def test_command_line_api(self, inp_format, inp_loc, out_format,
commandline, ng_device):
# Only run this test when grappler is enabled
if not ngraph_bridge.is_grappler_enabled():
return
assert TestConversionScript.format_and_loc_match(inp_format, inp_loc)
out_loc = inp_loc.split('.')[0] + '_modified' + (
'' if out_format == 'savedmodel' else ('.' + out_format))
try:
(shutil.rmtree, os.remove)[os.path.isfile(out_loc)](out_loc)
except:
pass
conversion_successful = False
try:
if commandline:
# In CI this test is expected to be run out of artifacts/test/python
command_executor('python ../../tools/tf2ngraph.py --input' +
inp_format + ' ' + inp_loc +
' --outnodes out_node --output' + out_format +
' ' + out_loc + ' --ngbackend ' + ng_device)
else:
convert(inp_format, inp_loc, out_format, out_loc, ['out_node'],
ng_device)
conversion_successful = True
finally:
if not conversion_successful:
try:
(shutil.rmtree, os.remove)[os.path.isfile(out_loc)](out_loc)
except:
pass
assert conversion_successful
gdef = get_gdef(out_format, out_loc)
(shutil.rmtree, os.remove)[os.path.isfile(out_loc)](out_loc)
with tf.Graph().as_default() as g:
tf.import_graph_def(gdef, name='')
# The graph should have exactly one encapsulate
assert len([
0 for i in g.get_operations() if i.type == 'NGraphEncapsulate'
]) == 1
x = self.get_tensor(g, "x:0", False)
y = self.get_tensor(g, "y:0", False)
out = self.get_tensor(g, "out_node:0", False)
sess_fn = lambda sess: sess.run(
[out], feed_dict={i: np.zeros((10,)) for i in [x, y]})
res1 = self.with_ngraph(sess_fn)
res2 = self.without_ngraph(sess_fn)
exp = [0.5 * np.ones((10,))]
# Note both run on Host (because NgraphEncapsulate can only run on host)
assert np.isclose(res1, res2).all()
# Comparing with expected value
assert np.isclose(res1, exp).all()
def test_command_line_api(self, inp_format, inp_loc, out_node_name,
save_ng_clusters, out_format, commandline,
ng_device, shape_hints, precompile):
# Only run this test when grappler is enabled
if not ngraph_bridge.is_grappler_enabled():
return
# Store and unset env variable NGRAPH_TF_BACKEND because the test
# implicitly tests with different options
env_var_map = self.store_env_variables(["NGRAPH_TF_BACKEND"])
self.set_env_variable("NGRAPH_TF_BACKEND", ng_device)
ngraph_bridge.set_backend("INTERPRETER")
assert Testtf2ngraph.format_and_loc_match(inp_format, inp_loc)
out_loc = inp_loc.split('.')[0] + '_modified' + ('' if out_format
== 'savedmodel' else
('.' + out_format))
try:
(shutil.rmtree, os.remove)[os.path.isfile(out_loc)](out_loc)
except:
pass
conversion_successful = False
try:
optional_backend_params = {
'CPU': {
'device_config': '0'
},
'INTERPRETER': {
'test_echo': '1'
}
}[ng_device]
config_file_name = 'temp_config_file.json'
Tf2ngraphJson.dump_json(config_file_name, optional_backend_params,
shape_hints)
if commandline:
# In CI this test is expected to be run out of artifacts/test/python
# out_node_str is empty if out_node_name is None.
# Automatic output node inference display diagnostic logs
# But the tf2ngraph call will still fail
command = [
'python', '../../tools/tf2ngraph.py',
'--input_' + inp_format, inp_loc, '--output_' + out_format,
out_loc, '--ng_backend', ng_device, '--config_file',
config_file_name
]
if out_node_name is not None:
command.extend(['--output_nodes', out_node_name])
if precompile:
command.append('--precompile')
if save_ng_clusters:
command.append('--save_ng_clusters')
p = Popen(command, stdin=PIPE, stdout=PIPE, stderr=PIPE)
output, err = p.communicate()
rc = p.returncode
if out_node_name is None:
assert rc != 0, "Call to tf2ngraph should fail when no output name is provided"
return
else:
convert(inp_format, inp_loc, out_format, out_loc, ['out_node'],
ng_device, "", optional_backend_params, shape_hints,
precompile, save_ng_clusters)
file_present = 'ngraph_cluster_0.pbtxt' in os.listdir()
assert save_ng_clusters == file_present
conversion_successful = True
finally:
if not conversion_successful:
try:
(shutil.rmtree,
os.remove)[os.path.isfile(out_loc)](out_loc)
os.remove(config_file_name)
except:
pass
if save_ng_clusters and 'ngraph_cluster_0.pbtxt' in os.listdir():
os.remove('ngraph_cluster_0.pbtxt')
assert conversion_successful
gdef = get_gdef(out_format, out_loc)
(shutil.rmtree, os.remove)[os.path.isfile(out_loc)](out_loc)
os.remove(config_file_name)
with tf.Graph().as_default() as g:
tf.import_graph_def(gdef, name='')
# The graph should have exactly one encapsulate
assert len([
0 for i in g.get_operations() if i.type == 'NGraphEncapsulate'
]) == 1
# TODO: check that the encapsulate op has correct backend and extra params attached to it
x = self.get_tensor(g, "x:0", False)
y = self.get_tensor(g, "y:0", False)
out = self.get_tensor(g, "out_node:0", False)
sess_fn = lambda sess: sess.run(
[out], feed_dict={i: np.zeros((10, ))
for i in [x, y]})
res1 = self.with_ngraph(sess_fn)
res2 = self.without_ngraph(sess_fn)
exp = [0.5 * np.ones((10, ))]
# Note both run on Host (because NgraphEncapsulate can only run on host)
assert np.isclose(res1, res2).all()
# Comparing with expected value
assert np.isclose(res1, exp).all()
# Restore env variable NGRAPH_TF_BACKEND that was stored
self.restore_env_variables(env_var_map)
def test_command_line_api(self, inp_format, inp_loc, out_format,
commandline, ng_device, shape_hints, precompile):
# Only run this test when grappler is enabled
if not ngraph_bridge.is_grappler_enabled():
return
assert Testtf2ngraph.format_and_loc_match(inp_format, inp_loc)
out_loc = inp_loc.split('.')[0] + '_modified' + ('' if out_format
== 'savedmodel' else
('.' + out_format))
try:
(shutil.rmtree, os.remove)[os.path.isfile(out_loc)](out_loc)
except:
pass
conversion_successful = False
try:
optional_backend_params = {
'CPU': {
'device_config': '0'
},
'INTERPRETER': {
'test_echo': '1'
}
}[ng_device]
config_file_name = 'temp_config_file.json'
Tf2ngraphJson.dump_json(config_file_name, optional_backend_params,
shape_hints)
if commandline:
# In CI this test is expected to be run out of artifacts/test/python
command_executor('python ../../tools/tf2ngraph.py --input_' +
inp_format + ' ' + inp_loc +
' --output_nodes out_node --output_' +
out_format + ' ' + out_loc +
' --ng_backend ' + ng_device +
' --config_file ' + config_file_name +
("", " --precompile ")[precompile])
else:
convert(inp_format, inp_loc, out_format, out_loc, ['out_node'],
ng_device, optional_backend_params, shape_hints,
precompile)
conversion_successful = True
finally:
if not conversion_successful:
try:
(shutil.rmtree,
os.remove)[os.path.isfile(out_loc)](out_loc)
os.remove(config_file_name)
except:
pass
assert conversion_successful
gdef = get_gdef(out_format, out_loc)
(shutil.rmtree, os.remove)[os.path.isfile(out_loc)](out_loc)
os.remove(config_file_name)
with tf.Graph().as_default() as g:
tf.import_graph_def(gdef, name='')
# The graph should have exactly one encapsulate
assert len([
0 for i in g.get_operations() if i.type == 'NGraphEncapsulate'
]) == 1
# TODO: check that the encapsulate op has correct backend and extra params attached to it
x = self.get_tensor(g, "x:0", False)
y = self.get_tensor(g, "y:0", False)
out = self.get_tensor(g, "out_node:0", False)
sess_fn = lambda sess: sess.run(
[out], feed_dict={i: np.zeros((10, ))
for i in [x, y]})
res1 = self.with_ngraph(sess_fn)
res2 = self.without_ngraph(sess_fn)
exp = [0.5 * np.ones((10, ))]
# Note both run on Host (because NgraphEncapsulate can only run on host)
assert np.isclose(res1, res2).all()
# Comparing with expected value
assert np.isclose(res1, exp).all()