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TF FE layer tests in precommit (#13254) 

* marks specified tests with precommit_tf_fe mark

* adds tf layer tests for new fe into the precommit

* removes redundant tab

* removes redundant tab

* clean-ups

* clean-ups

* change import path for build_graph func

* set path to mo

* set path to mo for PYTHONPATH

* get back imports

* left only CPU runs

* return back skip for LogSoftmax op since it still was not fixed

* adds test for GRUBlockCell op
This commit is contained in:
Ruslan Nugmanov 2022-09-30 10:39:06 +04:00 committed by GitHub
parent 6e7016ccda
commit 515ec44566
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
30 changed files with 81 additions and 88 deletions
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9
.ci/azure/linux.yml
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@ -452,6 +452,15 @@ jobs:
displayName: 'Layer Tests - Tensorflow'
continueOnError: false
- script: |
python3 -m pip install -r $(LAYER_TESTS_DIR)/requirements.txt
export PYTHONPATH=$(REPO_DIR)/tools/mo/:$(LAYER_TESTS_DIR):$PYTHONPATH
export OV_FRONTEND_PATH=$(INSTALL_DIR)/runtime/lib/intel64
export TEST_DEVICE=CPU
$(RUN_PREFIX) python3 -m pytest $(LAYER_TESTS_DIR)/tensorflow_tests/ --use_new_frontend -m precommit_tf_fe --junitxml=$(INSTALL_TEST_DIR)/TEST-tf_fe.xmlTEST
displayName: 'TensorFlow 1 Layer Tests - TF FE'
continueOnError: false
- script: |
python3 -m pip install -r $(LAYER_TESTS_DIR)/requirements.txt
export PYTHONPATH=$(LAYER_TESTS_DIR):$PYTHONPATH

3
tests/layer_tests/tensorflow_tests/test_tf_BatchToSpace.py
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@ -29,8 +29,7 @@ class TestBatchToSpace(CommonTFLayerTest):
x = tf.compat.v1.placeholder(tf.float32, in_shape, 'Input')
crops = tf.constant(crops_value)
block_shape = tf.constant(block_shape_value)
tf.batch_to_space_nd(x, block_shape, crops, name='Operation')
tf.compat.v1.batch_to_space(x, crops, block_shape, name='Operation')
tf.compat.v1.global_variables_initializer()
tf_net = sess.graph_def

2
tests/layer_tests/tensorflow_tests/test_tf_BiasAdd.py
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@ -159,7 +159,7 @@ class TestBiasAdd(CommonTFLayerTest):
test_data_4D = [
dict(shape=[1, 1, 100, 224]),
dict(shape=[1, 3, 100, 224])
pytest.param(dict(shape=[1, 3, 100, 224]), marks=pytest.mark.precommit_tf_fe)
]
@pytest.mark.parametrize("params", test_data_4D)

3
tests/layer_tests/tensorflow_tests/test_tf_BinaryOps.py
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@ -112,7 +112,8 @@ class TestBinaryOps(CommonTFLayerTest):
return tf_net, ref_net
test_data_precommits = [dict(x_shape=[2, 3, 4], y_shape=[2, 3, 4]),
dict(x_shape=[2, 3, 4, 5], y_shape=[2, 3, 4, 5])]
pytest.param(dict(x_shape=[2, 3, 4, 5], y_shape=[2, 3, 4, 5]),
marks=pytest.mark.precommit_tf_fe)]
@pytest.mark.parametrize("params", test_data_precommits)
@pytest.mark.parametrize("op_type",

3
tests/layer_tests/tensorflow_tests/test_tf_Bucketize.py
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@ -60,7 +60,8 @@ class TestBucketize(CommonTFLayerTest):
test_data_float32 = [
dict(input_shape=[5], input_type=tf.float32, boundaries_size=1),
dict(input_shape=[5], input_type=tf.float32, boundaries_size=3),
dict(input_shape=[4, 8], input_type=tf.float32, boundaries_size=5),
pytest.param(dict(input_shape=[4, 8], input_type=tf.float32, boundaries_size=5),
marks=pytest.mark.precommit_tf_fe),
dict(input_shape=[2, 4, 7], input_type=tf.float32, boundaries_size=10),
dict(input_shape=[2, 4, 7, 8], input_type=tf.float32, boundaries_size=12),
dict(input_shape=[2, 4, 7, 8, 10], input_type=tf.float32, boundaries_size=14)]

6
tests/layer_tests/tensorflow_tests/test_tf_Concat.py
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@ -80,9 +80,9 @@ class TestConcat(CommonTFLayerTest):
use_new_frontend=use_new_frontend, use_old_api=use_old_api)
test_data_3D = [
pytest.param(dict(shape=[1, 3, 224], axis=0), marks=pytest.mark.xfail(reason="*-19053")),
pytest.param(dict(shape=[1, 3, 224], axis=-1), marks=pytest.mark.xfail(reason="*-19053")),
pytest.param(dict(shape=[1, 3, 224], axis=2), marks=pytest.mark.xfail(reason="*-19053"))]
dict(shape=[1, 3, 224], axis=0),
pytest.param(dict(shape=[1, 3, 224], axis=-1), marks=pytest.mark.precommit_tf_fe),
dict(shape=[1, 3, 224], axis=2)]
@pytest.mark.parametrize("params", test_data_3D)
@pytest.mark.nightly

3
tests/layer_tests/tensorflow_tests/test_tf_Eltwise.py
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@ -57,7 +57,8 @@ class TestEltwise(CommonTFLayerTest):
test_data = []
for operation in ['sum', 'max', 'mul']:
test_data.extend([dict(shape=[1, 224], operation=operation),
dict(shape=[1, 224, 224], operation=operation),
pytest.param(dict(shape=[1, 224, 224], operation=operation),
marks=pytest.mark.precommit_tf_fe),
dict(shape=[1, 3, 224, 224], operation=operation)])
@pytest.mark.parametrize("params", test_data)

6
tests/layer_tests/tensorflow_tests/test_tf_FakeQuantize.py
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@ -5,8 +5,8 @@ import numpy as np
import pytest
from common.layer_test_class import check_ir_version
from common.tf_layer_test_class import CommonTFLayerTest
from openvino.tools.mo.front.common.partial_infer.utils import int64_array
from unit_tests.utils.graph import build_graph, regular_op_with_shaped_data, connect, \
shaped_data, connect_front, regular_op
@ -89,8 +89,8 @@ class TestFakeQuantize(CommonTFLayerTest):
test_data = [
# with8BitsNoScalingNoNudging
dict(il=0.0, ih=255.0, num_bits=8, narrow_range=False, nudged_il=0.0, nudged_ih=255.0,
expected_step=1.0),
pytest.param(dict(il=0.0, ih=255.0, num_bits=8, narrow_range=False, nudged_il=0.0, nudged_ih=255.0,
expected_step=1.0), marks=pytest.mark.precommit_tf_fe),
# with8BitsScalingAndNudgingDown
dict(il=0.5, ih=128.0, num_bits=8, narrow_range=False, nudged_il=0.0, nudged_ih=127.5,
expected_step=0.5),

2
tests/layer_tests/tensorflow_tests/test_tf_GRUBlockCell.py
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@ -58,7 +58,7 @@ class TestTFGRUBlockCell(CommonTFLayerTest):
dict(batch_size=1, input_size=15, hidden_size=10),
dict(batch_size=2, input_size=6, hidden_size=6),
dict(batch_size=2, input_size=12, hidden_size=6),
dict(batch_size=2, input_size=6, hidden_size=12),
pytest.param(dict(batch_size=2, input_size=6, hidden_size=12), marks=pytest.mark.precommit_tf_fe),
]
@pytest.mark.parametrize("params", test_data)

3
tests/layer_tests/tensorflow_tests/test_tf_Gather.py
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@ -50,7 +50,8 @@ class TestGather(CommonTFLayerTest):
dict(data_shape=[10, 12], axis=1, indices=[[0, 1, 3, 4, 5], [6, 7, 9, 10, 11]],
batch_dims=0),
dict(data_shape=[8, 10, 12], axis=0, indices=[3, 6], batch_dims=0),
dict(data_shape=[8, 10, 12], axis=-1, indices=[5, 8], batch_dims=0),
pytest.param(dict(data_shape=[8, 10, 12], axis=-1, indices=[5, 8], batch_dims=0),
marks=pytest.mark.precommit_tf_fe),
dict(data_shape=[6, 8, 10, 12], axis=0, indices=[2, 5], batch_dims=0),
dict(data_shape=[6, 8, 10, 12], axis=-1, indices=[5, 8], batch_dims=0),
dict(data_shape=[6, 8, 10, 12], axis=2, indices=[[0, 2, 4], [5, 7, 9]], batch_dims=0),

4
tests/layer_tests/tensorflow_tests/test_tf_Identity.py
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@ -76,8 +76,8 @@ class TestIdentity(CommonTFLayerTest):
use_new_frontend=use_new_frontend, use_old_api=use_old_api)
test_data = [dict(shape=[1]),
dict(shape=[1, 224]),
pytest.param(dict(shape=[1, 3, 224]), marks=pytest.mark.xfail(reason="*-19053")),
pytest.param(dict(shape=[1, 224]), marks=pytest.mark.precommit_tf_fe),
dict(shape=[1, 3, 224]),
dict(shape=[1, 3, 100, 224]),
dict(shape=[1, 3, 50, 100, 224])]

2
tests/layer_tests/tensorflow_tests/test_tf_LogSoftmax.py
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@ -131,7 +131,7 @@ class TestLogSoftmax(CommonTFLayerTest):
test_data = [dict(shape=[1], reduction_axis=-1),
dict(shape=[2, 5], reduction_axis=-1),
dict(shape=[5, 3, 7, 4], reduction_axis=-1),
pytest.param(dict(shape=[5, 3, 7, 4], reduction_axis=-1), marks=pytest.mark.precommit_tf_fe),
dict(shape=[3, 2, 3, 7, 6], reduction_axis=-1)]
@pytest.mark.parametrize("params", test_data)

2
tests/layer_tests/tensorflow_tests/test_tf_Mul.py
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@ -277,7 +277,7 @@ class TestMul(CommonTFLayerTest):
# Power
dict(x_shape=[1, 3, 1, 1, 1], y_shape=[1, 1]),
# ScaleShift
dict(x_shape=[1, 3, 1, 1, 1], y_shape=[3]),
pytest.param(dict(x_shape=[1, 3, 1, 1, 1], y_shape=[3]), marks=pytest.mark.precommit_tf_fe),
# Eltwise
dict(x_shape=[1, 1, 1, 1, 3], y_shape=[3]),
# Eltwise

4
tests/layer_tests/tensorflow_tests/test_tf_NormalizeL2.py
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@ -5,8 +5,8 @@ import numpy as np
import pytest
from common.tf_layer_test_class import CommonTFLayerTest
from common.utils.tf_utils import permute_nchw_to_nhwc
from openvino.tools.mo.front.common.partial_infer.utils import int64_array
from unit_tests.utils.graph import build_graph
@ -184,7 +184,7 @@ class TestNormalizeL2(CommonTFLayerTest):
dict(shape=[5, 6], axes=[1], output_axes=[1]),
dict(shape=[2, 3, 5], axes=[1], output_axes=[1]),
dict(shape=[2, 3, 5], axes=[-2], output_axes=[1]),
dict(shape=[2, 3, 5], axes=[1, -1], output_axes=[1, 2]),
pytest.param(dict(shape=[2, 3, 5], axes=[1, -1], output_axes=[1, 2]), marks=pytest.mark.precommit_tf_fe),
dict(shape=[2, 3, 5, 7], axes=[-1], output_axes=[1]),
dict(shape=[2, 3, 5, 7], axes=[1, 2, 3], output_axes=[2, 3, 1]),
]

3
tests/layer_tests/tensorflow_tests/test_tf_OneHot.py
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@ -103,7 +103,8 @@ class TestOneHot(CommonTFLayerTest):
# check for default on/off value, axis params
dict(shape=[5, 6, 7], depth=8, on_value=None, off_value=None, axis=0),
dict(shape=[5, 6, 7], depth=8, on_value=None, off_value=None, axis=1),
dict(shape=[5, 6, 7], depth=8, on_value=None, off_value=None, axis=2),
pytest.param(dict(shape=[5, 6, 7], depth=8, on_value=None, off_value=None, axis=2),
marks=pytest.mark.precommit_tf_fe),
]
@pytest.mark.parametrize("params", test_data_3D)

6
tests/layer_tests/tensorflow_tests/test_tf_RandomUniform.py
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@ -6,8 +6,8 @@ import tensorflow as tf
from common.layer_test_class import check_ir_version
from common.tf_layer_test_class import CommonTFLayerTest
from common.utils.tf_utils import permute_nchw_to_nhwc
from openvino.tools.mo.front.common.partial_infer.utils import int64_array
from unit_tests.utils.graph import build_graph, regular_op_with_shaped_data, connect, \
shaped_data, connect_front
@ -91,8 +91,8 @@ class TestTFRandomUniform(CommonTFLayerTest):
input_type=tf.float32),
dict(global_seed=None, op_seed=56197, min_val=-100, max_val=100, x_shape=[1, 2, 1, 1],
input_type=tf.float32),
dict(global_seed=78132, op_seed=None, min_val=-200, max_val=-50, x_shape=[5, 8],
input_type=tf.int32),
pytest.param(dict(global_seed=78132, op_seed=None, min_val=-200, max_val=-50, x_shape=[5, 8],
input_type=tf.int32), marks=pytest.mark.precommit_tf_fe),
dict(global_seed=4571, op_seed=48971, min_val=1.5, max_val=2.3, x_shape=[7],
input_type=tf.float32),
dict(global_seed=32465, op_seed=12335, min_val=-150, max_val=-100, x_shape=[18],

4
tests/layer_tests/tensorflow_tests/test_tf_ReLU6.py
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@ -76,8 +76,8 @@ class TestReLU6(CommonTFLayerTest):
use_new_frontend=use_new_frontend, use_old_api=use_old_api)
test_data = [dict(shape=[1]),
dict(shape=[1, 224]),
pytest.param(dict(shape=[1, 3, 224]), marks=pytest.mark.xfail(reason="*-19053")),
pytest.param(dict(shape=[1, 224]), marks=pytest.mark.precommit_tf_fe),
dict(shape=[1, 3, 224]),
dict(shape=[1, 3, 100, 224]),
dict(shape=[1, 3, 50, 100, 224])]

2
tests/layer_tests/tensorflow_tests/test_tf_Reduce.py
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@ -37,7 +37,7 @@ class TestReduceOps(CommonTFLayerTest):
for operation in ['sum', 'max', 'prod', 'min', 'mean']:
test_data.extend([
dict(shape=[2, 3], operation=operation, axis=1),
dict(shape=[2, 3, 5], operation=operation, axis=-2),
pytest.param(dict(shape=[2, 3, 5], operation=operation, axis=-2), marks=pytest.mark.precommit_tf_fe),
dict(shape=[2, 3, 5, 7], operation=operation, axis=2),
dict(shape=[2, 3, 5, 7, 9], operation=operation, axis=[2, -1]),
])

3
tests/layer_tests/tensorflow_tests/test_tf_Resample_pattern_new.py
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@ -72,13 +72,12 @@ class TestResamplePattern(CommonTFLayerTest):
return tf_net, ref_net
test_data = [dict(shape=[1, 1, 100, 200], factor=2),
test_data = [pytest.param(dict(shape=[1, 1, 100, 200], factor=2), marks=pytest.mark.precommit_tf_fe),
dict(shape=[1, 1, 200, 300], factor=3)]
# TODO mark as precommit (after successfully passing in nightly)
@pytest.mark.parametrize("params", test_data)
@pytest.mark.nightly
@pytest.mark.xfail(reason="*-22273")
def test_resample(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend,
use_old_api):
self._test(*self.create_resample_net(params['shape'], params['factor'], use_new_frontend),

2
tests/layer_tests/tensorflow_tests/test_tf_ReverseV2.py
View File

@ -30,7 +30,7 @@ class TestReverseV2Ops(CommonTFLayerTest):
test_data = []
test_data.extend([
dict(shape=[5], axis=[0]),
dict(shape=[2, 3], axis=[1]),
pytest.param(dict(shape=[2, 3], axis=[1]), marks=pytest.mark.precommit_tf_fe),
dict(shape=[2, 3, 5], axis=[-2]),
dict(shape=[2, 3, 5, 7], axis=[0]),
])

3
tests/layer_tests/tensorflow_tests/test_tf_Roll.py
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@ -29,7 +29,8 @@ class TestTFRoll(CommonTFLayerTest):
return tf_net, ref_net
test_data = [dict(shift=[1], axis=[-1], x_shape=[4, 3], input_type=tf.float32),
dict(shift=[1, 5, -7], axis=[0, 1, 1], x_shape=[2, 3, 5], input_type=tf.float16),
pytest.param(dict(shift=[1, 5, -7], axis=[0, 1, 1], x_shape=[2, 3, 5], input_type=tf.float16),
marks=pytest.mark.precommit_tf_fe),
dict(shift=[11, -8], axis=[-1, -2], x_shape=[3, 4, 3, 1], input_type=tf.int32),
dict(shift=[7, -2, 5], axis=[0, -1, -1], x_shape=[5, 2, 3, 7],
input_type=tf.int64),

4
tests/layer_tests/tensorflow_tests/test_tf_Rsqrt.py
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@ -64,8 +64,8 @@ class TestRsqrt(CommonTFLayerTest):
use_new_frontend=use_new_frontend, use_old_api=use_old_api)
test_data = [dict(shape=[1]),
dict(shape=[1, 224]),
pytest.param(dict(shape=[1, 3, 224]), marks=pytest.mark.xfail(reason="*-19053")),
pytest.param(dict(shape=[1, 224]), marks=pytest.mark.precommit_tf_fe),
dict(shape=[1, 3, 224]),
dict(shape=[1, 3, 100, 224]),
dict(shape=[1, 3, 50, 100, 224])]

3
tests/layer_tests/tensorflow_tests/test_tf_ScatterND.py
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@ -61,7 +61,8 @@ class TestTFScatterND(CommonTFLayerTest):
[[5.0, 5.0, 5.0, 5.0], [6.0, 6.0, 6.0, 6.0], [7.0, 7.0, 7.0, 7.0],
[8.0, 8.0, 8.0, 8.0]]]),
dict(x_shape=[2, 2, 2], indices=[[1, 1, 1], [0, 1, 0]], updates=[9.0, 6.3]),
dict(x_shape=[2, 2, 2], indices=[[0, 0], [0, 1]], updates=[[6.7, 9.0], [45.0, 8.3]]),
pytest.param(dict(x_shape=[2, 2, 2], indices=[[0, 0], [0, 1]], updates=[[6.7, 9.0], [45.0, 8.3]]),
marks=pytest.mark.precommit_tf_fe),
dict(x_shape=[2, 2, 2], indices=[[1]], updates=[[[6.7, 9.0], [45.0, 8.3]]]),
]

2
tests/layer_tests/tensorflow_tests/test_tf_Select.py
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@ -64,7 +64,7 @@ class TestSelect(CommonTFLayerTest):
use_new_frontend=use_new_frontend, use_old_api=use_old_api)
test_data_2D = [
dict(shape_condition=[2], shape_input=[2, 3]),
pytest.param(dict(shape_condition=[2], shape_input=[2, 3]), marks=pytest.mark.precommit_tf_fe),
dict(shape_condition=[3, 5], shape_input=[3, 5]),
]

4
tests/layer_tests/tensorflow_tests/test_tf_SpaceToBatch.py
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@ -49,8 +49,8 @@ class TestSpaceToBatch(CommonTFLayerTest):
out_shape=[4, 1, 1, 3]),
dict(in_shape=[1, 2, 2, 1], block_shape_value=[2, 2], pads_value=[[0, 0], [0, 0]],
out_shape=[4, 1, 1, 3]),
dict(in_shape=[1, 2, 2, 3], block_shape_value=[2, 2], pads_value=[[0, 0], [0, 0]],
out_shape=[4, 1, 1, 3]),
pytest.param(dict(in_shape=[1, 2, 2, 3], block_shape_value=[2, 2], pads_value=[[0, 0], [0, 0]],
out_shape=[4, 1, 1, 3]), marks=pytest.mark.precommit_tf_fe),
dict(in_shape=[1, 2, 9, 1], block_shape_value=[4, 3], pads_value=[[1, 1], [2, 4]],
out_shape=[12, 1, 1, 3]),
# todo: enable these tests after supporting the general case on CPU

24
tests/layer_tests/tensorflow_tests/test_tf_Squeeze.py
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@ -62,9 +62,9 @@ class TestSqueeze(CommonTFLayerTest):
use_new_frontend=use_new_frontend, use_old_api=use_old_api)
test_data_2D = [
pytest.param(dict(shape=[1, 1], axis=[]), marks=pytest.mark.xfail(reason="*-18807")),
dict(shape=[1, 1], axis=[]),
dict(shape=[1, 1], axis=[0]),
dict(shape=[1, 1], axis=[-1])
pytest.param(dict(shape=[1, 1], axis=[-1]), marks=pytest.mark.precommit_tf_fe)
]
@pytest.mark.parametrize("params", test_data_2D)
@ -77,11 +77,9 @@ class TestSqueeze(CommonTFLayerTest):
use_new_frontend=use_new_frontend, use_old_api=use_old_api)
test_data_3D = [
pytest.param(dict(shape=[1, 1, 3], axis=[]),
marks=[pytest.mark.xfail(reason="*-18807"),
pytest.mark.xfail(reason="*-19053")]),
pytest.param(dict(shape=[1, 1, 3], axis=[0]), marks=pytest.mark.xfail(reason="*-19053")),
pytest.param(dict(shape=[1, 1, 3], axis=[-1]), marks=pytest.mark.xfail(reason="*-19053"))
dict(shape=[1, 1, 3], axis=[]),
dict(shape=[1, 1, 3], axis=[0]),
dict(shape=[1, 1, 3], axis=[-1])
]
# TODO mark as precommit (after successfully passing in nightly)
@ -95,8 +93,7 @@ class TestSqueeze(CommonTFLayerTest):
use_new_frontend=use_new_frontend, use_old_api=use_old_api)
test_data_4D = [
pytest.param(dict(shape=[1, 1, 50, 100], axis=[]),
marks=pytest.mark.xfail(reason="*-18807")),
dict(shape=[1, 1, 50, 100], axis=[]),
dict(shape=[1, 1, 50, 100], axis=[0]),
dict(shape=[1, 1, 50, 100], axis=[-1]),
dict(shape=[1, 100, 50, 1], axis=[0, 2])
@ -113,12 +110,9 @@ class TestSqueeze(CommonTFLayerTest):
use_new_frontend=use_new_frontend, use_old_api=use_old_api)
test_data_5D = [
pytest.param(dict(shape=[1, 1, 50, 100, 224], axis=[]),
marks=pytest.mark.xfail(reason="*-18807")),
pytest.param(dict(shape=[1, 1, 50, 100, 224], axis=[0]),
marks=pytest.mark.xfail(reason="*-18879")),
pytest.param(dict(shape=[1, 1, 50, 100, 224], axis=[-1]),
marks=pytest.mark.xfail(reason="*-18879")),
dict(shape=[1, 1, 50, 100, 224], axis=[]),
dict(shape=[1, 1, 50, 100, 224], axis=[0]),
dict(shape=[1, 1, 50, 100, 224], axis=[-1]),
dict(shape=[1, 224, 1, 100, 1], axis=[0, 3]),
dict(shape=[1, 224, 1, 100, 1], axis=[0, 1, 3]),
dict(shape=[1, 224, 1, 1, 100], axis=[0, 1, 2]),

6
tests/layer_tests/tensorflow_tests/test_tf_StridedSlice.py
View File

@ -44,9 +44,9 @@ class TestStridedSlice(CommonTFLayerTest):
end_mask=0, ellipsis_mask=0, new_axis_mask=0, shrink_axis_mask=2),
dict(input_shape=[1, 5, 1], begin=[0, 0, 0], end=[1, 5, 1], strides=[1, 1, 1], begin_mask=0,
end_mask=0, ellipsis_mask=0, new_axis_mask=0, shrink_axis_mask=4),
dict(input_shape=[1, 5, 5, 3], begin=[0, 0, 0, 0], end=[1, 5, 5, 3], strides=[1, 1, 1, 1],
begin_mask=0,
end_mask=0, ellipsis_mask=0, new_axis_mask=0, shrink_axis_mask=1),
pytest.param(dict(input_shape=[1, 5, 5, 3], begin=[0, 0, 0, 0], end=[1, 5, 5, 3], strides=[1, 1, 1, 1],
begin_mask=0, end_mask=0, ellipsis_mask=0, new_axis_mask=0, shrink_axis_mask=1),
marks=pytest.mark.precommit_tf_fe),
dict(input_shape=[1, 1, 5, 3], begin=[0, 0, 0, 0], end=[1, 1, 5, 3], strides=[1, 1, 1, 1],
begin_mask=0,
end_mask=0, ellipsis_mask=0, new_axis_mask=0, shrink_axis_mask=2),

47
tests/layer_tests/tensorflow_tests/test_tf_Sub.py
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@ -64,7 +64,7 @@ class TestSub(CommonTFLayerTest):
# Power
dict(x_shape=[1], y_shape=[1]),
# Eltwise
pytest.param(dict(x_shape=[3], y_shape=[3]), marks=pytest.mark.xfail(reason="*-19180"))
dict(x_shape=[3], y_shape=[3])
]
@pytest.mark.parametrize("params", test_data_1D)
@ -82,8 +82,7 @@ class TestSub(CommonTFLayerTest):
# ScaleShift
dict(x_shape=[1, 3], y_shape=[1, 3]),
# Eltwise
pytest.param(dict(x_shape=[3, 1], y_shape=[3, 1]),
marks=pytest.mark.xfail(reason="*-19180")),
dict(x_shape=[3, 1], y_shape=[3, 1]),
# Eltwise
dict(x_shape=[2, 3], y_shape=[2, 3])
]
@ -101,12 +100,9 @@ class TestSub(CommonTFLayerTest):
# Power
dict(x_shape=[1, 1, 1], y_shape=[1, 1, 1]),
# ScaleShift
pytest.param(dict(x_shape=[1, 3, 1], y_shape=[1, 3, 1]),
marks=pytest.mark.xfail(reason="*-19053")),
dict(x_shape=[1, 3, 1], y_shape=[1, 3, 1]),
# Eltwise
pytest.param(dict(x_shape=[1, 1, 3], y_shape=[1, 1, 3]),
marks=[pytest.mark.xfail(reason="*-19053"),
pytest.mark.xfail(reason="*-18830")]),
dict(x_shape=[1, 1, 3], y_shape=[1, 1, 3]),
# Eltwise
pytest.param(dict(x_shape=[1, 3, 224], y_shape=[1, 3, 224]),
marks=pytest.mark.xfail(reason="*-19053"))
@ -128,8 +124,7 @@ class TestSub(CommonTFLayerTest):
# ScaleShift
dict(x_shape=[1, 3, 1, 1], y_shape=[1, 3, 1, 1]),
# Eltwise
pytest.param(dict(x_shape=[1, 1, 1, 3], y_shape=[1, 1, 1, 3]),
marks=pytest.mark.xfail(reason="*-19180")),
dict(x_shape=[1, 1, 1, 3], y_shape=[1, 1, 1, 3]),
# Eltwise
dict(x_shape=[1, 3, 222, 224], y_shape=[1, 3, 222, 224])
]
@ -150,8 +145,7 @@ class TestSub(CommonTFLayerTest):
# ScaleShift
dict(x_shape=[1, 3, 1, 1, 1], y_shape=[1, 3, 1, 1, 1]),
# Eltwise
pytest.param(dict(x_shape=[1, 1, 1, 1, 3], y_shape=[1, 1, 1, 1, 3]),
marks=pytest.mark.xfail(reason="*-19180")),
dict(x_shape=[1, 1, 1, 1, 3], y_shape=[1, 1, 1, 1, 3]),
# Eltwise
dict(x_shape=[1, 3, 50, 100, 224], y_shape=[1, 3, 50, 100, 224])
]
@ -195,8 +189,7 @@ class TestSub(CommonTFLayerTest):
# Eltwise
dict(x_shape=[3, 1], y_shape=[3]),
# Eltwise
pytest.param(dict(x_shape=[3, 1], y_shape=[1, 3, 1, 1]),
marks=pytest.mark.xfail(reason="*-19051"))
dict(x_shape=[3, 1], y_shape=[1, 3, 1, 1]),
]
@pytest.mark.parametrize("params", test_data_broadcast_2D)
@ -212,23 +205,17 @@ class TestSub(CommonTFLayerTest):
# Power
dict(x_shape=[1, 1, 1], y_shape=[1]),
# Power
pytest.param(dict(x_shape=[1, 3, 1], y_shape=[1]),
marks=pytest.mark.xfail(reason="*-19053")),
dict(x_shape=[1, 3, 1], y_shape=[1]),
# ScaleShift
pytest.param(dict(x_shape=[1, 3, 1], y_shape=[3]),
marks=pytest.mark.xfail(reason="*-19053")),
dict(x_shape=[1, 3, 1], y_shape=[3]),
# Eltwise
pytest.param(dict(x_shape=[1, 3, 1], y_shape=[3, 1]),
marks=pytest.mark.xfail(reason="*-19053")),
dict(x_shape=[1, 3, 1], y_shape=[3, 1]),
# Eltwise
pytest.param(dict(x_shape=[1, 1, 1], y_shape=[3, 1]),
marks=pytest.mark.xfail(reason="*-19053")),
dict(x_shape=[1, 1, 1], y_shape=[3, 1]),
# Eltwise
pytest.param(dict(x_shape=[3, 1, 224], y_shape=[1, 3, 224]),
marks=pytest.mark.xfail(reason="*-19053")),
dict(x_shape=[3, 1, 224], y_shape=[1, 3, 224]),
# Eltwise
pytest.param(dict(x_shape=[2, 3, 1], y_shape=[1, 3, 2]),
marks=pytest.mark.xfail(reason="*-19053")),
dict(x_shape=[2, 3, 1], y_shape=[1, 3, 2]),
]
# TODO mark as precommit (after successfully passing in nightly)
@ -259,8 +246,7 @@ class TestSub(CommonTFLayerTest):
# Eltwise
dict(x_shape=[1, 3, 1, 2], y_shape=[1, 3, 2]),
# Eltwise
pytest.param(dict(x_shape=[1, 3, 100, 224], y_shape=[1, 1, 1, 224]),
marks=pytest.mark.xfail(reason="*-19180")),
dict(x_shape=[1, 3, 100, 224], y_shape=[1, 1, 1, 224]),
# Eltwise
dict(x_shape=[2, 3, 1, 2], y_shape=[1, 3, 2, 1])
]
@ -287,12 +273,11 @@ class TestSub(CommonTFLayerTest):
# Eltwise
dict(x_shape=[1, 3, 1, 1, 1], y_shape=[3, 1]),
# Eltwise
dict(x_shape=[1, 3, 1, 1, 2], y_shape=[1, 3, 2]),
pytest.param(dict(x_shape=[1, 3, 1, 1, 2], y_shape=[1, 3, 2]), marks=pytest.mark.precommit_tf_fe),
# Eltwise
dict(x_shape=[1, 3, 5, 1, 2], y_shape=[5, 3, 2, 1]),
# Eltwise
pytest.param(dict(x_shape=[1, 3, 50, 100, 224], y_shape=[1, 1, 1, 1, 224]),
marks=pytest.mark.xfail(reason="*-19180")),
dict(x_shape=[1, 3, 50, 100, 224], y_shape=[1, 1, 1, 1, 224]),
# Eltwise
dict(x_shape=[2, 3, 1, 2, 1], y_shape=[1, 3, 2, 1, 1])
]

2
tests/layer_tests/tensorflow_tests/test_tf_TopK.py
View File

@ -5,8 +5,8 @@ import pytest
from common.layer_test_class import check_ir_version
from common.tf_layer_test_class import CommonTFLayerTest
from common.utils.tf_utils import permute_nchw_to_nhwc, permute_axis
from openvino.tools.mo.ops.op import PermuteAttrs
from unit_tests.utils.graph import build_graph

2
tests/layer_tests/tensorflow_tests/test_tf_UnaryOps.py
View File

@ -166,7 +166,7 @@ class TestUnaryOps(CommonTFLayerTest):
ie_device, precision, ir_version, temp_dir=temp_dir,
use_new_frontend=use_new_frontend, use_old_api=use_old_api)
test_data = [dict(shape=[10, 12]),
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])]