FM / modeling

/usr/local/lib64/python3.6/site-packages/caffe2/python/modeling/

/usr/local/lib64/python3.6/site-packages/caffe2/python/modeling

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
compute_histogram_for_blobs.py	3508	0644	edit dl rm
compute_histogram_for_blobs_test.py	4947	0644	edit dl rm
compute_norm_for_blobs.py	3642	0644	edit dl rm
compute_norm_for_blobs_test.py	7942	0644	edit dl rm
compute_statistics_for_blobs.py	1909	0644	edit dl rm
compute_statistics_for_blobs_test.py	2870	0644	edit dl rm
get_entry_from_blobs.py	3130	0644	edit dl rm
get_entry_from_blobs_test.py	3538	0644	edit dl rm
gradient_clipping.py	5766	0644	edit dl rm
gradient_clipping_test.py	10016	0644	edit dl rm
initializers.py	5378	0644	edit dl rm
initializers_test.py	2106	0644	edit dl rm
net_modifier.py	823	0644	edit dl rm
parameter_info.py	1438	0644	edit dl rm
parameter_sharing.py	3848	0644	edit dl rm
parameter_sharing_test.py	7223	0644	edit dl rm
__init__.py	0	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/caffe2/python/modeling/get_entry_from_blobs_test.py (3538B)

import unittest
from caffe2.python import workspace, brew, model_helper
from caffe2.python.modeling.get_entry_from_blobs import GetEntryFromBlobs

import numpy as np

class GetEntryFromBlobsTest(unittest.TestCase):
    def test_get_entry_from_blobs(self):
        model = model_helper.ModelHelper(name="test")
        data = model.net.AddExternalInput("data")
        fc1 = brew.fc(model, data, "fc1", dim_in=10, dim_out=8)

# no operator name set, will use default
        brew.fc(model, fc1, "fc2", dim_in=8, dim_out=4)
        i1, i2 = np.random.randint(4, size=2)
        net_modifier = GetEntryFromBlobs(
            blobs=['fc1_w', 'fc2_w'],
            logging_frequency=10,
            i1=i1,
            i2=i2,
        )
        net_modifier(model.net)

workspace.FeedBlob('data', np.random.rand(10, 10).astype(np.float32))
        workspace.RunNetOnce(model.param_init_net)
        workspace.RunNetOnce(model.net)

fc1_w = workspace.FetchBlob('fc1_w')
        fc1_w_entry = workspace.FetchBlob('fc1_w_{0}_{1}'.format(i1, i2))

self.assertEqual(fc1_w_entry.size, 1)
        self.assertEqual(fc1_w_entry[0], fc1_w[i1][i2])
        assert model.net.output_record() is None

def test_get_entry_from_blobs_modify_output_record(self):
        model = model_helper.ModelHelper(name="test")
        data = model.net.AddExternalInput("data")
        fc1 = brew.fc(model, data, "fc1", dim_in=4, dim_out=4)

# no operator name set, will use default
        brew.fc(model, fc1, "fc2", dim_in=4, dim_out=4)
        i1, i2 = np.random.randint(4), np.random.randint(5) - 1
        net_modifier = GetEntryFromBlobs(
            blobs=['fc1_w', 'fc2_w'],
            logging_frequency=10,
            i1=i1,
            i2=i2,
        )
        net_modifier(model.net, modify_output_record=True)

workspace.FeedBlob('data', np.random.rand(10, 4).astype(np.float32))
        workspace.RunNetOnce(model.param_init_net)
        workspace.RunNetOnce(model.net)

fc1_w = workspace.FetchBlob('fc1_w')
        if i2 < 0:
            fc1_w_entry = workspace.FetchBlob('fc1_w_{0}_all'.format(i1))
        else:
            fc1_w_entry = workspace.FetchBlob('fc1_w_{0}_{1}'.format(i1, i2))

if i2 < 0:
            self.assertEqual(fc1_w_entry.size, 4)
            for j in range(4):
                self.assertEqual(fc1_w_entry[0][j], fc1_w[i1][j])
        else:
            self.assertEqual(fc1_w_entry.size, 1)
            self.assertEqual(fc1_w_entry[0], fc1_w[i1][i2])

assert 'fc1_w' + net_modifier.field_name_suffix() in\
            model.net.output_record().field_blobs(),\
            model.net.output_record().field_blobs()
        assert 'fc2_w' + net_modifier.field_name_suffix() in\
            model.net.output_record().field_blobs(),\
            model.net.output_record().field_blobs()

# Copyright (c) 2016-present, Facebook, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. ############################################################################## import unittest from caffe2.python import workspace, brew, model_helper from caffe2.python.modeling.get_entry_from_blobs import GetEntryFromBlobs import numpy as np class GetEntryFromBlobsTest(unittest.TestCase): def test_get_entry_from_blobs(self): model = model_helper.ModelHelper(name="test") data = model.net.AddExternalInput("data") fc1 = brew.fc(model, data, "fc1", dim_in=10, dim_out=8) # no operator name set, will use default brew.fc(model, fc1, "fc2", dim_in=8, dim_out=4) i1, i2 = np.random.randint(4, size=2) net_modifier = GetEntryFromBlobs( blobs=['fc1_w', 'fc2_w'], logging_frequency=10, i1=i1, i2=i2, ) net_modifier(model.net) workspace.FeedBlob('data', np.random.rand(10, 10).astype(np.float32)) workspace.RunNetOnce(model.param_init_net) workspace.RunNetOnce(model.net) fc1_w = workspace.FetchBlob('fc1_w') fc1_w_entry = workspace.FetchBlob('fc1_w_{0}_{1}'.format(i1, i2)) self.assertEqual(fc1_w_entry.size, 1) self.assertEqual(fc1_w_entry[0], fc1_w[i1][i2]) assert model.net.output_record() is None def test_get_entry_from_blobs_modify_output_record(self): model = model_helper.ModelHelper(name="test") data = model.net.AddExternalInput("data") fc1 = brew.fc(model, data, "fc1", dim_in=4, dim_out=4) # no operator name set, will use default brew.fc(model, fc1, "fc2", dim_in=4, dim_out=4) i1, i2 = np.random.randint(4), np.random.randint(5) - 1 net_modifier = GetEntryFromBlobs( blobs=['fc1_w', 'fc2_w'], logging_frequency=10, i1=i1, i2=i2, ) net_modifier(model.net, modify_output_record=True) workspace.FeedBlob('data', np.random.rand(10, 4).astype(np.float32)) workspace.RunNetOnce(model.param_init_net) workspace.RunNetOnce(model.net) fc1_w = workspace.FetchBlob('fc1_w') if i2 < 0: fc1_w_entry = workspace.FetchBlob('fc1_w_{0}_all'.format(i1)) else: fc1_w_entry = workspace.FetchBlob('fc1_w_{0}_{1}'.format(i1, i2)) if i2 < 0: self.assertEqual(fc1_w_entry.size, 4) for j in range(4): self.assertEqual(fc1_w_entry[0][j], fc1_w[i1][j]) else: self.assertEqual(fc1_w_entry.size, 1) self.assertEqual(fc1_w_entry[0], fc1_w[i1][i2]) assert 'fc1_w' + net_modifier.field_name_suffix() in\ model.net.output_record().field_blobs(),\ model.net.output_record().field_blobs() assert 'fc2_w' + net_modifier.field_name_suffix() in\ model.net.output_record().field_blobs(),\ model.net.output_record().field_blobs()