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Remove run_deprecated_v1 qualifier from saved_model:simple_save_test.

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PiperOrigin-RevId: 323613279
Change-Id: I96f174f589c203acb7303627a33131867d9ac5bb
This commit is contained in:
Cesar Crusius 2020-07-28 11:18:23 -07:00 committed by TensorFlower Gardener
parent 482d273416
commit 111f48de6e
1 changed files with 39 additions and 36 deletions
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75
tensorflow/python/saved_model/simple_save_test.py
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@ -21,7 +21,6 @@ from __future__ import print_function
import os
from tensorflow.python.framework import ops
from tensorflow.python.framework import test_util
from tensorflow.python.ops import variables
from tensorflow.python.platform import test
from tensorflow.python.saved_model import loader
@ -32,7 +31,7 @@ from tensorflow.python.saved_model import tag_constants
class SimpleSaveTest(test.TestCase):
def _init_and_validate_variable(self, sess, variable_name, variable_value):
def _init_and_validate_variable(self, variable_name, variable_value):
v = variables.Variable(variable_value, name=variable_name)
self.evaluate(variables.global_variables_initializer())
self.assertEqual(variable_value, self.evaluate(v))
@ -54,50 +53,54 @@ class SimpleSaveTest(test.TestCase):
self.assertEqual(actual_tensor_info.tensor_shape.dim[i].size,
expected_tensor.shape[i])
@test_util.run_deprecated_v1
def testSimpleSave(self):
"""Test simple_save that uses the default parameters."""
export_dir = os.path.join(test.get_temp_dir(),
"test_simple_save")
# Initialize input and output variables and save a prediction graph using
# the default parameters.
with self.session(graph=ops.Graph()) as sess:
var_x = self._init_and_validate_variable(sess, "var_x", 1)
var_y = self._init_and_validate_variable(sess, "var_y", 2)
inputs = {"x": var_x}
outputs = {"y": var_y}
simple_save.simple_save(sess, export_dir, inputs, outputs)
# Force the test to run in graph mode.
# This tests a deprecated v1 API that both requires a session and uses
# functionality that does not work with eager tensors (such as
# build_tensor_info as called by predict_signature_def).
with ops.Graph().as_default():
# Initialize input and output variables and save a prediction graph using
# the default parameters.
with self.session(graph=ops.Graph()) as sess:
var_x = self._init_and_validate_variable("var_x", 1)
var_y = self._init_and_validate_variable("var_y", 2)
inputs = {"x": var_x}
outputs = {"y": var_y}
simple_save.simple_save(sess, export_dir, inputs, outputs)
# Restore the graph with a valid tag and check the global variables and
# signature def map.
with self.session(graph=ops.Graph()) as sess:
graph = loader.load(sess, [tag_constants.SERVING], export_dir)
collection_vars = ops.get_collection(ops.GraphKeys.GLOBAL_VARIABLES)
# Restore the graph with a valid tag and check the global variables and
# signature def map.
with self.session(graph=ops.Graph()) as sess:
graph = loader.load(sess, [tag_constants.SERVING], export_dir)
collection_vars = ops.get_collection(ops.GraphKeys.GLOBAL_VARIABLES)
# Check value and metadata of the saved variables.
self.assertEqual(len(collection_vars), 2)
self.assertEqual(1, collection_vars[0].eval())
self.assertEqual(2, collection_vars[1].eval())
self._check_variable_info(collection_vars[0], var_x)
self._check_variable_info(collection_vars[1], var_y)
# Check value and metadata of the saved variables.
self.assertEqual(len(collection_vars), 2)
self.assertEqual(1, collection_vars[0].eval())
self.assertEqual(2, collection_vars[1].eval())
self._check_variable_info(collection_vars[0], var_x)
self._check_variable_info(collection_vars[1], var_y)
# Check that the appropriate signature_def_map is created with the
# default key and method name, and the specified inputs and outputs.
signature_def_map = graph.signature_def
self.assertEqual(1, len(signature_def_map))
self.assertEqual(signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY,
list(signature_def_map.keys())[0])
# Check that the appropriate signature_def_map is created with the
# default key and method name, and the specified inputs and outputs.
signature_def_map = graph.signature_def
self.assertEqual(1, len(signature_def_map))
self.assertEqual(signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY,
list(signature_def_map.keys())[0])
signature_def = signature_def_map[
signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY]
self.assertEqual(signature_constants.PREDICT_METHOD_NAME,
signature_def.method_name)
signature_def = signature_def_map[
signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY]
self.assertEqual(signature_constants.PREDICT_METHOD_NAME,
signature_def.method_name)
self.assertEqual(1, len(signature_def.inputs))
self._check_tensor_info(signature_def.inputs["x"], var_x)
self.assertEqual(1, len(signature_def.outputs))
self._check_tensor_info(signature_def.outputs["y"], var_y)
self.assertEqual(1, len(signature_def.inputs))
self._check_tensor_info(signature_def.inputs["x"], var_x)
self.assertEqual(1, len(signature_def.outputs))
self._check_tensor_info(signature_def.outputs["y"], var_y)
if __name__ == "__main__":