wehub-resource-sync
ba4be087d5
Create PR to main with cherry-pick from release / cherry-pick (push) Failing after 0s
CICD NeMo / pre-flight (push) Failing after 0s
CICD NeMo / configure (push) Has been skipped
Build, validate, and release Neural Modules / pre-flight (push) Failing after 1s
CICD NeMo / code-linting (push) Has been skipped
Build, validate, and release Neural Modules / release (push) Has been skipped
Build, validate, and release Neural Modules / release-summary (push) Has been cancelled
CICD NeMo / cicd-test-container-build (push) Has been cancelled
CICD NeMo / cicd-import-tests (push) Has been cancelled
CICD NeMo / L0_Setup_Test_Data_And_Models (push) Has been cancelled
CICD NeMo / cicd-main-unit-tests (push) Has been cancelled
CICD NeMo / cicd-main-speech (push) Has been cancelled
CICD NeMo / Nemo_CICD_Test (push) Has been cancelled
CICD NeMo / Coverage (e2e) (push) Has been cancelled
CICD NeMo / Coverage (unit-test) (push) Has been cancelled
CodeQL / Analyze (python) (push) Has been cancelled
CICD NeMo / cicd-wait-in-queue (push) Has been cancelled
91 lines
3.3 KiB
Python
91 lines
3.3 KiB
Python
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
|
|
#
|
|
# 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 pytest
|
|
import torch
|
|
|
|
from nemo.collections.common.parts import adapter_modules
|
|
from nemo.core.classes.mixins import adapter_mixin_strategies
|
|
from nemo.utils import config_utils
|
|
|
|
|
|
class TestAdapterModules:
|
|
@pytest.mark.unit
|
|
def test_linear_adapter_config(self):
|
|
IGNORED_ARGS = ['_target_']
|
|
|
|
result = config_utils.assert_dataclass_signature_match(
|
|
adapter_modules.LinearAdapter, adapter_modules.LinearAdapterConfig, ignore_args=IGNORED_ARGS
|
|
)
|
|
|
|
signatures_match, cls_subset, dataclass_subset = result
|
|
|
|
assert signatures_match
|
|
assert cls_subset is None
|
|
assert dataclass_subset is None
|
|
|
|
@pytest.mark.unit
|
|
def test_linear_adapter_init(self):
|
|
torch.random.manual_seed(0)
|
|
x = torch.randn(2, 50)
|
|
|
|
adapter = adapter_modules.LinearAdapter(in_features=50, dim=5)
|
|
|
|
with torch.no_grad():
|
|
assert adapter.module[-1].weight.sum() == 0
|
|
if hasattr(adapter.module[-1], 'bias') and adapter.module[-1].bias is not None:
|
|
assert adapter.module[-1].bias.sum() == 0
|
|
|
|
out = adapter(x)
|
|
assert out.sum().abs() <= 1e-8
|
|
|
|
@pytest.mark.unit
|
|
def test_linear_adapter_dropout(self):
|
|
torch.random.manual_seed(0)
|
|
x = torch.randn(2, 50)
|
|
|
|
adapter = adapter_modules.LinearAdapter(in_features=50, dim=5, dropout=0.5)
|
|
|
|
with torch.no_grad():
|
|
assert adapter.module[-1].weight.sum() == 0
|
|
if hasattr(adapter.module[-1], 'bias') and adapter.module[-1].bias is not None:
|
|
assert adapter.module[-1].bias.sum() == 0
|
|
|
|
out = adapter(x)
|
|
assert out.sum().abs() <= 1e-8
|
|
|
|
@pytest.mark.unit
|
|
@pytest.mark.parametrize('norm_position', ['pre', 'post'])
|
|
def test_linear_adapter_norm_position(self, norm_position):
|
|
torch.random.manual_seed(0)
|
|
x = torch.randn(2, 50)
|
|
|
|
adapter = adapter_modules.LinearAdapter(in_features=50, dim=5, norm_position=norm_position)
|
|
|
|
with torch.no_grad():
|
|
assert adapter.module[-1].weight.sum() == 0
|
|
if hasattr(adapter.module[-1], 'bias') and adapter.module[-1].bias is not None:
|
|
assert adapter.module[-1].bias.sum() == 0
|
|
|
|
out = adapter(x)
|
|
assert out.sum().abs() <= 1e-8
|
|
|
|
@pytest.mark.unit
|
|
def test_linear_adapter_strategy(self):
|
|
adapter = adapter_modules.LinearAdapter(in_features=50, dim=5)
|
|
assert hasattr(adapter, 'adapter_strategy')
|
|
assert adapter.adapter_strategy is not None
|
|
# assert default strategy is set
|
|
assert isinstance(adapter.adapter_strategy, adapter_mixin_strategies.ResidualAddAdapterStrategy)
|