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[TF FE] Stabilize tests for unary operation defined on full real domain (openvinotoolkit#28111)
**Details:** Stabilize tests for unary operation defined on full real domain **Ticket:** TBD --------- Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>
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‎tests/layer_tests/tensorflow_tests/test_tf_UnaryOps.py

+8-43
Original file line numberDiff line numberDiff line change
@@ -1,11 +1,10 @@
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# Copyright (C) 2018-2024 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import platform
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import sys
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import numpy as np
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import platform
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import pytest
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import sys
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from common.tf_layer_test_class import CommonTFLayerTest
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@@ -14,7 +13,7 @@ class TestUnaryOps(CommonTFLayerTest):
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def _prepare_input(self, inputs_dict):
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non_negative = ['Sqrt', 'Log']
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narrow_borders = ["Sinh", "Cosh", "Tanh", "Exp", "Selu"]
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narrow_borders = ["Tanh"]
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within_one = ['Asin', 'Acos', 'Atanh']
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from_one = ['Acosh']
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@@ -76,25 +75,14 @@ def create_net_with_unary_op(self, shape, ir_version, op_type, use_legacy_fronte
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'Asin': tf.math.asin,
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'Asinh': tf.math.asinh,
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'Atan': tf.math.atan,
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'Atanh': tf.math.atanh,
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'BitwiseNot': tf.bitwise.invert,
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'Ceiling': tf.math.ceil,
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'Cos': tf.math.cos,
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'Cosh': tf.math.cosh,
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'Elu': tf.nn.elu,
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'Erf': tf.math.erf,
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'Exp': tf.math.exp,
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'Floor': tf.math.floor,
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'Log': tf.math.log,
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'LogicalNot': tf.math.logical_not,
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# 'Mish': tfa.activations.mish, # temporarily moved to `create_net_with_mish()`
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'Negative': tf.math.negative,
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'Selu': tf.nn.selu,
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'Sigmoid': tf.nn.sigmoid,
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'Sign': tf.math.sign,
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'Sin': tf.math.sin,
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'Sinh': tf.math.sinh,
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'SoftPlus': tf.nn.softplus,
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'Square': tf.math.square,
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'Tan': tf.math.tan,
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'Tanh': tf.math.tanh,
@@ -126,15 +114,8 @@ def create_net_with_unary_op(self, shape, ir_version, op_type, use_legacy_fronte
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test_data_precommit = [dict(shape=[4, 6, 8, 10, 12])]
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@pytest.mark.parametrize("params", test_data_precommit)
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@pytest.mark.parametrize("op_type", ['Elu',
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'Sigmoid',
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'Sin',
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'Sinh',
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'Cos',
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'Cosh',
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'Abs',
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@pytest.mark.parametrize("op_type", ['Abs',
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'Negative',
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'Exp',
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'Tan',
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'Tanh',
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'Floor',
@@ -145,15 +126,11 @@ def create_net_with_unary_op(self, shape, ir_version, op_type, use_legacy_fronte
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'Atan',
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'Log',
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'Sign',
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'SoftPlus',
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'Atanh',
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'Acosh',
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'Asinh',
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'LogicalNot',
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'Square',
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'Erf',
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'BitwiseNot'
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])
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'BitwiseNot'])
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@pytest.mark.nightly
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def test_unary_op_precommit(self, params, ie_device, precision, ir_version, temp_dir, op_type,
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use_legacy_frontend):
@@ -188,15 +165,8 @@ def test_unary_op_mish_precommit(self, params, ie_device, precision, ir_version,
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dict(shape=[4, 6, 8, 10, 12])]
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@pytest.mark.parametrize("params", test_data)
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@pytest.mark.parametrize("op_type", ['Elu',
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'Sigmoid',
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'Sin',
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'Sinh',
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'Cos',
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'Cosh',
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'Abs',
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@pytest.mark.parametrize("op_type", ['Abs',
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'Negative',
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'Exp',
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'Tan',
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'Tanh',
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'Floor',
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'Acos',
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'Atan',
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'Log',
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'LogicalNot',
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'Sign',
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'SoftPlus',
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'Atanh',
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'Acosh',
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'Asinh',
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'LogicalNot',
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'Square',
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'Erf',
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'Selu',
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'BitwiseNot'
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])
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'BitwiseNot'])
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@pytest.mark.nightly
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@pytest.mark.skipif(sys.platform == 'darwin', reason="Ticket - 122182")
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@pytest.mark.xfail(platform.machine() in ["aarch64", "arm64", "ARM64"], reason='Ticket - 122716')

‎tests/layer_tests/tensorflow_tests/test_tf_UnaryOpsAllRealDomain.py

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Original file line numberDiff line numberDiff line change
@@ -0,0 +1,70 @@
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# Copyright (C) 2018-2024 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import numpy as np
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import platform
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import pytest
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import tensorflow as tf
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from common.tf_layer_test_class import CommonTFLayerTest
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rng = np.random.default_rng(253512)
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class TestUnaryOpsAllRealDomain(CommonTFLayerTest):
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def _prepare_input(self, inputs_info):
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assert 'x:0' in inputs_info, "Test error: inputs_info must contain `x`"
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x_shape = inputs_info['x:0']
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inputs_data = {}
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inputs_data['x:0'] = rng.uniform(-5.0, 5.0, x_shape).astype(self.input_type)
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return inputs_data
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def create_unary_net(self, input_shape, input_type, op_type):
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op_type_map = {
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'Elu': lambda x: tf.raw_ops.Elu(features=x),
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'Sigmoid': tf.raw_ops.Sigmoid,
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'Sin': tf.raw_ops.Sin,
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'Sinh': tf.raw_ops.Sinh,
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'Cos': tf.raw_ops.Cos,
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'Cosh': tf.raw_ops.Cosh,
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'Exp': tf.raw_ops.Exp,
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'Atan': tf.raw_ops.Atan,
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'Softplus': lambda x: tf.raw_ops.Softplus(features=x),
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'Erf': tf.raw_ops.Erf,
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'Selu': lambda x: tf.raw_ops.Selu(features=x)
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}
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self.input_type = input_type
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tf.compat.v1.reset_default_graph()
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# Create the graph and model
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with tf.compat.v1.Session() as sess:
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x = tf.compat.v1.placeholder(input_type, input_shape, 'x')
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op_type_map[op_type](x=x)
42+
tf.compat.v1.global_variables_initializer()
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tf_net = sess.graph_def
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return tf_net, None
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@pytest.mark.parametrize("input_shape", [[], [2], [3, 4], [3, 2, 4]])
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@pytest.mark.parametrize("input_type", [np.float16, np.float32, np.float64])
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@pytest.mark.parametrize("op_type", ['Elu',
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'Sigmoid',
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'Sin',
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'Sinh',
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'Cos',
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'Cosh',
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'Exp',
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'Atan',
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'Softplus',
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'Erf',
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'Selu'])
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@pytest.mark.precommit
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@pytest.mark.nightly
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def test_unary_ops(self, input_shape, input_type, op_type,
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ie_device, precision, ir_version, temp_dir,
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use_legacy_frontend):
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if platform.machine() in ["aarch64", "arm64", "ARM64"] and op_type in ['Cos', 'Cosh', 'Sinh', 'Exp']:
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pytest.skip("159585: accuracy error on ARM")
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self._test(*self.create_unary_net(input_shape, input_type, op_type),
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ie_device, precision, ir_version, temp_dir=temp_dir,
70+
use_legacy_frontend=use_legacy_frontend, custom_eps=1e-3)

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