00c7da0f5f
* Revert submodule changes * Fix build on Win * Fix precommit: set correct shapes for broadcasting; disable check with ref for use_new_frontend mode * fix precommit * Fix precommits * Temporary skip new tests on GPU with FP16 * Resolve review comments, trigger CI * Resolve review comments * Resolve review comments
75 lines
2.7 KiB
Python
75 lines
2.7 KiB
Python
# Copyright (C) 2018-2021 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import os
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from common.layer_test_class import CommonLayerTest
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from common.utils.tf_utils import summarize_graph
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def transpose_nchw_to_nhwc(data, use_new_frontend):
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if use_new_frontend:
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return data
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if len(data.shape) == 4: # reshaping for 4D tensors
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return data.transpose(0, 2, 3, 1)
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elif len(data.shape) == 5: # reshaping for 5D tensors
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return data.transpose(0, 2, 3, 4, 1)
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else:
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return data
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def transpose_nhwc_to_nchw(data, use_new_frontend):
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if use_new_frontend:
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return data
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if len(data.shape) == 4: # reshaping for 4D tensors
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return data.transpose(0, 3, 1, 2) # 2, 0, 1
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elif len(data.shape) == 5: # reshaping for 5D tensors
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return data.transpose(0, 4, 1, 2, 3) # 3, 0, 1, 2
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else:
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return data
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def save_to_pb(tf_model, path_to_saved_tf_model):
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import tensorflow as tf
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tf.io.write_graph(tf_model, path_to_saved_tf_model, 'model.pb', False)
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assert os.path.isfile(os.path.join(path_to_saved_tf_model, 'model.pb')), "model.pb haven't been saved " \
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"here: {}".format(path_to_saved_tf_model)
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return os.path.join(path_to_saved_tf_model, 'model.pb')
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class CommonTFLayerTest(CommonLayerTest):
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def produce_model_path(self, framework_model, save_path):
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return save_to_pb(framework_model, save_path)
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def get_framework_results(self, inputs_dict, model_path):
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# Evaluate model via Tensorflow and IE
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# Load the Tensorflow model
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import tensorflow as tf
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from tensorflow.python.platform import gfile
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graph_summary = summarize_graph(model_path=model_path)
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outputs_list = graph_summary["outputs"]
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tf.compat.v1.reset_default_graph()
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with tf.compat.v1.Session() as sess:
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with gfile.FastGFile(model_path, 'rb') as f:
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graph_def = tf.compat.v1.GraphDef()
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graph_def.ParseFromString(f.read())
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sess.graph.as_default()
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tf.compat.v1.import_graph_def(graph_def, name='')
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input = dict()
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for key in inputs_dict.keys():
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data = inputs_dict.get(key)
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input[key + ':0'] = transpose_nchw_to_nhwc(data, self.use_new_frontend)
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tf_res = sess.run([out + ":0" for out in outputs_list], input)
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result = dict()
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for i, output in enumerate(outputs_list):
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_tf_res = tf_res[i]
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result[output] = transpose_nhwc_to_nchw(_tf_res, self.use_new_frontend)
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return result
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