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46b83212d1
Summary: This is basically a reborn version of https://github.com/pytorch/pytorch/issues/45254 . Ref: https://github.com/pytorch/pytorch/issues/42919 Pull Request resolved: https://github.com/pytorch/pytorch/pull/48077 Reviewed By: ngimel Differential Revision: D25687042 Pulled By: bugra fbshipit-source-id: 05f20a6f3c5212f73d0b1505b493b720e6cf74e5
233 lines
8.9 KiB
Python
233 lines
8.9 KiB
Python
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from caffe2.python import core, scope
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from caffe2.python.modeling.parameter_sharing import (
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ParameterSharing,
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)
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from caffe2.python.optimizer import AdagradOptimizer, AdamOptimizer
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from caffe2.python.layer_test_util import LayersTestCase
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class ParameterSharingTest(LayersTestCase):
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def test_layer_parameter_name(self):
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output_dims = 2
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with scope.NameScope('global_scope'):
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fc1_output = self.model.FC(
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self.model.input_feature_schema.float_features,
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output_dims
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)
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self.assertEquals(self.model.layers[-1].w, 'global_scope/fc/w')
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self.assertEquals(fc1_output(), 'global_scope/fc/output')
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with scope.NameScope('nested_scope'):
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fc2_output = self.model.FC(
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fc1_output,
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output_dims
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)
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self.assertEquals(self.model.layers[-1].w,
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'global_scope/nested_scope/fc/w')
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self.assertEquals(fc2_output(),
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'global_scope/nested_scope/fc/output')
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fc3_output = self.model.FC(
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fc1_output,
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output_dims
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)
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self.assertEquals(self.model.layers[-1].w,
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'global_scope/nested_scope/fc_auto_0/w')
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self.assertEquals(fc3_output(),
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'global_scope/nested_scope/fc_auto_0/output')
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def test_layer_shared_parameter_name_different_namescopes(self):
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output_dims = 2
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with scope.NameScope('global_scope'):
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with ParameterSharing({'scope_1': 'scope_0'}):
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with scope.NameScope('scope_0'):
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fc1_output = self.model.FC(
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self.model.input_feature_schema.float_features,
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output_dims
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)
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self.assertEquals(self.model.layers[-1].w,
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'global_scope/scope_0/fc/w')
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self.assertEquals(fc1_output(),
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'global_scope/scope_0/fc/output')
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with scope.NameScope('scope_1'):
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fc2_output = self.model.FC(
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self.model.input_feature_schema.float_features,
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output_dims
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)
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self.assertEquals(self.model.layers[-1].w,
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'global_scope/scope_0/fc/w')
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self.assertEquals(fc2_output(),
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'global_scope/scope_1/fc/output')
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def test_layer_shared_parameter_name_within_same_namescope(self):
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output_dims = 2
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with scope.NameScope('global_scope'):
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with ParameterSharing({'fc_auto_0': 'fc'}):
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self.model.FC(
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self.model.input_feature_schema.float_features,
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output_dims
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)
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self.assertEquals(self.model.layers[-1].w,
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'global_scope/fc/w')
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self.model.FC(
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self.model.input_feature_schema.float_features,
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output_dims
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)
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self.assertEquals(self.model.layers[-1].w,
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'global_scope/fc/w')
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def test_layer_shared_parameter_name_within_same_namescope_customized_name(self):
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output_dims = 2
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with scope.NameScope('global_scope'):
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with ParameterSharing({'new_fc': 'shared_fc'}):
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self.model.FC(
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self.model.input_feature_schema.float_features,
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output_dims,
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name='shared_fc'
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)
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self.assertEquals(self.model.layers[-1].w,
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'global_scope/shared_fc/w')
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self.model.FC(
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self.model.input_feature_schema.float_features,
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output_dims,
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name='new_fc'
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)
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self.assertEquals(self.model.layers[-1].w,
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'global_scope/shared_fc/w')
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def test_layer_shared_parameter_name_different_shapes(self):
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output_dims = 2
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with scope.NameScope('global_scope'):
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with ParameterSharing({'fc_auto_0': 'fc'}):
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self.model.FC(
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self.model.input_feature_schema.float_features,
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output_dims
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)
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self.assertEquals(self.model.layers[-1].w,
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'global_scope/fc/w')
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with self.assertRaisesRegex(ValueError, 'Got inconsistent shapes .*'):
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self.model.FC(
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self.model.input_feature_schema.float_features,
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output_dims + 1
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)
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def test_layer_duplicated_parameter_init(self):
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output_dims = 2
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with scope.NameScope('global_scope'):
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with ParameterSharing({'new_fc': 'shared_fc'}):
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self.model.FC(
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self.model.input_feature_schema.float_features,
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output_dims,
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name='shared_fc'
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)
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self.model.FC(
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self.model.input_feature_schema.float_features,
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output_dims,
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name='new_fc'
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)
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train_init_net = core.Net('train_init_net')
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train_net = core.Net('train_net')
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for layer in self.model.layers:
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layer.add_operators(train_net, train_init_net)
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op_outputs = []
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for op in train_init_net._net.op:
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op_outputs.extend(op.output)
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# only fill these parameter blobs once
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self.assertEquals(
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sorted(op_outputs),
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['global_scope/shared_fc/b', 'global_scope/shared_fc/w']
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)
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def test_layer_shared_parameter_optim_validator(self):
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"""
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This test is to cover the _validate_param_optim function in
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layer_model_helper class.
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"""
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output_dims = 2
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adagrad_optim = AdagradOptimizer(
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alpha=0.004,
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epsilon=0.02,
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)
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self.model.default_optimizer = adagrad_optim
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# the following covers the branch -- optim is None
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with scope.NameScope('global_scope_0'):
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with ParameterSharing({'scope_1': 'scope_0'}):
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with scope.NameScope('scope_0'):
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fc1_output = self.model.FC(
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self.model.input_feature_schema.float_features,
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output_dims,
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weight_optim=self.model.NoOptim,
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)
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with scope.NameScope('scope_1'), self.assertRaises(Exception):
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fc2_output = self.model.FC(
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self.model.input_feature_schema.float_features,
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output_dims
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)
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# the following covers the branch -- optim is NoOptim
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with scope.NameScope('global_scope_1'):
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with ParameterSharing({'scope_1': 'scope_0'}):
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with scope.NameScope('scope_0'):
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fc1_output = self.model.FC(
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self.model.input_feature_schema.float_features,
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output_dims,
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weight_optim=None,
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)
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with scope.NameScope('scope_1'), self.assertRaises(Exception):
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fc2_output = self.model.FC(
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self.model.input_feature_schema.float_features,
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output_dims,
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weight_optim=self.model.NoOptim,
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)
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# the following covers the branch -- optim is an instance of Optimizer
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adagrad_optim_2 = AdagradOptimizer(
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alpha=0.005,
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epsilon=0.02,
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)
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adam_optim = AdamOptimizer()
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self.model.default_optimizer = adagrad_optim_2
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with scope.NameScope('global_scope_2'):
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with ParameterSharing({'scope_1': 'scope_0', 'scope_2': 'scope_0'}):
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with scope.NameScope('scope_0'):
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fc1_output = self.model.FC(
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self.model.input_feature_schema.float_features,
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output_dims,
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weight_optim=None, # it will use adagrad_optim_2
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)
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with scope.NameScope('scope_1'), self.assertRaises(Exception):
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fc2_output = self.model.FC(
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self.model.input_feature_schema.float_features,
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output_dims,
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weight_optim=adagrad_optim,
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)
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with scope.NameScope('scope_2'), self.assertRaises(Exception):
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fc2_output = self.model.FC(
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self.model.input_feature_schema.float_features,
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output_dims,
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weight_optim=adam_optim,
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)
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