0c9abf43a9
* Updated copyright headers
* Revert "Fixed linker warnings in docs snippets on Windows (#15119)"
This reverts commit 372699ec49.
64 lines
2.9 KiB
Python
64 lines
2.9 KiB
Python
# Copyright (C) 2018-2023 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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import tensorflow as tf
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from common.tf_layer_test_class import CommonTFLayerTest
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class TestTFEye(CommonTFLayerTest):
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eye_output_type_param = np.float32
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# Overload inputs generation to fill dummy Add input with 0
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def _prepare_input(self, inputs_dict):
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for input in inputs_dict.keys():
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inputs_dict[input] = np.zeros(inputs_dict[input]).astype(self.eye_output_type_param)
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return inputs_dict
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def create_tf_eye_net(self, num_rows, num_columns, batch_shape, output_type):
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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.compat.v1.global_variables_initializer()
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# batch_shape_input = tf.constant(constant_value)
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if output_type is None:
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eye = tf.eye(num_rows=num_rows, num_columns=num_columns, batch_shape=batch_shape)
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else:
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self.eye_output_type_param = output_type
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eye = tf.eye(num_rows=num_rows, num_columns=num_columns, batch_shape=batch_shape, dtype=tf.as_dtype(output_type))
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# Dummy Add layer to prevent fully const network
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input_zero = tf.compat.v1.placeholder(tf.as_dtype(self.eye_output_type_param), [1], 'Input')
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add = tf.add(eye, input_zero)
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tf_net = sess.graph_def
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ref_net = None
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return tf_net, ref_net
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test_data = [dict(num_rows=5, num_columns=None, batch_shape=None, output_type=None),
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dict(num_rows=5, num_columns=5, batch_shape=[2, 3], output_type=np.float32),
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dict(num_rows=5, num_columns=5, batch_shape=[2, 3], output_type=np.float32),
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dict(num_rows=5, num_columns=5, batch_shape=[2, 3], output_type=np.float16),
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dict(num_rows=5, num_columns=5, batch_shape=[2, 3], output_type=np.int32),
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dict(num_rows=5, num_columns=5, batch_shape=[2, 3], output_type=np.int8),
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dict(num_rows=8, num_columns=5, batch_shape=None, output_type=np.float32),
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dict(num_rows=5, num_columns=8, batch_shape=None, output_type=np.float32),
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dict(num_rows=2, num_columns=2, batch_shape=None, output_type=np.float32),
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dict(num_rows=6, num_columns=6, batch_shape=[2], output_type=np.float32)]
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@pytest.mark.parametrize("params", test_data)
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@pytest.mark.nightly
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@pytest.mark.precommit
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def test_tf_eye(self, params, ie_device, precision, ir_version, temp_dir, use_new_frontend,
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use_old_api=True):
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if ie_device == 'GPU':
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pytest.skip("Roll is not supported on GPU")
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self._test(*self.create_tf_eye_net(**params), ie_device,
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precision,
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temp_dir=temp_dir, ir_version=ir_version, use_new_frontend=use_new_frontend,
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use_old_api=use_old_api, **params)
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