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Commit 8b9a9a1d authored by Matthew Newson's avatar Matthew Newson
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Add rescaling and unit tests for matmul

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2 merge requests!710.4.0,!48Adding MatMul operator
Pipeline #74197 failed
Stage: static_analysis
    Stage: build
      Stage: test
        Stage: coverage
          Stage: release
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            aidge_export_cpp/kernels/matmul.hpp
            + 3
            − 2
            View file @ 8b9a9a1d
            ......@@ -10,12 +10,13 @@ template<int INPUT_A_DIMS[], int INPUT_B_DIMS[], int OUTPUT_DIMS[],
            int _SIZE_DIM_IN_A, int _SIZE_DIM_IN_B, int SIZE_DIM_OUT,
            ActivationFunction_T ACTIVATION,
            typename Input_T, typename Output_T,
            typename Rescaling>
            typename Rescaling_T>
            __attribute__((always_inline)) inline
            void matmul_forward (
            const Input_T* __restrict inputs1,
            const Input_T* __restrict inputs2,
            Output_T* __restrict outputs)
            Output_T* __restrict outputs,
            const Rescaling_T& __restrict rescaling)
            {
            //initialize arrays storing broadcasted(or not) dims
            ......
            aidge_export_cpp/templates/configuration/matmul_config.jinja
            + 1
            − 2
            View file @ 8b9a9a1d
            ......@@ -22,9 +22,8 @@ int {{name|upper}}_INPUT_A_DIMS[] = { {{ in_dims[0]|join(", ") }} };
            int {{name|upper}}_INPUT_B_DIMS[] = { {{ in_dims[1]|join(", ") }} };
            #define {{ name|upper }}_ACTIVATION {{ activation }}
            static const {{ rescaling }} {{ name|upper }}_RESCALING = {};
            static const {{ rescaling }} {{ name|upper }}_RESCALING = {};
            {% include "./_rescaling.jinja" %}
            {#- Calculate sizes #}
            ......
            aidge_export_cpp/templates/kernel_forward/matmul_forward.jinja
            + 1
            − 1
            View file @ 8b9a9a1d
            ......@@ -7,7 +7,7 @@ matmul_forward<{{name|upper}}_INPUT_A_DIMS,
            {{name|upper}}_SIZE_DIM_IN_B,
            {{name|upper}}_SIZE_DIM_OUT,
            {{name|upper}}_ACTIVATION>
            ({{in_name[0]}}, {{in_name[1]}}, {{out_name[0]}});
            ({{in_name[0]}}, {{in_name[1]}}, {{out_name[0]}}, {{name|upper}}_RESCALING);
            {% include "./_save_outputs.jinja" %}
            {% include "./_aidge_cmp.jinja" %}
            {% endfilter %}
            aidge_export_cpp/unit_tests/test_export.py
            + 21
            − 347
            View file @ 8b9a9a1d
            ......@@ -480,377 +480,50 @@ class test_operator_export(unittest.TestCase):
            self.unit_test_export(model, "MatMul", [[8, 4]])
            def test_concat_axis_2(self):
            print("ConcatAxis2")
            def test_matmul_larger(self):
            print("MatmulLarger")
            model = aidge_core.sequential([
            aidge_core.Producer([1, 5, 7], name="producer"),
            aidge_core.Concat(nb_inputs=2, axis=2, name="concat")
            aidge_core.MatMul(name="MatMul")
            ])
            self.unit_test_export(model, "ConcatAxis2", [[1, 5, 7]])
            self.unit_test_export(model, "MatMul", [[1, 7, 5]])
            def test_concat_axis_negative(self):
            print("ConcatAxisNegative")
            def test_matmul_higher(self):
            print("MatMulHigher")
            model = aidge_core.sequential([
            aidge_core.Producer([1, 5, 7], name="producer"),
            aidge_core.Concat(nb_inputs=2, axis=-2, name="concat")
            ])
            self.unit_test_export(model, "ConcatAxisNegative", [[1, 5, 7]])
            def test_conv2D(self):
            print("Conv2D")
            model = aidge_core.sequential([
            aidge_core.Conv2D(in_channels=3, out_channels=3, kernel_dims=(3, 3), name="conv")
            ])
            self.unit_test_export(model, "Conv2D", [[1, 3, 12, 12]], False, False)
            def test_convDepthWise2D(self):
            print("ConvDepthWise2D")
            model = aidge_core.sequential([
            aidge_core.ConvDepthWise2D(nb_channels=3, kernel_dims=(3, 3), name="conv")
            ])
            self.unit_test_export(model, "ConvDepthWise2D", [[1, 3, 12, 12]], False, False)
            def test_max_pooling(self):
            print("MaxPooling2D")
            model = aidge_core.sequential([
            aidge_core.MaxPooling2D(kernel_dims=(3, 3), name="max_pool")
            ])
            self.unit_test_export(model, "MaxPooling2D", [[1, 2, 12, 12]], False, False)
            def test_avg_pooling(self):
            print("AvgPooling2D")
            model = aidge_core.sequential([
            aidge_core.AvgPooling2D(kernel_dims=(3, 3), name="avg_pool")
            ])
            self.unit_test_export(model, "AvgPooling2D", [[1, 2, 12, 12]], False, False)
            def test_pad2D(self):
            print("Pad2D")
            model = aidge_core.sequential([
            aidge_core.Pad2D((1, 1, 1, 1), name="pad2d")
            ])
            self.unit_test_export(model, "Pad2D", [[1, 1, 11, 11]])
            def test_pad2D_larger(self):
            print("Pad2DLarger")
            model = aidge_core.sequential([
            aidge_core.Pad2D((1, 3, 1, 3), name="pad2d")
            ])
            self.unit_test_export(model, "Pad2DLarger", [[1, 1, 7, 11]])
            def test_pad2D_higher(self):
            print("Pad2DHigher")
            model = aidge_core.sequential([
            aidge_core.Pad2D((3, 1, 3, 1), name="pad2d")
            ])
            self.unit_test_export(model, "Pad2DHigher", [[1, 1, 11, 7]])
            def test_pad2D_mismatch(self):
            print("Pad2DMismatch")
            model = aidge_core.sequential([
            aidge_core.Pad2D((1, 3, 5, 7), name="pad2d")
            ])
            self.unit_test_export(model, "Pad2DMismatch", [[3, 5, 11, 7]])
            def test_pad2D_denser(self):
            print("Pad2DDenser")
            model = aidge_core.sequential([
            aidge_core.Pad2D((3, 3, 3, 3), name="pad2d")
            ])
            self.unit_test_export(model, "Pad2DDenser", [[1, 5, 7, 11]])
            def test_pad2D_with_bigger_batch_size(self):
            print("Pad2DBiggerBatchSize")
            model = aidge_core.sequential([
            aidge_core.Pad2D((1, 1, 1, 1), name="pad2d")
            ])
            self.unit_test_export(model, "Pad2DBiggerBatchSize", [[3, 5, 7, 11]])
            @unittest.expectedFailure
            def test_pad2D_not_constant(self):
            print("Pad2DNotConstant")
            model = aidge_core.sequential([
            aidge_core.Pad2D((3, 3, 3, 3), border_type=aidge_core.pad_border_type.Wrap, name="pad2d")
            ])
            self.unit_test_export(model, "Pad2DNotConstant", [[1, 5, 7, 11]])
            def test_batchnorm2D(self):
            print("BatchNormalization2D")
            model = aidge_core.sequential([
            aidge_core.BatchNorm2D(nb_features=10, epsilon=2e-5, name="bn")
            ])
            self.unit_test_export(model, "BatchNorm2D", [[1, 1, 5, 5]], False, False)
            def test_batchnorm2D_Larger(self):
            print("BatchNormalization2DLarger")
            model = aidge_core.sequential([
            aidge_core.BatchNorm2D(nb_features=10, epsilon=2e-5, name="bn")
            ])
            self.unit_test_export(model, "BatchNorm2DLarger", [[1, 1, 5, 7]], False, False)
            def test_batchnorm2D_Higher(self):
            print("BatchNormalization2DHigher")
            model = aidge_core.sequential([
            aidge_core.BatchNorm2D(nb_features=10, epsilon=2e-5, name="bn")
            ])
            self.unit_test_export(model, "BatchNorm2DHigher", [[1, 1, 7, 5]], False, False)
            def test_batchnorm2D_Denser(self):
            print("BatchNormalization2DDenser")
            model = aidge_core.sequential([
            aidge_core.BatchNorm2D(nb_features=10, epsilon=2e-5, name="bn")
            ])
            self.unit_test_export(model, "BatchNorm2DDenser", [[1, 3, 5, 7]], False, False)
            def test_batchnorm2D_with_bigger_batch_size(self):
            print("BatchNormalization2DBiggerBatchSize")
            model = aidge_core.sequential([
            aidge_core.BatchNorm2D(nb_features=10, epsilon=2e-5, name="bn")
            ])
            self.unit_test_export(model, "BatchNormalization2DBiggerBatchSize", [[4, 3, 5, 7]], False, False)
            def test_batchnorm2D_Larger(self):
            print("BatchNormalization2DLarger")
            model = aidge_core.sequential([
            aidge_core.BatchNorm2D(nb_features=10, epsilon=2e-5, name="bn")
            ])
            self.unit_test_export(model, "BatchNorm2DLarger", [[1, 1, 5, 7]], False, False)
            def test_batchnorm2D_Higher(self):
            print("BatchNormalization2DHigher")
            model = aidge_core.sequential([
            aidge_core.BatchNorm2D(nb_features=10, epsilon=2e-5, name="bn")
            ])
            self.unit_test_export(model, "BatchNorm2DHigher", [[1, 1, 7, 5]], False, False)
            def test_batchnorm2D_Denser(self):
            print("BatchNormalization2DDenser")
            model = aidge_core.sequential([
            aidge_core.BatchNorm2D(nb_features=10, epsilon=2e-5, name="bn")
            ])
            self.unit_test_export(model, "BatchNorm2DDenser", [[1, 3, 5, 7]], False, False)
            def test_Conv(self):
            model = aidge_core.sequential([
            aidge_core.Conv2D(1, 1, [3, 3], name="InputNode")
            ])
            initFiller(model)
            self.unit_test_export(model, "Conv", [[1, 1, 9, 9]])
            def test_MatMul(self):
            print("Matmul")
            model = aidge_core.sequential([
            aidge_core.Producer([1, 5, 5], name="producer"),
            aidge_core.Add(name="add")
            ])
            self.unit_test_export(model, "Add", [[1, 5, 5]])
            def test_add_larger(self):
            print("AddLarger")
            model = aidge_core.sequential([
            aidge_core.Producer([1, 7, 5], name="producer"),
            aidge_core.Add(name="add")
            ])
            self.unit_test_export(model, "Add", [[1, 7, 5]])
            def test_add_higher(self):
            print("AddHigher")
            model = aidge_core.sequential([
            aidge_core.Producer([1, 5, 7], name="producer"),
            aidge_core.Add(name="add")
            ])
            self.unit_test_export(model, "Add", [[1, 5, 7]])
            # "Broadcast not supported yet in export operator"
            @unittest.expectedFailure
            def test_add_simple_broadcast(self):
            print("AddSimpleBroadcast")
            model = aidge_core.sequential([
            aidge_core.Producer([1, 1, 5], name="producer"),
            aidge_core.Add(name="add")
            ])
            self.unit_test_export(model, "AddSimpleBroadcast", [[1, 7, 5]])
            # "Broadcast not supported yet in export operator"
            @unittest.expectedFailure
            def test_add_double_broadcast(self):
            print("AddDoubleBroadcast")
            model = aidge_core.sequential([
            aidge_core.Producer([1, 1, 7], name="producer"),
            aidge_core.Add(name="add")
            ])
            self.unit_test_export(model, "AddDoubleBroadcast", [[1, 5, 1]])
            def test_sub(self):
            print("Sub")
            model = aidge_core.sequential([
            aidge_core.Producer([1, 5, 5], name="producer"),
            aidge_core.Sub(name="sub")
            ])
            self.unit_test_export(model, "Sub", [[1, 5, 5]])
            def test_sub_larger(self):
            print("SubLarger")
            model = aidge_core.sequential([
            aidge_core.Producer([1, 7, 5], name="producer"),
            aidge_core.Sub(name="sub")
            ])
            self.unit_test_export(model, "Sub", [[1, 7, 5]])
            def test_sub_higher(self):
            print("SubHigher")
            model = aidge_core.sequential([
            aidge_core.Producer([1, 5, 7], name="producer"),
            aidge_core.Sub(name="sub")
            ])
            self.unit_test_export(model, "Sub", [[1, 5, 7]])
            # "Broadcast not supported yet in export operator"
            @unittest.expectedFailure
            def test_sub_simple_broadcast(self):
            print("SubSimpleBroadcast")
            model = aidge_core.sequential([
            aidge_core.Producer([1, 1, 5], name="producer"),
            aidge_core.Sub(name="sub")
            ])
            self.unit_test_export(model, "SubSimpleBroadcast", [[1, 7, 5]])
            # "Broadcast not supported yet in export operator"
            @unittest.expectedFailure
            def test_sub_double_broadcast(self):
            print("SubDoubleBroadcast")
            model = aidge_core.sequential([
            aidge_core.Producer([1, 1, 7], name="producer"),
            aidge_core.Sub(name="sub")
            ])
            self.unit_test_export(model, "SubDoubleBroadcast", [[1, 5, 1]])
            def test_mul(self):
            print("Mul")
            model = aidge_core.sequential([
            aidge_core.Producer([1, 5, 5], name="producer"),
            aidge_core.Mul(name="mul")
            ])
            self.unit_test_export(model, "Mul", [[1, 5, 5]])
            def test_mul_larger(self):
            print("MulLarger")
            model = aidge_core.sequential([
            aidge_core.Producer([1, 7, 5], name="producer"),
            aidge_core.Mul(name="mul")
            ])
            self.unit_test_export(model, "Mul", [[1, 7, 5]])
            def test_mul_higher(self):
            print("MulHigher")
            model = aidge_core.sequential([
            aidge_core.Producer([1, 5, 7], name="producer"),
            aidge_core.Mul(name="mul")
            aidge_core.MatMul(name="matmul")
            ])
            self.unit_test_export(model, "Mul", [[1, 5, 7]])
            self.unit_test_export(model, "MatMul", [[1, 7, 1]])
            # "Broadcast not supported yet in export operator"
            @unittest.expectedFailure
            def test_mul_simple_broadcast(self):
            print("MulSimpleBroadcast")
            def test_matmul_simple_broadcast(self):
            print("MatMulSimpleBroadcast")
            model = aidge_core.sequential([
            aidge_core.Producer([1, 1, 5], name="producer"),
            aidge_core.Mul(name="mul")
            aidge_core.MatMul(name="MatMul")
            ])
            self.unit_test_export(model, "MulSimpleBroadcast", [[1, 7, 5]])
            self.unit_test_export(model, "MatMulSimpleBroadcast", [[1, 5, 7]])
            # "Broadcast not supported yet in export operator"
            @unittest.expectedFailure
            def test_mul_double_broadcast(self):
            print("MulDoubleBroadcast")
            def test_matmul_double_broadcast(self):
            print("MatMulDoubleBroadcast")
            model = aidge_core.sequential([
            aidge_core.Producer([1, 1, 7], name="producer"),
            aidge_core.Mul(name="mul")
            aidge_core.Producer([3, 1, 5], name="producer"),
            aidge_core.MatMul(name="MatMul")
            ])
            self.unit_test_export(model, "MulDoubleBroadcast", [[1, 5, 1]])
            self.unit_test_export(model, "MatMulDoubleBroadcast", [[3, 5, 5]])
            def test_mul_batch(self):
            print("MulBatch")
            def test_matmul_batch(self):
            print("MatMulBatch")
            model = aidge_core.sequential([
            aidge_core.Producer([3, 5, 7], name="producer"),
            aidge_core.Mul(name="mul")
            ])
            self.unit_test_export(model, "MulBatch", [[3, 5, 7]])
            def test_concat(self):
            print("Concat")
            model = aidge_core.sequential([
            aidge_core.Producer([1, 5, 7], name="producer"),
            aidge_core.Concat(nb_inputs=2, axis=1, name="concat")
            ])
            self.unit_test_export(model, "Concat", [[1, 5, 7]])
            def test_transpose(self):
            print("Transpose")
            model = aidge_core.sequential([
            aidge_core.Transpose(output_dims_order=[0, 2, 3, 1], name="transpose")
            ])
            self.unit_test_export(model, "Transpose", [[1, 7, 8, 2]])
            def test_reshape(self):
            print("Reshape")
            model = aidge_core.sequential([
            aidge_core.Reshape(name="reshape")
            ])
            shape = aidge_core.Producer(aidge_core.Tensor(np.array([7, 2, 1, 8], dtype=np.int64)), name="shape")
            shape.add_child(model.get_node("reshape"), 0, 1)
            model.add(shape)
            self.unit_test_export(model, "Reshape", [[1, 7, 8, 2]], random_weights=False)
            def test_matmul(self):
            print("MatMul")
            model = aidge_core.sequential([
            aidge_core.Producer([4, 8], name="producer"),
            aidge_core.MatMul(name="matmul")
            ])
            self.unit_test_export(model, "MatMul", [[8, 4]])
            self.unit_test_export(model, "MatMulBatch", [[3, 7, 7]])
            def test_concat_axis_2(self):
            print("ConcatAxis2")
            ......@@ -1030,6 +703,7 @@ class test_operator_export(unittest.TestCase):
            ])
            initFiller(model)
            self.unit_test_export(model, "Conv", [[1, 1, 9, 9]])
            if __name__ == '__main__':
            unittest.main()
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