mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 00:21:07 +01:00
d0621a2449
Summary: Remove the use of `NextName` in layer model helper, so that the same function return `model_helper` that should construct identical `Net`, when under the same NameScope. The `NextScopedBlob` should only take effect when there is real name conflicting, otherwise it returns ScopedBlobReference. This is critical for parameter blobs. In long run, we need to be able to specify parameter blobs more explicitly. (kennyhorror is working on this). This solution works in short term for e.g., two tower sparse nn models. Reviewed By: kennyhorror Differential Revision: D4555423 fbshipit-source-id: 2c4b99a61392e5d51aa878f7346466a8f14be187
300 lines
12 KiB
Python
300 lines
12 KiB
Python
import unittest
|
|
|
|
import numpy as np
|
|
from caffe2.proto import caffe2_pb2
|
|
from caffe2.python import core, workspace, test_util, cnn
|
|
|
|
|
|
class TestScopes(test_util.TestCase):
|
|
def testBlobReferenceIsIndependentFromNameScope(self):
|
|
blob_v = core.BlobReference("v")
|
|
with core.NameScope("foo"):
|
|
blob_w = core.BlobReference("w")
|
|
with core.NameScope("bar"):
|
|
blob_x = core.BlobReference("x")
|
|
self.assertEqual(str(blob_v), "v")
|
|
self.assertEqual(str(blob_w), "w")
|
|
self.assertEqual(str(blob_x), "x")
|
|
|
|
def testNameScopeWithOp(self):
|
|
global_x = core.BlobReference("x")
|
|
global_y = core.BlobReference("y")
|
|
with core.NameScope("foo"):
|
|
# Raw strings should have namescope prepended.
|
|
op = core.CreateOperator("Relu", "x", "y")
|
|
self.assertEqual(len(op.input), 1)
|
|
self.assertEqual(op.input[0], "foo/x")
|
|
self.assertEqual(len(op.output), 1)
|
|
self.assertEqual(op.output[0], "foo/y")
|
|
# BlobReferences should not.
|
|
op = core.CreateOperator("Relu", global_x, global_y)
|
|
self.assertEqual(len(op.input), 1)
|
|
self.assertEqual(op.input[0], "x")
|
|
self.assertEqual(len(op.output), 1)
|
|
self.assertEqual(op.output[0], "y")
|
|
|
|
def testNameScopeWithReset(self):
|
|
with core.NameScope("foo"):
|
|
# foo/
|
|
op = core.CreateOperator("Relu", "x", "y")
|
|
self.assertEqual(len(op.input), 1)
|
|
self.assertEqual(op.input[0], "foo/x")
|
|
self.assertEqual(len(op.output), 1)
|
|
self.assertEqual(op.output[0], "foo/y")
|
|
with core.NameScope("bar"):
|
|
# foo/bar/
|
|
op = core.CreateOperator("Relu", "x", "y")
|
|
self.assertEqual(len(op.input), 1)
|
|
self.assertEqual(op.input[0], "foo/bar/x")
|
|
self.assertEqual(len(op.output), 1)
|
|
self.assertEqual(op.output[0], "foo/bar/y")
|
|
# Back to foo/
|
|
op = core.CreateOperator("Relu", "x", "y")
|
|
self.assertEqual(len(op.input), 1)
|
|
self.assertEqual(op.input[0], "foo/x")
|
|
self.assertEqual(len(op.output), 1)
|
|
self.assertEqual(op.output[0], "foo/y")
|
|
with core.NameScope("bar", reset=True):
|
|
# bar/
|
|
op = core.CreateOperator("Relu", "x", "y")
|
|
self.assertEqual(len(op.input), 1)
|
|
self.assertEqual(op.input[0], "bar/x")
|
|
self.assertEqual(len(op.output), 1)
|
|
self.assertEqual(op.output[0], "bar/y")
|
|
# Back to foo/
|
|
op = core.CreateOperator("Relu", "x", "y")
|
|
self.assertEqual(len(op.input), 1)
|
|
self.assertEqual(op.input[0], "foo/x")
|
|
self.assertEqual(len(op.output), 1)
|
|
self.assertEqual(op.output[0], "foo/y")
|
|
|
|
def testDeviceScope(self):
|
|
# No device
|
|
op = core.CreateOperator("Relu", "x", "y")
|
|
self.assertFalse(op.HasField('device_option'))
|
|
# explicitly setting a device
|
|
device_option = caffe2_pb2.DeviceOption()
|
|
device_option.device_type = caffe2_pb2.CUDA
|
|
device_option.cuda_gpu_id = 1
|
|
op = core.CreateOperator("Relu", "x", "y", device_option=device_option)
|
|
self.assertTrue(op.HasField('device_option'))
|
|
self.assertEqual(op.device_option.device_type, caffe2_pb2.CUDA)
|
|
self.assertEqual(op.device_option.cuda_gpu_id, 1)
|
|
with core.DeviceScope(device_option):
|
|
# from device scope
|
|
op = core.CreateOperator("Relu", "x", "y")
|
|
self.assertTrue(op.HasField('device_option'))
|
|
self.assertEqual(op.device_option.device_type, caffe2_pb2.CUDA)
|
|
self.assertEqual(op.device_option.cuda_gpu_id, 1)
|
|
# from an overridden device option
|
|
override_device = caffe2_pb2.DeviceOption()
|
|
override_device.device_type = caffe2_pb2.CPU
|
|
op = core.CreateOperator(
|
|
"Relu", "x", "y", device_option=override_device)
|
|
self.assertTrue(op.HasField('device_option'))
|
|
self.assertEqual(op.device_option.device_type, caffe2_pb2.CPU)
|
|
# back from normal: no device
|
|
op = core.CreateOperator("Relu", "x", "y")
|
|
self.assertFalse(op.HasField('device_option'))
|
|
device_option = caffe2_pb2.DeviceOption()
|
|
|
|
def testNameAndDeviceScopeTogether(self):
|
|
device_option = caffe2_pb2.DeviceOption()
|
|
device_option.device_type = caffe2_pb2.CUDA
|
|
device_option.cuda_gpu_id = 1
|
|
with core.DeviceScope(device_option):
|
|
with core.NameScope("foo"):
|
|
op = core.CreateOperator("Relu", "x", "y")
|
|
self.assertTrue(op.HasField('device_option'))
|
|
self.assertEqual(op.device_option.device_type, caffe2_pb2.CUDA)
|
|
self.assertEqual(op.device_option.cuda_gpu_id, 1)
|
|
self.assertEqual(len(op.input), 1)
|
|
self.assertEqual(op.input[0], "foo/x")
|
|
self.assertEqual(len(op.output), 1)
|
|
self.assertEqual(op.output[0], "foo/y")
|
|
|
|
|
|
class TestCloneNet(test_util.TestCase):
|
|
def testPartialClone(self):
|
|
params = core.Net('params')
|
|
p1 = params.ConstantFill([], ['p1'])
|
|
workspace.CreateNet(params)
|
|
workspace.RunNetOnce(params)
|
|
|
|
n = core.Net('original')
|
|
a1 = n.AddExternalInput('a1')
|
|
a2 = n.AddExternalInput('a2')
|
|
b1, b2 = n.Concat([a1, a2], ['b1', 'b2'], axis=0)
|
|
c1 = n.Sum([b1, p1], ['c1'])
|
|
c2 = n.Sum([b2], ['c2'])
|
|
d = n.Sum([c1, c2], ['d'])
|
|
|
|
# test that gradient ops are ignored when partial-cloning
|
|
n.AddGradientOperators([d])
|
|
|
|
# test some in-place ops
|
|
k = n.Sum([p1], ['k'])
|
|
e = n.Sum([d], ['e'])
|
|
e = n.Sum([e, k], [e])
|
|
e = n.Sum([e], [e])
|
|
f = n.Sum(e, ['f'])
|
|
|
|
def net_assert(net, num_ops, inputs, outputs, internals):
|
|
self.assertEqual(len(net.Proto().op), num_ops)
|
|
self.assertEqual(set(net.Proto().external_input), inputs)
|
|
self.assertEqual(set(net.Proto().external_output), outputs)
|
|
all_blobs = set(net.Proto().external_input)
|
|
all_blobs |= set(net.Proto().external_output)
|
|
for op in net.Proto().op:
|
|
all_blobs |= set(op.input) | set(op.output)
|
|
self.assertEqual(all_blobs, inputs | outputs | internals)
|
|
# create net to make sure its valid
|
|
for input in inputs:
|
|
workspace.FeedBlob(input, np.array([]))
|
|
workspace.CreateNet(net)
|
|
|
|
n2, (d22, ) = n.ClonePartial('f1', {a1: 'a11', a2: 'a22'}, [d])
|
|
net_assert(
|
|
n2, 4, {'p1', 'a11', 'a22'}, {'f1/d'},
|
|
{'f1/b1', 'f1/b2', 'f1/c1', 'f1/c2', 'p1'})
|
|
self.assertTrue(isinstance(d22, core.BlobReference))
|
|
self.assertEqual(d22.Net(), n2)
|
|
self.assertEqual(str(d22), 'f1/d')
|
|
|
|
n3, (d22, ) = n.ClonePartial('f2', [b1, b2], [d])
|
|
net_assert(
|
|
n3, 3, {'p1', 'b1', 'b2'}, {'f2/d'}, {'f2/c1', 'f2/c2', 'p1'})
|
|
self.assertEqual(str(d22), 'f2/d')
|
|
|
|
n4, (c22, ) = n.ClonePartial('f3', [b1], [c1])
|
|
net_assert(n4, 1, {'p1', 'b1'}, {'f3/c1'}, {'p1'})
|
|
self.assertEqual(str(c22), 'f3/c1')
|
|
|
|
n5, (c11, c22) = n.ClonePartial('f4', [b1, b2], [c1, c2])
|
|
net_assert(n5, 2, {'p1', 'b1', 'b2'}, {'f4/c1', 'f4/c2'}, {'p1'})
|
|
self.assertEqual(str(c11), 'f4/c1')
|
|
self.assertEqual(str(c22), 'f4/c2')
|
|
|
|
with self.assertRaises(AssertionError):
|
|
n.ClonePartial('f4', [a1, a2, c2], [d])
|
|
|
|
n6, (e22, ) = n.ClonePartial('f5', [d], [e])
|
|
net_assert(n6, 4, {'p1', 'd'}, {'f5/e'}, {'f5/k', 'p1'})
|
|
self.assertEqual(str(e22), 'f5/e')
|
|
|
|
n8, (e22, f22) = n.ClonePartial('f7', [d], [e, f])
|
|
net_assert(n8, 5, {'p1', 'd'}, {'f7/e', 'f7/f'}, {'p1', 'f7/k'})
|
|
self.assertEqual(str(e22), 'f7/e')
|
|
self.assertEqual(str(f22), 'f7/f')
|
|
|
|
params._CheckLookupTables()
|
|
n._CheckLookupTables()
|
|
|
|
|
|
class TestCreateOperator(test_util.TestCase):
|
|
def testCreate(self):
|
|
device_option = caffe2_pb2.DeviceOption()
|
|
device_option.device_type = caffe2_pb2.CUDA
|
|
device_option.cuda_gpu_id = 1
|
|
op = core.CreateOperator(
|
|
"Ludicrous", "x", "y", name="ludicrous",
|
|
control_input="z", device_option=device_option,
|
|
engine="WARP", arg1=1, arg2="2", arg3=[1, 2, 3])
|
|
self.assertEqual(op.type, "Ludicrous")
|
|
self.assertEqual(op.name, "ludicrous")
|
|
self.assertEqual(op.engine, "WARP")
|
|
self.assertEqual(len(op.input), 1)
|
|
self.assertEqual(op.input[0], "x")
|
|
self.assertEqual(len(op.output), 1)
|
|
self.assertEqual(op.output[0], "y")
|
|
self.assertEqual(len(op.control_input), 1)
|
|
self.assertEqual(op.control_input[0], "z")
|
|
self.assertTrue(op.HasField('device_option'))
|
|
self.assertEqual(op.device_option.device_type, caffe2_pb2.CUDA)
|
|
self.assertEqual(op.device_option.cuda_gpu_id, 1)
|
|
self.assertTrue(len(op.arg), 3)
|
|
self.assertEqual(op.arg[0].name, "arg1")
|
|
self.assertEqual(op.arg[1].name, "arg2")
|
|
self.assertEqual(op.arg[2].name, "arg3")
|
|
self.assertEqual(op.arg[0].i, 1)
|
|
self.assertEqual(op.arg[1].s, "2")
|
|
self.assertEqual(list(op.arg[2].ints), [1, 2, 3])
|
|
|
|
def testCreateWithNoneKwarg(self):
|
|
with self.assertRaises(ValueError):
|
|
core.CreateOperator("Ludicrous", "x", "y", arg1=None)
|
|
|
|
|
|
class TestAutoNaming(test_util.TestCase):
|
|
"""
|
|
Test that operators are named with different names, and that automatically
|
|
named blob names don't clash intra or inter networks.
|
|
"""
|
|
def test_next_blob(self):
|
|
def create_net():
|
|
net = core.Net('net')
|
|
with core.NameScope('foo'):
|
|
net.Add(['a', 'b'], net.NextScopedBlob('ab'))
|
|
|
|
net.Add(['c', 'd'], net.NextBlob('cd'))
|
|
return net
|
|
|
|
net_a = create_net()
|
|
net_b = create_net()
|
|
# created net proto is predicatable.
|
|
self.assertEqual(net_a.Proto().op, net_b.Proto().op)
|
|
self.assertEqual(net_a.Proto().op[0].output[0], 'foo/ab')
|
|
self.assertEqual(net_a.Proto().op[1].output[0], 'cd')
|
|
|
|
net_c = core.Net('net')
|
|
# different calls return different blob names
|
|
self.assertNotEqual(str(net_c.NextBlob('b')), str(net_c.NextBlob('b')))
|
|
|
|
def test_auto_naming(self):
|
|
a = core.Net('net')
|
|
b = core.Net('net')
|
|
self.assertNotEqual(a.Proto().name, b.Proto().name)
|
|
a_in1 = a.AddExternalInput('a')
|
|
b_in1 = b.AddExternalInput('b')
|
|
all_outputs_single = []
|
|
all_outputs_list = []
|
|
|
|
def add_ops():
|
|
all_outputs_single.append(a.Sum([a_in1, a_in1]))
|
|
all_outputs_single.append(a.Sum([a_in1, a_in1]))
|
|
all_outputs_single.append(b.Sum([b_in1, b_in1]))
|
|
all_outputs_single.append(b.Sum([b_in1, b_in1]))
|
|
all_outputs_list.append(a.Sum([a_in1, a_in1], outputs=2))
|
|
all_outputs_list.append(a.Sum([a_in1, a_in1], outputs=2))
|
|
all_outputs_list.append(b.Sum([b_in1, b_in1], outputs=2))
|
|
all_outputs_list.append(b.Sum([b_in1, b_in1], outputs=2))
|
|
|
|
add_ops()
|
|
with core.NameScope('n1'):
|
|
add_ops()
|
|
|
|
# Force reset of lookup tables
|
|
dummy = a.Proto().name
|
|
|
|
with core.NameScope('n2'):
|
|
add_ops()
|
|
|
|
all_outputs = []
|
|
for s in all_outputs_single:
|
|
all_outputs.append(str(s))
|
|
for l in all_outputs_list:
|
|
for o in l:
|
|
all_outputs.append(str(o))
|
|
|
|
for i, o1 in enumerate(all_outputs):
|
|
for j, o2 in enumerate(all_outputs):
|
|
if i != j:
|
|
self.assertNotEqual(str(o1), str(o2))
|
|
|
|
a._CheckLookupTables()
|
|
b._CheckLookupTables()
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|