def test_get_metadata_multiple_inputs(self):
builder = graph_metadata_builder.GraphMetadataBuilder()
builder.add_image_metadata(
self.linear_layer, visualization={'type': 'Pixels'})
builder.add_numeric_metadata(self.x, name='my_input')
builder.add_output_metadata(self.prediction)
md_dict = builder.get_metadata()
expected_md = {
'framework': 'Tensorflow',
'inputs': {
'Add': {
'visualization': {
'type': 'Pixels'
},
'input_tensor_name': 'Add:0',
'encoding': 'identity',
'modality': 'image'
},
'my_input': {
'input_tensor_name': 'inp:0',
'encoding': 'identity',
'modality': 'numeric'
}
},
'outputs': {
'Relu': {
'output_tensor_name': 'Relu:0'
}
},
'tags': ['explainable_ai_sdk']
}
self.assertDictEqual(expected_md, md_dict)
def test_add_output_metadata(self):
builder = graph_metadata_builder.GraphMetadataBuilder()
builder.add_output_metadata(self.prediction, 'my_output')
md_dict = builder.get_metadata()
expected_out_md = {'my_output': {'output_tensor_name': 'Relu:0'}}
self.assertDictEqual(expected_out_md, md_dict['outputs'])
def test_add_numeric_metadata_no_name(self):
builder = graph_metadata_builder.GraphMetadataBuilder()
builder.add_numeric_metadata(self.x)
md_dict = builder.get_metadata()
expected_input_md = {
'inp': {
'input_tensor_name': 'inp:0',
'encoding': 'identity',
'modality': 'numeric',
}
}
self.assertDictEqual(expected_input_md, md_dict['inputs'])
def test_add_image_metadata_domain(self, domain, domain_dict):
builder = graph_metadata_builder.GraphMetadataBuilder()
builder.add_image_metadata(self.x, domain=domain)
md_dict = builder.get_metadata()
expected_input_md = {
'inp': {
'input_tensor_name': 'inp:0',
'encoding': 'identity',
'modality': 'image'
}
}
expected_input_md['inp'].update(domain_dict)
self.assertDictEqual(expected_input_md, md_dict['inputs'])
def test_add_numeric_metadata_index_feature_mapping(self):
builder = graph_metadata_builder.GraphMetadataBuilder()
builder.add_numeric_metadata(
self.x, name='mapped', index_feature_mapping=['a', 'b'])
md_dict = builder.get_metadata()
expected_input_md = {
'mapped': {
'input_tensor_name': 'inp:0',
'encoding': 'bag_of_features',
'modality': 'numeric',
'index_feature_mapping': ['a', 'b']
}
}
self.assertDictEqual(expected_input_md, md_dict['inputs'])
def test_add_text_metadata(self):
builder = graph_metadata_builder.GraphMetadataBuilder()
builder.add_text_metadata(
self.x, encoded_tensor=self.linear_layer, encoding='combined_embedding')
md_dict = builder.get_metadata()
expected_input_md = {
'inp': {
'input_tensor_name': 'inp:0',
'encoding': 'combined_embedding',
'encoded_tensor_name': 'Add:0',
'modality': 'text'
}
}
self.assertDictEqual(expected_input_md, md_dict['inputs'])
def test_add_image_metadata(self):
builder = graph_metadata_builder.GraphMetadataBuilder()
builder.add_image_metadata(self.x, visualization={'type': 'Pixels'})
md_dict = builder.get_metadata()
expected_input_md = {
'inp': {
'visualization': {
'type': 'Pixels'
},
'input_tensor_name': 'inp:0',
'encoding': 'identity',
'modality': 'image'
}
}
self.assertDictEqual(expected_input_md, md_dict['inputs'])
def test_save_model_with_metadata_kwargs(self):
builder = graph_metadata_builder.GraphMetadataBuilder(
session=self.sess, tags=['testing'], strip_default_attrs=False)
builder.add_image_metadata(self.linear_layer,
visualization={'type': 'Pixels'})
builder.add_numeric_metadata(self.x, name='my_input')
builder.add_output_metadata(self.prediction)
model_path = os.path.join(tf.test.get_temp_dir(), 'model_kwargs')
builder.save_model_with_metadata(model_path)
metadata_file_path = os.path.join(model_path,
'explanation_metadata.json')
saved_model_file_path = os.path.join(model_path, 'saved_model.pb')
self.assertTrue(os.path.isfile(metadata_file_path))
self.assertTrue(os.path.isfile(saved_model_file_path))
def test_save_model_with_metadata(self):
builder = graph_metadata_builder.GraphMetadataBuilder(session=self.sess)
builder.add_image_metadata(
self.linear_layer, visualization={'type': 'Pixels'})
builder.add_numeric_metadata(self.x, name='my_input')
builder.add_output_metadata(self.prediction)
model_path = os.path.join(tf.test.get_temp_dir(), 'multi_modal')
builder.save_model_with_metadata(model_path)
metadata_file_path = os.path.join(model_path, 'explanation_metadata.json')
saved_model_file_path = os.path.join(model_path, 'saved_model.pb')
self.assertTrue(os.path.isfile(metadata_file_path))
with tf.io.gfile.GFile(metadata_file_path, 'r') as f:
written_md = json.load(f)
self.assertDictEqual(builder.get_metadata(), written_md)
self.assertTrue(os.path.isfile(saved_model_file_path))
def test_add_numeric_metadata_same_tensor(self):
builder = graph_metadata_builder.GraphMetadataBuilder()
builder.add_numeric_metadata(self.x, name='same')
with self.assertRaisesRegex(ValueError, 'Input tensor .* exists'):
builder.add_numeric_metadata(name='different', input_tensor=self.x)
def test_add_numeric_metadata_same_name(self):
builder = graph_metadata_builder.GraphMetadataBuilder()
builder.add_numeric_metadata(self.x, name='same')
with self.assertRaisesRegex(ValueError, 'Input name .* exists'):
builder.add_numeric_metadata(name='same', input_tensor=self.linear_layer)
def test_add_output_metadata_multiple(self):
builder = graph_metadata_builder.GraphMetadataBuilder()
builder.add_output_metadata(self.prediction, 'my_output1')
with self.assertRaisesRegex(ValueError, 'Only one output can be added'):
builder.add_output_metadata(self.x, 'my_output2')
