* Add opset-13 bitwise ops * Fix issue in BinaryOps test --------- Co-authored-by: Katarzyna Mitrus <katarzyna.mitrus@intel.com>
254 lines
11 KiB
Python
254 lines
11 KiB
Python
# Copyright (C) 2018-2023 Intel Corporation
|
|
# SPDX-License-Identifier: Apache-2.0
|
|
|
|
import sys
|
|
|
|
import numpy as np
|
|
import pytest
|
|
from common.tf_layer_test_class import CommonTFLayerTest
|
|
from common.utils.tf_utils import permute_nchw_to_nhwc
|
|
|
|
|
|
class TestUnaryOps(CommonTFLayerTest):
|
|
current_op_type = None
|
|
|
|
def _prepare_input(self, inputs_dict):
|
|
non_negative = ['Sqrt', 'Log']
|
|
narrow_borders = ["Sinh", "Cosh", "Tanh", "Exp", "Selu"]
|
|
within_one = ['Asin', 'Acos', 'Atanh']
|
|
from_one = ['Acosh']
|
|
|
|
logical_type = ['LogicalNot']
|
|
bitwise_type = ["BitwiseNot"]
|
|
|
|
# usual function domain
|
|
lower = -256
|
|
upper = 256
|
|
|
|
# specific domains
|
|
if self.current_op_type in non_negative:
|
|
lower = 0
|
|
elif self.current_op_type in narrow_borders:
|
|
lower = -16
|
|
upper = 16
|
|
elif self.current_op_type in from_one:
|
|
lower = 1
|
|
elif self.current_op_type in within_one:
|
|
lower = -1
|
|
upper = 1
|
|
|
|
for input in inputs_dict.keys():
|
|
if self.current_op_type in logical_type:
|
|
inputs_dict[input] = np.random.randint(0, 1, inputs_dict[input]).astype(bool)
|
|
elif self.current_op_type in bitwise_type:
|
|
inputs_dict[input] = np.random.randint(lower, upper, inputs_dict[input]).astype(np.int32)
|
|
else:
|
|
inputs_dict[input] = np.random.uniform(lower, upper, inputs_dict[input]).astype(
|
|
np.float32)
|
|
|
|
return inputs_dict
|
|
|
|
def create_net_with_mish(self, shape, ir_version, use_new_frontend):
|
|
import tensorflow as tf
|
|
import tensorflow_addons as tfa
|
|
|
|
tf.compat.v1.reset_default_graph()
|
|
|
|
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)
|
|
|
|
input = tf.compat.v1.placeholder(tf.float32, tf_x_shape, 'Input')
|
|
tfa.activations.mish(input)
|
|
|
|
tf.compat.v1.global_variables_initializer()
|
|
tf_net = sess.graph_def
|
|
|
|
ref_net = None
|
|
|
|
return tf_net, ref_net
|
|
|
|
def create_net_with_unary_op(self, shape, ir_version, op_type, use_new_frontend):
|
|
import tensorflow as tf
|
|
|
|
self.current_op_type = op_type
|
|
op_type_to_tf = {
|
|
'Abs': tf.math.abs,
|
|
'Acos': tf.math.acos,
|
|
'Acosh': tf.math.acosh,
|
|
'Asin': tf.math.asin,
|
|
'Asinh': tf.math.asinh,
|
|
'Atan': tf.math.atan,
|
|
'Atanh': tf.math.atanh,
|
|
'BitwiseNot': tf.bitwise.invert,
|
|
'Ceiling': tf.math.ceil,
|
|
'Cos': tf.math.cos,
|
|
'Cosh': tf.math.cosh,
|
|
'Elu': tf.nn.elu,
|
|
'Erf': tf.math.erf,
|
|
'Exp': tf.math.exp,
|
|
'Floor': tf.math.floor,
|
|
'Log': tf.math.log,
|
|
'LogicalNot': tf.math.logical_not,
|
|
# 'Mish': tfa.activations.mish, # temporarily moved to `create_net_with_mish()`
|
|
'Negative': tf.math.negative,
|
|
'Selu': tf.nn.selu,
|
|
'Sigmoid': tf.nn.sigmoid,
|
|
'Sign': tf.math.sign,
|
|
'Sin': tf.math.sin,
|
|
'Sinh': tf.math.sinh,
|
|
'SoftPlus': tf.nn.softplus,
|
|
'Square': tf.math.square,
|
|
'Tan': tf.math.tan,
|
|
'Tanh': tf.math.tanh,
|
|
'ReLU': tf.nn.relu,
|
|
}
|
|
|
|
tf.compat.v1.reset_default_graph()
|
|
|
|
type = tf.float32
|
|
if op_type == "LogicalNot":
|
|
type = tf.bool
|
|
elif op_type == "BitwiseNot":
|
|
type = tf.int32
|
|
# 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)
|
|
|
|
input = tf.compat.v1.placeholder(type, tf_x_shape, 'Input')
|
|
if self.current_op_type == 'Mish':
|
|
# Mish has no attribute name
|
|
op_type_to_tf[self.current_op_type](input)
|
|
else:
|
|
op_type_to_tf[self.current_op_type](input, name='Operation')
|
|
|
|
tf.compat.v1.global_variables_initializer()
|
|
tf_net = sess.graph_def
|
|
|
|
ref_net = None
|
|
return tf_net, ref_net
|
|
|
|
test_data_precommit = [dict(shape=[4, 6, 8, 10, 12])]
|
|
|
|
@pytest.mark.parametrize("params", test_data_precommit)
|
|
@pytest.mark.parametrize("op_type", ['Elu',
|
|
'Sigmoid',
|
|
'Sin',
|
|
'Sinh',
|
|
'Cos',
|
|
'Cosh',
|
|
'Abs',
|
|
'Negative',
|
|
'Exp',
|
|
'Tan',
|
|
'Tanh',
|
|
'Floor',
|
|
'ReLU',
|
|
'Ceiling',
|
|
'Asin',
|
|
'Acos',
|
|
'Atan',
|
|
'Log',
|
|
'Sign',
|
|
'SoftPlus',
|
|
'Atanh',
|
|
'Acosh',
|
|
'Asinh',
|
|
'LogicalNot',
|
|
'Square',
|
|
'Erf',
|
|
'BitwiseNot'
|
|
])
|
|
@pytest.mark.precommit
|
|
def test_unary_op_precommit(self, params, ie_device, precision, ir_version, temp_dir, op_type,
|
|
use_new_frontend, use_old_api):
|
|
if not use_new_frontend and op_type in ['BitwiseNot']:
|
|
pytest.skip("Bitwise ops are supported only by new TF FE.")
|
|
if ie_device == 'GPU':
|
|
pytest.skip("5D tensors is not supported on GPU")
|
|
self._test(*self.create_net_with_unary_op(**params, ir_version=ir_version, op_type=op_type,
|
|
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.xfail(sys.version_info > (3, 10),
|
|
reason="tensorflow_addons package is not available for Python 3.11 and higher")
|
|
@pytest.mark.parametrize("params", test_data_precommit)
|
|
@pytest.mark.precommit
|
|
def test_unary_op_mish_precommit(self, params, ie_device, precision, ir_version, temp_dir,
|
|
use_new_frontend, use_old_api):
|
|
"""
|
|
TODO: Move to `test_unary_op_precommit()` once tensorflow_addons package is available for Python 3.11
|
|
"""
|
|
if ie_device == 'GPU':
|
|
pytest.skip("5D tensors is not supported on GPU")
|
|
self._test(*self.create_net_with_mish(**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 = [pytest.param(dict(shape=[10, 12]), marks=pytest.mark.precommit_tf_fe),
|
|
dict(shape=[8, 10, 12]),
|
|
dict(shape=[6, 8, 10, 12]),
|
|
dict(shape=[4, 6, 8, 10, 12])]
|
|
|
|
@pytest.mark.parametrize("params", test_data)
|
|
@pytest.mark.parametrize("op_type", ['Elu',
|
|
'Sigmoid',
|
|
'Sin',
|
|
'Sinh',
|
|
'Cos',
|
|
'Cosh',
|
|
'Abs',
|
|
'Negative',
|
|
'Exp',
|
|
'Tan',
|
|
'Tanh',
|
|
'Floor',
|
|
'ReLU',
|
|
'Ceiling',
|
|
'Asin',
|
|
'Acos',
|
|
'Atan',
|
|
'Log',
|
|
'LogicalNot',
|
|
'Sign',
|
|
'SoftPlus',
|
|
'Atanh',
|
|
'Acosh',
|
|
'Asinh',
|
|
'Square',
|
|
'Erf',
|
|
'Selu',
|
|
'BitwiseNot'
|
|
])
|
|
@pytest.mark.nightly
|
|
@pytest.mark.skipif(sys.platform == 'darwin', reason="Ticket - 122182")
|
|
def test_unary_op(self, params, ie_device, precision, ir_version, temp_dir, op_type,
|
|
use_new_frontend, use_old_api):
|
|
if not use_new_frontend and op_type in ['BitwiseNot']:
|
|
pytest.skip("Bitwise ops are supported only by new TF FE.")
|
|
if ie_device == 'GPU':
|
|
pytest.skip("5D tensors is not supported on GPU")
|
|
self._test(*self.create_net_with_unary_op(**params, ir_version=ir_version, op_type=op_type,
|
|
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.xfail(sys.version_info > (3, 10),
|
|
reason="tensorflow_addons package is not available for Python 3.11 and higher")
|
|
@pytest.mark.parametrize("params", test_data)
|
|
@pytest.mark.nightly
|
|
def test_unary_op_mish(self, params, ie_device, precision, ir_version, temp_dir, op_type,
|
|
use_new_frontend, use_old_api):
|
|
"""
|
|
TODO: Move to `test_unary_op()` once tensorflow_addons package is available for Python 3.11
|
|
"""
|
|
if ie_device == 'GPU':
|
|
pytest.skip("5D tensors is not supported on GPU")
|
|
self._test(*self.create_net_with_mish(**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)
|