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[TF FE] Switch on ConvLSTM2D layer tests in pre-commit (#21520)

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* [TF FE] Switch on ConvLSTM2D layer tests in pre-commit

Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>

* Remove extra blank line

---------

Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>
This commit is contained in:
Roman Kazantsev
2023-12-07 17:46:58 +04:00
committed by GitHub
parent e393678590
commit ec40652cea
1 changed files with 19 additions and 39 deletions
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58
tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_conv_lstm_2d.py
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@@ -15,19 +15,11 @@ class TestKerasConvLSTM2D(CommonTF2LayerTest):
assert len(input_names) == 1, "Test expects only one input"
x_shape = inputs_info[input_names[0]]
inputs_data = {}
inputs_data[input_names[0]] = np.random.uniform(-1, 1, x_shape)
inputs_data[input_names[0]] = np.random.uniform(-1, 1, x_shape).astype(np.float32)
return inputs_data
def create_keras_conv_lstm_2d_net(self, params, input_shapes):
activation_func_structure = {
"relu": tf.nn.relu,
"swish": tf.nn.swish,
"elu": tf.nn.elu,
}
if "activation" in params:
params["activation"] = activation_func_structure[params["activation"]]
# create TensorFlow 2 model with Keras ConvLSTM2D operation
tf.keras.backend.clear_session()
@@ -38,13 +30,24 @@ class TestKerasConvLSTM2D(CommonTF2LayerTest):
return tf2_net, None
test_data_basic = [
pytest.param(dict(params=dict(filters=4, kernel_size=(3, 3), padding='same', return_sequences=False,
activation="swish"),
input_shapes=[[2, 5, 20, 30, 2]]), marks=pytest.mark.skip(reason="*-108786")),
pytest.param(dict(params=dict(filters=6, kernel_size=(2, 3), padding='valid', dilation_rate=3,
recurrent_activation="elu", return_sequences=True, use_bias=True,
data_format="channels_first"),
input_shapes=[[2, 5, 1, 40, 30]]), marks=pytest.mark.skip(reason="110006")),
dict(params=dict(filters=4, kernel_size=(3, 3), padding='same', return_sequences=False,
activation=tf.nn.swish),
input_shapes=[[2, 5, 20, 30, 2]]),
dict(params=dict(filters=6, kernel_size=(2, 3), padding='valid', dilation_rate=3,
recurrent_activation=tf.nn.elu, return_sequences=True, use_bias=True,
data_format="channels_first"),
input_shapes=[[2, 5, 1, 40, 30]]),
dict(params=dict(filters=3, kernel_size=(3, 3), padding='valid', return_sequences=False),
input_shapes=[[2, 5, 20, 30, 1]]),
dict(params=dict(filters=2, kernel_size=(2, 2), padding='same', return_sequences=False, activation=tf.nn.swish),
input_shapes=[[2, 5, 25, 15, 3]]),
dict(params=dict(filters=3, kernel_size=(3, 3), padding='valid', strides=(2, 2),
return_sequences=True),
input_shapes=[[2, 5, 10, 15, 2]]),
dict(params=dict(filters=5, kernel_size=(2, 2), padding='valid', dilation_rate=3,
activation=tf.nn.relu, return_sequences=False, use_bias=True,
data_format="channels_last"),
input_shapes=[[2, 5, 18, 17, 1]])
]
@pytest.mark.parametrize("params", test_data_basic)
@@ -56,26 +59,3 @@ class TestKerasConvLSTM2D(CommonTF2LayerTest):
precision,
temp_dir=temp_dir, use_old_api=use_old_api, ir_version=ir_version,
use_new_frontend=use_new_frontend, **params)
test_data_others = [
dict(params=dict(filters=3, kernel_size=(3, 3), padding='valid', return_sequences=False),
input_shapes=[[2, 5, 20, 30, 1]]),
dict(params=dict(filters=2, kernel_size=(2, 2), padding='same', return_sequences=False, activation="swish"),
input_shapes=[[2, 5, 25, 15, 3]]),
dict(params=dict(filters=3, kernel_size=(3, 3), padding='valid', strides=(2, 2),
return_sequences=True),
input_shapes=[[2, 5, 10, 15, 2]]),
dict(params=dict(filters=5, kernel_size=(2, 2), padding='valid', dilation_rate=3,
activation="relu", return_sequences=False, use_bias=True,
data_format="channels_last"),
input_shapes=[[2, 5, 18, 17, 1]])
]
@pytest.mark.parametrize("params", test_data_others)
@pytest.mark.nightly
def test_keras_conv_lstm_2d_others(self, params, ie_device, precision, ir_version, temp_dir,
use_old_api, use_new_frontend):
self._test(*self.create_keras_conv_lstm_2d_net(**params), ie_device,
precision,
temp_dir=temp_dir, use_old_api=use_old_api, ir_version=ir_version,
use_new_frontend=use_new_frontend, **params)