00c7da0f5f
* Revert submodule changes * Fix build on Win * Fix precommit: set correct shapes for broadcasting; disable check with ref for use_new_frontend mode * fix precommit * Fix precommits * Temporary skip new tests on GPU with FP16 * Resolve review comments, trigger CI * Resolve review comments * Resolve review comments
80 lines
2.8 KiB
Python
80 lines
2.8 KiB
Python
# Copyright (C) 2018-2021 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 TestEltwise(CommonTFLayerTest):
|
|
def create_eltwise_net(self, shape, operation, ir_version, use_new_frontend):
|
|
"""
|
|
Tensorflow net IR net
|
|
|
|
Inputs->Eltwise => Inputs->Eltwise
|
|
|
|
"""
|
|
|
|
#
|
|
# 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:
|
|
|
|
tf_x_shape = shape.copy()
|
|
|
|
tf_x_shape = permute_nchw_to_nhwc(tf_x_shape, use_new_frontend)
|
|
|
|
x = tf.compat.v1.placeholder(tf.float32, tf_x_shape, 'Input')
|
|
y = tf.compat.v1.placeholder(tf.float32, tf_x_shape, 'Input') # Input_1 in graph_def
|
|
|
|
if operation == 'sum':
|
|
tf.add(x, y, name='Operation')
|
|
elif operation == 'max':
|
|
tf.maximum(x, y, name='Operation')
|
|
elif operation == 'mul':
|
|
tf.multiply(x, y, 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 = []
|
|
for operation in ['sum', 'max', 'mul']:
|
|
test_data.extend([dict(shape=[1, 224], operation=operation),
|
|
dict(shape=[1, 224, 224], operation=operation),
|
|
dict(shape=[1, 3, 224, 224], operation=operation)])
|
|
|
|
@pytest.mark.parametrize("params", test_data)
|
|
@pytest.mark.nightly
|
|
def test_eltwise(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend):
|
|
self._test(*self.create_eltwise_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 = []
|
|
for operation in ['sum', 'max', 'mul']:
|
|
test_data_5D.extend([dict(shape=[1, 3, 224, 224, 224], operation=operation)])
|
|
|
|
@pytest.mark.parametrize("params", test_data_5D)
|
|
@pytest.mark.precommit
|
|
def test_eltwise_5D_precommit(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend):
|
|
if ie_device == 'GPU':
|
|
pytest.skip("5D tensors is not supported on GPU")
|
|
self._test(*self.create_eltwise_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)
|