0c9abf43a9
* Updated copyright headers
* Revert "Fixed linker warnings in docs snippets on Windows (#15119)"
This reverts commit 372699ec49.
70 lines
3.0 KiB
Python
70 lines
3.0 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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from common.tf_layer_test_class import CommonTFLayerTest
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class TestTFGRUBlockCell(CommonTFLayerTest):
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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(np.float32)
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return inputs_dict
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def create_tf_gru_block_cell(self, batch_size, input_size, hidden_size):
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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 = [batch_size, input_size]
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tf_h_prev_shape = [batch_size, hidden_size]
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tf_w_ru_shape = [input_size + hidden_size, hidden_size * 2]
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tr_w_c_shape = [input_size + hidden_size, hidden_size]
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tf_b_ru_shape = [hidden_size * 2]
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tf_b_c_shape = [hidden_size]
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random_generator = np.random.default_rng(2022)
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x = random_generator.uniform(0, 1, tf_x_shape).astype(np.float32)
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h_prev = random_generator.uniform(0, 1, tf_h_prev_shape).astype(np.float32)
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w_ru = random_generator.uniform(0, 1, tf_w_ru_shape).astype(np.float32)
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w_c = random_generator.uniform(0, 1, tr_w_c_shape).astype(np.float32)
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b_ru = random_generator.uniform(0, 1, tf_b_ru_shape).astype(np.float32)
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b_c = random_generator.uniform(0, 1, tf_b_c_shape).astype(np.float32)
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r, u, c, h = tf.raw_ops.GRUBlockCell(x=x, h_prev=h_prev, w_ru=w_ru, w_c=w_c, b_ru=b_ru, b_c=b_c, name="TFGRUBlockCell")
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# Dummy Add layer to prevent from Const network, and compare only "h" output
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input_zero = tf.compat.v1.placeholder(tf.as_dtype(np.float32), tf_h_prev_shape, 'Input')
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add = tf.add(h, input_zero)
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tf.compat.v1.global_variables_initializer()
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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 = [
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dict(batch_size=1, input_size=6, hidden_size=6),
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dict(batch_size=1, input_size=10, hidden_size=15),
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dict(batch_size=1, input_size=15, hidden_size=10),
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dict(batch_size=2, input_size=6, hidden_size=6),
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dict(batch_size=2, input_size=12, hidden_size=6),
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pytest.param(dict(batch_size=2, input_size=6, hidden_size=12), marks=pytest.mark.precommit_tf_fe),
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]
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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_gru_block_cell(self, params, ie_device, precision, ir_version, temp_dir,
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use_new_frontend, use_old_api):
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if ie_device == 'GPU':
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pytest.skip("Skip TF GRUBlockCell test on GPU")
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self._test(*self.create_tf_gru_block_cell(**params),
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ie_device, precision, temp_dir=temp_dir, ir_version=ir_version,
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use_new_frontend=use_new_frontend, use_old_api=use_old_api, custom_eps=1e-3, **params)
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