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27c7158166
Summary: There is a module called `2to3` which you can target for future specifically to remove these, the directory of `caffe2` has the most redundant imports: ```2to3 -f future -w caffe2``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/45033 Reviewed By: seemethere Differential Revision: D23808648 Pulled By: bugra fbshipit-source-id: 38971900f0fe43ab44a9168e57f2307580d36a38
96 lines
3.5 KiB
Python
96 lines
3.5 KiB
Python
# Copyright (c) 2016-present, Facebook, Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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##############################################################################
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import unittest
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from caffe2.python import workspace, brew, model_helper
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from caffe2.python.modeling.get_entry_from_blobs import GetEntryFromBlobs
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import numpy as np
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class GetEntryFromBlobsTest(unittest.TestCase):
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def test_get_entry_from_blobs(self):
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model = model_helper.ModelHelper(name="test")
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data = model.net.AddExternalInput("data")
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fc1 = brew.fc(model, data, "fc1", dim_in=10, dim_out=8)
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# no operator name set, will use default
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brew.fc(model, fc1, "fc2", dim_in=8, dim_out=4)
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i1, i2 = np.random.randint(4, size=2)
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net_modifier = GetEntryFromBlobs(
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blobs=['fc1_w', 'fc2_w'],
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logging_frequency=10,
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i1=i1,
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i2=i2,
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)
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net_modifier(model.net)
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workspace.FeedBlob('data', np.random.rand(10, 10).astype(np.float32))
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workspace.RunNetOnce(model.param_init_net)
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workspace.RunNetOnce(model.net)
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fc1_w = workspace.FetchBlob('fc1_w')
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fc1_w_entry = workspace.FetchBlob('fc1_w_{0}_{1}'.format(i1, i2))
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self.assertEqual(fc1_w_entry.size, 1)
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self.assertEqual(fc1_w_entry[0], fc1_w[i1][i2])
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assert model.net.output_record() is None
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def test_get_entry_from_blobs_modify_output_record(self):
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model = model_helper.ModelHelper(name="test")
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data = model.net.AddExternalInput("data")
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fc1 = brew.fc(model, data, "fc1", dim_in=4, dim_out=4)
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# no operator name set, will use default
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brew.fc(model, fc1, "fc2", dim_in=4, dim_out=4)
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i1, i2 = np.random.randint(4), np.random.randint(5) - 1
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net_modifier = GetEntryFromBlobs(
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blobs=['fc1_w', 'fc2_w'],
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logging_frequency=10,
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i1=i1,
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i2=i2,
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)
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net_modifier(model.net, modify_output_record=True)
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workspace.FeedBlob('data', np.random.rand(10, 4).astype(np.float32))
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workspace.RunNetOnce(model.param_init_net)
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workspace.RunNetOnce(model.net)
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fc1_w = workspace.FetchBlob('fc1_w')
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if i2 < 0:
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fc1_w_entry = workspace.FetchBlob('fc1_w_{0}_all'.format(i1))
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else:
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fc1_w_entry = workspace.FetchBlob('fc1_w_{0}_{1}'.format(i1, i2))
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if i2 < 0:
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self.assertEqual(fc1_w_entry.size, 4)
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for j in range(4):
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self.assertEqual(fc1_w_entry[0][j], fc1_w[i1][j])
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else:
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self.assertEqual(fc1_w_entry.size, 1)
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self.assertEqual(fc1_w_entry[0], fc1_w[i1][i2])
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assert 'fc1_w' + net_modifier.field_name_suffix() in\
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model.net.output_record().field_blobs(),\
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model.net.output_record().field_blobs()
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assert 'fc2_w' + net_modifier.field_name_suffix() in\
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model.net.output_record().field_blobs(),\
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model.net.output_record().field_blobs()
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