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https://github.com/zebrajr/pytorch.git
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016f72537a
Summary: This is going to unblock Nvidia in their work on adding fp16 support to Caffe2. I discussed this with kennyhorror before to make sure this fits into his work on parameter sharing. Reviewed By: kennyhorror Differential Revision: D5127797 fbshipit-source-id: 4db155d320b1862570c23b77c4252bdacbf2296f
38 lines
1.3 KiB
Python
38 lines
1.3 KiB
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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import unittest
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from caffe2.python import brew, model_helper
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from caffe2.python.modeling.initializers import (
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Initializer,
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create_xavier_fill_initializer,
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)
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class InitializerTest(unittest.TestCase):
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def test_fc_initializer(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=1, dim_out=1)
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fc2 = brew.fc(model, fc1, "fc2", dim_in=1, dim_out=1,
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weight_initializer=create_xavier_fill_initializer())
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# no operator name set, will use default
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fc3 = brew.fc(model, fc2, "fc3", dim_in=1, dim_out=1,
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weight_initializer=Initializer())
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# no operator name set, will use custom
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fc4 = brew.fc(model, fc3, "fc4", dim_in=1, dim_out=1,
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weight_initializer=Initializer(),
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weight_init=("ConstantFill", {}),
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)
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# conflicting operator name
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with self.assertRaises(Exception):
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brew.fc(model, fc4, "fc5", dim_in=1, dim_out=1,
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weight_initializer=create_xavier_fill_initializer(),
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weight_init=("ConstantFill", {}),
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)
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