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import unittest
from caffe2.python import workspace, brew, model_helper
from caffe2.python.modeling.compute_statistics_for_blobs import (
ComputeStatisticsForBlobs
)
import numpy as np
class ComputeStatisticsForBlobsTest(unittest.TestCase):
def test_compute_statistics_for_blobs(self):
model = model_helper.ModelHelper(name="test")
data = model.net.AddExternalInput("data")
fc1 = brew.fc(model, data, "fc1", dim_in=4, dim_out=2)
# no operator name set, will use default
brew.fc(model, fc1, "fc2", dim_in=2, dim_out=1)
net_modifier = ComputeStatisticsForBlobs(
blobs=['fc1_w', 'fc2_w'],
logging_frequency=10,
)
net_modifier(model.net)
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')
fc1_w_summary = workspace.FetchBlob('fc1_w_summary')
# std is unbiased here
stats_ref = np.array([fc1_w.flatten().min(), fc1_w.flatten().max(),
fc1_w.flatten().mean(), fc1_w.flatten().std(ddof=1)])
self.assertAlmostEqual(np.linalg.norm(stats_ref - fc1_w_summary), 0,
delta=1e-5)
self.assertEqual(fc1_w_summary.size, 4)
assert model.net.output_record() is None
def test_compute_statistics_for_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=2)
# no operator name set, will use default
brew.fc(model, fc1, "fc2", dim_in=2, dim_out=1)
net_modifier = ComputeStatisticsForBlobs(
blobs=['fc1_w', 'fc2_w'],
logging_frequency=10,
)
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')
fc1_w_summary = workspace.FetchBlob('fc1_w_summary')
# std is unbiased here
stats_ref = np.array([fc1_w.flatten().min(), fc1_w.flatten().max(),
fc1_w.flatten().mean(), fc1_w.flatten().std(ddof=1)])
self.assertAlmostEqual(np.linalg.norm(stats_ref - fc1_w_summary), 0,
delta=1e-5)
self.assertEqual(fc1_w_summary.size, 4)
self.assertEqual(len(model.net.Proto().op), 8)
assert 'fc1_w' + net_modifier.field_name_suffix() in\
model.net.output_record().field_blobs()
assert 'fc2_w' + net_modifier.field_name_suffix() in\
model.net.output_record().field_blobs()
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