56f2bc2f12
* Add support api 2.0 * Upd imports * Update onnx_tests * Upd tenserflow_tests * Fix test_split_concat.py * Fixed comparing
207 lines
8.4 KiB
Python
207 lines
8.4 KiB
Python
# Copyright (C) 2018-2022 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import pytest
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from common.tf_layer_test_class import CommonTFLayerTest
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from common.utils.tf_utils import permute_nchw_to_nhwc
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class TestBiasAdd(CommonTFLayerTest):
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def create_bias_add_placeholder_const_net(self, shape, ir_version, use_new_frontend):
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"""
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Tensorflow net IR net
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Placeholder->BiasAdd => Placeholder->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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import numpy as np
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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 = shape.copy()
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tf_x_shape = permute_nchw_to_nhwc(tf_x_shape, use_new_frontend)
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tf_y_shape = tf_x_shape[-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(0, 1, 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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tf.nn.bias_add(x, y, name="Operation")
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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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ref_net = None
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return tf_net, ref_net
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def create_bias_add_2_consts_net(self, shape, ir_version, use_new_frontend):
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"""
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Tensorflow net IR net
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Const->BiasAdd-->Concat => Const---->Concat
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/ / /
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Const--/ / Placeholder-/
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/
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Placeholder---/
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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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import numpy as np
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tf.compat.v1.reset_default_graph()
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tf_concat_axis = -1
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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 = shape.copy()
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tf_x_shape = permute_nchw_to_nhwc(tf_x_shape, use_new_frontend)
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tf_y_shape = tf_x_shape[-1:]
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constant_value_x = np.random.randint(-256, 256, tf_x_shape).astype(np.float32)
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x = tf.constant(constant_value_x)
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constant_value_y = np.random.randint(-256, 256, tf_y_shape).astype(np.float32)
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y = tf.constant(constant_value_y)
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add = tf.nn.bias_add(x, y, name="Operation")
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placeholder = tf.compat.v1.placeholder(tf.float32, tf_x_shape,
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'Input') # Input_1 in graph_def
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concat = tf.concat([placeholder, add], axis=tf_concat_axis, name='Operation')
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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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ref_net = None
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return tf_net, ref_net
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test_data_2D = [
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dict(shape=[1, 1]),
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dict(shape=[1, 224])
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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_bias_add_placeholder_const_2D(self, params, ie_device, precision, ir_version, temp_dir,
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use_new_frontend, api_2):
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self._test(*self.create_bias_add_placeholder_const_net(**params, ir_version=ir_version,
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use_new_frontend=use_new_frontend),
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ie_device, precision, ir_version, temp_dir=temp_dir,
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use_new_frontend=use_new_frontend, api_2=api_2)
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@pytest.mark.parametrize("params", test_data_2D)
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@pytest.mark.nightly
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def test_bias_add_2_consts_2D(self, params, ie_device, precision, ir_version, temp_dir,
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use_new_frontend, api_2):
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self._test(*self.create_bias_add_2_consts_net(**params, ir_version=ir_version,
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use_new_frontend=use_new_frontend),
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ie_device, precision, ir_version, temp_dir=temp_dir,
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use_new_frontend=use_new_frontend, api_2=api_2)
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test_data_3D = [
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pytest.param(dict(shape=[1, 1, 224]), marks=pytest.mark.xfail(reason="*-19053")),
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pytest.param(dict(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_bias_add_placeholder_const_3D(self, params, ie_device, precision, ir_version, temp_dir,
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use_new_frontend, api_2):
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self._test(*self.create_bias_add_placeholder_const_net(**params, ir_version=ir_version,
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use_new_frontend=use_new_frontend),
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ie_device, precision, ir_version, temp_dir=temp_dir,
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use_new_frontend=use_new_frontend, api_2=api_2)
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@pytest.mark.parametrize("params", test_data_3D)
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@pytest.mark.nightly
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def test_bias_add_2_consts_3D(self, params, ie_device, precision, ir_version, temp_dir,
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use_new_frontend, api_2):
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self._test(*self.create_bias_add_2_consts_net(**params, ir_version=ir_version,
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use_new_frontend=use_new_frontend),
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ie_device, precision, ir_version, temp_dir=temp_dir,
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use_new_frontend=use_new_frontend, api_2=api_2)
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test_data_4D = [
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dict(shape=[1, 1, 100, 224]),
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dict(shape=[1, 3, 100, 224])
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]
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@pytest.mark.parametrize("params", test_data_4D)
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@pytest.mark.nightly
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@pytest.mark.precommit
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def test_bias_add_placeholder_const_4D(self, params, ie_device, precision, ir_version, temp_dir,
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use_new_frontend, api_2):
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self._test(*self.create_bias_add_placeholder_const_net(**params, ir_version=ir_version,
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use_new_frontend=use_new_frontend),
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ie_device, precision, ir_version, temp_dir=temp_dir,
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use_new_frontend=use_new_frontend, api_2=api_2)
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@pytest.mark.parametrize("params", test_data_4D)
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@pytest.mark.nightly
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def test_bias_add_2_consts_4D(self, params, ie_device, precision, ir_version, temp_dir,
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use_new_frontend, api_2):
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self._test(*self.create_bias_add_2_consts_net(**params, ir_version=ir_version,
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use_new_frontend=use_new_frontend),
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ie_device, precision, ir_version, temp_dir=temp_dir,
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use_new_frontend=use_new_frontend, api_2=api_2)
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test_data_5D = [
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dict(shape=[1, 1, 50, 100, 224]),
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dict(shape=[1, 3, 220, 222, 224])
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]
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@pytest.mark.parametrize("params", test_data_5D)
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@pytest.mark.nightly
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@pytest.mark.precommit
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def test_bias_add_placeholder_const_5D(self, params, ie_device, precision, ir_version, temp_dir,
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use_new_frontend, api_2):
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self._test(*self.create_bias_add_placeholder_const_net(**params, ir_version=ir_version,
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use_new_frontend=use_new_frontend),
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ie_device, precision, ir_version, temp_dir=temp_dir,
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use_new_frontend=use_new_frontend, api_2=api_2)
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@pytest.mark.parametrize("params", test_data_5D)
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@pytest.mark.nightly
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def test_bias_add_2_consts_5D(self, params, ie_device, precision, ir_version, temp_dir,
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use_new_frontend, api_2):
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self._test(*self.create_bias_add_2_consts_net(**params, ir_version=ir_version,
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use_new_frontend=use_new_frontend),
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ie_device, precision, ir_version, temp_dir=temp_dir,
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use_new_frontend=use_new_frontend, api_2=api_2)
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