Alexander Shchepetovandalexander.shchepetov
b0c508d4ff
Co-authored-by: alexander.shchepetov <ashchepe@nnlvdp-cflr51.inn.intel.com>
282 lines
11 KiB
Python
282 lines
11 KiB
Python
# Copyright (C) 2018-2021 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 pytest
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from common.tf_layer_test_class import CommonTFLayerTest
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class TestAdd(CommonTFLayerTest):
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def create_add_placeholder_const_net(self, x_shape, y_shape, ir_version):
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"""
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Tensorflow net IR net
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Placeholder->Add => Placeholder->Eltwise or Power or ScaleShift
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/ /
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Const-------/ Const-------/
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"""
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#
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# Create Tensorflow model
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#
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import tensorflow as tf
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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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tf_x_shape = x_shape.copy()
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tf_y_shape = y_shape.copy()
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# reshaping
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if len(tf_x_shape) >= 3:
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tf_x_shape.append(tf_x_shape.pop(1))
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if len(tf_y_shape) >= 3:
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tf_y_shape.append(tf_y_shape.pop(1))
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x = tf.compat.v1.placeholder(tf.float32, tf_x_shape, 'Input')
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constant_value = np.random.randint(-256, 256, tf_y_shape).astype(np.float32)
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if (constant_value == 0).all():
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# Avoid elimination of the layer from IR
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constant_value = constant_value + 1
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y = tf.constant(constant_value)
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add = tf.add(x, y, name="Operation")
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add_shape = add.shape.as_list()
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tf.compat.v1.global_variables_initializer()
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tf_net = sess.graph_def
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#
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# Create reference IR net
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# Please, specify 'type': 'Input' for input node
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# Moreover, do not forget to validate ALL layer attributes!!!
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#
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if len(add_shape) >= 3:
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# Permute add_shape to (N,C,...) format
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order = [0, len(add_shape) - 1] + list(range(1, len(add_shape) - 1))
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add_shape = [add_shape[i] for i in order]
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y_shape_to_compare = tf_y_shape.copy()
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while len(y_shape_to_compare) < len(x_shape):
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# Expand shape of constant with 1
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y_shape_to_compare = [1] + y_shape_to_compare
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constant_value = np.expand_dims(constant_value, axis=0)
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if len(y_shape_to_compare) >= 3:
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# Permute constant_value to (N,C,...) format for correct further reshape
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order = [0, len(y_shape_to_compare) - 1] + list(range(1, len(y_shape_to_compare) - 1))
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y_shape_to_compare = [y_shape_to_compare[i] for i in order]
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constant_value = np.transpose(constant_value, order)
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ref_net = None
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return tf_net, ref_net
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# TODO: implement tests for 2 Consts + Add
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test_data_1D = [
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# Power
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dict(x_shape=[1], y_shape=[1]),
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# Eltwise
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pytest.param(dict(x_shape=[3], y_shape=[3]), marks=pytest.mark.xfail(reason="*-19180"))
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]
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@pytest.mark.parametrize("params", test_data_1D)
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@pytest.mark.nightly
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def test_add_placeholder_const_1D(self, params, ie_device, precision, ir_version, temp_dir):
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self._test(*self.create_add_placeholder_const_net(**params, ir_version=ir_version),
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ie_device, precision, ir_version, temp_dir=temp_dir)
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test_data_2D = [
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# Power
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dict(x_shape=[1, 1], y_shape=[1, 1]),
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# ScaleShift
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dict(x_shape=[1, 3], y_shape=[1, 3]),
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# Eltwise
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pytest.param(dict(x_shape=[3, 1], y_shape=[3, 1]), marks=pytest.mark.xfail(reason="*-19180")),
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# Eltwise
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dict(x_shape=[2, 3], y_shape=[2, 3])
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]
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@pytest.mark.parametrize("params", test_data_2D)
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@pytest.mark.nightly
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def test_add_placeholder_const_2D(self, params, ie_device, precision, ir_version, temp_dir):
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self._test(*self.create_add_placeholder_const_net(**params, ir_version=ir_version),
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ie_device, precision, ir_version, temp_dir=temp_dir)
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test_data_3D = [
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# Power
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dict(x_shape=[1, 1, 1], y_shape=[1, 1, 1]),
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# ScaleShift
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pytest.param(dict(x_shape=[1, 3, 1], y_shape=[1, 3, 1]), marks=pytest.mark.xfail(reason="*-19053")),
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# Eltwise
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pytest.param(dict(x_shape=[1, 1, 3], y_shape=[1, 1, 3]),
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marks=[pytest.mark.xfail(reason="*-19053"), pytest.mark.xfail(reason="*-18830")]),
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# Eltwise
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pytest.param(dict(x_shape=[1, 3, 224], y_shape=[1, 3, 224]), marks=pytest.mark.xfail(reason="*-19053"))
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]
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@pytest.mark.parametrize("params", test_data_3D)
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@pytest.mark.nightly
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def test_add_placeholder_const_3D(self, params, ie_device, precision, ir_version, temp_dir):
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self._test(*self.create_add_placeholder_const_net(**params, ir_version=ir_version),
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ie_device, precision, ir_version, temp_dir=temp_dir)
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test_data_4D = [
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# Power
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dict(x_shape=[1, 1, 1, 1], y_shape=[1, 1, 1, 1]),
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# ScaleShift
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dict(x_shape=[1, 3, 1, 1], y_shape=[1, 3, 1, 1]),
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# Eltwise
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pytest.param(dict(x_shape=[1, 1, 1, 3], y_shape=[1, 1, 1, 3]), marks=pytest.mark.xfail(reason="*-19180")),
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# Eltwise
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dict(x_shape=[1, 3, 222, 224], y_shape=[1, 3, 222, 224])
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]
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# TODO mark as precommit (after successfully passing in nightly)
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@pytest.mark.parametrize("params", test_data_4D)
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@pytest.mark.nightly
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def test_add_placeholder_const_4D(self, params, ie_device, precision, ir_version, temp_dir):
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self._test(*self.create_add_placeholder_const_net(**params, ir_version=ir_version),
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ie_device, precision, ir_version, temp_dir=temp_dir)
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test_data_5D = [
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# Power
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dict(x_shape=[1, 1, 1, 1, 1], y_shape=[1, 1, 1, 1, 1]),
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# ScaleShift
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dict(x_shape=[1, 3, 1, 1, 1], y_shape=[1, 3, 1, 1, 1]),
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# Eltwise
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pytest.param(dict(x_shape=[1, 1, 1, 1, 3], y_shape=[1, 1, 1, 1, 3]),
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marks=pytest.mark.xfail(reason="*-19180")),
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# Eltwise
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dict(x_shape=[1, 3, 50, 100, 224], y_shape=[1, 3, 50, 100, 224])
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]
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# TODO mark as precommit (after successfully passing in nightly)
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@pytest.mark.parametrize("params", test_data_5D)
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@pytest.mark.nightly
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def test_add_placeholder_const_5D(self, params, ie_device, precision, ir_version, temp_dir):
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self._test(*self.create_add_placeholder_const_net(**params, ir_version=ir_version),
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ie_device, precision, ir_version=ir_version, temp_dir=temp_dir)
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###############################################################################################
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# #
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# Broadcast cases #
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# #
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###############################################################################################
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test_data_broadcast_1D = [
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# Power
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dict(x_shape=[3], y_shape=[1])
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]
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@pytest.mark.parametrize("params", test_data_broadcast_1D)
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@pytest.mark.nightly
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def test_add_placeholder_const_broadcast_1D(self, params, ie_device, precision, ir_version, temp_dir):
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self._test(*self.create_add_placeholder_const_net(**params, ir_version=ir_version),
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ie_device, precision, ir_version=ir_version, temp_dir=temp_dir)
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test_data_broadcast_2D = [
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# Power
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dict(x_shape=[1, 1], y_shape=[1]),
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# Power
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dict(x_shape=[1, 3], y_shape=[1]),
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# ScaleShift
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dict(x_shape=[1, 3], y_shape=[3]),
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# Eltwise
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dict(x_shape=[3, 1], y_shape=[3]),
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# Eltwise
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pytest.param(dict(x_shape=[3, 1], y_shape=[1, 3, 1, 1]), marks=pytest.mark.xfail(reason="*-19051"))
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]
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@pytest.mark.parametrize("params", test_data_broadcast_2D)
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@pytest.mark.nightly
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def test_add_placeholder_const_broadcast_2D(self, params, ie_device, precision, ir_version, temp_dir):
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self._test(*self.create_add_placeholder_const_net(**params, ir_version=ir_version),
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ie_device, precision, ir_version=ir_version, temp_dir=temp_dir)
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test_data_broadcast_3D = [
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# Power
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dict(x_shape=[1, 1, 1], y_shape=[1]),
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# Power
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pytest.param(dict(x_shape=[1, 3, 1], y_shape=[1]), marks=pytest.mark.xfail(reason="*-19053")),
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# ScaleShift
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pytest.param(dict(x_shape=[1, 3, 1], y_shape=[3]), marks=pytest.mark.xfail(reason="*-19053")),
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# Eltwise
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pytest.param(dict(x_shape=[1, 3, 1], y_shape=[3, 1]), marks=pytest.mark.xfail(reason="*-19053")),
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# Eltwise
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pytest.param(dict(x_shape=[1, 1, 1], y_shape=[3, 1]), marks=pytest.mark.xfail(reason="*-19053")),
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# Eltwise
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pytest.param(dict(x_shape=[3, 1, 224], y_shape=[1, 3, 224]), marks=pytest.mark.xfail(reason="*-19053")),
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# Eltwise
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pytest.param(dict(x_shape=[2, 3, 1], y_shape=[1, 3, 2]), marks=pytest.mark.xfail(reason="*-19053")),
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]
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@pytest.mark.parametrize("params", test_data_broadcast_3D)
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@pytest.mark.nightly
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def test_add_placeholder_const_broadcast_3D(self, params, ie_device, precision, ir_version, temp_dir):
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self._test(*self.create_add_placeholder_const_net(**params, ir_version=ir_version),
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ie_device, precision, ir_version=ir_version, temp_dir=temp_dir)
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test_data_broadcast_4D = [
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# Power
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dict(x_shape=[1, 1, 1, 1], y_shape=[1]),
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# Power
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dict(x_shape=[1, 3, 1, 1], y_shape=[1]),
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# ScaleShift
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dict(x_shape=[1, 3, 1, 1], y_shape=[3]),
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# ScaleShift
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dict(x_shape=[1, 3, 100, 224], y_shape=[3]),
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# Eltwise
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dict(x_shape=[1, 1, 1, 3], y_shape=[3]),
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# Eltwise
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dict(x_shape=[1, 3, 1, 1], y_shape=[3, 1]),
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# Eltwise
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dict(x_shape=[1, 3, 1, 2], y_shape=[3, 1, 2]),
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# Eltwise
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dict(x_shape=[1, 3, 1, 2], y_shape=[1, 3, 2]),
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# Eltwise
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dict(x_shape=[1, 3, 100, 224], y_shape=[1, 1, 1, 224]),
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# Eltwise
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dict(x_shape=[2, 3, 1, 2], y_shape=[1, 3, 2, 1])
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]
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@pytest.mark.parametrize("params", test_data_broadcast_4D)
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@pytest.mark.nightly
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@pytest.mark.precommit
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def test_add_placeholder_const_broadcast_4D(self, params, ie_device, precision, ir_version, temp_dir):
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self._test(*self.create_add_placeholder_const_net(**params, ir_version=ir_version),
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ie_device, precision, ir_version=ir_version, temp_dir=temp_dir)
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test_data_broadcast_5D = [
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# Power
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dict(x_shape=[1, 1, 1, 1, 1], y_shape=[1]),
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# Power
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dict(x_shape=[1, 3, 1, 1, 1], y_shape=[1, 1]),
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# ScaleShift
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dict(x_shape=[1, 3, 1, 1, 1], y_shape=[3]),
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# Eltwise
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dict(x_shape=[1, 1, 1, 1, 3], y_shape=[3]),
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# Eltwise
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dict(x_shape=[1, 3, 1, 1, 1], y_shape=[3, 1]),
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# Eltwise
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dict(x_shape=[1, 3, 1, 1, 2], y_shape=[1, 3, 2]),
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# Eltwise
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dict(x_shape=[1, 3, 5, 1, 2], y_shape=[5, 3, 2, 1]),
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# Eltwise
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dict(x_shape=[1, 3, 50, 100, 224], y_shape=[1, 1, 1, 1, 224]),
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# Eltwise
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dict(x_shape=[2, 3, 1, 2, 1], y_shape=[1, 3, 2, 1, 1])
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]
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@pytest.mark.parametrize("params", test_data_broadcast_5D)
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@pytest.mark.nightly
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@pytest.mark.precommit
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def test_add_placeholder_const_broadcast_5D(self, params, ie_device, precision, ir_version, temp_dir):
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self._test(*self.create_add_placeholder_const_net(**params, ir_version=ir_version), ie_device, precision,
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ir_version=ir_version, temp_dir=temp_dir)
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