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test_tf_BiasAdd.py
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# Copyright (C) 2018-2023 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
import tensorflow as tf
import numpy as np
class TestBiasAdd(CommonTFLayerTest):
def create_bias_add_placeholder_const_net(self, shape, ir_version, use_new_frontend, output_type=tf.float32):
"""
Tensorflow net IR net
Placeholder->BiasAdd => Placeholder->Add
/ /
Const-------/ Const-------/
"""
tf.compat.v1.reset_default_graph()
# Create the graph and model
with tf.compat.v1.Session() as sess:
tf_x_shape = shape.copy()
tf_x_shape = permute_nchw_to_nhwc(tf_x_shape, use_new_frontend)
tf_y_shape = tf_x_shape[-1:]
x = tf.compat.v1.placeholder(output_type, tf_x_shape, 'Input')
constant_value = np.random.randint(0, 1, tf_y_shape).astype(output_type.as_numpy_dtype())
if (constant_value == 0).all():
# Avoid elimination of the layer from IR
constant_value = constant_value + 1
y = tf.constant(constant_value)
tf.nn.bias_add(x, y, name="Operation")
tf.compat.v1.global_variables_initializer()
tf_net = sess.graph_def
ref_net = None
return tf_net, ref_net
def create_bias_add_2_consts_net(self, shape, ir_version, use_new_frontend, output_type=tf.float32):
"""
Tensorflow net IR net
Const->BiasAdd-->Concat => Const---->Concat
/ / /
Const--/ / Placeholder-/
/
Placeholder---/
"""
#
# Create Tensorflow model
#
tf.compat.v1.reset_default_graph()
tf_concat_axis = -1
# Create the graph and model
with tf.compat.v1.Session() as sess:
tf_x_shape = shape.copy()
tf_x_shape = permute_nchw_to_nhwc(tf_x_shape, use_new_frontend)
tf_y_shape = tf_x_shape[-1:]
constant_value_x = np.random.randint(-256, 256, tf_x_shape).astype(output_type.as_numpy_dtype())
x = tf.constant(constant_value_x)
constant_value_y = np.random.randint(-256, 256, tf_y_shape).astype(output_type.as_numpy_dtype())
y = tf.constant(constant_value_y)
add = tf.nn.bias_add(x, y, name="Operation")
placeholder = tf.compat.v1.placeholder(output_type, tf_x_shape,
'Input') # Input_1 in graph_def
concat = tf.concat([placeholder, add], axis=tf_concat_axis, name='Operation')
tf.compat.v1.global_variables_initializer()
tf_net = sess.graph_def
ref_net = None
return tf_net, ref_net
test_data_2D = [
dict(shape=[1, 1]),
dict(shape=[1, 224])
]
@pytest.mark.parametrize("params", test_data_2D)
@pytest.mark.nightly
def test_bias_add_placeholder_const_2D(self, params, ie_device, precision, ir_version, temp_dir,
use_new_frontend, use_old_api):
self._test(*self.create_bias_add_placeholder_const_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)
@pytest.mark.parametrize("params", test_data_2D)
@pytest.mark.nightly
def test_bias_add_2_consts_2D(self, params, ie_device, precision, ir_version, temp_dir,
use_new_frontend, use_old_api):
self._test(*self.create_bias_add_2_consts_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_3D = [
pytest.param(dict(shape=[1, 1, 224]), marks=pytest.mark.xfail(reason="*-19053")),
pytest.param(dict(shape=[1, 3, 224]), marks=pytest.mark.xfail(reason="*-19053"))
]
@pytest.mark.parametrize("params", test_data_3D)
@pytest.mark.nightly
def test_bias_add_placeholder_const_3D(self, params, ie_device, precision, ir_version, temp_dir,
use_new_frontend, use_old_api):
self._test(*self.create_bias_add_placeholder_const_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)
@pytest.mark.parametrize("params", test_data_3D)
@pytest.mark.nightly
def test_bias_add_2_consts_3D(self, params, ie_device, precision, ir_version, temp_dir,
use_new_frontend, use_old_api):
self._test(*self.create_bias_add_2_consts_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=[1, 1, 100, 224]),
pytest.param(dict(shape=[1, 3, 100, 224]), marks=pytest.mark.precommit_tf_fe),
pytest.param(dict(shape=[1, 3, 100, 224], output_type=tf.float16), marks=pytest.mark.precommit_tf_fe)
]
@pytest.mark.parametrize("params", test_data_4D)
@pytest.mark.nightly
@pytest.mark.precommit
def test_bias_add_placeholder_const_4D(self, params, ie_device, precision, ir_version, temp_dir,
use_new_frontend, use_old_api):
self._test(*self.create_bias_add_placeholder_const_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)
@pytest.mark.parametrize("params", test_data_4D)
@pytest.mark.nightly
def test_bias_add_2_consts_4D(self, params, ie_device, precision, ir_version, temp_dir,
use_new_frontend, use_old_api):
self._test(*self.create_bias_add_2_consts_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=[1, 1, 50, 100, 224]),
dict(shape=[1, 3, 220, 222, 224])
]
@pytest.mark.parametrize("params", test_data_5D)
@pytest.mark.nightly
@pytest.mark.precommit
def test_bias_add_placeholder_const_5D(self, params, ie_device, precision, ir_version, temp_dir,
use_new_frontend, use_old_api):
self._test(*self.create_bias_add_placeholder_const_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)
@pytest.mark.parametrize("params", test_data_5D)
@pytest.mark.nightly
def test_bias_add_2_consts_5D(self, params, ie_device, precision, ir_version, temp_dir,
use_new_frontend, use_old_api):
self._test(*self.create_bias_add_2_consts_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)