organize tests

Author: irenab

tests_pytest/common/core/common/mixed_precision/resource_utilization_tools/test_resource_utilization_calculator.py

@@ -13,16 +13,14 @@
 # limitations under the License.
 # ==============================================================================
 from types import MethodType
-from typing import Iterable, Union
 from unittest.mock import Mock
 
 import numpy as np
 import pytest
-from mct_quantizers import QuantizationMethod
 
 from model_compression_toolkit.constants import FLOAT_BITWIDTH
-from model_compression_toolkit.core import QuantizationConfig, ResourceUtilization
-from model_compression_toolkit.core.common import Graph, BaseNode
+from model_compression_toolkit.core import ResourceUtilization
+from model_compression_toolkit.core.common import Graph
 from model_compression_toolkit.core.common.graph.edge import Edge
 from model_compression_toolkit.core.common.graph.memory_graph.compute_graph_max_cut import compute_graph_max_cut
 from model_compression_toolkit.core.common.graph.memory_graph.cut import Cut
@@ -34,100 +32,7 @@
     RUTarget
 from model_compression_toolkit.core.common.mixed_precision.resource_utilization_tools.resource_utilization_calculator import \
     Utilization, ResourceUtilizationCalculator, TargetInclusionCriterion, BitwidthMode
-from model_compression_toolkit.core.common.quantization.candidate_node_quantization_config import \
-    CandidateNodeQuantizationConfig
-from model_compression_toolkit.core.common.quantization.node_quantization_config import \
-    NodeActivationQuantizationConfig, NodeWeightsQuantizationConfig
-from model_compression_toolkit.target_platform_capabilities.schema.mct_current_schema import OpQuantizationConfig, \
-    AttributeQuantizationConfig, Signedness
-
-
-def full_attr_name(canonical_name: Union[str, dict, Iterable]):
-    """ Convert canonical attr (such as 'kernel') into a full name originated from the layer (e.g. 'conv2d_1/kernel:0')
-        We just need the names to differ from canonical to make sure we call the correct apis. We use the same
-        template for simplicity, so we don't have to explicitly synchronize names between node and weight configs."""
-    convert = lambda name: f'{name[0]}/{name}/{name[-1]}' if isinstance(name, str) else name
-    if isinstance(canonical_name, str):
-        return convert(canonical_name)
-    assert isinstance(canonical_name, (list, tuple, set))
-    return canonical_name.__class__([convert(name) for name in canonical_name])
-
-
-def build_qc(a_nbits=8, a_enable=True, w_attr=None, pos_attr=(32, False, ())):
-    """ Build quantization config for tests.
-        w_attr contains {canonical name: (nbits, q_enabled)}
-        pos_attr: (nbits, q enabled, indices) """
-    w_attr = w_attr or {}
-    attr_weights_configs_mapping = {
-        k: AttributeQuantizationConfig(weights_n_bits=v[0], enable_weights_quantization=v[1])
-        for k, v in w_attr.items()
-    }
-    qc = QuantizationConfig()
-    # positional attrs are set via default weight config (so all pos attrs have the same q config)
-    op_cfg = OpQuantizationConfig(
-        # canonical names (as 'kernel')
-        attr_weights_configs_mapping=attr_weights_configs_mapping,
-        activation_n_bits=a_nbits,
-        enable_activation_quantization=a_enable,
-        default_weight_attr_config=AttributeQuantizationConfig(weights_n_bits=pos_attr[0],
-                                                               enable_weights_quantization=pos_attr[1]),
-        activation_quantization_method=QuantizationMethod.POWER_OF_TWO,
-        quantization_preserving=False,
-        supported_input_activation_n_bits=[2, 4, 8],
-        fixed_scale=None,
-        fixed_zero_point=None,
-        simd_size=None,
-        signedness=Signedness.AUTO
-    )
-    a_qcfg = NodeActivationQuantizationConfig(qc=qc, op_cfg=op_cfg,
-                                              activation_quantization_fn=None,
-                                              activation_quantization_params_fn=None)
-    # full names from the layers
-    attr_names = [full_attr_name(k) for k in w_attr.keys()]
-    w_qcfg = NodeWeightsQuantizationConfig(qc=qc, op_cfg=op_cfg,
-                                           weights_channels_axis=None,
-                                           node_attrs_list=attr_names + list(pos_attr[2]))
-    qc = CandidateNodeQuantizationConfig(activation_quantization_cfg=a_qcfg,
-                                         weights_quantization_cfg=w_qcfg)
-
-    # we generate q configs via constructors to follow the real code as closely as reasonably possible.
-    # verify that we actually got the configurations we want
-    assert qc.activation_quantization_cfg.activation_n_bits == a_nbits
-    assert qc.activation_quantization_cfg.enable_activation_quantization is a_enable
-    for k, v in w_attr.items():
-        # get_attr_config accepts canonical attr names
-        assert qc.weights_quantization_cfg.get_attr_config(k).weights_n_bits == v[0]
-        assert qc.weights_quantization_cfg.get_attr_config(k).enable_weights_quantization == v[1]
-    for pos in pos_attr[2]:
-        assert qc.weights_quantization_cfg.get_attr_config(pos).weights_n_bits == pos_attr[0]
-        assert qc.weights_quantization_cfg.get_attr_config(pos).enable_weights_quantization == pos_attr[1]
-
-    return qc
-
-
-class DummyLayer:
-    """ Only needed for repr(node) to work. """
-    pass
-
-
-def build_node(name='node', canonical_weights: dict=None, qcs=None, input_shape=(4, 5, 6), output_shape=(4, 5, 6),
-               layer_class=DummyLayer, reuse=False):
-    """ Build a node for tests.
-        Canonical weights are converted into full unique names.
-        candidate_quantization_cfg is set is qcs is passed."""
-    weights = canonical_weights or {}
-    weights = {k if isinstance(k, int) else full_attr_name(k): w for k, w in weights.items()}
-    node = BaseNode(name=name,
-                    framework_attr={},
-                    input_shape=input_shape,
-                    output_shape=output_shape,
-                    weights=weights,
-                    layer_class=layer_class,
-                    reuse=reuse)
-    if qcs:
-        node.candidates_quantization_cfg = qcs
-    return node
-
+from tests_pytest.test_util.graph_builder_utils import build_node, build_qc, full_attr_name
 
 BM = BitwidthMode
 TIC = TargetInclusionCriterion

tests_pytest/common/test_model_collector.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ==============================================================================
 import pytest
-from unittest.mock import Mock, call
+from unittest.mock import Mock
 import numpy as np
 from numpy.testing import assert_array_equal
 
@@ -23,7 +23,7 @@
 from model_compression_toolkit.core.common.graph.edge import Edge
 from model_compression_toolkit.core.common.hessian import HessianInfoService
 from model_compression_toolkit.core.common.model_collector import create_stats_collector_for_node, create_tensor2node, ModelCollector
-from tests_pytest.common.graph_builder_utils import build_node, DummyLayer, build_qc
+from tests_pytest.test_util.graph_builder_utils import build_node, DummyLayer, build_qc
 
 
 @pytest.fixture

tests_pytest/keras/core/mixed_precision/test_resource_utilization.py

@@ -19,7 +19,7 @@
 from keras.layers import Conv2D, Conv2DTranspose, DepthwiseConv2D, Dense, Input, Subtract, Flatten
 
 from tests_pytest.base_test_classes.base_test_ru_integration import BaseRUIntegrationTester
-from tests_pytest.keras.keras_test_mixin import KerasFwMixin
+from tests_pytest.keras.keras_test_util.keras_test_mixin import KerasFwMixin
 
 
 class TestRUIntegrationKeras(BaseRUIntegrationTester, KerasFwMixin):

tests_pytest/keras/keras_test_util/__init__.py

@@ -0,0 +1,14 @@
+# Copyright 2025 Sony Semiconductor Israel, Inc. 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.
+# ==============================================================================

tests_pytest/keras/keras_test_mixin.py …eras/keras_test_util/keras_test_mixin.pytests_pytest/keras/keras_test_mixin.py renamed to tests_pytest/keras/keras_test_util/keras_test_mixin.py tests_pytest/keras/keras_test_mixin.py renamed to tests_pytest/keras/keras_test_util/keras_test_mixin.py

@@ -17,7 +17,7 @@
 
 from model_compression_toolkit.core.pytorch.utils import to_torch_tensor
 from tests_pytest.base_test_classes.base_test_ru_integration import BaseRUIntegrationTester
-from tests_pytest.pytorch.torch_test_mixin import TorchFwMixin
+from tests_pytest.pytorch.torch_test_util.torch_test_mixin import TorchFwMixin
 
 
 class TestRUIntegrationTorch(BaseRUIntegrationTester, TorchFwMixin):

tests_pytest/pytorch/core/mixed_precision/test_resource_utilization.py

@@ -0,0 +1,14 @@
+# Copyright 2025 Sony Semiconductor Israel, Inc. 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.
+# ==============================================================================