tf_utils import permute_nchw_to_nhwc
|
|
|
|
|
|
class TestSelect(CommonTFLayerTest):
|
|
def create_select_net(self, shape_condition, shape_input, ir_version, use_new_frontend):
|
|
"""
|
|
Tensorflow net IR net
|
|
|
|
Condition --| Condition --|
|
|
v v
|
|
Input_1-> Select Input_1-> Select
|
|
^ ^
|
|
Input_2-----| Input_2-----|
|
|
"""
|
|
|
|
#
|
|
# Create Tensorflow model
|
|
#
|
|
|
|
import tensorflow as tf
|
|
|
|
tf.compat.v1.reset_default_graph()
|
|
|
|
# Create the graph and model
|
|
with tf.compat.v1.Session() as sess:
|
|
# Permute shapes NCHW -> NHWC for TF network creation
|
|
shape_condition_net = permute_nchw_to_nhwc(shape_condition)
|
|
shape_input_net = permute_nchw_to_nhwc(shape_input)
|
|
|
|
condition = tf.compat.v1.placeholder(tf.bool, shape_condition_net, 'Input_condition')
|
|
input_1 = tf.compat.v1.placeholder(tf.float32, shape_input_net, 'Input_1')
|
|
input_2 = tf.compat.v1.placeholder(tf.float32, shape_input_net, 'Input_2')
|
|
|
|
tf.compat.v1.where(condition, input_1, input_2, name='Operation')
|
|
|
|
tf.compat.v1.global_variables_initializer()
|
|
tf_net = sess.graph_def
|
|
|
|
#
|
|
# Create reference IR net
|
|
# Please, specify 'type': 'Input' for input node
|
|
# Moreover, do not forget to validate ALL layer attributes!!!
|
|
#
|
|
|
|
ref_net = None
|
|
|
|
return tf_net, ref_net
|
|
|
|
test_data_1D = [dict(shape_condition=[2], shape_input=[2])]
|
|
|
|
@pytest.mark.parametrize("params", test_data_1D)
|
|
@pytest.mark.nightly
|
|
def test_select_1D(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend):
|
|
self._test(*self.create_select_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)
|
|
|
|
test_data_2D = [
|
|
dict(shape_condition=[2], shape_input=[2, 3]),
|
|
dict(shape_condition=[3, 5], shape_input=[3, 5]),
|
|
]
|
|
|
|
@pytest.mark.parametrize("params", test_data_2D)
|
|
@pytest.mark.nightly
|
|
def test_select_2D(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend):
|
|
self._test(*self.create_select_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)
|
|
|
|
test_data_3D = [
|
|
dict(shape_condition=[3], shape_input=[3, 4, 5]),
|
|
dict(shape_condition=[3, 4, 5], shape_input=[3, 4, 5]),
|
|
]
|
|
|
|
@pytest.mark.parametrize("params", test_data_3D)
|
|
@pytest.mark.nightly
|
|
def test_select_3D(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend):
|
|
self._test(*self.create_select_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)
|
|
|
|
test_data_4D = [
|
|
dict(shape_condition=[3], shape_input=[3, 4, 5, 6]),
|
|
dict(shape_condition=[3, 4, 5, 6], shape_input=[3, 4, 5, 6]),
|
|
]
|
|
|
|
@pytest.mark.parametrize("params", test_data_4D)
|
|
@pytest.mark.nightly
|
|
@pytest.mark.precommit
|
|
def test_select_4D(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend):
|
|
self._test(*self.create_select_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)
|
|
|
|
test_data_5D = [
|
|
dict(shape_condition=[3], shape_input=[3, 4, 5, 6, 7]),
|
|
dict(shape_condition=[3, 4, 5, 6, 7], shape_input=[3, 4, 5, 6, 7]),
|
|
]
|
|
|
|
# TODO mark as precommit (after successfully passing in nightly)
|
|
@pytest.mark.parametrize("params", test_data_5D)
|
|
@pytest.mark.nightly
|
|
def test_select_5D(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend):
|
|
self._test(*self.create_select_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)
|