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Tests adjusted
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@daniil-lyakhov
daniil-lyakhov committed Apr 25, 2024
1 parent 66c80bd commit 808d068
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Showing 5 changed files with 76 additions and 37 deletions.
30 changes: 23 additions & 7 deletions tests/torch/data/reference_scales/TwoConvTestModel_overflow_fix_disable.json
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"TwoConvTestModel/NNCFNetworkInterface[_nncf]/ModuleDict[external_quantizers]/SymmetricQuantizer[TwoConvTestModel/Sequential[features]/Sequential[0]/NNCFConv2d[0]/conv2d_0|OUTPUT]": {
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30 changes: 23 additions & 7 deletions tests/torch/data/reference_scales/TwoConvTestModel_overflow_fix_enable.json
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Expand Up @@ -12,14 +12,14 @@
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"TwoConvTestModel/NNCFNetworkInterface[_nncf]/ModuleDict[external_quantizers]/SymmetricQuantizer[TwoConvTestModel/Sequential[features]/Sequential[0]/NNCFConv2d[0]/conv2d_0|OUTPUT]": {
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30 changes: 23 additions & 7 deletions tests/torch/data/reference_scales/TwoConvTestModel_overflow_fix_first_layer_only.json
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Expand Up @@ -12,14 +12,14 @@
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"TwoConvTestModel/NNCFNetworkInterface[_nncf]/ModuleDict[external_quantizers]/SymmetricQuantizer[TwoConvTestModel/Sequential[features]/Sequential[0]/NNCFConv2d[0]/conv2d_0|OUTPUT]": {
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}
13 changes: 0 additions & 13 deletions tests/torch/ptq/helpers.py
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Expand Up @@ -20,7 +20,6 @@
from nncf.torch.graph.operator_metatypes import PTModuleDepthwiseConv2dSubtype
from nncf.torch.graph.operator_metatypes import PTModuleLinearMetatype
from nncf.torch.graph.operator_metatypes import PTSumMetatype
from nncf.torch.tensor_statistics.statistics import PTMinMaxTensorStatistic
from tests.post_training.test_templates.models import NNCFGraphToTest
from tests.post_training.test_templates.models import NNCFGraphToTestDepthwiseConv
from tests.post_training.test_templates.models import NNCFGraphToTestSumAggregation
Expand Down Expand Up @@ -81,15 +80,3 @@ def get_nncf_network(model: torch.nn.Module, input_shape: Optional[List[int]] =
model = model.eval()
device = next(model.named_parameters())[1].device
return wrap_model(model, torch.ones(input_shape).to(device=device), trace_parameters=True)


def mock_collect_statistics(mocker):
_ = mocker.patch(
"nncf.common.tensor_statistics.aggregator.StatisticsAggregator.collect_statistics", return_value=None
)
min_, max_ = 0.0, 1.0
min_, max_ = torch.tensor(min_), torch.tensor(max_)
_ = mocker.patch(
"nncf.experimental.common.tensor_statistics.collectors.TensorCollector.get_statistics",
return_value=PTMinMaxTensorStatistic(min_values=min_, max_values=max_),
)
10 changes: 7 additions & 3 deletions tests/torch/ptq/test_graphs.py
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Expand Up @@ -24,7 +24,6 @@
from tests.post_training.test_templates.helpers import EmbeddingModel
from tests.post_training.test_templates.helpers import get_static_dataset
from tests.torch import test_models
from tests.torch.ptq.helpers import mock_collect_statistics
from tests.torch.quantization.test_algo_quantization import SharedLayersModel
from tests.torch.test_compressed_graph import ModelDesc
from tests.torch.test_compressed_graph import check_graph
Expand Down Expand Up @@ -95,15 +94,20 @@ def get_model_name(description):
("desc", "quantization_parameters"), TEST_MODELS_DESC, ids=[get_model_name(m) for m in TEST_MODELS_DESC]
)
def test_min_max_classification_quantized_graphs(desc: ModelDesc, quantization_parameters, graph_dir, mocker):
mock_collect_statistics(mocker)
model = desc.model_builder()

nncf_network = wrap_model(model, torch.ones(desc.input_sample_sizes), trace_parameters=True)
quantization_parameters["advanced_parameters"] = AdvancedQuantizationParameters(disable_bias_correction=True)
quantization_parameters["subset_size"] = 1
quantization_algorithm = PostTrainingQuantization(**quantization_parameters)

def transform_fn(input_) -> torch.Tensor:
return torch.tensor(input_[0])

quantized_model = quantization_algorithm.apply(
nncf_network, nncf_network.nncf.get_graph(), dataset=get_static_dataset(desc.input_sample_sizes, None, None)
nncf_network,
nncf_network.nncf.get_graph(),
dataset=get_static_dataset(desc.input_sample_sizes, transform_fn, None),
)

check_graph(quantized_model.nncf.get_graph(), desc.dot_filename(), graph_dir)

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