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import tempfile
import unittest
import numpy as np
from caffe2.python import cnn, workspace, core
from future.utils import viewitems
from caffe2.python.predictor_constants import predictor_constants as pc
import caffe2.python.predictor.predictor_exporter as pe
import caffe2.python.predictor.predictor_py_utils as pred_utils
from caffe2.proto import caffe2_pb2, metanet_pb2
class MetaNetDefTest(unittest.TestCase):
def test_minimal(self):
'''
Tests that a NetsMap message can be created with a NetDef message
'''
# This calls the constructor for a metanet_pb2.NetsMap
metanet_pb2.NetsMap(key="test_key", value=caffe2_pb2.NetDef())
def test_adding_net(self):
'''
Tests that NetDefs can be added to MetaNetDefs
'''
meta_net_def = metanet_pb2.MetaNetDef()
net_def = caffe2_pb2.NetDef()
meta_net_def.nets.add(key="test_key", value=net_def)
def test_replace_blobs(self):
'''
Tests that NetDefs can be added to MetaNetDefs
'''
meta_net_def = metanet_pb2.MetaNetDef()
blob_name = "Test"
blob_def = ["AA"]
blob_def2 = ["BB"]
replaced_blob_def = ["CC"]
pred_utils.AddBlobs(meta_net_def, blob_name, blob_def)
self.assertEqual(blob_def, pred_utils.GetBlobs(meta_net_def, blob_name))
pred_utils.AddBlobs(meta_net_def, blob_name, blob_def2)
self.assertEqual(blob_def + blob_def2, pred_utils.GetBlobs(meta_net_def, blob_name))
pred_utils.ReplaceBlobs(meta_net_def, blob_name, replaced_blob_def)
self.assertEqual(replaced_blob_def, pred_utils.GetBlobs(meta_net_def, blob_name))
class PredictorExporterTest(unittest.TestCase):
def _create_model(self):
m = cnn.CNNModelHelper()
m.FC("data", "y",
dim_in=5, dim_out=10,
weight_init=m.XavierInit,
bias_init=m.XavierInit)
return m
def setUp(self):
np.random.seed(1)
m = self._create_model()
self.predictor_export_meta = pe.PredictorExportMeta(
predict_net=m.net.Proto(),
parameters=[str(b) for b in m.params],
inputs=["data"],
outputs=["y"],
shapes={"y": (1, 10), "data": (1, 5)},
)
workspace.RunNetOnce(m.param_init_net)
self.params = {
param: workspace.FetchBlob(param)
for param in self.predictor_export_meta.parameters}
# Reset the workspace, to ensure net creation proceeds as expected.
workspace.ResetWorkspace()
def test_meta_constructor(self):
'''
Test that passing net itself instead of proto works
'''
m = self._create_model()
pe.PredictorExportMeta(
predict_net=m.net,
parameters=m.params,
inputs=["data"],
outputs=["y"],
shapes={"y": (1, 10), "data": (1, 5)},
)
def test_param_intersection(self):
'''
Test that passes intersecting parameters and input/output blobs
'''
m = self._create_model()
with self.assertRaises(Exception):
pe.PredictorExportMeta(
predict_net=m.net,
parameters=m.params,
inputs=["data"] + m.params,
outputs=["y"],
shapes={"y": (1, 10), "data": (1, 5)},
)
with self.assertRaises(Exception):
pe.PredictorExportMeta(
predict_net=m.net,
parameters=m.params,
inputs=["data"],
outputs=["y"] + m.params,
shapes={"y": (1, 10), "data": (1, 5)},
)
def test_meta_net_def_net_runs(self):
for param, value in viewitems(self.params):
workspace.FeedBlob(param, value)
extra_init_net = core.Net('extra_init')
extra_init_net.ConstantFill('data', 'data', value=1.0)
global_init_net = core.Net('global_init')
global_init_net.ConstantFill(
[],
'global_init_blob',
value=1.0,
shape=[1, 5],
dtype=core.DataType.FLOAT
)
pem = pe.PredictorExportMeta(
predict_net=self.predictor_export_meta.predict_net,
parameters=self.predictor_export_meta.parameters,
inputs=self.predictor_export_meta.inputs,
outputs=self.predictor_export_meta.outputs,
shapes=self.predictor_export_meta.shapes,
extra_init_net=extra_init_net,
global_init_net=global_init_net,
net_type='dag',
)
db_type = 'minidb'
db_file = tempfile.NamedTemporaryFile(
delete=False, suffix=".{}".format(db_type))
pe.save_to_db(
db_type=db_type,
db_destination=db_file.name,
predictor_export_meta=pem)
workspace.ResetWorkspace()
meta_net_def = pe.load_from_db(
db_type=db_type,
filename=db_file.name,
)
self.assertTrue("data" not in workspace.Blobs())
self.assertTrue("y" not in workspace.Blobs())
init_net = pred_utils.GetNet(meta_net_def, pc.PREDICT_INIT_NET_TYPE)
# 0-fills externalblobs blobs and runs extra_init_net
workspace.RunNetOnce(init_net)
self.assertTrue("data" in workspace.Blobs())
self.assertTrue("y" in workspace.Blobs())
print(workspace.FetchBlob("data"))
np.testing.assert_array_equal(
workspace.FetchBlob("data"), np.ones(shape=(1, 5)))
np.testing.assert_array_equal(
workspace.FetchBlob("y"), np.zeros(shape=(1, 10)))
self.assertTrue("global_init_blob" not in workspace.Blobs())
# Load parameters from DB
global_init_net = pred_utils.GetNet(meta_net_def,
pc.GLOBAL_INIT_NET_TYPE)
workspace.RunNetOnce(global_init_net)
# make sure the extra global_init_net is running
self.assertTrue(workspace.HasBlob('global_init_blob'))
np.testing.assert_array_equal(
workspace.FetchBlob("global_init_blob"), np.ones(shape=(1, 5)))
# Run the net with a reshaped input and verify we are
# producing good numbers (with our custom implementation)
workspace.FeedBlob("data", np.random.randn(2, 5).astype(np.float32))
predict_net = pred_utils.GetNet(meta_net_def, pc.PREDICT_NET_TYPE)
self.assertEqual(predict_net.type, 'dag')
workspace.RunNetOnce(predict_net)
np.testing.assert_array_almost_equal(
workspace.FetchBlob("y"),
workspace.FetchBlob("data").dot(self.params["y_w"].T) +
self.params["y_b"])
def test_load_device_scope(self):
for param, value in self.params.items():
workspace.FeedBlob(param, value)
pem = pe.PredictorExportMeta(
predict_net=self.predictor_export_meta.predict_net,
parameters=self.predictor_export_meta.parameters,
inputs=self.predictor_export_meta.inputs,
outputs=self.predictor_export_meta.outputs,
shapes=self.predictor_export_meta.shapes,
net_type='dag',
)
db_type = 'minidb'
db_file = tempfile.NamedTemporaryFile(
delete=False, suffix=".{}".format(db_type))
pe.save_to_db(
db_type=db_type,
db_destination=db_file.name,
predictor_export_meta=pem)
workspace.ResetWorkspace()
with core.DeviceScope(core.DeviceOption(caffe2_pb2.CPU, 1)):
meta_net_def = pe.load_from_db(
db_type=db_type,
filename=db_file.name,
)
init_net = core.Net(pred_utils.GetNet(meta_net_def,
pc.GLOBAL_INIT_NET_TYPE))
predict_init_net = core.Net(pred_utils.GetNet(
meta_net_def, pc.PREDICT_INIT_NET_TYPE))
# check device options
for op in list(init_net.Proto().op) + list(predict_init_net.Proto().op):
self.assertEqual(1, op.device_option.device_id)
self.assertEqual(caffe2_pb2.CPU, op.device_option.device_type)
def test_db_fails_without_params(self):
with self.assertRaises(Exception):
for db_type in ["minidb"]:
db_file = tempfile.NamedTemporaryFile(
delete=False, suffix=".{}".format(db_type))
pe.save_to_db(
db_type=db_type,
db_destination=db_file.name,
predictor_export_meta=self.predictor_export_meta)
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