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[TF FE] Fix layer tests for BatchToSpace and add to the pre-commit (#16722)

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* [TF FE] Fix layer tests for BatchToSpace and add to the pre-commit

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

* Specify type for batch_shape

---------

Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>
This commit is contained in:
Roman Kazantsev 2023-04-04 18:46:12 +04:00 committed by GitHub
parent d4b394c1b6
commit c034975183
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1 changed files with 27 additions and 43 deletions
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tests/layer_tests/tensorflow_tests/test_tf_BatchToSpace.py
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@ -7,77 +7,61 @@ from common.tf_layer_test_class import CommonTFLayerTest
class TestBatchToSpace(CommonTFLayerTest):
def create_batch_to_space_net(self, in_shape, crops_value, block_shape_value, out_shape,
ir_version, use_new_frontend):
"""
Tensorflow net IR net
Input->BatchToSpace => Input->BatchToSpace
"""
def create_batch_to_space_net(self, in_shape, crops_value, block_shape_value):
import tensorflow as tf
tf.compat.v1.reset_default_graph()
# Create the graph and model
with tf.compat.v1.Session() as sess:
x = tf.compat.v1.placeholder(tf.float32, in_shape, 'Input')
crops = tf.constant(crops_value)
block_shape = tf.constant(block_shape_value)
tf.compat.v1.batch_to_space(x, crops, block_shape, name='Operation')
crops = tf.constant(crops_value, dtype=tf.int32)
block_shape = tf.constant(block_shape_value, dtype=tf.int32)
tf.batch_to_space(input=x, block_shape=block_shape, crops=crops, name='Operation')
tf.compat.v1.global_variables_initializer()
tf_net = sess.graph_def
#
# Create reference IR net
# Please, specify 'type': 'Input' for input node
# Moreover, do not forget to validate ALL layer attributes!!!
#
return tf_net, None
ref_net = None
test_data_basic = [
dict(in_shape=[4, 1, 1, 3], block_shape_value=[1], crops_value=[[0, 0]]),
dict(in_shape=[12, 1, 1, 3], block_shape_value=[3, 1, 4], crops_value=[[1, 0], [0, 0], [1, 1]]),
dict(in_shape=[72, 2, 1, 4, 2], block_shape_value=[3, 4, 2],
crops_value=[[1, 2], [0, 0], [3, 0]]),
]
return tf_net, ref_net
@pytest.mark.parametrize("params", test_data_basic)
@pytest.mark.precommit_tf_fe
@pytest.mark.nightly
def test_batch_to_space_basic(self, params, ie_device, precision, ir_version, temp_dir,
use_new_frontend, use_old_api):
self._test(*self.create_batch_to_space_net(**params),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_new_frontend=use_new_frontend, use_old_api=use_old_api)
test_data_4D = [
dict(in_shape=[4, 1, 1, 3], block_shape_value=[1], crops_value=[[0, 0]],
out_shape=[4, 1, 1, 3]),
dict(in_shape=[4, 1, 1, 3], block_shape_value=[2, 2], crops_value=[[0, 0], [0, 0]],
out_shape=[1, 2, 2, 3]),
dict(in_shape=[60, 100, 30, 30], block_shape_value=[3, 2], crops_value=[[1, 5], [4, 1]],
out_shape=[2, 2, 1, 1]),
# todo: enable these tests after supporting the general case on CPU
# dict(in_shape=[4, 1, 1, 1], block_shape_value=[2, 1, 2], crops_value=[[0, 0], [0, 0], [0, 0]],
# out_shape=[]),
# dict(in_shape=[12, 1, 1, 3], block_shape_value=[3, 2, 2], crops_value=[[1, 0], [0, 1], [1, 1]],
# out_shape=[1, 2, 1, 4]),
# dict(in_shape=[36, 2, 2, 3], block_shape_value=[2, 3, 3], crops_value=[[1, 0], [0, 0], [2, 2]],
# out_shape=[2, 3, 6, 5])
dict(in_shape=[4, 1, 1, 3], block_shape_value=[2, 2], crops_value=[[0, 0], [0, 0]]),
dict(in_shape=[60, 100, 30, 30], block_shape_value=[3, 2], crops_value=[[1, 5], [4, 1]]),
dict(in_shape=[4, 1, 1, 1], block_shape_value=[2, 1, 2], crops_value=[[0, 0], [0, 0], [0, 0]]),
dict(in_shape=[36, 2, 2, 3], block_shape_value=[2, 3, 3], crops_value=[[1, 0], [0, 0], [2, 2]])
]
@pytest.mark.parametrize("params", test_data_4D)
@pytest.mark.nightly
def test_batch_to_space_4D(self, params, ie_device, precision, ir_version, temp_dir,
use_new_frontend, use_old_api):
self._test(*self.create_batch_to_space_net(**params, ir_version=ir_version,
use_new_frontend=use_new_frontend),
self._test(*self.create_batch_to_space_net(**params),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_new_frontend=use_new_frontend, use_old_api=use_old_api)
test_data_5D = [
dict(in_shape=[72, 2, 1, 4, 2], block_shape_value=[3, 4, 2],
crops_value=[[1, 2], [0, 0], [3, 0]],
out_shape=[3, 3, 4, 5, 2]),
# todo: enable these tests after supporting the general case on CPU
# dict(in_shape=[144, 2, 1, 4, 1], block_shape_value=[3, 4, 2, 2],
# crops_value=[[1, 2], [0, 0], [3, 0], [0, 0]], out_shape=[3, 3, 4, 5, 2]),
dict(in_shape=[144, 2, 1, 4, 1], block_shape_value=[3, 4, 2, 2],
crops_value=[[1, 2], [0, 0], [3, 0], [0, 0]]),
]
@pytest.mark.parametrize("params", test_data_5D)
@pytest.mark.nightly
def test_batch_to_space_5D(self, params, ie_device, precision, ir_version, temp_dir,
use_new_frontend, use_old_api):
self._test(*self.create_batch_to_space_net(**params, ir_version=ir_version,
use_new_frontend=use_new_frontend),
self._test(*self.create_batch_to_space_net(**params),
ie_device, precision, ir_version, temp_dir=temp_dir,
use_new_frontend=use_new_frontend, use_old_api=use_old_api)