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Modify test cases which are failing parallel execution #21877

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LakshmiGayathri19
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  • Addressing the "Known limitation" issue for test cases which failed parallel execution.

Details:

  • Few tests cases failed when parallel execution is enabled.
  • These failed test cases are modified in order to execute with out errors.
  • After modification, two test cases failed due to inconsistent number of parameters passed to the test case.
  • The two test cases which failed due to parameter inconsistency is addressed in this commit.

Tickets:

* Addressing the "Known limitation" issue for test cases which
      failed parallel execution.
@github-actions github-actions bot added the category: TF FE OpenVINO TensorFlow FrontEnd label Dec 27, 2023
Comment on lines -57 to 89
self._test(*self.create_keras_upsampling2d_net(**params, input_type=input_type, data_format=data_format,
interpolation=interpolation, ir_version=ir_version),
self._test(*self.create_keras_upsampling2d_net(**params, ir_version=ir_version),
ie_device, precision, temp_dir=temp_dir, use_old_api=use_old_api, ir_version=ir_version,
use_new_frontend=use_new_frontend, **params)

# Tests for bilinear interpolation
test_data_bilinear = [
pytest.param((["x1"], [[1, 6, 2, 1]], tf.float32, (3, 1), 'channels_last', 'bilinear'), marks=pytest.mark.precommit_tf_fe),
(["x1"], [[1, 3, 1, 6]], tf.float32, (5, 2), 'channels_last', 'bilinear')
]

@pytest.mark.parametrize("params", test_data_bilinear)
@pytest.mark.nightly
def test_keras_upsampling2d_bilinear(self, params, ie_device, precision, ir_version, temp_dir,
use_old_api, use_new_frontend):
input_names, input_shapes, input_type, size, data_format, interpolation = params
self._test(*self.create_keras_upsampling2d_net(input_names=input_names, input_shapes=input_shapes, input_type=input_type, size=size, data_format=data_format, interpolation=interpolation,
ir_version=ir_version), ie_device, precision, temp_dir=temp_dir, use_old_api=use_old_api, ir_version=ir_version, use_new_frontend=use_new_frontend, **params)

test_data_channels_first = [
dict(input_names=["x1"], input_shapes=[[5, 4, 5, 3]], input_type=tf.float32,
size=(3, 4), data_format='channels_first', interpolation='nearest'),
dict(input_names=["x1"], input_shapes=[[3, 2, 7, 2]], input_type=tf.float32,
size=(2, 3), data_format='channels_first', interpolation='nearest'),
dict(input_names=["x1"], input_shapes=[[3, 5, 4, 6]], input_type=tf.float32,
size=(5, 2), data_format='channels_first', interpolation='nearest'),
]

@pytest.mark.parametrize("params", test_data_channels_first)
@pytest.mark.nightly
def test_keras_upsampling2d_channels_first(self, params, ie_device, precision, ir_version,
temp_dir, use_old_api, use_new_frontend):
self._test(*self.create_keras_upsampling2d_net(**params, ir_version=ir_version),
ie_device, precision, temp_dir=temp_dir, use_old_api=use_old_api, ir_version=ir_version,
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please revert these changes. The latest update covers sufficient cases

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@rkazants rkazants left a comment

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please address one comment

@rkazants
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rkazants commented Dec 27, 2023

@LakshmiGayathri19, why did you open new PR?:)
It seems to be a duplicate PR. Let us close this one and proceed the work here: #21851

I just resolved conflicts there:)

Best regards,
Roman

@LakshmiGayathri19
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@rkazants, I was asked to resolve merge conflict and push the changes. So I misunderstood and raised a new PR. I will close this PR and continue working on the old one.

@LakshmiGayathri19
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Duplicate PR.

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2 participants