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## @package onnx
# Module caffe2.python.onnx.tests.ssa_test
import copy
import numpy as np
from caffe2.proto import caffe2_pb2
from caffe2.python import core
from onnx import TensorProto
import caffe2.python.onnx.frontend as c2_onnx
from caffe2.python.onnx.helper import c2_native_run_net
from caffe2.python.onnx.tests.test_utils import TestCase
class TestFrontendSSAConversion(TestCase):
def test_ssa(self):
X = np.random.randn(4, 2).astype(np.float32)
W = np.random.randn(3, 2).astype(np.float32)
b = np.random.randn(3).astype(np.float32)
s = np.random.randn(1).astype(np.float32)
np_result = X.dot(W.transpose()) + b + s
net = caffe2_pb2.NetDef()
net.name = 'test-ssa'
net.external_input[:] = ['W', 'X', 'b', 's']
net.op.extend([
core.CreateOperator(
'FC',
['X', 'W', 'b'],
['Y']
),
core.CreateOperator(
'Add',
['Y', 's'],
['Y'],
broadcast=True,
)
])
net.external_output[:] = ['Y']
init_net = caffe2_pb2.NetDef()
init_net.name = 'test-ssa-init'
init_net.op.extend([
core.CreateOperator(
'GivenTensorFill',
[],
['W'],
values=W,
shape=W.shape,
),
core.CreateOperator(
'GivenTensorFill',
[],
['b'],
values=b,
shape=b.shape,
),
core.CreateOperator(
'GivenTensorFill',
[],
['s'],
values=s,
shape=s.shape,
)
])
init_net.external_output[:] = ['W', 'b', 's']
_, orig_output = c2_native_run_net(
predict_net=net,
init_net=init_net,
inputs=[X])
value_info = {'X': (TensorProto.FLOAT, X.shape)}
c2_onnx.Caffe2Frontend._ssa_rewrite(
net,
init_net,
value_info)
self.assertEqual(net.external_input, ['W', 'X', 'b', 's'])
self.assertEqual(net.op[0].input, ['X', 'W', 'b'])
self.assertEqual(net.op[0].output, ['Y_1'])
self.assertEqual(net.op[1].input, ['Y_1', 's'])
self.assertEqual(net.op[1].output, ['Y_2'])
self.assertEqual(net.external_output, ['Y_2'])
self.assertEqual(init_net.external_input, [])
self.assertEqual(init_net.op[0].input, [])
self.assertEqual(init_net.op[0].output, ['W'])
self.assertEqual(init_net.op[1].input, [])
self.assertEqual(init_net.op[1].output, ['b'])
self.assertEqual(init_net.op[2].input, [])
self.assertEqual(init_net.op[2].output, ['s'])
self.assertEqual(init_net.external_output, ['W', 'b', 's'])
self.assertEqual(value_info, {'X': (TensorProto.FLOAT, X.shape)})
_, ssa_output = c2_native_run_net(
predict_net=net,
init_net=init_net,
inputs=[X])
self.assertSameOutputs(ssa_output, orig_output)
self.assertSameOutputs(ssa_output, [np_result])
def test_idempotence(self):
net = caffe2_pb2.NetDef()
net.name = 'test-idempotence'
net.external_input[:] = ['W', 'X', 'b', 's']
net.op.extend([
core.CreateOperator(
'FC',
['X', 'W', 'b'],
['Y']
),
core.CreateOperator(
'Add',
['Y', 's'],
['Z'],
broadcast=True,
)
])
net.external_output[:] = ['Z']
value_info = {'X': (TensorProto.FLOAT, [4, 2])}
net_copy = copy.deepcopy(net)
c2_onnx.Caffe2Frontend._ssa_rewrite(
net_copy,
None,
value_info)
self.assertEqual(net, net_copy)
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