reshape() takes 2 positional arguments but 5 were given - fix (#1086)

model_compression_toolkit/core/pytorch/back2framework/pytorch_model_builder.py

@@ -125,6 +125,7 @@ def _run_operation(n: BaseNode,
 
     op_call_args = n.op_call_args if isinstance(n, FunctionalNode) else []
     functional_kwargs = n.op_call_kwargs if isinstance(n, FunctionalNode) else {}
+
     if isinstance(n, FunctionalNode) and n.inputs_as_list:
         out_tensors_of_n_float = op_func(input_tensors, *op_call_args, **functional_kwargs)
     else:

model_compression_toolkit/core/pytorch/graph_substitutions/substitutions/permute_call_method.py → model_compression_toolkit/core/pytorch/graph_substitutions/substitutions/transform_function_call_method.py

@@ -12,30 +12,30 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ==============================================================================
-from torch import permute
+from torch import permute, reshape
 from model_compression_toolkit.core.common.graph.graph_matchers import NodeOperationMatcher
 from model_compression_toolkit.core import common
 from model_compression_toolkit.core.common.graph.base_graph import Graph
 from model_compression_toolkit.core.common.graph.base_node import BaseNode
 
 
-class PermuteCallMethod(common.BaseSubstitution):
+class TransformFunctionCallMethod(common.BaseSubstitution):
     """
-    Find "permute" node to substitute new dimension argument if needed
+    Find "permute or reshape" node to substitute new dimension argument if needed
     """
 
     def __init__(self):
         """
-        Matches: 'permute' node
+        Matches: 'permute or reshape' node
         """
-        nodes = NodeOperationMatcher(permute)
+        nodes = NodeOperationMatcher(permute) | NodeOperationMatcher(reshape)
         super().__init__(matcher_instance=nodes)
 
     def substitute(self,
                    graph: Graph,
                    node: BaseNode) -> Graph:
         """
-        Wrap dimension of permute with tuple if it's missing
+        Wrap dimension of permute or reshape with tuple if it's missing
 
         Args:
             graph: Graph we apply the substitution on.
@@ -45,6 +45,6 @@ def substitute(self,
             Graph after applying the substitution.
         """
         # Check op_call_args is not empty and has its argument as a tuple
-        if node.op_call_args and not isinstance(node.op_call_args[0], tuple):
+        if node.op_call_args and not isinstance(node.op_call_args[0], (list,tuple)):
             node.op_call_args = [node.op_call_args]
         return graph

model_compression_toolkit/core/pytorch/pytorch_implementation.py

@@ -52,8 +52,8 @@
     pytorch_linear_collapsing
 from model_compression_toolkit.core.pytorch.graph_substitutions.substitutions.multi_head_attention_decomposition \
     import MultiHeadAttentionDecomposition
-from model_compression_toolkit.core.pytorch.graph_substitutions.substitutions.permute_call_method import \
-    PermuteCallMethod
+from model_compression_toolkit.core.pytorch.graph_substitutions.substitutions.transform_function_call_method import \
+    TransformFunctionCallMethod
 from model_compression_toolkit.core.pytorch.graph_substitutions.substitutions.const_holder_conv import \
     FunctionalConvSubstitution
 from model_compression_toolkit.core.pytorch.graph_substitutions.substitutions.relu_bound_to_power_of_2 import \
@@ -236,7 +236,7 @@ def get_substitutions_prepare_graph(self, fw_info: FrameworkInfo = None) -> List
         """
         return [ReshapeWithStaticShapes(),
                 MultiHeadAttentionDecomposition(),
-                PermuteCallMethod(),
+                TransformFunctionCallMethod(),
                 FunctionalConvSubstitution(fw_info),
                 FunctionalBatchNorm(),
                 FunctionalLayerNorm(),

tests/pytorch_tests/model_tests/feature_models/reshape_substitution_test.py

@@ -0,0 +1,62 @@
+# Copyright 2024 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.
+# ==============================================================================
+import torch
+import torch.nn as nn
+import model_compression_toolkit as mct
+from model_compression_toolkit.core.pytorch.utils import to_torch_tensor, set_model
+from tests.pytorch_tests.model_tests.base_pytorch_feature_test import BasePytorchFeatureNetworkTest
+from tests.common_tests.helpers.generate_test_tp_model import generate_test_tp_model
+from model_compression_toolkit.target_platform_capabilities.tpc_models.imx500_tpc.latest import generate_pytorch_tpc
+
+
+tp = mct.target_platform
+
+
+class BaseReshapeSubstitutionTest(BasePytorchFeatureNetworkTest):
+
+    def __init__(self, unit_test):
+        super().__init__(unit_test=unit_test)
+
+    def get_tpc(self):
+        tp = generate_test_tp_model({'weights_n_bits': 32,
+                                     'activation_n_bits': 32,
+                                     'enable_weights_quantization': False,
+                                     'enable_activation_quantization': False})
+        return generate_pytorch_tpc(name="permute_substitution_test", tp_model=tp)
+
+    def get_quantization_config(self):
+        return mct.core.QuantizationConfig(mct.core.QuantizationErrorMethod.NOCLIPPING,
+                                           mct.core.QuantizationErrorMethod.NOCLIPPING, False, False)
+
+    def compare(self, quantized_model, float_model, input_x=None, quantization_info=None):
+        in_torch_tensor = to_torch_tensor(input_x[0])
+        set_model(float_model)
+        y = float_model(in_torch_tensor)
+        y_hat = quantized_model(in_torch_tensor)
+        self.unit_test.assertTrue(y.shape == y_hat.shape, msg=f'out shape is not as expected!')
+
+class ReshapeSubstitutionTest(BaseReshapeSubstitutionTest):
+    def __init__(self, unit_test):
+        super().__init__(unit_test)
+
+    class ReshapeNet(nn.Module):
+        def __init__(self, ):
+            super().__init__()
+            self.gamma = nn.Parameter(1 * torch.ones((1, 3, 1, 1)))  
+        def forward(self, x):
+            x=x.mul(self.gamma.reshape(1,-1,1,1))
+            return x
+    def create_networks(self):
+        return self.ReshapeNet()

tests/pytorch_tests/model_tests/test_feature_models_runner.py

@@ -57,6 +57,7 @@
 from tests.pytorch_tests.model_tests.feature_models.test_softmax_shift import SoftmaxLayerNetTest, \
     SoftmaxFunctionNetTest
 from tests.pytorch_tests.model_tests.feature_models.permute_substitution_test import PermuteSubstitutionTest
+from tests.pytorch_tests.model_tests.feature_models.reshape_substitution_test import ReshapeSubstitutionTest
 from tests.pytorch_tests.model_tests.feature_models.constant_conv_substitution_test import ConstantConvSubstitutionTest, \
     ConstantConvReuseSubstitutionTest, ConstantConvTransposeSubstitutionTest
 from tests.pytorch_tests.model_tests.feature_models.multi_head_attention_test import MHALayerNetTest, \
@@ -97,6 +98,7 @@
 
 
 class FeatureModelsTestRunner(unittest.TestCase):
+
     def test_remove_identity(self):
         """
         This test checks that identity layers are removed from the model.
@@ -272,13 +274,19 @@ def test_const_representation(self):
                                                enable_weights_quantization=enable_weights_quantization).run_test()
             ConstRepresentationLinearLayerTest(self, func=nn.ConvTranspose2d(16, 16, 1),
                                                const=c_img, enable_weights_quantization=enable_weights_quantization).run_test()
-
+    
     def test_permute_substitution(self):
         """
         This test checks the permute substitution feature
         """
         PermuteSubstitutionTest(self).run_test()
-
+
+    def test_reshape_substitution(self):
+        """
+        This test checks the reshape substitution feature
+        """
+        ReshapeSubstitutionTest(self).run_test()
+
     def test_constant_conv_substitution(self):
         """
         This test checks the constant conv substitution feature

tutorials/notebooks/imx500_notebooks/pytorch/pytorch_yolov8n_seg_for_imx500.ipynb

@@ -10,7 +10,7 @@
       "source": [
         "# YOLOv8n Object Detection PyTorch Model - Quantization for IMX500\n",
         "\n",
-        "[Run this tutorial in Google Colab](https://colab.research.google.com/github/sony/model_optimization/blob/main/tutorials/notebooks/pytorch/ptq/pytorch_yolov8n_seg_for_imx500.ipynb)\n",
+        "[Run this tutorial in Google Colab](https://colab.research.google.com/github/sony/model_optimization/blob/main/tutorials/notebooks/imx500_notebooks/pytorch/pytorch_yolov8n_seg_for_imx500.ipynb)\n",
         "\n",
         "## Overview\n",
         "\n",